Climate-Based Models for Understanding and Forecasting Dengue Epidemics

Abstract

BackgroundDengue dynamics are driven by complex interactions between human-hosts, mosquito-vectors and viruses that are influenced by environmental and climatic factors. The objectives of this study were to analyze and model the relationships between climate, Aedes aegypti vectors and dengue outbreaks in Noumea (New Caledonia), and to provide an early warning system.Methodology/Principal FindingsEpidemiological and meteorological data were analyzed from 1971 to 2010 in Noumea. Entomological surveillance indices were available from March 2000 to December 2009. During epidemic years, the distribution of dengue cases was highly seasonal. The epidemic peak (March–April) lagged the warmest temperature by 1–2 months and was in phase with maximum precipitations, relative humidity and entomological indices. Significant inter-annual correlations were observed between the risk of outbreak and summertime temperature, precipitations or relative humidity but not ENSO. Climate-based multivariate non-linear models were developed to estimate the yearly risk of dengue outbreak in Noumea. The best explicative meteorological variables were the number of days with maximal temperature exceeding 32°C during January–February–March and the number of days with maximal relative humidity exceeding 95% during January. The best predictive variables were the maximal temperature in December and maximal relative humidity during October–November–December of the previous year. For a probability of dengue outbreak above 65% in leave-one-out cross validation, the explicative model predicted 94% of the epidemic years and 79% of the non epidemic years, and the predictive model 79% and 65%, respectively.Conclusions/SignificanceThe epidemic dynamics of dengue in Noumea were essentially driven by climate during the last forty years. Specific conditions based on maximal temperature and relative humidity thresholds were determinant in outbreaks occurrence. Their persistence was also crucial. An operational model that will enable health authorities to anticipate the outbreak risk was successfully developed. Similar models may be developed to improve dengue management in other countries.

Clinical Presentation of Dengue by Serotype and Year of Epidemic in Martinique

“…A recent publication showed that secondary DENV-2 infections could result from more virulent clades than others, depending on the serotype of the primary infecting serotype, DENV-1 or DENV-3. 21 Under these conditions, the development dynamics of epidemics, the function of the implicated genotypes, and the intervals between the successive epidemics, 22 the immune and genetic status of the population, 23 and other environmental factors such as the population density, 24 the climate and density of mosquitoes of the Aedes genus, 25 could create specific situations in each endemic region and thus create many confounding factors. This could explain the differences in results shown in various publications on the theme of clinical presentation by serotype.…”

Temporal analysis of the relationship between dengue and meteorological variables in the city of Rio de Janeiro, Brazil, 2001-2009

“…Several studies have reported a positive association between minimum temperature lagged by one month and dengue incidence 3,4,12,23,24 . Minimum temperature is thus a critical limiting factor in the development and maintenance of the vector population.…”

“…The variables used in these studies have been temperature, precipitation, relative humidity, wind velocity, and El Niño Southern Oscillation (ENSO) 2,3,4,5,6,7,8 . Studies have also evaluated dengue's relationship with socio-demographic and environmental variables in the municipality of Rio de Janeiro, Brazil, with a view to examining the effect of seasonal and annual factors on increases and decreases in dengue cases, as well as to make predictions 9,10,11,12 .…”

Modelización del efecto de la variabilidad climática local sobre la transmisión de dengue en Medellín (Colombia) mediante análisis de series temporales

“…A pesar de los diversos hallazgos sobre la asociación entre la transmisión del dengue y la precipitación, y de que en otros estudios no se ha observado tal relación (incluso se ha descrito como una relación no estacionaria y probablemente espuria) (37) Las demostraciones de la fuerte asociación entre la incidencia de dengue y los factores climáticos, han permitido la construcción de diversos modelos (15,(44)(45)(46). En particular, considerando las condiciones climáticas locales para un período de 11 años, en el presente estudio se desarrolló un modelo que captó los principales cambios en la tendencia en la incidencia de dengue en Medellín por efecto de la precipitación.…”