Elimination and eradication

In 1997 a workshop on the Eradication of Infectious Diseases was held to discuss and define the terms elimination and eradication, identify lessons that can be learned from previous and current programs and develop the science of eradication. Mathematical models were discussed at this meeting, and their inference has been informative from the beginning. At that time, only smallpox had been eradicated after decades of intensive control efforts through use of vaccination and surveillance for outbreaks of this deadly disease. Other eradication programmes had failed; yellow fever, malaria, and yaws. Public health professionals became increasingly cautious to proclaim an eradication programme rather than one simply for control.

Since this time world has changed; there is new enthusiasm for eradication. In the 1980s polio was successfully eliminated from the Americas and enormous efforts have been undertaken to eradicate. In veterinary medicine rinderpest has not been reported in animals since 2006 and an intense serological surveillance program was necessary to confirm eradication. Guinea-worm disease is restricted only to 4 countries in sub-Saharan Africa. For some vector-borne diseases new control tools are becoming available and eradication is once again being discussed.

These exciting public health developments require an informed analysis to help support development of feasible elimination and eradication plans. Central to this is an understanding of the feasibility of eradication and mathematical modelling can have a role. Mathematical and statistical models can be used to inform;

  • The feasibility of moving from control to elimination
  • Whether an epidemic will die out within a period of time
  • The probability that transmission has been eliminated
  • How diagnostic tools and the extent of use affects inference on elimination.



Kathleen O’Reilly (theme co-ordinator), Paul FinePetra Klepac, Grace Macklin, Amy Pinsent, Richard White

Especially when there are multiple options for an intervention, it is possible to compare the interventions by estimating the the probability of each preferred outcome. Common to many of these themes is the use of data from outbreaks of infectious diseases to understand disease dynamics, and how they can be altered through control activities. The aim of this research theme is to:

Share knowledge and experiences in developing mathematical models for the purpose of informing elimination and eradication Develop and refine methodological approaches specific to elimination and eradication.