Dengue disease surveillance: an updated systematic literature ......Dengue disease surveillance: an...

Dengue disease surveillance: an updated systematic literature

review

S. Runge-Ranzinger1, P. J. McCall2, A. Kroeger1,2 and O. Horstick3

1 Special Programme for Research and Training in Tropical Diseases, World Health Organization, Geneva, Switzerland2 Liverpool School of Tropical Medicine, Liverpool, UK3 Institute of Public Health, University of Heidelberg, Heidelberg, Germany

Abstract objectives To review the evidence for the application of tools for dengue outbreak prediction/

detection and trend monitoring in passive and active disease surveillance systems in order to develop

recommendations for endemic countries and identify important research needs.

methods This systematic literature review followed the protocol of a review from 2008, extending

the systematic search from January 2007 to February 2013 on PubMed, EMBASE, CDSR, WHOLIS

and Lilacs. Data reporting followed the PRISMA statement. The eligibility criteria comprised (i)

population at risk of dengue, (ii) dengue disease surveillance, (iii) outcome of surveillance described

and (iv) empirical data evaluated. The analysis classified studies based on the purpose of the

surveillance programme. The main limitation of the review was expected publication bias.

results A total of 1116 papers were identified of which 36 articles were included in the review.

Four cohort-based prospective studies calculated expansion factors demonstrating remarkable levels

of underreporting in the surveillance systems. Several studies demonstrated that enhancement

methods such as laboratory support, sentinel-based reporting and staff motivation contributed to

improvements in dengue reporting. Additional improvements for passive surveillance systems are

possible by incorporating simple data forms/entry/electronic-based reporting; defining clear system

objectives; performing data analysis at the lowest possible level (e.g. district); seeking regular data

feedback. Six studies showed that serotype changes were positively correlated with the number of

reported cases or with dengue incidence, with lag times of up to 6 months. Three studies found that

data on internet searches and event-based surveillance correlated well with the epidemic curve derived

from surveillance data.

conclusions Passive surveillance providing the baseline for outbreak alert should be strengthened

and appropriate threshold levels for outbreak alerts investigated. Additional enhancement tools such

as syndromic surveillance, laboratory support and motivation strategies can be added. Appropriate

alert signals need to be identified and integrated into a risk assessment tool. Shifts in dengue

serotypes/genotype or electronic event-based surveillance have also considerable potential as indicator

in dengue surveillance. Further research on evidence-based response strategies and cost-effectiveness is

needed.

keywords dengue, surveillance, systematic review, epidemic preparedness, dengue outbreaks

Introduction

Dengue remains a major and growing public health

threat worldwide. With the most recent study estimating

that global infection rates of 390 million infections occur

annually (Bhatt et al. 2013), the need for improved den-

gue surveillance is evident. Dengue surveillance is essen-

tial for the detection of outbreaks and, in the longer

term, to monitor disease trends. In order to trigger timely

interventions, outbreak alerts are particularly important

to mobilise vector control and to prime or reorganise

healthcare delivery services in preparation for a surge in

suspected cases. Although vector control tools can be

effective in principle, implementation remains an issue

and effective dengue routine prevention is rarely

achieved, particularly in high-density urban communities

(Horstick et al. 2010; Pilger et al. 2010). Emergency vec-

tor control operations in response to dengue outbreaks

1116 © 2014 The Authors. Tropical Medicine and International Health published by John Wiley & Sons Ltd.

This is an open access article under the terms of the Creative Commons Attribution License,

which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Tropical Medicine and International Health doi:10.1111/tmi.12333

volume 19 no 9 pp 1116–1160 september 2014

are more typically applied, even though the efficacy of

the most widespread method used, insecticide fogging or

space-spraying, is dubious (Esu et al. 2010). Surveillance

for dengue can include different indicators and systems

(Harrington et al. 2013; Henning 2004; Stroup et al.

1989) to detect outbreaks and monitor trends. The

authors’ earlier systematic literature review (Runge Ranz-

inger et al. 2008) analysed ‘the evidence on the structure,

purpose and usefulness of dengue disease surveillance in

dengue endemic countries’ and described a general lack

of evidence for the usefulness of dengue disease surveil-

lance for early outbreak detection, especially the lack of

indicators/alert signals available to trigger response. A

stepwise adaptation of surveillance systems after evalua-

tion in combination with active surveillance was recom-

mended. Since then, new articles in the field of dengue

surveillance have been published, and new initiatives

towards early detection of dengue outbreaks have been

launched (WHO expert meeting on dengue outbreak

detection and response, June 2012). Common to all

reports and recommendations is an increased recognition

of the need for dengue control to focus on surveillance,

vector control and adequate case management.

The aims of this review were to strengthen the evidence

base and (where required) adjust the recommendations of

Runge Ranzinger et al. (2008) by incorporating new

trends and tools and to identify and summarise advances

or improvements made. As in the earlier review, dengue

vector surveillance was not covered here, but has been

reviewed independently elsewhere (Bowman et al. 2014,

in press).

Methodology

This review followed the protocol (York 2001) used in a

previous systematic literature review on dengue disease

surveillance, and the reporting guidelines set out in the

PRISMA Statement for systematic reviews and meta-

analyses (Liberati et al. 2009). The eligibility criteria of

the reviewed literature were as follows: (i) population at

risk of dengue, (ii) dengue disease surveillance, (iii) out-

come of surveillance described and (iv) empirical data

evaluated. After the recent dengue outbreaks in France

and Croatia (29 and 30), the population at risk in the

search was extended to include the European region. Lit-

erature reported in English, German and Spanish was

included although the search was conducted in English

only. Studies focusing on risk mapping, transmission

dynamics, forecasting or prediction methods were

excluded (e.g. Buczak et al. 2012; Chen & Chang 2013;

Racloz et al. 2012), as they did not directly study surveil-

lance systems.

The literature search and analyses were developed and

continued until 15th February 2013, with two persons

working as data extractors. Search fields included Medi-

cal Subject Heading (MeSH) terms/subjects and free text,

considering population, intervention and outcome. The

terms ‘dengue’ and ‘severe dengue’ (dengue fever (DF),

dengue h(a)emorrhagic fever (DHF) and dengue shock

syndrome (DSS)), ‘surveillance’ (disease, clinical, active,

passive, sentinel, epidemiologic, population), ‘communi-

cable disease control’, ‘effectiveness’, ‘evaluation’, ‘disease

notification’, ‘disease outbreaks’, ‘hospital and clinical

laboratory information system’ were used. The search

strategy was adapted according to the databases, consis-

tent with the process undertaken during the primary

review published in 2008.

The search strategy was applied to the following data-

bases to locate peer-reviewed studies: The United States

National Library of Medicine and the National Institutes

of Health Medical Database (PubMed) (1966–2013), Ex-cerpta Medica Database (EMBASE) (1983–2013), theCochrane Database of Systematic Reviews (CDSR), the

World Health Organization (WHO) library database

(WHOLIS) and the Latin American and Caribbean

Health Sciences Database (Lilacs) (1967–2013). The ref-

erences cited by relevant literature, including grey litera-

ture, were also screened for further articles. Grey

literature and unpublished studies were included if found

relevant to the research question and if they fulfilled the

inclusion and exclusion criteria.

All results were screened for duplication by author,

title, journal and publication date, and then screened

for relevance, based on the title and abstract only. The

full text of all studies considered to be relevant was

then reviewed for final assessment by two independent

data extractors. Where necessary, consensus was

achieved by discussion. Relevant information, including

study bibliographic information, study design and

objectives, levels of endemicity and population, compo-

nents of the surveillance system (surveillance subjects,

scope and method), resources spent on the system,

delivery of the surveillance system (information flow,

outbreak and/or case definition, additional relevant

information), purpose of the surveillance system and

outcome attributes, was extracted and tabulated in evi-

dence tables (Table 1).

As many studies were descriptive or ‘ecological studies’

and therefore could not be ranked according to the ‘hier-

archy of study designs’ (York 2001), the National Health

and Medical Research Council (NHMRC 2000) evidence

hierarchy (Merlin et al. 2009) was used to group the

studies according to study design. Only studies at evi-

dence ‘level IV or level III-2 and III-3’ were included.

© 2014 The Authors. Tropical Medicine and International Health published by John Wiley & Sons Ltd. 1117

Tropical Medicine and International Health volume 19 no 9 pp 1116–1160 september 2014

S. Runge-Ranzinger et al. Dengue surveillance

Table

1Evidence

tables

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system

Outbreakdefinition,Case

definition

Resultsandoutcomeattributes

Conclusionsofstudyauthors

andrisk

ofbias

A.Su

rveillan

ceforoutbreak

predictionan

d/orearlyoutbreak

detection

1.ChanEH

etal.(2011)

Bolivia,Brazil,

India,

Indonesia

and

Singapore

(2003–2

010)

Tocomplement

traditional

surveillance

by

potentiallyfacilitating

earlierdetection,

capturinghealth-

seekingbehaviour,

as

wellascapturingthe

populationoftheill

whodonotseek

medicalcare

form

ally.

Tobuildmodels

able

toestimate

adisease

activity

indicatorusing

data

onGoogle

searchpatternsfit

toatimeseries

of

case

counts

from

officialdata

sources.

Aggregatinghistorical

anonymised

logsof

onlineGoogle

search

queriessubmitted

between2003and2010.

Tim

eseries

are

computed

forthemost

common

searchqueriesin

the

selected

countries,

irrespectiveofquery

language.

Each

time

series

wasnorm

alisedby

dividingthecountfor

each

queryona

particulardaybythe

totalnumber

ofonline

searchqueriessubmitted.

Spikes

inthetimeseries

indicate

anincrease

ininterest

indengue.

To

determinewhether

they

are

‘truespikes’or

‘spuriousspikes’(e.g.

panic

driven)canbe

distinguished

when

the

rate

ofgrowth

exceeds

thenorm

alrate

ofspread

asdetermined

bythe

basicreproduction

number

R0orifpwas

foundto

exceed

five

standard

deviationsfrom

themean.

Model-fitted

‘expected’

epidem

iccurves

generally

matched

‘observed’epidem

iccurves

quitewellforallfive

countries,

withtheexception

ofBolivia

in2007when

the

model

overestimatedthe

activityin

thatseason,and

India

in2005forwhichit

underestimated

Tim

eliness:

Potentialto

provideearlier

signals

ofepidem

icswithout

delayofofficialcase

counts

Sensitivity:

Underreporting(e.g.dueto

misdiagnosisorsubclinical

cases)

extendsto

themodels

aswell;however,itcould

be

asourceofinform

ationfor

those

otherwisenot

dem

andinghealthcare

atall

orin

thereportingsector.

Conclusionsofstudyauthor

-Could

supplementtraditional

surveillance.

-Would

bealow-cost

option

-Estim

atinganindicatornear

real-time

-Dengue-relatedsearch

queriesare

generallynotas

influencedbynew

s

coverage(panic-driven

searches)

-Despitestronghistorical

correlations,

itremains

susceptible

tofalsealerts.

-Sufficientsearchvolumeis

needed.

-Ruralareasanddeveloping

nationstendto

lack

or

havelimited

Internet

access

currently.

-Intercountrycomparisons

maybedifficult,each

presentedcountryand

model

must

beconsidered

independently.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

2.Althouse

BM

etal.(2011)

Singapore

(weekly

incidence,

2004–2

011)

andBangkok

(monthly

incidence,

2004–2

011)

Google

searchquery

Dengueincidence

data

andInternet

searchdata

for

thesameperiod

were

downloaded.

Searchterm

swere

chosen.Three

modelsto

predict

incidence

were

compared.

Logisticregressionand

support

vectormachine

(SVM)modelswereused

topredictabinary

outcome.

Incidence

predictionmodelswere

assessedusingr2

and

Pearsoncorrelation.

Logisticregressionand

SVM

model

perform

ance

wereassessed.Models

werevalidatedusing

multiple

cross-validation

techniques.

NA

-InBangkok,themodel

hasan

r2~0:943,andacorrelation

of0.869betweenfitted

and

observed.

-InSingapore,themodel

has

anr2

~0:948,anda

correlationof0.931.

-Inboth

Singapore

and

Bangkok,SVM

models

outperform

edlogistic

regressionin

predicting

periodsofhighincidence.

-TheAUC

fortheSVM

modelsusingthe75th

percentile

cut-off

is0.906in

Singapore

and0.960in

Bangkok.

-Ourpredictionsoftime

periodswithhighdengue

incidence

are

veryaccurate

withsensitivitiesand

specificities

of0.861–1

.00

and0.765–1

.00formultiple

thresholdsin

each

location.


-Internet

searchterm

spredict

incidence

ofdenguewith

highaccuracy.

-Themethodsuse

freely

available

data

andanalysis

tools

andcanbereadily

adaptedto

other

settings.

-Insettings,

withless

developed

surveillance

system

s,aninternet

search

term

-basedsystem

mayyield

significantgainsin

the

rapidityofpredictions.

-Itisconceivable

thatan

internet

searchterm

-based

model

maybeaproxyfor

routinesurveillance

in

specificsettings.

-Individualmodelsneedto

be

developed

forspecificsettings

usinglocalsurveillance

data

andsearchterm

s.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

3.Lee

KSet

al.

(2010)

Singapore

2006–2

008

2005laboratory-based

denguevirus

surveillance

was

established

forclose

monitoringand

investigationofthe

circulatingdengue

virusserotypes.

Toproofa

serotypesw

itch

forthe2007/

2008outbreak.

Phylogenetic

analysisof

DENV

sequenceswas

conducted

usingthe

maxim

um-likelihood

methodasim

plemented

andcomparedwith

sequence

data

obtained

from

GenBank.

Warninglevel

=256cases/

epidem

iologic

weekas

reported

bytheMinistry

ofHealth.

-Thenumbersofdengue-

positivesamplesserotyped

were186in

2006,889in

2007and918in

2008and

represent�1

0%

ofthetotal

denguecases

-DuringJanuary–September

2006,75%

–100%

of

samplescollectedeach

month

contained

DENV-1.

-InearlyJanuary

2007,the

predominantcirculating

serotypesw

itched

from

DENV-1

toDENV-2.

-TheproportionofDENV-2-

positivesamplesdetectedby

PCR

rose

from

57.9%

in

January

2007to

apeakof

91.0%

inJuly

2007.

-Earlydetectionofthis

switch

warned

ofapossible

upcomingdengueoutbreak.


-Denguesurveillance

provided

earlywarningand

contributedto

early

activationofenhanced

vectorcontrol.

-Unable

toassessthe

effectivenessofthecontrol

measures,

consideringthe

regionalsituationin

2007,

withoutthesemeasuresthe

denguesituationin

Singapore

in2007would

havebeenworsethanor

comparable

tothatin

2004–

2005.

-Dem

onstrateshow

rapidly

denguevirusserotypes

can

bereplacedwithin

a

population.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

4.Lee

KSet

al.

(2012)

Singapore

January

2008–

Decem

ber

2010

Alaboratory-based

denguevirus

surveillance

programme

established

since

2005provides

an

opportunityto

study

thecirculatingdengue

virusesin

this

island

state.

This

studyaim

sto

understandthe

dynamicsof

denguevirusesin

cosm

opolitan

Singapore.

Envelopeprotein

genesequencesof

allfourdengue

serotypes

(DENV-

1–D

ENV-4)

obtained

from

humansera

inSingapore

(2008–

2010)were

perform

edand

analysed.

Clinicalbloodsamples

werecollectedfrom

hospitals

andgeneral

practitioner

(GP)clinics

from

dengue-suspected

patients.Real-timePCR

(RT-PCR)fordengue

RNA

detectionand

serotypingwascarried

outin

Environmental

HealthInstitute

(EHI)

accordingto

itsin-house

protocol.

PCR

positiveforDENV

-Ofatotalof6515samples

(2008–2

010)from

general

practitionersandhospitals,

994sampleswerepositive

fordenguebyRT-PCR.All

4serotypes

weredetected

withDENV-2

(80.5%)

continuingasthe

predominantserotype.

DENV-1

(8.7%)and

DENV-3

(8.2%)werealso

regularlydetectedwhile

DENV-4

wasrare

(2.4%).

-380(38.2%)sampleswere

sequencedandanalysed,the

255DENV

2Egene

sequencesobtained

revealed

thatallbut22wereclosely

relatedto

cladeIIofthe

cosm

opolitangenotypethat

wereassociatedwiththe

2007dengueoutbreakthis

cladeIIlineagehasfurther

expanded

since

2007,into

twoseparate

new

erclades;

designatedhereasclades

III

andIV

.Notably,by2010,

thetw

onew

erclades

(III

andIV

)replacedcladeII

to

bethepredominantvirus

andwereinvolved

inthe

larger

clustersoccurringin

Singapore,particularlyatthe

endof2010.

Conclusionsofstudyauthor:

-Atthepointofwriting(July

2011),Singapore

was

experiencingasignificant

rise

innumber

ofcases,

whichwerepredominantly

dueto

cladeIIIandIV

of

cosm

opolitanDENV-2.

Reachingabout260cases

per

week,itrepresented

thehighestnumber

of

casesper

weeksince

the

2007outbreakandwas

equivalentto

ormore

thantw

icetheweekly

numbersdocumentedin

thesameperiodin

2008–

2010.Suggestingthat

currentdata

show

thata

replacementofa

predominantviralclade,

even

intheabsence

ofa

switch

inpredominant

serotype,

could

signala

possible

increase

indenguetransm

ission.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

5.Koh

Benjamin

KW

etal.(2008)

Singapore

2005

Population-w

ide

routinereporting

includinglaboratory

components.

Epidem

iological,

entomological

andvirological

data

were

analysed

retrospectively.

Allmedicalpractitioners

should

notify

allcases

anddeath

ofdengueto

theMOH

within

24hby

faxorvia

awebsite.

Laboratories

are

also

required

tonotify

MOH

ofallpatients

whose

bloodsamplestested

positiveforacute

dengue

infection.

Acluster

isdefined

as2or

more

cases

epidem

iologicallylinked

byplace

ofresidence

or

work/school(w

ithin

150m)andtime(onset

ofillnesswithin

14days).

-Atotalof1190clusters

involving5362

epidem

iologicallylinked

caseswereidentified.This

constituted38.3%

ofall

reported

cases.

Themean

number

ofcasesin

each

cluster

was3(range,

2to

75),andthemeanduration

oftransm

issionwas5days

(range,

1to

54).

-Asignificantcorrelation

betweenweekly

mean

temperature

andcaseswas

noted.Thecorrelationwas

strongwhen

theincrease

in

temperature

preceded

rise

incasesbyaperiodof

18weeks(r

=0.60;

P<0.001)


Factors

contributingto

this

resurgence

included

-lower

herdim

munityand

-thepredominantdengue

serotypefor2001–2

003was

DEN-2.This

wasreplacedby

DEN-1

inJune2004

althoughthis

strain

hadbeen

circulatingin

Singapore

since

2002.This

changein

dengue

serotypecould

haveexposed

asignificantproportionof

thepopulationwhomaybe

immunologicallynaiveto

the

new

circulatingserotype,

althoughthis

isdifficultto

proveconclusively.

-Therewasnoevidence

from

genesequencingofthe

denguevirusesthatthe

epidem

icwasprecipitatedby

theintroductionofanew

virulentstrain.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

6.Schreiber

MJ

etal.(2009)

Singapore

April–

Novem

ber

2005

Population-w

ide

routinereporting

includinglaboratory

components.

Byexploiting

genomic

data

from

an

intensively

studiedmajor

outbreak,

molecular

epidem

iologyof

DENV

atafine-

scaledtemporal

andspatial

resolutionis

analysed.

Allmedicalpractitioners

should

notify

allcases

anddeath

ofdengueto

theMOH

within

24hby

faxorvia

awebsite.

Laboratories

are

also

required

tonotify

MOH

ofallpatients

whose

bloodsamplestested

positiveforacute

dengue

infection(from

study5).

Acluster

isdefined

as2or

more

cases

epidem

iologicallylinked

byplace

ofresidence

or

work/school(w

ithin

150m)andtime(onset

ofillnesswithin

14days)

(from

study5).

133RT-PCR

dengue-positive

patients

collected;66

(48.9%)DENV-1,62

(46.6%)DENV-3

and5

DENV-2

(3.8%).Allbutone

oftheDENV-1

genomes

from

this

epidem

icwere

classified

asgenotypeI.The

majority

ofDENV-3

genomes

fellinto

genotype

III,andanisolate

from

genotypeIIIwasfirst

detectedin

Singapore

in2003

whichfellbasalto

the2005

outbreakvirusesin

our

phylogenetic

analysis.

-Epidem

icsurveillance

ofviral

genomesequencesin

this

case

would

nothavebeen

sufficientto

predictthe2005

outbreak.

-Concurrentsurveillance

of

viralisolates,

mosquito

vectors

andperiodic

surveys

ofseroprevalence

ratesof

thepopulationmay

therefore

providethe

additionalrequired

predictiveinform

ation.

-Thechance

discoveryofthe

DENV-3

outbreakalso

highlights

thevalueof

comprehensivecity-w

ide

fever

surveysin

detecting

rare

events.

7.YamanakaA

(2011)

Indonesia

Surabaya

2007–2

010

Virussurveillance,

studybased

Threesurveysin

Surabayaduring:

(i)April2007,(ii)

June2008to

April2009and

(iii)September

2009to

Decem

ber

2010.

Atotalof231

isolatesfrom

denguepatients

examined

byPCR

typing.

Phylogenetic

analyseswere

perform

edrandomly.

Samplesfrom

1071

patients

aged

from

four

monthsto

14years,who

wereclinicallydiagnosed

withDForDHF.The

associationbetween

DENV

typeanddisease

severitywasevaluatedby

thechi-square

test

with

theYates’

correction

factor.

Theprobability

valueofP(0.05)was

considered

statistically

significant.

PositivePCR

forDENV

-Wefoundthatthe

predominantDENV

shifted

from

type2to

type1

betweenOctober

and

Novem

ber

2008.

-All22selected

isolatesin

the

secondsurvey

belonged

to

genotypeIV

,andall17

selected

isolatesin

thethird

survey

belonged

togenotype

I,indicatingagenotypeshift

betweenApriland

September

2009.

-TheproportionofDHFcases

increasedaboutthreetimes

after

thetypeshiftin

2008.

-Thesubsequentgenotypeshift

in2009wasassociatedwith

theincreasednumber

of

totaldenguecases.

-This

studyshowsaquicktype

shiftofthepredominant

circulatingDENV

from

DENV2to

DENV1in

SurabayabetweenOctober

andNovem

ber

2008.

-10%

ofdenguecaseswere

linked

withDHFin

2008,

increasingto

28%

in2009.

-WealsofoundaDENV1

genotypeshiftfrom

IVto

I

betweenApril2009and

September

2009,less

than

oneyearafter

displacement

oftheviraltype

-Thetotalnumber

ofdengue

patients

increasedin

2010,

with2169,2268and3379

casesin

2008,2009and

2010,respectively.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

8.LiDSet

al.

(2010)2007–

2009Pacific

Region

Notstated

During1997–

2000,the

serotypewas

alm

ost

exclusively

DENV-2,but

during2000–

2001,<1year,

DENV-2

was

displacedby

multiple

genotypes

of

DENV-1.Rapid

replacementof

DENV-1

by

DENV-4

during

2008is

described.

Routinereporting

discovered

increased

transm

issionwithDENV-

4introduction:May

2008in

Kiribati

outbreak,July

2008

Samoa,Decem

ber

2008

shiftfrom

DENV-1

toDENV-4

inTonga,

Novem

ber

2008DENV-4

inNew

Caledonia,

February

2009French

Polynesia.Phylogenetic

analysiswasperform

ed

Notstated

-Thechronologyofthe

recoveryofDENV-4

from

patients

intheregion

suggests

thatDENV-4

was

introducedfrom

Indonesia/

Malaysiabefore

2007.

-Therelativegenetic

homogeneity

oftheDENV-4

recovered

duringthis

most

recentoutbreakin

the

Pacificregionsuggests

introductionofasingle

genotyperather

than

introductionofmultiple

genotypes

andto

different

locations,

aswasthecase

withDENV-1.


-Outbreaksare

initiatedbythe

introductionofDENV,but

thepopulationsofmost

islandnationstatesare

too

smallto

sustain

transm

issionofasingle

DENV

serotypefor>4–

5years.

-Interislandmobilityin

this

regionensuresrapid

spread

ofanynew

lyintroduced

viruses.

-This

synchronisationof

spreadmayreflectthe

relativelysm

allpopulations

ofmost

islandstates

(�250000residents),high

attack

ratesandahighbirth

rate

(�30%

ofthe

populationis<14years)

-Ifonly

1DENV

serotype

circulatesatanytime,

and

serotypereplacementoccurs

approxim

ately

every5years,

thesedata

suggestthat

�30%

(75000)of250000

susceptible

hostsare

sufficientin

thesesettingsto

support

aserotype

replacementandthatDENV-

3mayreappearin

thePacific

islandstatesin

�2012.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

9.Rocha

Claudio

etal.

2009Iquitos,

PeruMay

2000–A

ugust

2003

Twoactivesurveillance

system

s,studybased

ascohorts,

a)

monitoringschool

absenteeism

among

thestudents

b)

community-based

programmeofdoor-

to-doorfebrile

surveillance

instudy

neighbourhoods.

Tobetter

understandthe

epidem

iologyof

dengue

transm

issionin

Iquitos,

multiple

activesurveillance

system

sto

detect

symptomatic

infectionswere

established.

a)1100childrenwere

recruited

into

aschool-

basedfebrile

surveillance

programmeandmonitored

inschooldaily,during

vacationperiodsonce

per

week.

b)5000neighbourhood

residents

wereinvited

to

participate

inadoor-to-

doorfebrile

illness

surveillance

programme.

Healthworkers

interviewed

each

residence

threetimes

Ifachildwasabsentfrom

school,ahomevisitwas

madeto

determine

whether

theabsence

was

because

offebrile

illness

(≥38°C

).

-Febrile

episodes

weredetected

byboth

system

swithequal

rapidityafter

disease

onset.

-Duringtheperiodthatboth

programmes

wererunning

simultaneouslyin

2004,a

higher

number

offebrile

casesin

general(4.52/100

versus1.64/100person-

years)anddenguecases

specifically(2.35/100versus

1.29/100person-years)were

detectedin

school-aged

childrenthroughthe

community-based

surveillance

programme.

Sim

ilarresultswere

obtained

bydirect

comparisonof435

participants

concurrently

enrolled

inboth

programmes

(P<0.005).


Thecommunity-based

programmecaptured

twofold

more

fever

and

symptomaticdengue

infectionsrelativeto

study

populationsize

thanthe

school-basedsystem

while

monitoringfivetimes

as

manypeople

usingthesame

number

ofpersonnel

and

thesameamountof

resources.

-Community-basedsurveillance

allowed

toidentify

symptomaticdenguecasesin

allagegroupsandwasnot

solely

limited

toschool-aged

children.

-Severalfactors,includingthe

researchobjective,

site-

specificdengueepidem

iology

andculturalcharacteristics

ofthestudypopulation,will

helpdeterminethetypeof

activesurveillance

system

to

implement.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

10.Meynard

Jean-Baptiste

etal.(2008)

French

Guiana

week41of

2005to

week

25of2006.

Syndromic

andclinical

surveillance

reporting

onthearm

edforces

andlaboratory

surveillance

reporting

onthecivilian

population.

Theobjectives

wereto

studythe

valueofa

syndromic

surveillance

system

set-up

within

thearm

edforces,compared

withthe

traditional

clinical

surveillance

system

duringthis

outbreak.The

main

studied

perform

ance

was

theearlywarning

capacity.

a)U

ntil2006,surveillance

wasbasedonthe

weekly

civilian

laboratory

surveillance

ofconfirm

edcases

within

the200000

generalpopulation.

b)Forthearm

edforces,the

surveillance

isbasedon

theclinicalmilitary

mandatory

system

within

the3000

soldiers.

c)Toenhance

this

clinical

surveillance,anew

syndromic

prototype

wassetupin

October

2004combined

with

theclinicalsystem

.

a)Threshold=6casesper

weekformore

than2

consecutiveweeks.

b)A

weekly

statisticalnon-

automatedanalysis

usingtheCurrentPast

ExperiencedGraph

(CPEG)to

compare

withhistoricaldata.

c)Data

analysisis

automatedanduses

both

theCPEG

andthe

ExponentialWeighted

MovingAverage.

-Syndromic

surveillance

detectedthedenguefever

outbreakseveralweeks

before

clinicalsurveillance,a

pre-alarm

wasactivated

duringweek41,this

wasnot

confirm

edforthreemore

weeks.

Therealalarm

with

thearm

edforces

started

duringweek44of2005.

-Onthecivilianside,

more

timewasnecessary

todetect

thenew

denguefever

outbreak,in

particular

because

itdid

notuse

any

statisticaltoolto

identify

an

increase

incasesabovea

threshold.

-Severalweekswerealso

necessary

forthelocalvector

bornedisease

committeeto

requestastrengtheningof

existingvectorcontrol

measures.


-Laboratory-basedand

syndromic

surveillance

is

complementary;both

contribute

different

surveillance

data

andtogether

allow

abetterassessm

entof

theepidem

iologicalsituation.

-Theadditionofsyndromic

surveillance

required

the

involvem

entofnumerousnew

contributors.

-Itallowed

anestimationof

theim

pact

ofthe2006

outbreak,recording16200

suspectedcases,

whereasthe

previoussystem

countedonly

2500confirm

edcases.

-However,syndromic

surveillance

isassociatedwith

anincreasedrisk

offalse

alarm

sandofsystem

saturationin

case

ofoutbreak.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

11.Jefferson

Henry

(2008)

French

Guiana

Jan2005–D

ec2006Arm

edForces

Syndromic

fever

surveillance

(2SE

FAG)system

has

beenin

operation

since

October

2004

andis

aprototype,

nearreal-time

syndromic

surveillance

system

operatingamong

some3000arm

edforces

inFrench

Guiana.

Theaim

ofthis

studywasto

evaluate

the

syndromic

system

usingtheCDC

guidelines

‘Framew

ork

for

EvaluatingPublic

Health

Surveillance

System

sforEarly

Detectionof

Outbreaks’.

Thesystem

isdesigned

toallow,in

nearreal-time,

geolocationand

epidem

iologicalanalysis

ofcasesoffever

(tem

perature,>38°C

).Interviewswithin

two

main

stakeholder

groups

ofdata

inputanddata

analysispersonnel

have

beenperform

ed.A

quantitativepart

investigatedvalidityof

reporting.

Suspecteddengue:

sudden

onsetoffever

withno

evidence

ofother

infection(particularly

malaria),associatedwith

oneormore

non-specific

symptomsincluding

headache,

myalgia,

arthralgia

and/orretro-

orbitalpain.

Tim

eliness:

Idealwithin

60min.Delaysandnon-

reportingdueto

reporting

process

identified.

Data

quality:could

be

optimised

System

costs:

Development

275000Euro,annualcosts

about235000Euro

Flexibility:adaptable

and

transferrable.

Usefulness:

89%:alarm

sstim

ulatedactivities,

84%:

betteratdetectingfebrile

episodes

thantraditional

surveillance.83%

ofdata

analysisstakeholder

missed

astandardised

response

protocol.100%

agreed

on

adequate

detectionof

outbreaks

Acceptability:48%

feel

time

investedisnotproportional

tobenefit,24%

believed

noteasy

touse.

Stability:68%

replied

that

thesystem

wasnot

available

when

needed,

main

barrierin

data

entry.


-Specificareasofacceptability

toenterdata

could

be

significantlyim

proved

-Thehighsensitivityandlow

specificity

ofsyndromic

surveillance

ischaracteristic.

This

lack

ofspecificity

may

leadto

costly

falsealarm

s.

-Sensitivityofthesystem

meansthatifutilised

correctlybysstakeholders,

it

isunlikelyto

missany

disease

epidem

icwherethe

primary

symptom

isfever.

-Thetimelinessandsensitivity

weremajorstrongpoints.

-Loggingofpatients

into

the

system

tooktoomuch

time




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

12.FlamandC

etal.(2011)

French

Guiana

January

2006–

Decem

ber

2010

In2006laboratory,

sentinel,hospitaland

healthcentre-based

surveillance

was

implemented,to

improveearly

detectionof

outbreaksandto

allow

abetter

provisionof

inform

ation.

37812clinical

casesand10724

confirm

edcases

wereanalysedto

validate

the

perform

ancesof

thesystem

.

a)30voluntary

general

practitioners(35%

oftotal

GP’s)

b)Surveillance

from

Emergency

Departments

(EDs)

ofthethree

hospitals

c)17healthcentres

weekly

report

number

ofcasesby

satellite.

1Sporadic

transm

ission

2Denguefever

clusters

3Pre-alert

(exceeding

threshold

for2weeks)

4Epidem

ic(exceeding

threshold

for2more

weeks)

5Endofepidem

ic(below

threshold)

6Increase

ofpositivity

ratesofbiological

analysisandre-

emergence

ofaserotype

isusedto

confirm

the

entryin

thenextstage.

-Threemajoroutbreakswere

detected

-Duringtheseoutbreaks,

80

signals

weretriggered

for

confirm

edcasesand64for

clinicalcases,

allthese

outbreakswereconfirm

ed

-Averagedurationofthe

epidem

icsvaried

between38

and41weeks.

-Reinforcem

entvectorcontrol

measuresproportionate

to

theseverityandmagnitude

oftheepidem

iological

situation.


-Validityofthesurveillance

system

anditsperform

ance

tomonitordenguepatterns,

todetectoutbreaksandto

providereal-time

inform

ation

-Greatvarietyofdata

sources

constitutesaverysound

basisfortheanalysisand

interpretation

-Tim

e-series

methodologyand

takinginto

accountdata

characteristics

such

as

seculartrends,

seasonality

andabruptchanges

should

beconsidered

infuture.

-Outbreakpredictionin

future

willconsist

intheuse

of

other

data

sources

for

surveillance

such

as

environmentalfactors

(i.e.

clim

atic,

meteorological,

plantcover

andlanduse)so

asto

helpmonitorand

predictthespatialand

temporaldistributionofthe

virus.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

13.Hoen

Anne

G(2012)

(Dez.2009–

March2011)

TheAmericas

Investigatedreal-time

electronic

sources

for

monitoringspreadof

dengueinto

new

regions.

Modelled

outbreak

probability

density

representinga

risk

mapof

recentDENV

spreadinto

areas

ofpreviously

unknowndengue

endem

icity

accordingto

the

2010Yellow

Bookby

collecting

outbreakdata

from

HealthMap

Usedreceiver-operating

characteristicanalysis

withcross-validationto

setathreshold

dengue

report

density

thatbest

identifies

new

dengue-

endem

icareas

Knowndengue-endem

icareasweredefined

as

denguerisk

areas

identified

bytheUS

Centers

forDisease

ControlandPrevention.

HealthInform

ationfor

InternationalTravel

(commonly

referred

toas

theYellow

Book),2010

and2012editions

Ofthe19new

dengue-endem

icareasreported

inthe2012

Yellow

Book,this

threshold

identified

14(74%)asbeing

atelevatedrisk

of

endem

icity,accordingto

the

dengueoutbreakprobability

density

estimatedbyour

model.Ofthe41areasthat

remained

unidentified

as

dengue-endem

icareasin

the

2012Yellow

Book,our

model

classified

35(85%)as

havingreducedrisk

of

endem

icity.When

compared

withtheYellow

Book,our

model

incorrectlyclassified

6areasasatelevatedrisk


Electronic

event-based

surveillance

system

ssuch

as

HealthMapandothersare

frequentlyusedbypublic

healthauthorities,travellers,

physiciansandpatients,to

gain

areal-time

understandingofglobal

outbreakactivity.Usedin

combinationwithtraditional

case

reporting,HealthMap

andother

electronic

surveillance

system

shave

proven

valueforenhancing

thetimelinessofoutbreak

discoveryandinform

ation

dissemination(11).However,

theseinform

ationsources

mayalsoprovideadded

value

formonitoringongoing

spread.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

14.Randriana-

solo

Laurence

(2010)

Madagascar

01.04.2007–

31.12.2008

Asentinel

syndromic-

basedsurveillance

system

wassetupin

March2007.Theaim

wasto

allow

the

rapid

detectionofan

epidem

icandto

identify

circulating

arboviruses.

Challenges

and

stepsinvolved

indevelopinga

sentinel

surveillance

system

are

described.

Useshealthservice-based

indicators

andmostly

focusesonfever

syndromes.Foursentinel

primary

healthcentres

withhighpopulation

densities

werealso

implementedwith

arbovirussurveillance.

Sentinel

general

practitioners(SGP)report

weekly,usingform

saddressed

within

24hto

themanagem

entteam.

Fever

(axillary

temperature

ofmore

than37.5

°C).

Threeillnessesin

relation

withfever

wereselected

forsurveillance:malaria,

influenza-likeillness,

arbovirus(fever

without

respiratory

symptom

and

atleast

twoother

symptoms:

headache,

arthralgia,myalgia-like

backache,

skin

rash,

retro-orbitalpain,

haem

orrhagic

manifestations).

In2008,thesentinel

surveillance

system

included

13healthcentres.

-Ofthe218849visitsto

SGPs,

12.2%

wererelated

tofever

syndromes.Of

these26669fever

cases,

12.3%

wererelatedto

dengue-likefever

-89%

ofcaseshavebeen

reported

within

24h

-Ten

casesoffever

clusters

occurred;they

werenot

detectedbytraditional

surveillance

system

.

Laboratory

investigation

confirm

edtheclinical

signals.Thesentinel

surveillance

system

confirm

edfiveoutbreaks:

twovia

anincrease

inthe

dengue-likesyndromeratio,

oneofchikungunyavirus

circulation;tw

oInfluenza

A

(H1N1seasonal);one

malaria


-Asentinel

real-time-like

surveillance

system

maybe

thekey

tothedetectionof

disease

outbreaks.

-Cost

ofdata

transm

issionwas

minim

al,butmaintenance

requirem

ents

ofthesystem

needto

bebetterquantified

-Thetimerequired

toconduct

investigationsmightnegate

theadvantageoftimelydata

acquisition

-This

system

cannotreplace

traditionalsurveillance

-Epidem

iologicalbaselines

for

each

centreneedto

be

determined,to

helpdevelop

betterstatisticalmethods

andsensible

alarm

thresholds,

whichcanthen

beextended

tomore

sentinel

centres.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

B.Su

rveillan

cefortrendmonitoringofdengu

edisease

15.Standish

Katherine

etal.(2010)

Nicaragua,

Managua

2004–2

008

Laboratory-confirm

eddenguecases

identified

througha

DengueCohort

Study

(PDCS)were

comparedto

those

reported

from

other

healthfacilities

tothe

National

Epidem

iologic

Surveillance

(NES)

programme.

Toaddress

the

difference

indenguecase

capture

rates

betweena

paediatric

dengue

cohort

study

(PDCS)andthe

Ministryof

Healthdengue

surveillance

programme

(‘expansion

factor’)

calculated.

Thestudycaptured

possible

denguecases

through‘enhanced’

passivesurveillance

by

studyphysiciansand

nurses

attheHCSFV

and

periodic

homevisitsfor

follow-upand

monitoring.Inapparent

DENV

infectionswere

identified

through

serologicaltestingof

paired

annualblood

drawsfrom

healthy

subjects.

WHO

criteria

for

suspecteddengue,

aswell

asundifferentiatedfever.

Adenguecase

was

considered

laboratory-

confirm

edwhen

(i)

DENV

wasisolated,(ii)

DENV

RNA

was

dem

onstratedbyRT-

PCR,(iii)seroconversion

wasobserved

(iv)a

fourfold

increase

inantibodytitrein

paired

sera.

-PDCSidentified

14to

28

(average21.3)times

more

denguecaseseach

yearper

100000personsthanwere

reported

totheNES.

-Incidence

ofdengueranging

from

343to

1759casesper

100000personsin

the

cohort

study,ascomparedto

21to

77casesper

100000

personsacross

allManagua’s

healthcentres.

-Theratioofinapparentto

symptomaticDENV

infectionin

PDCS

participants

alsovaried

year

toyearfrom

16in

2004–

2005and2006–2

007,to

5

and3in

2005–2

006and

2007–2

008,respectively.


-This

wasnotaclassic

capture-recapture

study,but

rather

anecologicalstudy

comparingincidence

ratesin

acohort

tonational

surveillance

ratesin

the

surroundingurbanareas.

-TheHCSFV

district,which

bordersLakeManagua,may

havehigher

denguerates

thanother

healthcentres,as

therewasmore

reported

dengueamongthenon-study

populationoftheHCSFV.

-However,another

plausible

explanationis

thatthese

higher

numbersare

dueto

theim

pact

ofthePDCS

studyprotocoland

increasedawareness.

-Theexpansionfactors

fallsin

thesamerangeastheonly

published

expansionfactors

forambulatory

dengue.

Meltzer

etal.calculatedthat

10and27times

more

DENV

casesoccurin

Puerto

Rico.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

16.Wichmann

Ole

(2011)

Cambodia

Thailand

Estim

ationofthetrue

burden

ifdisease

by

calculatinga

multiplicationfactor.

Toutilise

laboratory-

confirm

edincidence

of

symptomatic

DENV

infection

both

ininpatients

andoutpatients

identified

inprospective

cohort

studiesto

estimate

dengue

under-

recognition.

Cohort

studieswere

conducted

among

childrenaged

15years.

Agegroup-specific

multiplicationfactors

(MFs)

werecomputed.In

Thailand,14627person-

years

ofprospective

cohort

data

were

obtained

intw

oprovincesand14493

person-years

from

one

province

inCambodia.

Thailand:paired

samples

wereobtained

from

all

students

withahistory

of

fever

within

theprevious

7daysoranoral

temperature

of>38°C

.Cambodia:Children(i.e.

>38°C

,acute

orin

the

previous7days)

for

2days(in2006)or1day

(in2007),paired

serum

sampleswerecollected

-Averageannualincidence

of

laboratory-confirm

eddengue

was23/1000and25/1000in

Thailandand41/1000in

Cambodia.

-CalculatedMFsin

these

provincesvaried

byage

groupandyear(range0.4–

29).In

Thailand,amedian

229886(range210612–

331236)denguecases

occurred

annuallyduring

2003–2

007andamedian

111178(range80452–

357135)casesoccurred

in

Cambodia

inchildren

<15years

ofage.

-Averageunder-recognitionof

totalandinpatientdengue

caseswas8.7-and2.6-fold

inThailand,and9.1-and

1.4-fold

inCambodia,

respectively.

Conclusionofstudyauthor:

-Thesedata

indicate

that

althoughdengueisregularly

reported

inmanycountries,

nationalsurveillance

data

significantlyunder-recognise

thetrueburden

ofdisease.

-Themajorfindingofour

analysiswasthatdengue

incidence

wasunder-

recognised

bymore

than8-

times

inThailandandmore

than9-tim

esin

Cambodia.

-Weconcludethatthenational

surveillance

system

sin

ThailandandCambodia

wereefficientin

capturing

inpatientdenguecase

with

only

2.6-and1.4-fold

under-detection,

respectively.

-However,thesurveillance

system

inThailandlargely

under-recognises

theburden

ofdengueoutpatients

and

thesystem

inCambodia

does

notallow

reportingof

outpatients

atall.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

17.VongS

etal.(2012)

Cambodia

Province

Kampong

Cham

2006–

2008

Passivepopulation-

basedsurveillance

system

withactive

sentinel

component

versusacommunity-

basedactivefever

cohort.

Two-sample,

capture–recapture

studyin

the

largestprovince

inCambodia

todeterminedisease

under-recognition

totheNational

Dengue

Surveillance

System

(NDSS).

Capture:Community-

basedactivesurveillance

foracute

febrile

illness

wasconducted

in0-to

19-year-olds.

Recapture:TheNDSSis

basedonreportingof

hospitalised,clinically

diagnoseddenguecases

aged

≤15years,reported

passivelyfrom

referral

hospitals

andatsentinel

hospitals.

Truedengue=febrile

illnessDENV-positiveby

serologyormolecular

testing.Denguecasesfor

thepurposesofNDSS

reportingwereidentified

onaclinicalbasisusing

the1997WHO

case

definition.

-Of14354individuals

under

activesurveillance

(22498

person-seasons),theannual

incidence

ranged

from

13.4

to57.8/1000person-

seasons.

-Duringthesameperiod,

NDSSincidence

rates

ranged

from

1.1/1000to

5.7/1000,whichwas3.9-to

29.0-fold

lower

thanfound

inthecapture–recapture

study.

-Inhospitalisedcases,

therate

ofunder-recognitionwas1.1-

to2.4-fold.


-Weconservativelyestimated

thattherewasafourfold

to

30-fold

degreeofdengue

under-recognitionand

underreportingto

NDSS

-Under-detectionlevels

changed

from

fourfold

to

22-fold

duringthe2006and

2008non-epidem

icyears,

and29-fold

duringthe2007

large-scale

epidem

icyear.

-Under-recognitionand

reportingforhospitalised

casesofdengueweremuch

lower

andgenerallymore

stable

from

yearto

year.

However,duringthelarge

epidem

icin

2007,

underreportingwastw

ofold

higher

thanin

other

years.

-Ourfindingsshow

thatNDSS

appearedto

accurately

capture

hospitalisedcases

over

time.

18.VongS

etal.(2010)

32villages

and10urban

areasof

Cambodia

during2006–

2008during

dengue

seasons

Community-based

activedenguefever

surveillance

among

the0-to

19-yearage

group.

Tomakearobust

estimate

ofthe

actualincidence

ofsymptomatic

denguevirus

(DENV)infection

inchildrenand

adolescents

living

inruraland

urbanareas

Conducted

bymothers

trained

touse

digital

thermometersandvillage

teams(V

T)from

each

respectivevillageandfive

investigationteams(IT).

VTsmadeweekly

home

visitsto

identify

persons

withfever

orhistory

of

fever

(axillary

temperature

of37.5

°C).

Adenguecase

isdefined

as

afebrile

personpositive

foranti-D

ENV

IgM

intheconvalescent-phase

serum.

Over

thethreeyears,6121

fever

episodes

wereidentified

with736laboratory-

confirm

eddenguevirus

(DENV)infectionsfor

incidencesof13.4–5

7.8/1000

person-seasons.


-This

activesurveillance

found

ahigher

disease

incidence

thanreported

tothe

nationalsurveillance

system

,

particularlyin

preschool

childrenandthatdisease

incidence

washighin

both

ruralandurbanareas.

-Italsoconfirm

edthe

previouslyobserved

focal

nature

ofdenguevirus

transm

ission.

C.Trendmonitoringan

doutbreak

detection




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

19.Mark

E.

Beattyet

al.

(2010)22

countries

Multiple

approaches

as

in22countries

practised.

Experts

attended

meetingsto

discuss

dengue

surveillance.

Literature

and

reportson

surveillance

programmes

were

reviewed,and

expertopinions

shared.

-12/22(55%)ofcountries

representedconfirm

ed

reported

caseswith

laboratory

testing.

-Nearlyeverycountry

includes

suspecteddengue

cases.

-Cambodia

report

children

less

than15years

ofage.

-Singapore

andBrazil

monitorvectorindices

not

soPuerto

Rico.

-Allcountriesare

dependentonpaper

form

s

forcase

reportingbefore

anyadditional

investigationoraction.

Notapplicable

-Surveillance

andlaboratory

methodsvaried

making

comparisonsdifficult.

-InKolkata,specialmapping

hasbeenusedto

target

controlactivities.

-InSingapore

andBrazil,

ministriesusingintranet-

baseddata

entry

-Tim

erequired

toreceivea

resultofasample

istoo

longandso

useless

forthe

treatingphysician.

-Data

are

rarely

usedlocally

missingtheopportunityfor

alocalresponse.

-Under-detectionandunder-

reportingofdenguecases

weresignificantandoften

dueto

thedesignofthe

surveillance

system

.

-Virologicalsurveillance

is

under-utilisedorcompletely

lacking.

-Effectivelinksbetweenthe

variousstakeholdersexists;

manyoftheseare

dependent

onpersonalcontacts.


-Everydengue-endem

ic

countryshould

make

reportingofdenguecasesto

thegovernmentmandatory.

-Electronic

reportingsystem

s

should

bedeveloped

and

used.

-Atminim

um

dengue

surveillance

data

should

includeincidence,

hospitalisationrates,

deaths

byagegroup.

-Additionalstudiesshould

be

completedto

checkthe

sensitivityofthesystem

.

-Laboratories

should

share

expertise

anddata.

-Tests

thatidentify

dengue

virusshould

beusedin

patients

withfever

forfour

daysorless

andantibody

testsshould

beusedafter

day4to

diagnose

dengue;

-Earlydetectionandprediction

ofdengueoutbreaksshould

begoals

fornational

surveillance

system

s.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

20.RekolHuy

etal.(2010)

Cambodia

Currently,national

surveillance

comprisespassiveand

activedata

collection

andreportingon

hospitalisedchildren

aged

0–1

5years.

This

report

summarises

surveillance

data

ondengue

collectedin

Cambodia

since

1980.In

addition,

theim

pact

ofa7-

yearvector

control

programmeon

theincidence

of

thedisease

was

evaluated.

NDCPgathered

data

reported

passivelyfrom

referralhospitals

and

collectedactivelyat

sentinel

sitesonweekly

basis.

Data

wereentered

centrallyinto

acomputeriseddatabase.

Since

2002,clinicalcase

definitionofdenguefever

anditscomplications

havebeenbasedon

WorldHealth

Organization(W

HO)

definitionsandadapted

forhealthcentres

and

referralhospitals.

Thealert

system

predictedthe

2007epidem

ic,theweekly

incidence

wasconsistently

abovethealert

threshold

of

twostandard

deviations

abovethemeanin

early

2007;theresponse

tothe

outbreakcametoolate.

-Noassociationbetween

routineinterventionsand

disease

incidence

was

observed.

-57.0%

in2002to

89.1%

in

2008ofreported

data

came

from

sentinel

sites.

-Between2000and2008,

paired

serum

sampleswere

collectedfrom

anannual

meanof715patients,

comprising5.2%

ofdengue

casesreported.Overall,

87.8%

ofsampleswere

seropositivefordengue,

and

therewaslittle

variation

across

sentinel

sites.


Theuse

ofsurveillance

has

severallimitations:

-Weaknessesin

thedesignof

thesurveillance

covered

patients

hospitalisedat

majorpublicandnon-

profit-makingpaediatric

hospitals

andpaediatric

wardsonly.

-Difficultyin

classifyingdisease

severityusingstandard

WHO

definitions

-Thesize

ofthepatient

samplesusedin

virological

surveillance

wassm

all.

-Patients

werenotselected

randomly

butbecause

there

wasahighlevel

ofsuspicion

ofhavingdengue

-Denguewasfrequentlyover-

diagnosedduringepidem

ics

andunder-diagnosedduring

theinterveningperiods.

-Despitetheselimitations,

our

observationthatdengue

activitypatternsfor

differentages

andgenders

haveremained

consistent

over

timeindicatesthatthe

surveillance

data

are

reliable.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

21.Ramos

Mary

(2008)

Puerto

Rico

Patillas

Municipality

June2005–

May2006

Alaboratory-based,

enhanceddengue

surveillance

system

(EDSS)was

developed

and

implementedatthe

healthcentrein

the

municipality

of

Patillas.

Toprovideamore

accurate

estimate

oftheincidence

ofsymptomatic

dengueand

describethe

clinicaloutcomes

ofdengue

infectionusing

data

representativeof

this

community.

Twofull-tim

eCDC

staff

mem

berswork

atthe

healthcentrein

Patillas

toencourageHCPsto

complete

denguecase

investigationform

sand

submitserum

samples.

CDC

on-sitestaff

verifies

theaccuracy

and

completenessofreporting

andprovidesystem

atic

feedback

WorldHealth

Organization(W

HO)

criteria

toclassifycases

andasimplified

case

definitionforsevere

dengueillnesswas

applied.

-Atotalof1393casesof

suspecteddenguewere

reported

totheEDSS156

(11.2%)werelaboratory-

positive,

422(30.3%)were

laboratory-negative,

and

815(58.5%)were

laboratory-indeterminate.

-7.7

laboratory-positivedengue

casesper

1000population

detectedbyEDSSwere

nearlythreetimes

higher

thanratesreported

under

thepassivesurveillance

system

duringthetw

omost

recentepidem

icsin

1994

and1998(1.3

casesper

1000in

1994and2.8

in

1998).


Enhancedsurveillance

isusefulfordetecting

population-basedincidence

of

symptomaticinfections

-This

surveillance

does

not

detectasymptomatic

infectionsorsymptomatic

infectionsamongthose

who

did

notseek

medicalcare.

-Incidence

oflaboratory-

positivedengueinfectionwas

high,particularlyamong

adolescents

andyoung

adults.

Althoughfew

cases

met

theWHO

criteria

for

DHF,10times

asmanyhad

atleast

onereported

severe

clinicalmanifestation,

indicatingthatsimplified

case

definitioncould

beusefulin

clinic-basedsurveillance.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

22.Schwartz

Eliet

al.

(2008)Ill-

returned

travellers

seen

atGeoSentinel

sitesfrom

Oct

1997–F

eb2006

GeoSentinel

sitesare

specialisedtravel/

tropicalmedicine

clinicson6

continents

and33

surveillance

sites.

Seasonality

and

annualtrendsfor

denguecases

among522

returned

travellers

are

reported.

Analysisover

timewasbased

onproportionate

morbidity.

Tobeeligible

forinclusion

intheGeoSentinel

database,patients

must

havecrossed

an

internationalborder

and

beseekingmedicaladvice

ataGeoSentinel

clinic

forapresumed

travel-

relatedillness.

Laboratory-diagnosed

denguein

aresidentofa

non-dengue-endem

icarea

whohastravelledto

adengue-endem

icareain

the14daysbefore

symptom

onset.

Amongill-returned

travellers,

24920met

thecriteria

for

analysis.

522(2.1%)hada

diagnosisoftravel-related

denguefever.

-Theincreasesin

1998and

2002werefoundentirely

in

travellers

toSouth-East

Asia;

for2003,in

travellers

to

South

CentralAsia;andfor

2005,in

travellers

toSouth

CentralAsiaandIndonesia.

Theseincreasescorrespond

toknownepidem

icyears

within

localpopulationsfor

those

regions.

-Themajorepidem

icpeakin

sentinel

travellers

preceded

theepidem

icpatternin

the

localpopulationduring

1998and2002,asreflected

inThaireportsto

theWorld

HealthOrganization.


InApril2002,GeoSentinel

alerted

theinternational

communityoftheincrease

intravel-relateddenguefrom

Thailandonline.

Data

reported

laterconfirm

edthe

observation.Theincrease

indenguecasesin

returned

travellers

from

South

CentralAsiain

2003was

alsoevidentbefore

official

surveillance

data

were

available.

-A2001outbreakin

Thailand

apparentlydid

notaffect

travellers,asitwasnot

associatedwithapeakin

reportsto

GeoSentinel.

-Nevertheless,

travellers

may

besentinelsable

torapidly

inform

theinternational

communityabouttheonset

ofepidem

icsin

disease-

endem

icareas.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

23.Domingo

Christina

(2011)

European

Travellers

2002–2

008

Molecularsurveillance

inreturning

travellers.

Todem

onstrate

the

role

oftravellers

asanadditional

sourceof

epidem

iological

inform

ation

complementary

tocountriesdata.

Sampleswerecollectedby

virologyresearch

laboratories

ofthe

EuropeanNetwork

or

travel

clinics,

mem

bersof

theEuropeanNetwork

(TropNetEurop).Seven

nationalreference

laboratories

participated

Suspecteddenguecase

was

defined

asapatientwith

travel

history

inthe

previous15daysto

adengue-endem

icarea,

whopresentedfever

plus

twospecified

symptoms.

Confirm

ationwascarried

outbymolecularand

serologicaldiagnosis.

-186DENV

strains(12

distinct

genotypes)were

detectedin

acute

dengue-

infected

Europeantravellers

(82DENV-1,39DENV-2,

48DENV-3

and17DENV-

4)

-10new

Africanstrainsare

described.Thedetectionof

threedifferentDENV

serotypes

intravellers

returningfrom

Cameroon

pointedto

ahyperendem

ic

situationin

thecountryin

theabsence

ofreported

denguehaem

orrhagic

outbreaks.

-Theidentificationofthe

emergence

ofdifferent

serotypes

andgenotypes,the

appearance

ofnew

clades

correlatingwithoutbreaks,

andtheidentificationofa

dengue-4genotypenot

previouslyreported

have

beenachieved.


-Returningtravellers

provided

data

even

from

areaswith

scarceDENV

epidem

iologicalinform

ation

likeAfricancountries,

-Theincrease

inDENV

correlatingwith

observationsin

the

respectivecountries(e.g.in

Cuba,Ecuador,

etc)

-Oneofthemain

achievem

ents

wasthedetectionofDENV-

3genotypeIin

Ecuador,

confirm

ingtherecent

detectionofthis

genotypein

theAmericas.

-Wewould

liketo

remark

that

travellers

constitute

just

a

random

sample

anddonot

substitute

themore

comprehensivenational

surveysthatwould

address

thecirculationofthis

genotypemore

accurately.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

24.Runge-

Ranzinger

(2011)

Cambodia

Thailand

Thailand:

Passivepopulation-

widereportingsystem

Cambodia:

Passivepopulation-

widereportingsystem

ofhospitalised

paediatric

casesand

activesentinel

sites.

Qualitativestudy

basedonkey

inform

ant

interviewsand

secondary

data

analysis.

Aim

:To

studythe

practical

applicationof

denguedisease

surveillance,

analyse

programme

response

and

their

interlinkages.

Thailand:passive

integratedreportingof

clinicalconfirm

edcases

mainly

public(indoor)

sector.

Serological

surveillance

at6sites,

3%

caseslaboratory

confirm

ed.

Cambodia:passive,

paper-basedintegrated

reportingofsuspected

hospitalisedpaediatric

denguepatients,public

sectorexclusively.

Virologicalsurveillance

at

5sentinel

sites

implemented,data

analysed,10%

cases

laboratory

confirm

ed.

Thailand:

Hospital:Fever+pos.

TT

(Tourniquet

Test)

=suspected;+Leucopenia

(<5000)=confirm

ed.2

confirm

edDHFper

village

in28days=outbreak.

Medianofpast

5years-

20%

=outbreak.

Cambodia:<15years,38–

40°C

fever,

mucocutaneous

haem

orrhagic

signsor

positiveTT.

Outbreak:meanofcases

(over

past

3years)plus2

SD

(Standard

Deviations)

Sensitivity:Thailand/

Cambodia:Underreporting:

shownbystudiesto

be40%

inahospital/1:3

hospitalised

and1:5–6

fortotalpaediatric

casesare

strong

underestimations.

Sensitivityofalert:20%

lowered

threshold

and

additional

localdefinition

increasedsensitivity/

observationofexcess

reportingin

low

transm

ission

seasoncould

potentiallybe

usedin

addition.

Falsealerts:

non-experienced

applyingthethresholds

above.

Tim

eliness:

4weeks/6–

7weeks

Usefulness:

both

fornational

planningyes,foroutbreak

detectiontoolate

Preparedness:

Both

no

contingency

plansoralert

algorithmsavailable.Lack

of

linkagefrom

data

toresponse.

Response:Mainly

case

based,

response

team

sim

plemented/

noeffect

betweenroutine

interventionsand

transm

issioncould

be

dem

onstrated,lack

of

resources.


Low

sensitivitydueto

(i)low

userrates,

(ii)clinical

assessm

entonly,(iii)

reportinglimited

topublic

sector,

certain

agegroupsor

inpatients

only,(iv)limited

acceptabilityatalllevelsand

(v)aninsensitivecase

classification.

Tim

elines

could

beim

proved

by(i)reportingofsuspected

cases,

(ii)avoid

double

reportingandcompiling,(iii)

theuse

ofpromptto

fill

form

s,(iv)data

analysisatall

levels,

includingdistrict,(v)

electronic

reporting.

Other

recommendations:

a)Establish

acommon

understandingofall

stakeholdersonthe

surveillance

purpose

and

objectives

b)Ensure

aclose

linkageof

analysedsurveillance

data

toevidence-based

response,bedded

inproper

contingency

planning

c)Increase

additionalactive/

sentinel/syndromic

components

basedona

clearrational

d)Further

researchon

appropriate

thresholds/

alert

indicators

orarisk

assessm

enttools

isneeded.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

25.Carolina

Fracalossi

Rediguieri

2009Bolivia

Brasil(G

oi� as

State)

Bolivia:

Passivepopulation-

widereporting

system

.Brazil:Passive

population-w

ide

reportingsystem

and

activesentinel

sites.

*Themeanincidence

ofeach

epidem

iologicalweek

iscalculatedby

takinginto

account

theincidence

inthe

twopreviousweeks

andin

thetw

oweeks

after

that

epidem

iologicalweek

Qualitativestudy

basedonkey

inform

ant

interviewsand

secondary

data

analysis.

Aim

:To

studythe

practical

applicationof

denguedisease

surveillance,

analyse

programme

response

and

their

interlinkages.

Bolivia:passiveintegrated

reportingofsuspectand

laboratory-confirm

edcasesmainly

public

sector.

Activesearchof

severecases(after

an

index

case).10%

cases

laboratory

confirm

ed.

Brazil:passiveintegrated

reportingofsuspectand

laboratory-confirm

edcasesmainly

public

sector.

Border

sentinels

(passive),activesearch

forviruscirculation63

PHC

(passive),active

searchforseverecases,

after

index

case.10%

caseslaboratory

confirm

ed.

Bolivia:

Number

ofcases

1.24times

abovethe

medianofthepast

5years.Endem

icarea+

fever

+anorexia

and

nauseaorskin

eruptions

orheadaches

or

leucopenia

orpositive

TT=suspectcase;

serologyorPCR

=confirm

edBrazil:Mobilemean*of

thepast

5years

+2SD;

incidence

above300

cases/

100000

inhabitants.Endem

icarea

+acute

fever

(upto

7days)

+2orspecific

symptoms.

Sensitivity:Bolivia/Brazil:

Underreportingin

both

countries.

Sensitivityofalert:notgo

od

foroutbreak

detectionor

prediction/highforoutbreak

detection.

Falsealerts:

notexperienced

applyingthethresholds

above.

Tim

eliness:

45days/3weeks.

Usefulness:

both

fornational


detectiontoolate

Preparedness:

Both

contingency

plansavailable,

butnoalert

algorithms

available.

Response:Mass

interventions,

such

asfumigationan

dsocial

mobilisationthrough

campaign

s/Response

targets

thevector(larvaecontrol,

ULV),urbancleaning,social

mobilisation,case

detection

andmanagem

ent.


Low

sensitivityofcase

detectiondueto:(i)the

existence

ofasymptomatic

dengueorundifferentiated

febrile

illness,

(ii)patient’s

non-care

seekingbehaviour,

(iii)pooraccessto

health

facility,(iv)low

specificity

of

case

classification,(v)average

acceptabilityofthesystem

,(vi)reportinglimited

topublicsector,

certain

age

groupsorinpatients

only.

Tim

elines

could

beim

proved

by(i)avoidingdouble

reportingandcompiling,(ii)

analysingdata

atalllevels,

(iii)electronic

reporting.

Recommendations:

a)A

simple

andstandardised

case

definition

b)Theestablishmentof

criteria

forselecting

patients

forvirus

circulationto

increase

its

representativeness;

c)Theestablishmentofactive

virologicalandserological

surveillance

d)Feedback

ofdata

reported

should

beim

proved

e)Developmentofaccurate

triggersthatwillallow

the

earlyresponse

to

epidem

ics;

f)Researchondevelopmentof

indicators

foroutbreak

prediction;

g)Developmentofalgorithm

foroutbreakdeclaration




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

26.NovartiI

2010

Indonesia

WestJavain

JavaIsland

andLampung

inSumatera

Island.

Passivepopulation-

basedreporting

system

.Active

surveillance

system

insomesentinel

primary

healthcare

Sem

i-structured

interviewswith

key

inform

ants

andsecondary

data

analysis

Aim

:to

explore

theexisting

surveillance

system

and

analyse

programme

response

Passivereportingof

denguecases.

Nodata

available

onhow

many

per

cents

ofthereported

caseswerelaboratory

confirm

ed.Virological

surveillance

only

for

researchpurpose.

Hospital:Clinical

examination(fever,rash/

torniquet

test)+

thrombocytopenia+

Haem

agglutinationtest

positivefordengueor

NS1

Outbreak:Increasing

casesbytw

ofoldsor

more

compare

withsame

periodoflast

yearora

new

case

ataplace

wheretherewereno

denguecasespreviously.

Sensitivity:casesreported

from

hospitalonly

in30%

reached

thedistricthealthoffice

Sensitivityforalert:excess

reportingin

interepidem

icsessionusuallybeusedasan

earlyalert.

Falsealert:non-experienced

applyingthethreshold

before.

Tim

eliness:

3–4

weeks

Usefulness:

fornational


detectiontoolate

Preparedness:

No

contingency

plansoralert

algorithmsavailable.

Response:Nolinkage

betweenroutinecontroland

transm

issions.

Data

quality:incomplete

data

are

themain

problem

Representativeness:

Dengue

patients

seekingtreatm

entat

thehealthfacilities

estimated

only

30%.


-Low

sensitivityis

dueto

(i)

low

userrate,(ii)clinical

examinationonly,(iii)not

allhealthfacilities

report

the

casesto

publichealth

authorities.

-Tim

elinessisregarded

toolate

topredictoutbreaks

-Tim

elinessanddata

quality

could

beim

proved

by(i)

simple

data

form

,(ii)data

analysisincludinglowest

possible

level,(iii)also

private

healthcentres

should

report

allsuspectedcases

(iv)integrateddata

reporting

Other

recommendations:

a)Case

classificationistoo

insensitive.

b)Studyonhealth-seeking

behaviourandtreatm

ent

response

aswellas

perceptionsofhealthstaff

regardingdenguecasesand

denguesurveillance

c)Commonunderstandingon

purpose

andobjectives

of

thesurveillance

system

sby

allstakeholders

d)Data

flow

andreporting

lines

more

consistent

e)Further

researchon

appropriate

thresholds/

alert

indicators

isneeded




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

27.Aishath

Aroona

Abdulla2011

outbreak

Maldives

Objectiveofthe

surveillance

system

notclearlydefined.

Passivepopulation-

wide,

integrated,

manualreporting

system

.Sofarnot

clearlymandatory.

Evaluationbased

on7interviews

andsecondary

data

analysis.

To

identify

room

for

improvem

ent

after

the2011

outbreak.

Dailyreportingofclinical

suspected/confirm

eddenguepatients

via

fax,

E-m

ail,telephone

accordingto

Communicable

Disease

NotificationForm

(varies

from

hospitalto

hospital)

inpaediatric

andinternal

healthfacilities.

Old

WHO

case

definition.

Laboratory

rarely

available.Nooutbreak

definitionapplied.

Sensitivity:Reportingrate

of

selected

hospitalin

Mai

2011:54%,lower

for

outpatients,mildandadult

cases.

Sensitivityofalert:Cases

wereabovetheprevious

meansince

Decem

ber

2010.

Shootingupthanaround

week25in

2011.Outbreak

declarationthen

beginningof

June2011

Tim

elinessofcase

notification:upto

4days

Usefulness:

Formonitoring

yes,foroutbreakdetection

threshold/trigger

wasmissing-

late

alert.

Representativeness:

Variable

dueto

atollscommitment

Acceptability:Low

atall

levels

-Late

disseminationofdata

-Littledata

analysiscapacity


-Agreeonspecificobjectives

forsurveillance

-Changeto

thenew

WHO

case

classification(2011)

-Revisereportingform

,include

instructionsandharm

onise

them

.

-Reportingneedsto

be

mandatory

-Implementlaboratory

componentandeventually

surveillance

-Manualreportingshould

be

electronicallywherever

possible

-Regulartrainingespeciallyon

case

reportinganddata

analysisandoutbreak

detection

-Earlierdata

dissemination

-Regularevaluationofthe

system




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

D.Low

andnon-endem

iccountriesmonitoringofim

ported

cases,

detectionofau

tochthonoustran

smission

28.Gobbi

Federico

(2012)Italy

VenetoRegion

In2010,aspecial

surveillance

forWest

Nilevirus(W

NV),

denguevirus

(DENV),and

chikungunyavirus

(CHIK

V)was

initiatedin

the

VenetoRegionof

north-easternItaly.

The(pilotstudy)

surveillance

had2

main

objectives.

To(i)increase

the

detectionrate

of

imported

CHIK

VandDENV

intravellers

and

identify

autochthonous

cases,

(ii)detect

autochthonous

casesofWNF

Possible

casesdetectedby

generalphysiciansand

emergency

department

physicianshadto

be

referred

within

24hto

theclosest

Unitof

InfectiousorTropical

Diseases.

Serum

samples

weresentto

theregional

reference

laboratory

(Padua,Italy)for

confirm

ation.

Suspected:Fever

>38°C

duringthepast

7daysin

atravellerwhohad

returned

within

the

previous15daysfrom

an

endem

iccountry,absence

ofleucocytosisandother

obviouscausesoffever.

Probale

=NS1rapid

test

positive.

Confirm

ed:

PCR,SerologyorNT

positive

Of79possible

cases,

we

detected14casesofDENV

infectionand1case

of

CHIK

Vinfectionamong

travellers

withfever.No

casesweresevere.

No

autochthonouscase

offever

causedbyDENV

hasbeen

documentedin

Italy.


Theproportionofvirus-

positivepatients

was

strikingly

high:�2

0%

of

personstested

whohad

imported

fever

werepositive

forDENV

orCHIK

V,as

were10%

ofpersonswith

locallyacquired

feversfor

WNV.Comparedwiththe2

previousyears,thespecial

surveillance

enableddetection

ofsubstantiallymore

cases,

showingthatyouonly

find

whatyouare

lookingfor.

Thesuccessofthis

pilot

phase

promptedregional

authorities

topropose

a3-

yearplanaspart

ofthe

integratedsurveillance

of

arboviraldiseases,

alongwith

anim

alandentomologic

surveillance




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

29.Gjenero

Marganet

al.

(2011)Croatia

Enhancedsurveillance

andsurvey

after

alert

byIH

R.Routine

reportingnotstated.

Presumably

not

mandatory,passive.

Case

study:

Theinform

ation

aboutareturning

Germantraveller

received

from

RKI(30.09.11)

onthefirst

autochthonous

case

ofdengue

fever

wassentto

theWorldHealth

Organization

(WHO)via

the

International

Health

Regulations

(IHR)

inform

ation

network.

Acirculatory

letter

inform

ingallservices

and

hospitalinfectology

clinicsin

thecountryto

consider

thepossibilityof

denguefever

inclinically

compatible

cases

includingthose

withno

history

oftravelling.14

bloodsamplesfrom

neighbours

and112from

anonymouspatents

were

examined.

Notstated

-Inthefollowingweeks,

a

number

ofclinicallysuspect

caseswerereported,and

serum

samplesweretested

negativefordenguevirus.

-22October

2010,apossible

case

ofdenguefever

was

reported

inaresidentof

thesamevillagewherethe

Germanpatienthadstayed,

then

confirm

edbypaired

sera

withincrease

inIgM

andIgG.

-From

the14samples,

nine

werepositiveforIgG

and7

hadpositiveorborderline

resultsforIgM

-From

the112samples,

6had

positiveIgG

(5.4%)andfive

positiveorborderlineIgM.


-After

France,Croatiaisthe

secondcountryin

Europein

whichautochthonous

transm

issionafter

1927/28

inGreece.

-Althoughuntilrecently

denguefever

wasnota

notifiable

disease

inCroatia,

itisunlikelyservices

would

havemissedtheoccurrence

ofaconfirm

edcase

of

imported

denguefever.

-Each

cluster

ofinfectious

diseasesisreported

usingthe

nationalcommunicable

diseasesearlywarning

system

:Duringsummer

2010,therewerenosuch

reportsfrom

Pelje� sac.

Only

fouroftheDENV-positive

villagerscontacted

health

services

forfebrile

illnessin

August

andSeptember

and

werenotrecognised

asan

outbreak.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

30.RucheG

laet

al.(2010)

France

1)Passiveroutine

reporting

2)Enhanced

surveillance

(Mayto

Novem

ber)since

2006

3)Laboratory

surveillance

system

(most

sensitive)

Case

study

describingthe

firsttw

oautochthonous

casesin

France

andpublichealth

measures

subsequently

implemented.

Laboratory

surveillance

detected350–4

00

imported

denguecases

/year(2006–2

009).In

thesameperiod,

enhancedsurveillance

reported

33im

ported

denguecases.

Between

1.5

-17.9.2010,120

imported

casesofdengue

havebeenreported

bythe


system

(11-fold

increase)

Notstated

-Case

one:

Nice(23.08.2010):

detectedbyenhanced

surveillance

-Case

two:Nice(11.09.2010):

70m

from

thefirstcase,

hospitalisedforfever

of

unknownorigin.

-Level

2ofthenational

contingency

planwas

activatedafter

thefirstcase:

-Level

3wasactivatedafter

thecluster

wasidentified


-Theeventwasnotunexpected

andaspecificpreparedness

plantimelydeveloped.

-Thehighvectordensity

in

Niceandtheincrease

inthe

number

ofim

ported

cases

(dueto

theepidem

icin

French

WestIndies)

are

two

majorfactors

-Thereactivesurveillance

in

additionto

theroutine


is

likelyto

identify

new

symptomaticcasesin

the

area.

-This

eventshowsthe

advantageofpreparedness

inorder

toim

plementrapid

andproportionate

measures

ofsurveillance

andresponse.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

31.Hyo-Soon

Yoo(2009)

Korea2001–

2006

Passivepopulation-

basedsurveillance

system

.

Theaim

wasto

identify

the

timelinessof

KoreanNational

Notifiable

Disease

Surveillance

System

(NNDSS).

TheNDDSisanelectronic

(since

2000)reporting

system

covering50

diseases(in4categories)

since

2008organised

at

threelevels:

local,

provincialandcentral.

Reportingisexpected

within

1(group1+4)or

7(group2+3)days.

Notstated

-Themediantimefrom

disease

onsetto

notificationto

KCDC

ranged

between6

and20days.

-Themediantimefrom

onset

toregistrationatthelocal

level

ranged

between2and

15days.

-Most

timelagsarose

from

a

delayin

diagnosis,

especiallyfortyphoid

fever

(T1,10days),denguefever

(T1,10days)

and

shigellosis(T1,5days).

Denguefever

that

represents

GroupIV

showed

thelongestdelay

primarily

dueto

delaysin

both

stepsofdiagnosis(T1)

anddoctor’sreport

(T2).


Tim

efrom

disease

onsetto

diagnosisgenerally

contributedmost

tothedelay

inreporting.

-Electronic

reportingsystem

s

canbeanim

portantmeans

toenhance

timeliness.

-Oneofthemain

reasonsfor

thevariationin

reporting

amongdifferentdiseasesis

theclinicalcharacteristics

of

thediseasessuch

asmodeof

onsetandseverity.

-Thenecessity

fortime-

consuminglaboratory

tests

fordiagnosismayalsodelay

reporting




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

32.Mei-M

eiKuan(2010)

Taiw

an1998–

2007

In2003,active

surveillance

for

denguewas

integratedinto

the

airport

fever

screeningprogramme

toreduce

the

importationofDENV

strains.

This

studyaim

edto

examinethe

epidem

iological

trendsandthe

impact

of

imported

cases

andairport

fever

screeningon

community

transm

ission.The

impact

of

implementing

airport

fever

screeningwas

evaluated.

During1998–2

002,airport

screeningforDENV

was

implementedin

theform

ofaquestionnairefilled

outbyallpassengers.

Followingthermal

scanningbynon-contact

infraredthermometersto

detectthose

whose

body

temperature

was

>37.58°C

,blood

samplesweretested

by

molecularand/or

serologicaldiagnosis.

Imported

cases:

cases

reported

bylocalclinics

orairport

fever

screening

withatravel

history

intheprevious2weeks,

whereastheindigenous

casesweredefined

as

casesreported

bylocal

clinicswithoutanytravel

history.

-Atotalof10351dengue

cases,

including(7.1%

imported)between1998

and2007.

-Themajority

ofindigenous

denguecases(98.5%)were

significantlyclustered

in

southernTaiw

an;62.9%

-PeakseasonwasSeptto

Nov.

-Airport

fever

screeningwas

successfulin

identifying

45%

ofim

ported

dengue

caseswithfever.

-Nostatisticalim

pact

on

communitytransm

ission

comparingpresence

and

absence

ofairport

fever

screening.

-Denguecasesappearedto

be

positivelyassociatedwith

populationdensity

(RID

–PD

=0.4–0

.6)andpopulation

number

(RID

–PN

=0.5–0

.7)

intheepidem

icyears

of

2002,2006and2007.


-55.0%

(298/542)ofim

ported

casesweretemporary,non-

febrile,thatis,latentcases,

undetectedbyairport

fever

screening.

-50–9

0%

ofdengueinfection

casesare

asymptomatic,

and

therefore,transm

issionof

DENV

into

Taiw

anvia

incomingtravellers

maybe

inevitable.

-Theefficacy

ofscreening

symptomaticpassengers

passingthroughTaiw

an

airportsbyNCIT

wasfound

tohaveaPPV

=30.5–

62.6%

when

fever

prevalence

among

passengerswas<1%.

-Theeffect

onmitigating

communitytransm

issionin

dengueepidem

icswasnot

significantlydifferent

betweenpre-2003border

controlmethodsandpost-

2003methods(fever

screening).




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

33.Chien-C

hou

Lin

etal.

(2009)

Taiw

an2002–

2007

1)hospital-based

reportingsystem

and

hospitalsyndrome

reportingsystem

for

viralhaem

orrhagic

fever.

2)Activesurveillance

system

s(individual

self-suspectedreports,

expanded

epidem

iological

contact

surveys,

school

andcommunity

screeningsystem

s,

airport

fever

screening).

Unlikesero-

epidem

iological

studies,

thedata

presentedin

this

studywere

derived

from

routinediagnosis

andanalysed

anonymously.

Report

completedwithin

6–2

4hthen

online

available

forthelocal

healthbureauand

hospital.Once

thecase

isconfirm

ed,sheetis

completedbythelocal

healthbureauorhospital.

Staff

willvisitand

interview

theindex

case.

Bloodsampleswillbe

drawnfrom

contacts

within

aradiusof50

metres,

those

whomay

havehadcontact

orhad

fever.

Aconfirm

eddenguecase

isdefined

as(i)positivefor

denguevirusisolation;or

(ii)positivefordengue

virusgenomebyRT-

PCR;or(iii)positivefor

denguevirus-specificIgM

andIgG

inasingle

serum

sample,or(iv)fourfold

increase

ofIgG

antibody

inpaired

samples.

First

indigenousindex

case

usuallyoccurs

MayorJune,

imported

from

South-East

Asia.

-Eventually,theoutbreakthen

spreadsoutgraduallyand

peaksaroundOctober

and

endingin

thewinter.

-3to

~6denguevirusstrains

imported

andlocally

transm

ittedeach

year.Only

onestrain

ofserotypehas

dominatedin

each

year.

-This

patternhasbeen

repeatedyearly-42150

bloodsamplesweredrawn

forserologicalanalysis,

of

which1.1%

(464/42150)

werefoundto

bedengue

virusinfected.All464

personsdid

notfeel

sick

enoughto

goto

thehospital

formedicaltreatm

ent.

-Ratioofsymptomaticto

asymptomaticcasesis

1.78

(64%/36%)


-Denguein

Taiw

anisanadult

infectiousdisease;elderly

havehighmorbidityand

mortality

rates.

-Secondary

infectionincreases

thedisease

severity,butnot

mortality,dengue-infected

adultsare

more

symptomatic.

-Thetransm

issioncyclein

Taiw

anisunique,

beginning

withim

portationin

the

summer

andendingin

the

winter.

-Most

(64%)ofthedengue-

infected

personsshowed

clinicalsymptomsafter

DENV-1

/DENV-3

infection.

-Severedisease

canbecaused

bysecondary

infectionwith

DENV-2

orprimary

infectionwithDENV-1

or

DENV-3.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

34.HuangJyh-

Hsiunget

al.

(2007)2005

Taiw

an

(i)passive(hospital-

basedreporting)and

(ii)active(fever

screeningatairports,

self-reporting,

screeningforcontacts

ofconfirm

edcases,

patients

withfever

of

unknownorigin,

school-based

reporting)

surveillance

system

s.

Presentationofthe

resultsofa

laboratory-based

dengue

surveillance

and

phylogenetic

studyin

Taiw

an

for2005.Human

samplesused

werederived

from

confirm

eddenguecases

submittedto

the

Taiw

anCDC

in2005.

Dengueisacategory

2reportable

infectious

disease

inTaiw

an.

Suspectedcasesmust

be

reported

within

24h

usingtheold

WHO

classificationschem

e.Surveillance

system

sare

established

bycentraland

localhealthdepartments

inTaiw

an.

Laboratory

diagnosis:

InfectionwithDENV

wasdefined

asafebrile

illnessassociatedwiththe

detectionofDENV-

specificIgM

andIgG

antibodies,

isolationof

DENV

ordetectionof

DENV

RNA

byreverse-

transcription–p

olymerase

chain

reaction(R

T-PCR).

-Atotalof104laboratory-

confirm

edim

ported

dengue

caseswereidentified

in

Taiw

anduring2005,46

(44.2%)caseswere

identified

byfever

screening

atairports.

-Sim

ilarto

thefindingsofour

previousstudy,Indonesia,

Vietnam,thePhilippines

and

Thailandwerethemost

frequentim

portingcountries

-Atotalof202laboratory-

confirm

edindigenous

denguecaseswererecorded

inTaiw

anduring2005.12

DENV-1,othersDENV-3

(twostrains)

andDENV-2.


-Laboratory-baseddengue

surveillance

system

to

identify

febrile

patients

at

theairportsbyaninfrared

thermalscanner.Most

(44

of46)oftheconfirm

edcases

identified

byairport

fever

screeningwerein

the

viraem

icstages.These34

caseswereidentified

ondays

1–3

after

onsetofillness.

-Incontrast,theim

ported

casesreported

from

passive

(hospital)surveillance

system

swereevenly

distributed1–2

0daysafter

theonsetofillness.

-Phylogenetic

analyses

suggestedthatthethree

epidem

icstrains,

DENV-3,

genotypeI,DENV-3,

genotypeIIandDENV-2,

American/AsianGenotype)

whichcocirculatedin

southernTaiw

anin

2005,

wererecentlyim

ported

from

thePhilippines

andVietnam,

respectively.




Table

1(C

ontinued)

Author

Publication

year,Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

35.ShuPei-

Yunet

al.

(2009)2003–

2007Taiw

an

(i)passive(hospital-

basedreporting)and

(ii)active(fever

screeningatairports,

self-reporting,

screeningforcontacts

ofconfirm

edcases,

patients

withfever

of

unknownorigin,

school-based

reporting)

surveillance

system

s.

Presentationofthe

resultsofa

laboratory-based

dengue

surveillance

and

phylogenetic

studyin

Taiw

an

for2003–2

007.

Humansamples

usedwerederived

from

confirm

eddenguecases

submittedto

the

Taiw

anCDC

in2003–2

007.

Dengueisacategory

2reportable

infectious

disease

inTaiw

an.

Suspectedcasesmust

be

reported

within

24h

usingtheold

WHO

classificationschem

e.Surveillance

system

sare

established

bycentraland

localhealthdepartments

inTaiw

an.

-Imported

denguecase

=infected

patienttravelling

abroad>2weeksbefore

theonsetofillness.

-Indigenouscase=when

overseastravel

isnot

indicated

-DENV

infection=febrile

illnesswiththedetection

ofDENV-specificIgM

and

IgG

antibodies,

the

isolationofDENV

byRT-

PCR.

-Atotalof542im

ported

denguecaseswereidentified

inTaiw

anduring2003–

2007.Amongthem

,17

(28.8%),57(62.6%),46

(44.2%),48(44.0%)and75

(41.9%)caseswere

identified

byfever

screening

atairportsfrom

atotalof

59,91,104,109and179

imported

casesfor2003,

2004,2005,2006and2007,

respectively.

-Withtheincreasingtrendof

imported

denguecases,

we

alsowitnessedlarger

dengueoutbreaksin

Taiw

anresultingin

965

and2000indigenous

denguecasesin

2006and

2007,respectively


->95%

oftheim

ported

patients

detectedbyfever

screeningatairportsare

in

theirviraem

icstage.

-Amongtheseim

ported

cases,

74%

caseswereidentified

ondays1–3

after

onsetof

illness.

-Incontrast,theim

ported

casesreported

from

passive

(hospital)surveillance

system

swereevenly

distributed1–2

0daysafter

theonsetofillness.

-thedistributionofthe

countriesoforigin

accurately

reflectedthefrequency

ofair

travel

betweenTaiw

anand

thesenations,

aswellas

dengueoutbreaksduringthe

sameperiodin

thecountryof

origin.

-Geographic

distributionof

strainsandgenotypes

of

DENV-3

isolatedfrom

South-East

Asiancountries

remain

unchanged

during

2003–2

007.

-However,themovem

entand

new

establishmentof

DENV-1,DENV-2

and

DENV-4

strainswere

observed

incertain

areasof

Asia.




Table

1(C

ontinued)

Author

Publication

year,

Study

population

Purpose

&type

(active/passive)

of

surveillance

Studydesign&

objectives

Development&

deliveryof

surveillance

system


definition



andrisk

ofbias

36.Mei

Mei

Kuanand

Feng-Y

eeChang(2012)

(2007–2

010)

Taiw

an

Theactivesurveillance

includes

fever

screeningatthe

airport

(since

2003)

within

others.

The

passivesurveillance

refers

tothehospital-

basedreporting

system

forthe

notificationofeither

imported

ordomestic

dengue

This

studyis

intended

toassess

theperform

ance

oftheairport

screening

proceduresfor

dengueinfection

Travellers

withathermal

NCIT-detected

temperature

ofhigher

than37.5

°Cwere

detained

attheentry

gate,rechecked

by

quarantineofficers

witha

survey

andreassessed

usinganear

thermometer.Travellers

withatemperature

above

38°C

weredefined

as

confirm

edfever

cases.

Confirm

eddenguecase

=positiveRNA,antigen

or

antibodybylaboratory

diagnoses.

Domestic

denguecase=confirm

edcase

nottravelledin

the

twoweekspriorto

the

onset.Im

ported

=confirm

edcase

travelled

toendem

iccountriestw

oweekspriorto

illness.

44.9%

(95%

CI:35.73–

54.13%)oftheconfirm

edim

ported

denguecaseswith

anapparentsymptom

(febrile)weredetectedvia

the

airport

fever

screening

programme,

withan

estimatedpositivepredictive

valueof2.36%

anda

negativepredictivevalue>

99.99%.Additionally,the

fluctuatingpatternsin

the

cumulativenumbersofthe

imported

denguecaseswith1

–2monthsleadtime(t)was

inparallel

withthatofthe

domesticdenguecasesbased

onaconsecutive4-year

surveillance.

Conclusions.

Thescreening

programmecould

assistin

therapid

triageforself-

quarantineofsome

symptomaticdenguecases

thatwerein

theviraem

icstageatthebordersand

contribute

toactivesentinel

surveillance;however,the

blockingofviraltransm

ission

tosusceptible

populations

(neighbours

orfamily)from

alloftheviraem

ictravellers,

includingthose

withor

withoutsymptoms,

iscritical

topreventdengueepidem

ics.

Therefore,thereinforcem

ent

ofmosquitobiteprevention

andhousehold

vectorcontrol

indengue-endem

icor

dengue-competenthotspots

duringanepidem

icseasonis

essentialandhighly

recommended.




Studies were grouped according to study types: models,

time-series, case studies, ecological studies, evaluations,

expert consensus, descriptive studies, prospective and ret-

rospective cohorts.

No studies were excluded in the analysis for quality

reasons if the eligibility criteria were met, and the limita-

tions and possible biases in such studies are reported in

the results section. The analysis grouped studies into four

categories based on the purpose of the surveillance

approach under investigation: (A) outbreak prediction/

detection; (B) trend monitoring; (C) both outbreak pre-

diction/detection and trend monitoring; and (D) low/non-

endemic countries.

Results

A total of 1116 studies, including duplicates, were identi-

fied during the electronic search as potentially relevant to

the research question. After screening of titles and

abstracts, 90 studies remained eligible. Full assessment of

the text eliminated 54 further studies, leaving 36 studies

included (Figure 1). Data of the 36 studies were extracted

to a table (Table 1), also assigning a unique identifier

number for each study.

When grouped according to purpose of the surveillance

system studied and compared with the 2008 review, an

increase in research interest in early outbreak detection

was apparent, particularly in endemic countries: (A) out-

break prediction or detection (14 studies/previously 5); (B)

monitoring dengue trends (4 studies/previously 6); (C) out-

break prediction and trend monitoring (9 studies/previ-

ously 7); and (D) non-endemic countries (9 studies/

previously 6). Within each of these categories, key compo-

nents essential for improving surveillance in endemic and

non-endemic countries were identified. The detailed find-

ings are summarised and presented in Table 1.

Studies retrieved for full text evaluation (n = 90)I (PubMed) = 44II (CDSR) = 0III (WHOLIS) = 0IV (EMBASE) = 21V (Lilacs) = 7

VI (Grey literature) = 18Reference lists of 72 publications were screened forrelevant citations, thesis and other grey literature wereanalysed as available (n = 87): fulltext assessment of 18additional documents, 2 papers could not be obtained.

Potential relevant citations identified by the search of databases. (n = 1116; including duplications and grey literature)I (PubMed) = 318II (CDSR) = 0III (WHOLIS) = 0IV (EMBASE) = 639V (Lilacs) = 72VI (Grey Literature) = 87

Citations excluded after 1 application of inclusion criteria (n = 1026)

a) Duplications n = 157b) Not fulfilling all inclusion

criteria judged by abstract n = 869

Studies excluded after evaluation of full text and application of inclusion and exclusion criteria from the systematic review (n = 54). The majority of the exclusions were made as not fulfilling criteria b) and c):

a) Population at risk b) Dengue disease surveillance c) Outcome of surveillance described d) Empirical data evaluated

Relevant studies included in systematic review: (n = 36)

Figure 1 Flow chart of articles included and excluded.




Surveillance systems for outbreak detection and/or

prediction (Groups A and C)

Most of these studies were from highly endemic settings

and were intended to predict or detect outbreaks at an

early stage.

Using electronic event-/search query-based surveillance

for early detection of increased dengue activity. Two

studies investigated the value of data quantifying the

numbers of internet searches seeking dengue information

in a number of countries (Bolivia, Brazil, India, Indonesia

and Singapore; studies 1 and 2), by comparing with epi-

demiological data from the surveillance system using

time-series analysis. The curve of the search queries over

time was similar to the epidemic curve constructed from

surveillance data, underlining the usefulness of this new

and relatively simple approach. Study 13 used a real-time

electronic approach based on Health Map in order to

enhance timeliness and outbreak detection and to provide

an added value for monitoring the ongoing spread of

dengue.

Using the appearance of a new dengue serotype/genotype

as an alert signal for dengue outbreaks. Six studies inves-

tigated serotype changes as a dengue outbreak signal

(studies 3–8) using virus surveillance information, analy-

sing laboratory data (genotyped or sequenced data) or

hospital data (severity of cases) and examining how these

correlated with the number of reported cases or dengue

incidence. Five of these studies (3–7) also analysed

whether a serotype shift or a clade replacement was

positively associated with a subsequent epidemic. The

sixth study investigated the correlation between

population-wide serotype-specific data and an increase in

cases (study 8) and showed that outbreaks occurred

following the introduction of new serotypes in specific

islands.

Examining these studies in detail, retrospective studies

in Singapore (studies 3, 5) found that a serotype switch

from DENV-2 to DENV-1 in 2004/2005 was associated

with the 2005 epidemic. However, according to Schreiber

(study 6), viral genome sequencing would not have been

sufficient to predict this outbreak. A switch from DENV-1

back to DENV-2 in early 2007 was used as a warning sign

and led to response actions that were believed to have

reduced the impact of an outbreak 6 months later. A clade

replacement within DENV-2 was also considered a con-

tributing factor to the 2007 Singapore outbreak (study 3)

and another outbreak at the end of 2010 (study 4).

Similarly, three surveys in Surabaya (Indonesia) investi-

gated prospectively the correlation of DENV type and

disease incidence. Here, an increase in case numbers in

2010 was attributed to a genotype shift in DENV-1 from

genotype IV to I between April and September 2009 (study

7). Retrospective analysis of serotype-specific surveillance

data in the Pacific region (study 8) demonstrated that the

rapid replacement of DENV-1 by DENV-4 in the region

was associated with dengue outbreaks in 2008 and 2009

in Kiribati, New Caledonia, Samoa, Tonga and other

islands.

Using syndromic surveillance to create alert signals for

dengue outbreaks. Five studies investigated the value of

syndromic surveillance for early outbreak detection.

These included a comparison of community-based fever

surveillance with surveillance of school absenteeism in

Peru (study 9) and two studies in French Guiana (studies

10 and 12) that described the advantages of reporting

dengue cases using a syndromic case definition compared

with routine reporting. These two French Guiana studies

and another in Madagascar (study 14) used sentinel sites

and reported higher sensitivity and outbreak early warn-

ing capacity compared with the routine reporting systems

(which were based on laboratory surveillance and passive

case reporting). Studies 10 and 12 highlighted the need

for maintaining the traditional surveillance and consider-

ing the increased potential for false alerts in syndromic

surveillance systems.

The prospective study in Peru indicated that commu-

nity door-to-door fever surveillance had higher sensitivity

than school absenteeism records as an indicator for den-

gue (study 9); the community-based fever cohort captured

twice as many cases as the school-based approach.

In French Guiana (study 10), the syndromic clinical

surveillance in a military population and the routine

laboratory reporting systems were found to be comple-

mentary: the syndromic approach detected an outbreak

3–4 weeks earlier and was six times more sensitive than

laboratory-based surveillance, but the specificity was

lower in the former. Further analysis (study 11) using

CDC criteria (CDC 2001) showed that the ideal report-

ing time was often not achieved due to barriers at data

entry and that an increased risk of false alerts needed

to be considered. However, all respondents perceived

that this system detected outbreaks adequately and sub-

sequent countrywide introduction of sentinel-based syn-

dromic reporting in French Guiana identified 80 signals

for confirmed cases and 64 for clinical cases and pre-

dicted three major epidemics (study 12). In Madagascar,

a sentinel-based syndromic surveillance system for six

diseases was evaluated: it detected ten outbreaks, five

were confirmed and two of which were dengue (study

14).




Use of other sentinel site-based approaches to increase

capacity for outbreak detection. Three studies analysed

sentinels sites for early outbreak warning, either in the

form of sentinel-based reporting and virus surveillance

(Cambodia, study 20) or for non-endemic countries (stud-

ies 22, 23, see group D below). One study described an

enhanced routine surveillance system in Puerto Rico by

motivating public health staff, which resulted in an

increase in reported dengue incidence three times above

the incidence during the two most recent epidemics in

1994 and 1998 (study 21). In Cambodia, passive surveil-

lance plus sentinel site surveillance including virus surveil-

lance increased the sensitivity of detecting outbreaks

(defined as numbers of cases exceeding two standard

deviations [SD] above the mean) although the response

was delayed, mainly due to inadequate financial manage-

ment (study 24).

In Europe, ten new strains of dengue viruses were

detected in travellers returning from Africa, and increased

observation of dengue in travellers by surveillance net-

works (TropNetEurop) was correlated with outbreaks

documented in national data (study 23).

Surveillance for describing endemic⁄epidemic trends

(Group B and C)

These surveillance systems under investigation were

mostly population-based and passive. Some included

additional sentinel sites or virus surveillance but they

were used only to monitor viral trends and were not

applied to early warning.

Four cohort-based studies calculated the level of und-

erreporting, either using capture–recapture approaches

comparing two independent surveillance systems or by

comparing cohort-based data with the national routine

reporting. The expansion factor indicating the level of

underreporting was calculated to be:

• 14–28 times in Nicaragua for a paediatric cohort

(study 15)

• 8.7 times in Thailand (2.6 times for hospitalised

cases) (study 16)

• 9.1 times in Cambodia (1.4 for hospitalised cases)

(study 16, 18)

• 3.9–29 times in Cambodia following a capture–recapture analysis (study 17)

• 1.1–2.4 times in Cambodia following a capture–recapture analysis of hospitalised cases (study 17)

The results demonstrated remarkably high levels of

underreporting in the surveillance systems, particularly

for non-hospitalised cases. It was a common experience

that a large proportion of the affected population was

not captured by passive routine reporting (e.g. non-users

of health services, users of private/traditional sectors or

certain age groups (e.g. adults in Cambodia).

Four evaluations of routine dengue surveillance systems

(studies 24–27) in 6 countries (Brazil, Bolivia, Cambodia,

Indonesia, Maldives and Thailand) were conducted using

a similar protocol for evaluations based on CDC Guide-

lines (CDC 2001). Both trend monitoring and outbreak

detection were evaluated. All evaluations found that a

clear understanding of the objectives of the surveillance

system by all stakeholders was crucial. The routine

reporting systems – some of them with laboratory sup-

port – were perceived to be useful for trend monitoring

and national planning but, as they did not apply appro-

priate thresholds/alert signals or include additional sur-

veillance components, they had little capacity for early

outbreak detection. In particular, reporting timeliness

was perceived to be low, ranging from a few days for

notification in the Maldives (study 27) to six to seven

weeks until data analysis in Cambodia (study 24). More-

over, the responses were delayed, as shown in the Mal-

dives, where no threshold for taking action was

implemented, and in Cambodia, where lack of sufficient

financial management and other constraints undermined

any response to the alert signal of ‘increased transmission

(above two SD) in low transmission season’. In Thailand,

where the system relied exclusively on clinically con-

firmed cases, respondents felt that outbreak responses

were delayed because decision-makers did not trust the

data and feared false alerts (study 24). All evaluations

reported that timeliness could have been increased by

electronic reporting or simplified reporting forms and

that data analysis should have been performed at the

lowest possible level (e.g. every district, once per week),

given that sufficient capacity was available.

Dengue surveillance in low⁄non-endemic countries (Group

D)

The value or effectiveness of primarily laboratory-sup-

ported active dengue surveillance systems in non-endemic

settings was described in several studies from Asia and

Europe. Timeliness of the system and laboratory support

were reported to be crucial elements.

Three European studies described the recent detection

of dengue in France (study 30) and in Croatia (study 29)

and imported dengue cases in Italy (study 28). In Croatia,

the notification of returning travellers led to the detection

of autochthonous cases, while survey-based investigations

revealed additional cases (29).

An evaluation of routine reporting in Korea (study 31)

reported a 2- to 15-day delay from disease onset to




reporting, which was shortened when electronic reporting

components were introduced.

Four studies from Taiwan (studies 32–36) demon-

strated the effectiveness of linking routine reporting with

strong laboratory support and active and syndromic

reporting elements in monitoring epidemiological,

virological and clinical trends. Airport fever screening

(studies 32 and 36) detected around 45% of imported

dengue cases, but any impact this might have had on

subsequent autochthonous transmission could not be

determined.

Discussion

Key findings

A greater number of the studies included in the present

study (19/36) were performed in Asia than in the Ameri-

cas (8/36; previously 17/24), illustrating a shift in

research attention to Asia from the Americas since the

2008 review, when 17 and 6 studies, respectively, of 24

were recorded. In the present study, four studies (4/36)

had a global focus, one study was from Africa and three

studies were from Europe, most likely reflecting the glo-

bal spread of, and consequent interest in, dengue disease

in these regions in recent years.

Tools for trend monitoring (Group B and C), and as

baseline for ‘excess reporting’ for outbreak detection

The surveillance systems deployed for this purpose were

mainly population-based and passive. Some included

additional sentinel sites or virus surveillance, but in those

cases, the data were used only to monitor viral trends

and were not applied to early warning. Four cohort-based

prospective studies calculated an expansion factor with a

range between 1.1 and 2.6 for inpatients in Cambodia

and Thailand, respectively, and between 3.9 and 29 in

Cambodian, Nicaraguan and Thai cohorts for non-hospi-

talised cases.

The results demonstrate remarkable levels of underre-

porting in the surveillance systems, particularly for non-

hospitalised cases. It was a common experience that a

large proportion of the affected population was not cap-

tured by passive routine reporting (e.g. non-users of

health services, users of private/traditional sectors or cer-

tain age groups, e.g. adults in Cambodia). However,

while less than satisfactory, this does not mean that such

a system is entirely inadequate, because as long as it is

accurately reflecting the disease trend, it may still be used

effectively as a baseline for detecting excess reporting

(e.g. more than 2xSD above the mean of the previous

5 years) and thus outbreak detection. In the context of a

public health system, it is not clear how sensitive surveil-

lance data need to be (i.e. what is an acceptable level of

under-reporting) in order to fulfil the dual purposes of

reflecting disease trends accurately and providing a base-

line for outbreak early alert. The studies reviewed here

indicated that underreporting to a limited extent can be

tolerated in high endemic settings, as long as the data are

geographically representative and, ideally, laboratory

confirmed as dengue. The calculation of an expansion

factor enables a more accurate value for the national bur-

den of disease, which is important for targeting public

health measures and advocacy.

In the earlier systematic review, the sensitivity of the

DF/DHF/DSS case classification was considered to be too

low (studies 20, 24–26), especially for DHF cases (Ban-

dyopadhyay et al. 2006). With the new WHO dengue

case classification, described in the WHO dengue guide-

lines (World Health Organization and the Special Pro-

gramme for Research and Training in Tropical Diseases

(TDR) 2009) and the Handbook on Clinical Manage-

ment of Dengue (WHO 2012), this problem has been

overcome, because the new WHO dengue case classifica-

tion classifies according to disease severity, permitting

more sensitive reporting of severe disease and allowing

comparison of data across all regions (Barniol et al.

2010, Horstick et al. 2012, Horstick et al. 2014) as

described in study 27.

Four evaluations of routine dengue surveillance systems

(studies 24–27) in 6 countries (Brazil, Bolivia, Cambodia,

Indonesia, Maldives and Thailand) were conducted using

similar protocols for trend monitoring and outbreak

detection, based on the CDC Guidelines (CDC 2001).

However, all evaluations found that a clear understand-

ing of the objectives of the surveillance system by all

stakeholders was crucial. All routine reporting systems,

with or without laboratory support, were perceived to be

useful for trend monitoring and national planning. How-

ever, without the use of appropriate thresholds or alert

signals or additional surveillance components to increase

timeliness or sensitivity (e.g. as sentinel sites or syndromic

surveillance components), they had little capacity for

early outbreak detection. Improvements indicated by the

evaluations were not exploited.

An appropriate alert signal with a defined threshold

level (‘trigger’) for initiation of a response is crucial for

any system. None of the reviewed studies investigated the

specific threshold for excess reporting within a routine

surveillance system. However, analysis of the included

articles suggested that in general, an excess of reported

cases (pattern recognition technique; Buehler et al. 2004)

– identified through a population-based routine surveil-




lance system – has potential for dengue outbreak predic-

tion. Studies that evaluate sensitivity, specificity and posi-

tive predictive values of such a threshold are likely to be

particularly valuable.

Throughout the studies, reporting time was slow, and

without any threshold, responses were delayed while

poor financial management and lack of trust in the data

by decision-makers hindered further the delivery of

adequate and timely response measures. Despite that,

all evaluations reported that timeliness could have been

increased by electronic reporting or the use of simplified

reporting forms and that data analysis should have been

performed at the lowest possible level (e.g. once per

week in every district) if sufficient capacity was

available.

In summary, the country evaluations consistently high-

lighted that immediate improvement is possible using a

number of options, many of which are already available

and easily implementable: (i) simplified data forms/data

entry protocols/electronic-based reporting, (ii) clearly

defined and easily understood system objectives, (iii)

appropriate and regular/frequent data analysis at the low-

est possible level (iv) and regular data feedback from top

to bottom levels. As evidence becomes available, two

additional components will be required to complete the

model: (i) clearly defined and locally appropriate triggers

for an outbreak response (no studies were found explor-

ing the optimal sensitivity and specificity of such thresh-

olds) and (ii) implementation of evidence-based response

strategies.

Alert signals1 (triggers/indicators/thresholds) for epidemic

response (Group A, C and D)

Predicting outbreaks through the introduction or shift of

a dengue sero-/genotype: six studies (studies 3–8) investi-gated serotype changes as a dengue outbreak signal dem-

onstrated a positive correlation with the number of

reported cases or dengue incidence, although the lag

times could extend up to 6 months. However, viral gen-

ome sequencing alone would, according to Schreiber

(study 6), not have been sufficient to predict an outbreak.

But these events are highly site-specific and are influ-

enced by herd immunity, population size, co-circulation

of additional dengue viruses and potentially numerous

other factors. Moreover, only those countries with reli-

able serotype-/genotype-specific surveillance would be

able to monitor changes in any patterns. Genotypic shifts

were used as an early warning signal in Singapore prior

to the 2007 epidemic and initiated an early response

(study 3). Taking into consideration the possibility that

publication bias (i.e. that only positive results are likely

to be published) would have excluded additional studies

where serotype shifts were not associated with subse-

quent outbreaks and that numerous potential confound-

ing factors would have been possible in all studies, it is

not yet possible to draw any firm conclusions on the

value of this as a measure in surveillance. Nonetheless,

the sensitivity, specificity and positive predictive value of

this parameter merit evaluation in prospective and com-

parative studies.

Predicting or detecting dengue outbreaks by syndromic

surveillance data: Five studies investigated the value of

syndromic surveillance for early outbreak detection.

These included a comparison of community-based fever

surveillance with school absenteeism in Peru (study 9),

and two studies in French Guiana (studies 10 and 12)

describing the advantages of reporting dengue cases using

a syndromic case definition as compared to routine

reporting. The prospective study in Peru indicated that

community door-to-door fever surveillance had higher

sensitivity than school absenteeism records. In French

Guiana (study 10), the syndromic approach detected an

outbreak 3–4 weeks earlier and was six times more sensi-

tive than laboratory-based surveillance, but specificity

was lower. However, in another study in French Guiana

(11), the ideal reporting time of 60 min for a real-time

syndromic surveillance approach was often not achieved

due to barriers at data entry, while a risk of false alerts

was expected, given the high sensitivity of the system. In

Madagascar (14) and French Guiana (12), syndromic sen-

tinel-based surveillance built on clinical syndromic case

definitions showed promising results, increasing the sensi-

tivity of dengue case detection in comparison with rou-

tine reporting and allowing the early detection of

epidemic events.

Two studies investigated the value of data quantifying

internet searches for dengue information carried out in a

number of countries (Bolivia, Brazil, India, Indonesia and

Singapore; studies 1 and 2). The curve of the search que-

ries over time was similar to the epidemic curve con-

structed from surveillance data underlining the usefulness

of this new and remarkably simple approach. Study 13

used a real-time electronic event-based approach based

1

Alert signals for an unexpected increase in dengue case numbers

(an ‘outbreak’) could include signals from within the denguetime series itself, or signals from external indicators associated

with changes in dengue transmission. Other indicators (addi-

tional to the increase in cases) could be considered as indicators

for a dengue outbreak. (Note: ‘Alert signals’ – also called alarmsignals – are indicators that, at a defined threshold, are intended

to ‘trigger’ a response).




on Health Map to enhance timeliness, outbreak discovery

and provide an added value for monitoring the ongoing

spread of dengue.

A number of studies that were included in the earlier

2008 review also dealt with this topic; in summary, the

following syndromic surveillance-based indicators were

identified:

• Proportion of virologically confirmed cases (study 3,

Rigau-P�erez & Clark 2005)

• Malaria negative rate in fever patients in a malaria

endemic areas (Carme et al. 2003, Talarmin et al.

2000)

• Fever alerts (Pirard et al. 1997; Kourı et al. 1998)

• Clinical syndromic case definitions (study 10, 11, 12

and 14)

• School absenteeism (study 9)

• Google search queries or event-based surveillance

(Study 1, 2 and 13)

Fever alert for the purpose of outbreak detection was

not found to be useful in Cuba and Bolivia (Pirard et al.

1997; Kourı et al. 1998). None of the studies included in

this update analysed syndromic surveillance based on lab-

oratory parameters or the proportion of virologically con-

firmed cases. One study from Singapore (study 3)

mentioned that during the 2007/2008 epidemic, the pro-

portion of DENV-positive samples detected by PCR rose

from 57.9% in January 2007 to 91.0% in July 2007 at

the peak of transmission. A similar trend has been shown

in Puerto Rico previously (Rigau-P�erez & Clark 2005).

In summary, detection of increases in proportions of

positive tested samples and quantification of electronic

search queries are both promising approaches to dengue

outbreak detection. They are inexpensive and offer near

real-time data and their value for operational use should

be considered and investigated. Syndromic surveillance

based on a clinical case definition remains a complemen-

tary tool to national routine reporting.

Limitations

The main limitation of this review was its restriction to

English, German and Spanish. However, as the bulk of

literature accessible on electronic databases today is

indexed in English by title and abstract, and no addi-

tional articles in other languages were found during the

extensive search, the impact of a language bias is likely

to be limited. While publication bias is a potential con-

cern, by screening carefully the reference lists of assessed

articles and grey literature, the bias has been reduced.

A ‘research hot spot’ in Singapore and Taiwan was

identified: these two countries accounted for 10 of the

total of 36 studies, potentially introducing some level of

bias in the overall assessment of the published literature.

Potential for bias also may have occurred with respect to

the evidence demonstrating an association between newly

introduced dengue serotypes and subsequent outbreaks

(see below), because no studies reporting the absence of

any association (i.e. new serotypes not followed by an

increase in dengue; a phenomenon that is arguably, less

likely to be published) were found.

Two key knowledge gaps were identified: none of the

studies investigated whether the thresholds currently in

use for triggering an outbreak response were at an appro-

priate level of sensitivity or geographical scale, and none

indicated how outbreaks were distinguished from stan-

dard or ‘expected’ seasonal changes in transmission. Fur-

ther research in this area remains of the highest priority

and is strongly recommended.

Conclusions

Following the systematic review of the evidence of the

value or potential of various tools or approaches for

dengue outbreak prediction or trend monitoring, the

following conclusions can be drawn:

• Passive surveillance remains the backbone of disease

monitoring, also providing the baseline for outbreak

alert. All opportunities for improvement should be

exploited to ensure that disease trends are accurately

reflected. While underreporting could be tolerated to

a certain extent, further research will be required to

determine how much.

• The usefulness of the new dengue case classification

for epidemiological use should be evaluated, as it is

currently underway for its clinical use.

• Country evaluations of dengue surveillance systems

should be conducted and published following CDC

criteria.

• More research is necessary to identify appropriate

thresholds of excess reporting that can be used to

trigger an outbreak response; such studies must take

into account both the geographical scale as well as

the level of sensitivity.

• Appropriate additional alert signals need to be iden-

tified and tested and integrated risk assessment tools

need to be developed.

• Additional well-designed and well-implemented

enhancement tools (such as active surveillance com-

ponents, laboratory support or motivation strategies)

would strengthen surveillance.

• Shifts in dengue serotypes or genotype have consider-

able potential in dengue surveillance, and the value

of these data merits evaluation in prospective and




comparative studies. It is crucial that both negative

and positive results be published to overcome publi-

cation bias in favour of positive associations.

• Syndromic surveillance approaches have potential as

useful complementary tools offering increased timeli-

ness and sensitivity but with an increased risk of

false alerts. Further studies investigating laboratory

parameters (e.g. the proportion of confirmed-to-

requested laboratory tests) are also merited. Internet

searches or electronic event-based surveillance strate-

gies also show promise, although their operational

usefulness remains to be demonstrated.

• Further research on evidence-based response strate-

gies and cost-effectiveness is still needed.

Acknowledgement

The project was financially supported by a grant from

the European Commission (Grant Number m281803) to

the IDAMS network (International Research Consortium

on Dengue Risk Assessment, Management and Surveil-

lance) within the 7th Framework Programme of the

European Commission and by the Special Programme

for Research and Training in Tropical Diseases

(WHO-TDR).

References

General ReferencesBandyopadhyay S, Lum LC & Kroeger A (2006) Classifying den-

gue: a review of the difficulties in using the WHO case classifi-

cation for dengue haemorrhagic fever. Tropical Medicine and

International Health 11, 1238–1255.

Barniol J, Gaczkowski R, Barbato EV, et al. (2010) Usefulness

and applicability of the revised dengue case classification by

disease: multi-centre study in 18 countries. BMC Infectious

Diseases 11, 106.

Bhatt S, Gething PW, Brady OJ et al. (2013) The global distribu-

tion and burden of dengue. Nature, Doi:10.1038/nature12060.

Bowman LR, Runge-Ranzinger S & McCall PJ (2014) Assessing

the relationship between vector indices and dengue transmis-

sion: a systematic review of the evidence. PLoS NTDs, in

press

Buczak AL, Koshute PT, Babin SM, Feighner BH & Lewis SH

(2012) A data-driven epidemiological prediction method for

dengue outbreaks using local and remote sensing data. BMC

Medical Informatics and Decision Making 12, 124.

Buehler JW, Hopkins RS, Overhage JM, Sosin DM & Tong V

(2004) Framework for evaluating public health surveillance

systems for early detection of outbreaks. Morbidity and Mor-

tality Weekly Report 53, 1–11.Carme B, Sobesky M, Biard MH, Cotellon P, Aznar C & Fonta-

nella JM (2003) Non-specific alert system for dengue epidemic

outbreaks in areas of endemic malaria A hospital-based

evaluation in Cayenne (French Guiana). Epidemiology and

Infection 130, 93–100.

CDC (2001). Updated guidelines for evaluating public health

surveillance systems. Morbidity and Mortality Weekly Report

50, RR 13, 1–35Chen CC & Chang HC (2013) Predicting dengue outbreaks

using approximate entropy algorithm and pattern recognition.

Journal of Infection 67, 65–71.

Esu E, Lenhart A, Smith L & Horstick O (2010) Effectiveness of

peridomestic space spraying with insecticide on dengue trans-

mission; systematic review. Tropical medicine and interna-

tional health, 15, 619–631.

Harrington J, Kroeger A, Runge-Ranzinger S & O’Dempsey T

(2013) Detecting and responding to a dengue outbreak: evalu-

ation of existing strategies in country outbreak response plan-

ning. The Journal of Tropical Medicine, 2013, 9 pages, Article

ID 756832.

Henning KJ (2004). Overview of syndromic surveillance what

is syndromic surveillance? MMWR. Morbidity and Mortality

Weekly Report 53(Suppl); 5–11. http://www.cdc.gov/mmwr/

preview/mmwrhtml/su5301a3.htm (accessed 2 May 2014)

Horstick O, Runge Ranzinger S, Nathan MB & Kroeger A

(2010) Dengue vector-control services: how do they work? A

systematic literature review and country case studies. Transac-

tions of the Royal Society of Tropical Medicine and Hygiene

104, 379–386.Horstick O, Farrar J, Lum L et al. (2012) Reviewing the develop-

ment, evidence base and application of the revised dengue case

classification. Pathogens and Global Health, 106, 94–101(8).

Horstick O, Jaenisch T, Martinez E et al. (2014) Comparing the

usefulness of the 1997 and 2009 WHO dengue case classifica-

tion: a systematic literature review. Accepted AJTMH 2014

Kourı G, Guzman MG, Valdes L et al. (1998) Reemergence of

dengue in Cuba: a 1997 epidemic in Santiago de Cuba.

Emerging Infectious Diseases 4, 89–92.

Liberati A, Altman DG, Tetzlaff J, et al. (2009) The PRISMA

statement for reporting systematic reviews and meta-analyses

of studies that evaluate health care interventions: explanation

and elaboration. PLoS Med 6, e1000100.

Merlin T, Weston A & Tooher R (2009). Extending an evidence

hierarchy to include topics other than treatment: revising the

Australian ‘level of evidence’. BMC Medical Research Method-

ology. www.biomedcentral.com/1471-2288/9/34

NHMRC (2000). National Health and Medical Research Coun-

cil, How to use the evidence: assessment and application of

scientific evidence, February 2000. http://www.nhmrc.gov.au/

_files_nhmrc/publications/attachments/cp69.pdf

Pilger D, De Maesschalck M, Horstick O & San Martin JL

(2010). Dengue outbreak response: documented effective

interventions and evidence gaps. TropIKA Reviews. http://jour

nal.tropika.net/scielo.php?script=sci_arttext&pid=S2078-

86062010000100002&lng=en&nrm=iso (accessed 2 May

2014)

Pirard M, Lora J, Boelaert M, Gianella A & Van der Stuyft P

(1997) Desarrollo de un Sistema de Vigilancia para dengue en

Santa Cruz, Bolivia. Bol. Centif. De CENETROP XVI.




Racloz V, Ramsey R, Tong S & Hu W (2012) Surveillance of

dengue fever virus: a review of epidemiological models and

early warning systems. PLoS Neglected Tropical Diseases 6,

e1648.

Rigau-P�erez JG & Clark GG (2005) Como responder a una epi-

demia de dengue: vision global y experiencia en Puerto Rico.

Revista Panamericana de Salud P�ublica 17, 282–293.Runge Ranzinger S, Horstick O, Marx M & Kroeger A (2008)

Systematic Review: what does dengue disease surveillance con-

tribute to predicting and detecting outbreaks and describing

trends? Tropical Medicine and International Health, 13,

1022–1041.

Stroup DF, Williamson GD, Hendon JL & Karon JM (1989)

Detection of aberrations in the occurrence of notifiable

diseases surveillance data. Statistics in Medicine 8, 323–329.Talarmin A, Peneau C, Dussart P, et al. (2000) Surveillance of

dengue fever in French Guiana by monitoring the results of

negative malaria diagnoses. Epidemiology and Infection 125,

189–193.

World Health Organization and the Special Programme for

Research and Training in Tropical Diseases (TDR) (2009)

Dengue guidelines for diagnosis, treatment, prevention and

control: new edition. 147. ISBN: 9789241547871.

WHO (2012). Global Strategy for dengue prevention and control

2012–2020. http://apps.who.int/iris/bitstream/10665/75303/1/

9789241504034_eng.pdf (accessed 2 May 2014)

York Centre for Reviews and Dissemination (2001) Report for

undertaking systematic reviews of research on effectiveness.

http://www.york.ac.uk/inst/crd/report4.htm (accessed 2 May

2014).

References of included studies (in numerical order as

referenced in the text)

1 Chan EH, Sahai V, Conrad C & Brownstein JS (2011) Using

web search query data to monitor dengue epidemics: a new

model for neglected tropical disease surveillance. PLoS

Neglected Tropical Diseases 5, e1206.

2 Althouse BM, Ng YY & Cummings DAT (2011) Prediction

of dengue incidence using search query surveillance. PLoS

Neglected Tropical Diseases 5, e1258.

3 Lee K-S, Lai Y-L, Lo S et al. (2010). Dengue virus surveil-

lance for early warning Singapore. Emerging Infectious Dis-

eases 16. www.cdc.gov/eid

4 Lee K-S, Lo S, Tan SS-Y et al. (2012) Dengue virus surveil-

lance in Singapore reveals high viral diversity through multi-

ple introductions and in situ evolution. Infection Genetics

and Evolution 12, 77–85.5 Koh BK, Ng LC, Kita Y et al. (2008) The 2005 dengue epi-

demic in Singapore: epidemiology, prevention and control.

Annals Academy of Medicine Singapore 37, 538–545.

6 Schreiber MJ, Holmes EC, Ong SH et al. (2009) Genomic

epidemiology of a dengue virus epidemic in urban Singapore.

Journal of Virology, 83, 4163–4173.7 Yamanaka A, Mulyatno KC, Susilowati H, Hendrianto E &

Ginting AP (2011) Displacement of the predominant dengue

virus from type 2 to type 1 with a subsequent genotype shift

from IV to I in Surabaya, Indonesia 2008–2010. PLoS One

6, e27322.

8 Li D-s, Liu W, Guigon A, Mostyn C, Grant R & Aaskov J

(2010) Rapid displacement of dengue virus type 1 by type 4,

Pacific region 2007–2009. Emerging Infectious Diseases 16.

www.cdc.gov/eid.

9 Rocha C, Morrison AC, For SB et al. (2009) Comparison of

two active surveillance programs for the detection of clinical

dengue cases in Iquitos, Peru. The American Journal of

Tropical Medicine and Hygiene, 80, 656–660.10 Jean-Baptiste M, Herv�e C, Gaetan T et al. (2008) Value of

syndromic surveillance within the Armed Forces for early

warning during a dengue fever outbreak in French Guiana in

2006. BMC Medical Informatics and Decision Making 8, 29.

11 Jefferson H, Dupuy B, Chaudet H et al. (2008) Evaluation of

a syndromic surveillance for the early detection of outbreaks

among military personnel in a tropical country. Journal of

Public Health, 30, 375–383. Advance Access Publication 15

April 2008.

12 Flamand C, Quenel P, Ardillon V, Carvalho L, Bringay S &

Teisseire M (2011) The epidemiologic surveillance of den-

gue-fever in French Guiana: when achievements trigger

higher goals. In: User Centred Networked Health Care Vol.

169, 629–633. SeriesStudies in Health Technology and Infor-

matics Ebook. IOS Press 2011© 2011 European Federation

for Medical Informatics. All rights reserved. DOI:10.3233/

978-1-60750-806-9-629.

13 Hoen AG, Keller M, Verma AD, Buckeridge DL & Brown-

stein JS (2012) Electronic event–based surveillance for moni-

toring dengue, Latin America. Emerging Infectious Diseases

18. www.cdc.gov/eid.

14 Randrianasolo L, Raoelina Y, Ratsitorahina M et al. (2010)

Sentinel surveillance system for early outbreak detection in

Madagascar. BMC Public Health 10, 31. http://www.bio-

medcentral.com/1471-2458/10/31.

15 Standish K, Kuan G, Avil�es W, Balmaseda A & Harris E

(2010) High dengue case capture rate in four years of a

cohort study in Nicaragua compared to national surveillance

data. PLoS Neglected Tropical Diseases 4, e633.

16 Wichmann O, Yoon I-K, Vong S, Limkittikul K & Gibbons

RV (2011) Dengue in Thailand and Cambodia: an assessment

of the degree of underrecognized disease burden based on

reported cases. PLoS Neglected Tropical Diseases 5, e996.

17 Vong S, Goyet S, Ngan C et al. (2012) Under-recognition

and reporting of dengue in Cambodia: a capture–recaptureanalysis of the National Dengue Surveillance System. Epide-

miology and Infection, 140, 491–499.18 Vong S, Khieu V, Glass O et al. (2010) Dengue Incidence in

urban and rural Cambodia: results from population-based

active fever surveillance 2006–2008. PLoS Neglected Tropi-

cal Diseases 4, e903.

19 Beatty ME, Stone A, Fitzsimons DW, Hanna JN & Lam SK

(2010) Best practices in dengue surveillance: a report from

the Asia-Pacific and Americas Dengue Prevention Boards.

PLoS Neglected Tropical Diseases 4, e890.




20 Huy R, Buchy P, Conan A et al. (2010) National dengue sur-

veillance in Cambodia 1980–2008: epidemiological and viro-

logical trends and the impact of vector control. Bulletin of

the World Health Organization 88, 650–657.

21 Ramos MM, Arg€uello DF, Luxemburger C et al. (2008) Epi-

demiological and clinical observations on patients with den-

gue in Puerto Rico: results from the first year of enhanced

surveillance—June 2005–May 2006. The American Journal

of Tropical Medicine and Hygiene, 79, 123–127.22 Schwartz E, Weld LH, Wilder-Smith A et al. (2008) Season-

ality, annual trends, and characteristics of dengue among Ill

returned travelers 1997–2006. Emerging Infectious Diseases

14. www.cdc.gov/eid.

23 Domingo C, Niedrig M, Gascon J et al. (2011) Molecular

surveillance of circulating dengue genotypes through

European travelers. Journal of Travel Medicine 18, 183–

190.

24 Runge-Ranzinger S (2010). Is dengue disease surveillance

able to predict or detect outbreaks and initiate timely

response? Assessment of National Dengue Control Pro-

grammes in Thailand and Cambodia. Doctorate Thesis, Uni-

versity of Heidelberg.

25 Rediguieri CF (2009). Is dengue disease surveillance able to

predict or detect outbreaks in Brazil and Bolivia? Thesis:

Master of Science in International Health, University of Hei-

delberg

26 Isma NY(2010). Analysis of dengue surveillance system in

Indonesia: Is it effective to detect and predict outbreaks?

Thesis: Master of Science in International Health, University

of Heidelberg

27 Aishath AA (2011). An Evaluation of the Surveillance System

for Dengue virus infections in Maldives. Performed as a

major assignment for the course on Infectious Disease Sur-

veillance – EPID6470. Master of Clinical Epidemiology, Uni-

versity of Newcastle Australia.

28 Gobbi F, Barzon L, Capelli G et al. (2012) Surveillance for

West Nile, dengue, and chikungunya virus infections, Veneto

Region, Italy 2010. Emerging Infectious Diseases 18. www.

cdc.gov/eid.

29 Gjenero-Margan I, Aleraj B, Krajcar D et al. (2011). Autoch-

thonous dengue fever in Croatia, August–September 2010.

Euro Surveillance: Bulletin Europ�een sur les Maladies Trans-

missibles = European Communicable Disease Bulletin;16:

pii=19805. http://www.eurosurveillance.org/ViewArticle.

aspx?ArticleId=19805

30 Ruche L, Souar�es Y, Armengaud A et al. (2010). First two

autochthonous dengue virus infections in metropolitan

France, September 2010. Euro Surveillance: Bulletin Eu-

rop�een sur les Maladies Transmissibles = European Commu-

nicable Disease Bulletin; 15: pii=19676. http://www.

eurosurveillance.org/ViewArticle.aspx?ArticleId=19676

31 Yoo H-S, Park O, Park H-K et al. (2009). Timeliness of

national notifiable diseases surveillance system in Korea: a

cross-sectional study. http://www.biomedcentral.com/

1471-2458/9/93

32 Kuan M-M, Lin T, Chuang J-H & Wu H-S (2010) Epidemi-

ological trends and the effect of airport fever screening on

prevention of domestic dengue fever outbreaks in Taiwan

1998–2007. International Journal of Infectious Diseases 14,

e693–e697.33 Lin C-C, Huang Y-H, Shu P-Y et al. (2010) Characteristic

of dengue disease in Taiwan: 2002–2007. The American

Journal of Tropical Medicine and Hygiene, 82,

731–739.

34 Huang J-H, Liao T-L, Chang S-F et al. (2007) Laboratory-

based dengue surveillance in Taiwan 2005: a molecular epi-

demiologic study. The American Journal of Tropical Medi-

cine and Hygiene, 77, 903–909.

35 Shu P-Y, Su C-L, Liao T-L et al. (2009) Molecular character-

ization of dengue viruses imported into Taiwan during

2003–2007: geographic distribution and genotype shift. The

American Journal of Tropical Medicine and Hygiene, 80,

1039–1046.36 Kuan MM & Chang F-Y (2012). Airport sentinel surveil-

lance and entry quarantine for dengue infections following a

fever screening program in Taiwan. BMC Infectious Dis-

eases, 12:182. http://www.biomedcentral.com/1471-2334/12/

182

Corresponding Author Silvia Runge-Ranzinger, Special Programme for Research and Training in Tropical Diseases, World Health

Organization, Geneva, Switzerland. E-mail: [email protected]




Dengue disease surveillance: an updated systematic literature ......Dengue disease surveillance: an...

Documents

Transcript of Dengue disease surveillance: an updated systematic literature ......Dengue disease surveillance: an...