A Dynamic Model of Poliomyelitis Outbreaks:
Learning from the Past to Help Inform the Future
by Radboud J. Duintjer Tebbens, Mark A. Pallansch, Olen M. Kew, Victor M. Cáceres,
Roland W. Sutter, and Kimberly M. Thompson, American
Journal of Epidemiology 2005; 162(4):358-372 Technical Appendix
Abstract
Policy makers now face important questions regarding the tradeoffs among different
strategies to manage polio risks after they succeed with polio eradication.
To estimate the potential consequences of reintroductions of polioviruses and
the resulting outbreaks, we developed a dynamic disease transmission model that
can simulate many aspects of outbreaks for different post-eradication conditions.
We identify the issues related to prospective modeling of future outbreaks using
such a model, including the reality that predicting the conditions and the associated
model inputs accurately prior to future outbreaks remains challenging. We explore
the model’s behavior in the context of three recent outbreaks that resulted
from importation of poliovirus into previously polio-free countries and find
that the model reproduces reported data on the incidence of cases. We expect
that this model can provide important insights into the dynamics of future potential
polio outbreaks and in this way serve as a useful tool for risk assessment.
Correction to the printed article: The values for the proportion
of susceptible children who will eventually get infected due to secondary
OPV exposure from a mass immunization round inputs in Tables 2 and A5
should be 41.2% instead of 46.4%. The value for the proportion of susceptible
children who will eventually get infected due to secondary OPV exposure from
a response immunization round in a low-income country listed in Table
3 should be 0.56 instead of 0.60. In Figure 2, the epidemic curve should shift
to the right by 10 days on the x-axis such that the peak of over 1,700 cases
occurs on day 208 instead of day 197 (as shown above). None of these errors
change the conclusions or insights from the paper. See the corrected version
of the Figure 2 below.
Answers to frequently asked questions
What are the study’s main findings?
What are the study’s main recommendations?
Background on polio
What are the study’s main findings?
- Developing a dynamic model for polio outbreaks offers the ability to simulate
both historical and potential future outbreaks. The outbreak model reasonably
reproduced large polio outbreaks (Albania 1996, Netherlands 1992-1993), but
insufficient data somewhat limits the ability of the model to reproduce smaller
outbreaks (Dominican Republic 2000-2001).
- Uncertain inputs that drive the magnitude of outbreaks include: duration
of infectiousness of various types of immunes, relative infectiousness and
relative susceptibility of previously vaccinated persons (notably IPV vaccinees),
transmissibility of polioviruses in a given population (R0),
time between virus introduction and response drive, and population size and
structure.
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What are the study’s main recommendations?
- This model may help in the evaulation of post-eradication policy development
and evaluation. Analysts should appreciate the assumptions and uncertainties
involved in modeling outbreaks in an unknown prospective outbreak population
and strive to incorporate situation-specific inputs rather than the “average”
prospective inputs provided in this paper when the specifics become available.
- Clinical or expert judgment studies aimed at better characterization of
the ability of IPV vaccinees to participate in poliovirus transmission will
further improve utility of the model as a tool for post-eradication polio
risk management policies.
- Figure 2 (shown below) gives an example of a prospectively modeled outbreak
occurring after cessation of poliomyelitis vaccination in a hypothetical country.
This model assumes a low-income country with R0=13
and a population of 100 million people 5 years after cessation of all polio
immunizations and 10 years after stopping supplemental immunization activities.
Detection occurs as soon as the cumulative incidence reaches one paralytic
case, and the delay from detection to response is 70 days. The response scenarios
assume two immunization rounds at a 30-day interval covering 90% of all children
under age 5 years in 3 days. The ‘‘no response’’ curve
reaches a peak of over 1,700 cases on day 208. tOPV, trivalent oral polio
vaccine; mOPV, monovalent oral polio vaccine.

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