Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.7/56
Título: Heterogeneity in susceptibility to infection can explain high reinfection rates
Autor: Rodrigues, P.
Margheri, A.
Rebelo, C.
Gomes, M.G.M.
Palavras-chave: Partial immunity
Interventions
Tuberculosis
Models, Biological
Disease Susceptibility
Communicable Diseases/immunology
Data: Jul-2009
Citação: Rodrigues, P., Margheri, A., Rebelo, C., Gomes, M.G.M. (2009). "Heterogeneity in susceptibility to infection can explain high reinfection rates". Journal of Theoretical Biology. 259(2): 280-290
Resumo: Heterogeneity in susceptibility and infectivity is inherent to infectious disease transmission in nature. Here we are concerned with the formulation of mathematical models that capture the essence of heterogeneity while keeping a simple structure suitable of analytical treatment. We explore the consequences of host heterogeneity in the susceptibility to infection for epidemiological models for which immunity conferred by infection is partially protective, known as susceptible-infected-recovered-infected (SIRI) models. We analyze the impact of heterogeneity on disease prevalence and contrast the susceptibility profiles of the subpopulations at risk for primary infection and reinfection. We present a systematic study in the case of two frailty groups. We predict that the average rate of reinfection may be higher than the average rate of primary infection, which may seem paradoxical given that primary infection induces life-long partial protection. Infection generates a selection mechanism whereby fit individuals remain in S and frail individuals are transferred to R. If this effect is strong enough we have a scenario where, on average, the rate of reinfection is higher than the rate of primary infection even though each individual has a risk reduction following primary infection. This mechanism may explain high rates of tuberculosis reinfection recently reported. Finally, the enhanced benefits of vaccination strategies that target the high-risk groups are quantified.
URI: http://hdl.handle.net/10400.7/56
ISSN: 1095-8541
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