Pandemic preparedness:What can epidemiological modelling offer policy?Nim Arinaminpathy

Department of Zoology

University of Oxford

Talk plan

Influenza: a background

From today to emergence of a novel influenza virus

Antiviral drugs for control of pandemic influenza

Influenza

RNA virus

Clinical manifestations:Headache, sore throat, chills, fever, myalgia, anorexia, malaise

TransmissionBy contact with respiratory droplets, generated by coughing or sneezing

Infectiousnesscan start a day before symptoms and continue for 3 – 5 days after symptoms developing in adults

The seasonal influenza burden Disease:

5 – 15% of population affected with upper respiratory tract infections in annual ‘flu season

Estimated 3-4,000 annual deaths in UK caused by influenza infection (mainly elderly and immunocompromised)

The Economy: Europe: flu accounts for ~10% of sick leave Costs US estimated $90bn a year

Influenza family tree

Orthomyxoviridae

Influenza

A B C

H1N1H3N2

…

Type

Subtype

From http://www.abc.net.au/health

…

Pandemic and seasonal influenza

Taken from www.en.influenza.pl

Social and economic disruption

Social and economic disruption

H5N1: Future pandemic?

Wild bird reservoir Poultry Humans Transmitted from bird to human by inhaling dried aerosolised

faeces First major outbreak in 1997, Hong Kong Resurgence in 2003 has seen virus established in poultry in

South-East Asia So far human-to-human spread is non-existent or very limited 387 human cases, 245 deaths to date Wide geographical spread, from S.E.Asia (inc. Indonesia, Viet

Nam) to Africa (Nigeria, Egypt) However, H7N7 and N9N2 are also pandemic candidates

Evolution and emergence of pandemic influenza Each human case is an opportunity for an

avian virus to adapt for human transmission

Antiviral drugs for pandemic control No vaccine for at least first 6 months Oseltamivir (Tamiflu) is main antiviral drug of choice UK stockpile:

Currently enough for 25% of population Drugs intended mainly for treatment, not prophylaxis For all clinical cases

How best to minimise epidemic size and impact with a limited stockpile?

A simple compartmental model

, 0 1T N

S

IT

IN

RT

RN

γT

γN

αλ

(1-α)λ

T NI I

( ) ( ) ( )T TU t R t I t M

A simple compartmental model

S

IT

IN

RT

RN

γT

γN

αλ

(1-α)λ

1957 ‘Asian Flu’ pandemic

0 20 40 60 80 100 120 140 160 180 2000

100

200

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400

500

600

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800

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1000

1100

Time (days)

Num

ber o

f dea

ths

Mortality data,1957 England & Wales

30/11/5722/02/58

0 20 40 60 80 100 120 140 160 180 2000

100

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Time (days)

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Mortality data, 1957England & WalesBest fit, basic model

1957 ‘Asian Flu’ pandemic

0 20 40 60 80 100 120 140 160 180 2000

100

200

300

400

500

600

700

800

900

1000

1100

Time (days)

Num

ber o

f dea

ths

Mortality data, 1957England & WalesBest fit, basic model30% antiviral coverage

1957 ‘Asian Flu’ pandemic

0 20 40 60 80 100 120 140 160 180 2000

100

200

300

400

500

600

700

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Time (days)

Num

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f dea

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Mortality data, 1957England & WalesBest fit, basic model30% antiviral coverage70% antiviral coverage

25% stockpileexhausted

CFR 0.16%

R0

1.65

1957 ‘Asian Flu’ pandemic

How many drugs are needed?

0 0.2 0.4 0.6 0.8 10

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

AV coverage,

Min

imum

req

uire

d st

ockp

ile

R

0 = 3.0

R0 = 2.0

R0 = 1.5

‘Secondary’ effect of mass antiviral treatment is to reduce the spread of infection in the community

Its strength depends on drug efficacy and disease transmissibility

Antiviral programmes

By shortening infectious period and reducing infectiousness, antiviral drugs can influence the course of infection Broadening and delaying epidemic peak Reducing numbers of cases

If there is a risk-group for whom the drug has little protective effect, the stockpile is better deployed in the general population. Priority shifts to protection from infection rather

than from illness.

The ‘social element’

Potential wastage of drugs on the ‘worried well’

Personal stockpiles Non-compliance with treatment regime may

lead to drug resistance Pressing ethical questions, eg distributive

justice

Conclusions Mathematical models can offer valuable insights into

disease control Transmission dynamics are often fundamental to

epidemic outcomes and effects of interventions …sometimes offering counterintuitive results!

However models always entail simplifications, often about human behaviour (important factors)

Effective pandemic preparedness could involve a synergy between such models and the social sciences