An overview of factors affecting dengue transmission in Asian region and its predictive models
Article Main
Abstract
Among various mosquito-borne diseases, dengue is one of the most prevalent and quickly spreading diseases primarily transmitted by Aedes aegypti and Aedes albopictus. This review discusses the dengue epidemics in Asian countries with a focus on India and recognizes various climatic, socio-economic, and demographic factors and their complex interaction, involved in dengue expansion. The impact of climatic factors, such as temperature, moisture, and precipitation has been elucidated on the mosquito breeding and disease outbreaks; demonstrating a linear correlation of ambient temperature and humidity with dengue transmission, in contrast with the uncertain association of rainfall. Multifarious empirical models have been developed for estimating the climatic effects on dengue and are used as a baseline to assess the impact on future infections. However, the spatiotemporal distribution of dengue cases can only be predicted best using dynamic modelling based on a blend of long-term climatic data, vector ecology, and multiple etiological parameters. The human economic profile, migration and the behavioural pattern towards the epidemic have also impacted dengue transmission. Moreover, the impoverished countries are facing higher risks due to the lack of resources for proper medical care and mosquito management measures. Thus, advanced and confirmatory vector control interventions increased awareness of Aedes-borne diseases, and adequate decisions and policies may play a key role to prepare and combat the disease incidences across varied geographic range. Moreover, the increasing support for the research and development along with regular monitoring can help recognize the current and predict future distributions of Aedes and DENV better.
Article Details
Article Details
Keywords
Aedes, Climate change, Dengue, Predicting models, Socio-economic factors
References
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An overview of factors affecting dengue transmission in Asian region and its predictive models. (2020). Journal of Applied and Natural Science, 12(3), 460-470. https://doi.org/10.31018/jans.v12i3.2360
