Spatially weak syncronization of spreading pattern between Aedes Albopictus and dengue fever

Tarteel Abdalgader, Malay Banerjee and Lai Zhang

Ecological Modelling, 2022, vol. 473, issue C

Abstract: Understanding the response of dengue fever to climate change remains a global public health concern. A rich array of mathematical models have been proposed to help estimate future population exposure and vulnerability. While these models have proved helpful in modeling mosquito distribution and/or revealing dengue transmission mechanism, they have rarely been incorporated into distribution estimates, particularly at large spatial and temporal scales, to evaluate dengue response to long-term environmental change. Here, we develop a novel mechanistic phenology model that explicitly describes the dengue epidemic process completion (DPEC) according to empirically derived responses to environmental conditions. Further, we apply this model to Aedes albopictus and dengue transmission in mainland China. We validate the model with recorded indigenous dengue cases, and reveal the power of model prediction. Results suggest that future temperature rise promotes geographic expansion of mosquitoes and dengue fever, respectively around 3–15% and 4–10% increment in the area by 2080, compared to nowadays. Results also indicate a more extended season (1–2 months increment) and stronger intensity (up to 4 DEPC increment) of dengue transmission by 2080. Most importantly, our model discloses a weak correlation between the spreading pattern of dengue and Aedes albopictus. Using the spatial expansion trend of mosquito to infer the risk of dengue to the human population is likely to bring about strong bias in spreading direction and/or overestimate dengue distribution. Our study paves a way to provide a useful tool and precise information for predicting dengue dynamics. It also helps design control strategies to prevent arbovirus outbreaks worldwide in areas colonized by Aedes mosquitoes.

Keywords: Aedes albopictus; Dengue fever; Indigenous dengue cases; Phenology model; Climate change (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:473:y:2022:i:c:s0304380022002241

DOI: 10.1016/j.ecolmodel.2022.110123

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