DIMACS Working Group on Methodologies for Comparing Vaccination Strategies

May 17 - 20, 2004
DIMACS Center, CoRE Building, Rutgers University

John Glasser, CDC, jwg3@cdc.gov
Herbert Hethcote, University of Iowa, herbert-hethcote@uiowa.edu
Presented under the auspices of the Special Focus on Computational and Mathematical Epidemiology.

Link to the DIMACS Workshop on Evolutionary Considerations in Vaccine Use, June 27 - 30, 2005.

This working group will focus on the use of mathematical modeling and computer simulations to provide theoretical comparisons of vaccination and other intervention programs. Examples of the effective use of modeling will be studied for vaccine-preventable diseases such as measles, rubella, varicella, pertussis, polio, Haemophilus influenza type b and pneumococcal, Hepatitis A and B, and Lyme disease. (See, e.g., [Garnett and Waddell (2000), Grenfell and Bolker (1998), Hethcote (1999), Rohani, Earn and Grenfell (2000), Schuette and Hethcote (1999)].) When vaccination strategies compare vaccination of different age groups, age-structured mathematical models are necessary. Computer simulations of these highly complex systems with hundreds of demographic and epidemiological classes allow comparisons of vaccination strategies and rapid evaluation of potential intervention programs when field trials would be prohibitively expensive. Both expected and worst case scenarios must be considered. We will bring working epidemiologists and policymakers together with experts in mathematical modeling and computer simulation in order to formulate and analyze models to deal with current problems and explore ways to simulate larger, more complex, more realistic models. It is likely that a subgroup of this working group will emphasize influenza. The persistence of influenza depends on its ability to evolve [Andreasen, Lin and Levin (1997), Gupta, Ferguson and Anderson (1998), Lin, Andreasen and Levin (1999)] so that new strains and subtypes of the virus appear and old ones reappear. This constant evolution means that vaccines need to be updated frequently and that resistance to drug therapies can easily arise. These issues make modeling difficult and require large, powerful computational methods to analyze the models. Some specific research issues to which the group will apply its methods are the following. How will varicella vaccination affect the incidence of shingles? Is acellular pertussis vaccinatiion of adolescents or adults more effective in reducing cases among infants than vaccination of children? Because the oral polio vaccine virus can mutate back to the wild virus, as occurred recently in the Caribbean and the Philippines, can polio be eradicated using the oral polio vaccine alone? How does the yearly composition of the influenza vaccine affect the drift of the influenza virus? We expect that this working group will spawn a separate group to develop and analyze models for vaccination strategies in the event of or in anticipation of bioterrorist attacks involving smallpox, anthrax, or influenza. Research issues here include: what are the risks/advantages of different smallpox vaccination strategies using existing supplies of the vaccine? How do the conclusions change if we dilute existing supplies so as to allow more people to be vaccinated but can only achieve a certain probability of protection or only a reduction of symptoms to treatable levels? How do vaccination strategies depend upon our ability to identify a spot smallpox epidemic? How do these conclusions change for diseases such as anthrax where transmission is not person-to-person? Recent work on smallpox and anthrax (e.g., [Kaufman, Meltzer and Schmid (1997), Meltzer, Damon, LeDuc and Millar (2001)]) will provide background for this work.


Andreasen, V., Lin, J., and Levin, S.A. (1997), "The dynamics of cocirculating influenza strains conferring partial cross-immunity," J. Math. Biol., 35, 825-842.

Garnett, G.P., and Waddell, H.C. (2000), "Public health paradoxes and the epidemiological impact of an HPV vaccine," J. Clin. Virol., 19, 101-111.

Grenfell, B.T., and Bolker, B.M. (1998), "Cities and villages: Infection hierarchies in a measles metapopulation," Ecol. Let., 1, 63-70.

Gupta, S., Ferguson, N., and Anderson, R. (1998), "Chaos, persistence, and evolution of strain structure in antigenically diverse infectious agents," Science, 280, 912-915.

Hethcote, H.W. (1999), "Simulations of pertussis epidemiology in the United States: Effects of adult booster doses," Math. Biosci., 158, 47-73.

Kaufman, A.F., Meltzer, M.I., and Schmid, G.P. (1997), "The economic impact of a bioterrorist attack: Are prevention and postattack intervention programs justificable?" Emerging Infectious Diseases, 3, http://www.cdc.gov/ncidod/eid/vol3no2/kaufman.htm

Lin, J., Andreasen, V., and Levin, S.A. (1999), "Dynamics of influenza A drift: the linear three-strain model," Math Biosci, 162, 33-51.

Meltzer, M.I., Damon, I., LeDuc, J.W., and Millar, J.D. (2001), "Modeling potential responses to smallpox as a bioterrorist weapon," Emerging Infectious Diseases, 7, http://www.cdc.gov/ncidod/EID/vol7no6/meltzer.htm

Rohani, P., Earn, D.J.D., and Grenfell, B.T. (2000), "Impact of immunisation on pertussis transmission in England and Wales," LANCET, 355, 285-286.

Schuette, M.C. and Hethcote, W.H. (1999), "Modeling the effects of varicella vaccination programs on the incidence of chickenpox and shingles," Bull. Math. Biol., 61, 1031-1064.

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Document last modified on March 10, 2004.