Transcript Document

Pandemic preparedness:
What can epidemiological modelling
offer policy?
Nim Arinaminpathy
Department of Zoology
University of Oxford
Talk plan
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Influenza: a background
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From today to emergence of a novel
influenza virus
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Antiviral drugs for control of pandemic
influenza
Influenza
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RNA virus
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Clinical manifestations:
Headache, sore throat, chills, fever,
myalgia, anorexia, malaise
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Transmission
By contact with respiratory droplets,
generated by coughing or sneezing
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Infectiousness
can start a day before symptoms and continue for 3 – 5 days
after symptoms developing in adults
The seasonal influenza burden
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Disease:
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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:
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Europe: flu accounts for ~10% of sick leave
Costs US estimated $90bn a year
Influenza family tree
Orthomyxoviridae
…
Influenza
From http://www.abc.net.au/health
Type
Subtype
A
B
…
H1N1
H3N2
C
Pandemic and seasonal influenza
Taken from www.en.influenza.pl
Social and economic disruption
Social and economic disruption
H5N1: Future pandemic?
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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
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Each human case is an opportunity for an
avian virus to adapt for human transmission
Antiviral drugs for pandemic control
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No vaccine for at least first 6 months
Oseltamivir (Tamiflu) is main antiviral drug of choice
UK stockpile:
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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
αλ
IT
γT
RT
S
(1-α)λ
    IT  I N 
IN
γN
RN
T   N , 0    1
A simple compartmental model
αλ
IT
γT
RT
S
(1-α)λ
IN
γN
U (t )  RT (t )  IT (t )  M
RN
1957 ‘Asian Flu’ pandemic
1100
Mortality data,
1957 England & Wales
1000
900
Number of deaths
800
700
600
500
30/11/57
22/02/58
400
300
200
100
0
0
20
40
60
80
100
Time (days)
120
140
160
180
200
1957 ‘Asian Flu’ pandemic
1100
Mortality data, 1957
England & Wales
Best fit, basic model
1000
900
Number of deaths
800
700
600
500
400
300
200
100
0
0
20
40
60
80
100
Time (days)
120
140
160
180
200
1957 ‘Asian Flu’ pandemic
1100
Mortality data, 1957
England & Wales
Best fit, basic model
30% antiviral coverage
1000
900
Number of deaths
800
700
600
500
400
300
200
100
0
0
20
40
60
80
100
Time (days)
120
140
160
180
200
1957 ‘Asian Flu’ pandemic
1100
Mortality data, 1957
England & Wales
Best fit, basic model
30% antiviral coverage
70% antiviral coverage
1000
900
Number of deaths
800
CFR
0.16%
700
600
R0
1.65
25% stockpile
exhausted
500
400
300
200
100
0
0
20
40
60
80
100
Time (days)
120
140
160
180
200
How many drugs are needed?
0.8
R = 3.0
0
0.7
‘Secondary’ effect
of mass antiviral
treatment is to
reduce the spread
of infection in the
community
R = 2.0
0
Minimum required stockpile
R = 1.5
0.6
0
0.5
0.4
Its strength
depends on
drug efficacy and
disease
transmissibility
0.3
0.2
0.1
0
0
0.2
0.4
0.6
AV coverage, 
0.8
1
Antiviral programmes
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By shortening infectious period and reducing
infectiousness, antiviral drugs can influence
the course of infection
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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.
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Priority shifts to protection from infection rather
than from illness.
The ‘social element’
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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
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Mathematical models can offer valuable insights into
disease control
Transmission dynamics are often fundamental to
epidemic outcomes and effects of interventions
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…sometimes offering counterintuitive results!
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However models always entail simplifications, often
about human behaviour (important factors)
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Effective pandemic preparedness could involve a
synergy between such models and the social
sciences