Dynamical malaria models reveal how immunity buffers effect of climate variability

• Autores: Laneri, Karina Fabiana; Paul, Richard E.; Tall, Adama; Faye, Joseph; Diene Sarr, Fatoumata; Sokhna, Cheikh; Trape, Jean François; Rodó, Xavier
• Año de publicación: 2015
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: CLIMATE; ENDEMICITY; IMMUNITY; PLASMODIUM FALCIPARUM MALARIA; VECTOR-BORNE DISEASES
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human-mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity.
Fil: Laneri, Karina Fabiana. Institut Catala de Ciencies del Clima; España. Comisión Nacional de Energía Atómica. Gerencia del Área de Investigaciones y Aplicaciones No Nucleares. Gerencia de Física (cab). División Física Estadística; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; Argentina
Fil: Paul, Richard E.. Institut Pasteur de Paris.; Francia. Centre National de la Recherche Scientifique; Francia
Fil: Tall, Adama. Institut Pasteur de Dakar; Senegal
Fil: Faye, Joseph. Institut Pasteur de Dakar; Senegal
Fil: Diene Sarr, Fatoumata. Institut Pasteur de Dakar; Senegal
Fil: Sokhna, Cheikh. Institut de Recherche Pour Le Developement; Senegal
Fil: Trape, Jean François. Institut de Recherche Pour Le Developement; Senegal
Fil: Rodó, Xavier. Institut Catala de Ciencies del Clima; España. Institució Catalana de Recerca i Estudis Avancats; España