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Human birth seasonality: latitudinal gradient and interplay with childhood disease dynamics.
Martinez-Bakker, Micaela; Bakker, Kevin M; King, Aaron A; Rohani, Pejman.
Afiliación
  • Martinez-Bakker M; Department of Ecology and Evolutionary Biology, University of Michigan, , Ann Arbor, MI 48109, USA, Center for the Study of Complex Systems, University of Michigan, , Ann Arbor, MI 48109, USA, Department of Mathematics, University of Michigan, , Ann Arbor, MI 48109, USA, Fogarty International Center, National Institutes of Health, , Bethesda, MD 20892, USA.
Proc Biol Sci ; 281(1783): 20132438, 2014 May 22.
Article en En | MEDLINE | ID: mdl-24695423
More than a century of ecological studies have demonstrated the importance of demography in shaping spatial and temporal variation in population dynamics. Surprisingly, the impact of seasonal recruitment on infectious disease systems has received much less attention. Here, we present data encompassing 78 years of monthly natality in the USA, and reveal pronounced seasonality in birth rates, with geographical and temporal variation in both the peak birth timing and amplitude. The timing of annual birth pulses followed a latitudinal gradient, with northern states exhibiting spring/summer peaks and southern states exhibiting autumn peaks, a pattern we also observed throughout the Northern Hemisphere. Additionally, the amplitude of United States birth seasonality was more than twofold greater in southern states versus those in the north. Next, we examined the dynamical impact of birth seasonality on childhood disease incidence, using a mechanistic model of measles. Birth seasonality was found to have the potential to alter the magnitude and periodicity of epidemics, with the effect dependent on both birth peak timing and amplitude. In a simulation study, we fitted an susceptible-exposed-infected-recovered model to simulated data, and demonstrated that ignoring birth seasonality can bias the estimation of critical epidemiological parameters. Finally, we carried out statistical inference using historical measles incidence data from New York City. Our analyses did not identify the predicted systematic biases in parameter estimates. This may be owing to the well-known frequency-locking between measles epidemics and seasonal transmission rates, or may arise from substantial uncertainty in multiple model parameters and estimation stochasticity.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Estaciones del Año / Tasa de Natalidad / Epidemias / Sarampión Tipo de estudio: Incidence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Estaciones del Año / Tasa de Natalidad / Epidemias / Sarampión Tipo de estudio: Incidence_studies / Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Proc Biol Sci Asunto de la revista: BIOLOGIA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos