Pertussis remains a major epidemiological burden, accounting for roughly 300,000 deaths worldwide each year, most of them children. The early success of infant immunization programs in the 1950s and 1960s led to a substantial reduction in incidence and a sense of optimism that elimination of pertussis might be a achievable. Over the past two decades, however, documented outbreaks in a number of wellvaccinated populations has pointed out major gaps in our understanding of pertussis epidemiology, immunology, evolution, and control. The availability and use of various vaccines with poorly understood efficacy and immunity profiles contributes to the uncertainty. We propose to improve our understanding of these important determinants of pertussis transmission by splitting the problem into manageable units. By conducting a comprehensive, comparative testing of multiple alternative hypotheses on long-term, spatially replicated, and age-specific data from different countries in the pre-vaccine era, we will aim to pin down the duration of infection-derived immunity, the epidemiological impact of repeat infections, the role played by sub-clinical immune boosting, and the respective contributions of population demography, age-specific contacts, and seasonality. The next phase of research will aim to address the vaccine-specific aspects of the problem by focusing on countries with known vaccine usage (whole cell vs. acellular) and immunization schedules. The ultimate test of whether our understanding of pertussis has significantly advanced will be to explain an enigmatic body of data, namely the changing patterns of pertussis incidence in the US over the past thirty years. This work will rely heavily on the use of mathematical models of pertussis transmission and statistical methods for extracting information from data. A major ingredient in this project, therefore, is the development, use, and dissemination of novel methodological tools that will be implemented in open-source public software. Finally, we will bring together the intellectual fruits of this effort in order to develop optimal, cost-effective immunization policy.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01AI101155-03
Application #
8651879
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Taylor, Christopher E,
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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