Z Score,T Score, Percential Rank and Box Plot Graph
Working Life of Infectious Disease Models - Dr Erika Mansnerus
1. Working life of
infectious disease models
Dr Erika Mansnerus
London School of Economics
and Political Science
2. Working life of models
• Processes and practices when models are in use;
when they ‘make things happen’
• Working at a distance…
– Evidence eventually informs policy, can be contested
(e.g. Oreskes and Conway 2010 on Climate research)
• …Or very close
– Results taken into account prior to final publication
(case on measles modelling in the UK 1990s)
• Discursive space (Evans 2000)
– Dialogue with different actors in order to create
shared understanding
4. Why measles booster campaign?
• 1988: Introduction of the MMR triple vaccine
• Incidence of measles in England and Wales
declined to all time low
• Characteristic seasonal and 2-yearly cycles
have disappeared
• But, measles persists
– Should the single dose campaign be enough or is a
policy change justified?
5. 1994 National measles and rubella
campaign in the UK
• Why? - Meant to prevent an epidemic by vaccinating 95%
of 7 million schoolchildren (5-16 year olds)
• Cost-effectiveness of a preventive action
• Based on epidemiological surveillance data
– Serological studies
– Number of notified and confirmed cases
– Rates of complications and deaths
– Immunisation coverage
• Data used in two independent mathematical models that
predict high probability of a major “resurgence of measles”
– Resurgence result of poor vaccine coverage and vaccine failure
(Miller 1994)
6. Responding to policy
• Two independent models were built prior to
the introduction of the 1994 campaign
– 1) Gay, N., Hesketh, L., Morgan-Capner P., and E.
Miller (1995): WAIFW-model (who acquires
infection from whom)
– 2) Babad, H., Nokes, D., Gay, N., Miller, E, Morgan-
Capner P., and R.M. Anderson (1995): RAS-model
(a realistic age-structured measles transmission
model)
7. Interpreting data with WAIF-model
• Gay et al (1995): Models used to interpret
susceptibility data from the surveillance programme
and evaluate the potential for an epidemic.
• The population is divided into several age-groups and
the transmission rates between these groups are
derived from pre-vaccination case notification data.
• The transmission rates are combined with data
susceptibility in the population to generate a ‘next
generation matrix’ = WAIFW matrix (contains values
of the transmission rates between groups)
• Two different scenarios are modelled with different
reproduction rates
8. Outcomes from the WAIFW-model
• Increasing population of schoolchildren susceptible to
measles provided the potential for a major epidemic
of measles in the mid 1990s.
• This prediction was confirmed by using other data
(disease notifications from England and Wales 1993/4)
• The vaccination campaign is expected to have a
“dramatic effect” on susceptibility to measles
• New role for models in public health setting: applying
them to interpret serological surveillance data allows
the potential for an epidemic to be identified, and
provides time to plan and implement appropriate
interventions
9. The RAS-model
• A realistic, age-structured mathematical model of
measles transmission to reconstruct the impact of
measles vaccination in England and Wales from 1968
to the present and to evaluate the merits of future
policy options.
• Good agreement between the observation and
prediction, hence model is used to explore measles
epidemiology in the future under existing vaccination
strategy and a variety of alterations
• Notification data is ‘messy’: age-specific bias in
reporting; the proportion of misdiagnosed cases.
11. Outcomes from the RAS-model
• Predictive capacity of a mathematical model of the impact
of mass vaccination on the epidemiology of infectious
disease
• It has not been possible to fully account for the
discrepancies between the observed impact of vaccination
on measles and that predicted
• Model projections suggest that the current policy of
immunization may not be sufficient in to eliminate
measles
• One-off campaign targeted at school-age children would
reduce deficits in the herd immunity profile, depress the
potential for seasonal outbreaks, thus enhancing the effect
of current policy
12. Discussion: Benefits and limitations
• Able to interpret serological data and predict
outbreak
– Planning interventions before the outbreak
– Integrating various sources of evidence in the process
• Modelling along with decision-making feeds
results and evidence directly to the process
– Advice through modelling
• Not able to address vaccine compliance
• Discrepancy between observed and predicted
impact of vaccinations
13. Acknowledgements
• British Academy Post-Doctoral Fellowship held
jointly at CRASSH, and LSE Health (2009-2012)
• Health Protection Agency, Centre for
Infections, Colindale
• The National Institute for Health and
Welfare, Helsinki
