Predic'ngpropaga'onofdenguewithhumanmobility:

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DanajaMaldeniya

Planningmee'ng:“Forecas'ngpropaga'onofdengue/zikainSriLanka

withMobileNetworkBigData”06May2016

ThisworkwascarriedoutwiththeaidofagrantfromtheInterna'onalDevelopmentResearchCentre,CanadaandtheDepartmentforInterna'onalDevelopmentUK..

APakistancasestudy

Theroleofhumanmobilityinspreadingdengue

•  Thedenguemosquitohasalifespanof2-4weeksandarangeless1km

•  Dengueisspreadbeyondthenaturalrangeofthemosquitobythemovementofinfectedhosts

•  AsaresultknowledgeofhumanmobilitypaWernscanshedlightonthepaWernofdenguepropaga'onandthelevelofdiseaseincidenceinaregion

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Outline•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons3

Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons4

Dengue in Pakistan

•  Firstconfirmedcasein1994inKarachi•  Priorto2008,majorityofcaseswereinKarachi

•  Sincethendenguehasbeenspreadingtootherregions.(Lahoreepidemicin2011)

•  PeakseasonoccursintheFall(October-November)

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Popula'onsandhumanmovementsinPakistan

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Popula'ondensityandmobilephonedataavailabilitybytehsil

TravelintensitybetweenKarachi,Lahore,andMingoraregions

Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons7

Amul'-disciplinaryresearcheffort

•  Collabora'onbetweenanumberofresearchgroupsaffiliatedwith,–  TelenorResearch–  HowardT.HChanSchoolofPublicHealth–  CenterofDiseaseControl–  OxfordUniversityclinicalresearchunit–  DepartmentofZoology,UniversityofPeshawar–  etc.

•  Leadauthor,AmyWeslowski,isaninfec'ousdiseaseepidemiologistwithpreviousexperienceonu'lizingmobilenetworkdataforepidemiologicalpurposes

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Research models spatial spread of dengue with human mobility across Pakistan as the primary

driver

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Themodelpredictsthe'mingofimporta'onofdenguefrom

endemicregions(Karachi)torestofthecountry

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Mapofepidemicriskbyevalua'ngclimatecondi'onsand

travelpaWerns

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Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons12

Data•  MobilephoneCDRdata

–  7monthsofCDRdatafromTelenorPakistanfromJunetoDecemberof2013(~40millionSIMs)

–  Onaverage28millionSIMsac'vedailywith15millionSIMsgenera'ngoutgoingcallswithloca'ondata

–  Coverageof352of388tehsilsofsub-districtsinPakistan

•  Denguedata–  De-iden'fieddailydenguecountsaggregatedtothetehsilsorsub-

districts

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Data...

•  Popula'ondata– Uptodatepopula'ones'matesatthetehsillevelfromworldpop.co.uk

•  Climatedata– Temperature&rela'vehumiditybasedontemperaturetakenfrom38weathersta'onsacrossPakistan

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Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons15

A clear distinction is made between endemic and naive

regions•  Karachiandsorroundingregionsinthesouthofthe

countrywereiden'fiedasbeingendemicregions•  Allotherregionsareassumedtobenaive.•  Theanalysisinpar'cularfocusesonthenorthernregions

ofLahoreandMingorainparttoevaluatetheeffec'venessofthisassump'on

•  Givena2011epidemic,Lahorewaslikelytohavebuiltupimmunityandalimiteddenguemosquitopopula'onby2013

•  Mingorawaseffec'velyanaiveregionin2013

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Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons17

Anexis'ngento-epidemiologicalmodelwasusedtomodeldiseasedynamicsinlocalizedregions

•  Themodelusestwosetsofrateordifferen'alequa'onstomodelhumananddenguemosquitopopula'ondynamics

•  Humanpopula'ondynamics– Suscep'ble->Exposed->Infected->Recovered– Atthestarttheen'repopula'onisconsideredimmunologicallynaïve(i.e.suscep'ble)

– Theexistenceofmul'plestrainsofthediseaseisignored

– Re-infec'onisignored(followsfromignoringmul'plestrains)

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Anexis'ngento-epidemiologicalmodel…

•  Denguemosquitopopula'ondynamics–  Suscep'ble->Exposed->Infected–  Elementsofthelife-cycleofthemosquitoisincorporated(Aqua'c->Adult)–  Oviposi'onrate(egglayingrate)–  carryingcapacityorsustainablemosquitopopula'onforaregion

limits

•  Modelconstantssuchini'almosquitopopula'onsandhost-vectorincidenceratesarederivedfromtemperaturebasedformulae

•  Otherconstantssuchasthesustainablemosquitopopula'on,bi'ngrateandrepor'ngrateswerees'matedusingsensi'vityanalysis

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Theuseofthemodelistwofold•  ModelisfittotheendemicregionofKarachistar'ngatDay1,toes'matedailyinfectednumberofpeopleover'mebasedonreportedcases–  Usedes'matelikelihoodofdengueimporta'onfromKarachitootherregionsonagivenday

•  Modelisfit(inreverse)tonaïveregionstoes'matethe'meintroduc'onofdenguefromoutsidesolelywithreportedcases.–  Usedtovalidatees'matesofdengueintroduc'onbasedonhumanmobilitypaWerns

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Weeklyreportedandes'mateddenguecasesinKarachi

Es'mateddateofintroduc'onofdenguetoMingoraandLahoreusingtheento-epidemiologicalmodelandreportedcases

Theore'calmodel

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humanpopula'ondynamics mosquitopopula'ondynamicsN-Suscep'blehumanpopula'onEh-Exposedindividualsλv→h–vectortohumanincidencerate1/γh-meanincuba'onperiod(days)Ih-Infectedindividuals1/σh-meandura'onofinfec'onRh-Recoveredindividuals

A-earlystagemosquitopopula'onV-Adultmosquitopopula'onSv-Suscep'blemosquitoesEv-Incuba'ngmosquitoes1/γv-meanincuba'onperiod(days)λh→v–humantovectorincidencerateIv-InfectedmosquitoesεA-rateofprogressiontomaturityμA

V-mortalityrateofearlystagemosquitoesμV

V-mortalityrateofadultmosquitoesK-sustainablemaximummosquitopopula'on

Es'ma'nghost-vectorincidenceratesandtransmission

probabili'es

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Es'ma'ngtemperaturedrivenconstantsofthedenguemosquito

lifecycle

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Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons25

CountrywidetravelpaWernsareextractedfromCDR

•  Foreachday,eachsubscriberinthedataisassignedtothehis/hermostfrequentlyobservedmobilephonetower

•  Travelises'matedeachdaybetweenmobilephonetowersbyconsideringasubscriber'sloca'onw.r.ttheirloca'onthepreviousday

•  Movementsareaggregatedatthetehsillevelbasedontheoriginanddes'na'onandnormalizedbythenumberofac'vesubscribersintheorigintehsil(flux)

•  Movementes'matesfortheperiod1stJanuaryto1stJuneweregeneratedbyassumingthesamemeannumberofnormalizednumberoftripsandaddingnoise

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Predic'ngimporta'onofdenguetonaiveregionsfromendemic

regionsthroughtravel•  Approximately30%ofthesubscribersinKarachitraveledoutsidedaily(β)

•  Themodelprovidesadailyes'mateofnumberofinfectedhostsinKarachi(mt)

•  Naïvees'mateofinfectedtravelers:mtβ

•  β isvariedbetween10%,20%and30%insimula'ons,toaccountforuncertaintyandlikelihoodofoveres'ma'ngtravelwithCDR27

Predic'ngimporta'onofdenguetonaiveregions…

•  Es'matedinfectedtravelersareappor'onedtodes'na'ontehsilsbasedonthepercentageofes'matedtraveltothosedes'na'ons

•  Thestateofinfec'onofan‘infected’hostisaspectrumduetoviraldynamics.ThisaffectstransmissionlikelihoodwhenbiWen– Viraldynamicsarenotdealtwithdirectly–  Insteadsimula'onsaredoneusingprobabili'estransmissionsampledfromaseriesofbinomialdistribu'onswithdifferentfixedprobabili'es(0.01to0.9)

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Predic'ngimporta'onofdenguetonaiveregions…

•  200simula'ondoneforeachcombina'onofthefrac'onofKarachipopula'ontravelingoutsideandthefixedtransmissionprobability

•  Themostlikelydateoffirstcaseofimporteddengueatthedes'na'onsises'matedfromresultsofthesimula'ons

•  Es'matespredominantlyaffectedbythenumberofpeopletravelingoutfromKarachiandisnotverysensi'vetotransmissionprobability 29

Es'matesdemonstrateaccuracyofmodelbutalsotheeffectofpriorepidemicsandimmunity

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Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons31

AmapofdengueepidemicriskwasdevelopedforPakistanby

combiningclima'csuitabilityandmobilitypaWerns

𝑟𝑖𝑠𝑘↓𝑒𝑝𝑖𝑑𝑒𝑚𝑖𝑐(𝑋) = ∑𝑡=1↑𝑁▒𝑍↓𝑋 ( 𝑇↓𝑡 ) 𝑌↓𝑋,𝑡  Where,𝑍↓𝑋  −𝑉𝑒𝑐𝑡𝑜𝑟 𝑠𝑢𝑖𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑎𝑡 𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 𝑋

𝑇↓𝑡  −𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒 𝑎𝑡 𝑋 𝑎𝑡 𝑡𝑖𝑚𝑒 𝑡𝑌↓𝑋,𝑡 −𝑡ℎ𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑖𝑛𝑓𝑒𝑐𝑡𝑒𝑑 𝑡𝑟𝑎𝑣𝑒𝑙𝑒𝑟𝑠 𝑎𝑟𝑟𝑖𝑣𝑖𝑛𝑔 𝑎𝑡 𝑋 𝑎𝑡 𝑡𝑖𝑚𝑒 𝑡

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Environmentsuitabilityfordenguemosquitoesisdrivenby

temperature 𝑍↓𝑋 (𝑇)= exp(−𝜇↓𝑉↑𝑉 (𝑇)𝛾↓𝑉↑𝑉 (𝑇))/𝜇↓𝑉↑𝑉 (𝑇)↑2  Where,𝑇 −𝑡𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒𝑍↓𝑋 (𝑇) −𝑆𝑢𝑖𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑎𝑡 𝑋

𝜇↓𝑉↑𝑉  − 𝑖𝑛𝑠𝑡𝑎𝑛𝑡𝑎𝑛𝑒𝑜𝑢𝑠 𝑑𝑒𝑎𝑡ℎ 𝑟𝑎𝑡𝑒 𝑜𝑓 𝑎𝑑𝑢𝑙𝑡 𝑓𝑒𝑚𝑎𝑙𝑒 𝑚𝑜𝑠𝑞𝑢𝑖𝑡𝑜𝑒𝑠𝛾↓𝑉↑𝑉  −𝑖𝑛𝑐𝑢𝑏𝑎𝑡𝑖𝑜𝑛 𝑝𝑒𝑟𝑖𝑜𝑑 𝑜𝑓 𝑑𝑒𝑛𝑔𝑢𝑒•  Suitabilityisarela'vequan'typropor'onaltothevectoralcapacity.•  Itisdifficulttoes'matevectoralcapacityduetolackofdataonfactorssuchas

humanbloodfeedingrateetc.

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Epidemicriskisdominatedbyimporta'onthroughtravel

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Outline

•  Background•  Introduc'ontocasestudy•  Data•  Methodology

-Ento-epidemiologicalmodel-Es'ma'nghumanmobility-Predic'onofdengueimporta'onusingtravelpaWerns-Epidemicriskmaps

•  Limita'ons35

Researchhighlightspoten'alvalueofhumanmobility

es'mates,butisnotwithoutissues

•  Thereisadisconnectbetweentheepidemiologicalmodelandthepredic'onofdengueintroduc'onthroughtravel

•  Ignoresexistenceofdiseaseserotypes(strains)•  Ignoreshistoryofdengueintheregionand

immunologicalcovariates•  Validityandalignmentoftemperaturebasedexpressions

forentomologicalproper'esfordengueinalocalcontext•  Mul'pleparameterses'matedthroughbruteforcesearch

(travelerpercentage,mosquitocarryingcapacity,bi'ngrateetc.)

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Issues…

•  Rela'velylowspa'alsamplingofweatherdata(38weathersta'ons,Pakistanisabout14'mesSriLankainarea)

•  Differencesbetweenairandwatertemperatures(alsomicroclimates?)

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Placementofweatherdatausedintheresearch

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Keydataandparametersthatmaydeterminethesuccessofsimilar

workinSriLanka•  Unitofspa'alanalysis-(MoHregion,basesta'oncoverage

region,DSD?)•  Accuratespa'o-temporaldataonreporteddenguecases

(daily?)•  Repor'ngrate(~100%inSL?)•  Regionaldenguepopula'ons•  Regionalserotypeprevalence•  Regionalimmunologicaldata/historicalcaseserotypes•  Entomologicalparametersacceptablefortheregion•  Spa'otemporalinforma'ononpreven'vemeasures?

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