A climate-driven and field data-assimilated population dynamics model of sand flies

作者：Kamil Erguler, Irene Pontiki, George Zittis, Yiannis Proestos, Vasiliki Christodoulou, Nikolaos Tsirigotakis, Μαρία Αντωνίου, Özge Erişöz Kasap, Bülent Alten, Jos Lelieveld · 发表于：Scientific Reports · 年份：2019 · DOI：10.1038/s41598-019-38994-w · 被引用次数：27 · 研究领域：Research on Leishmaniasis Studies、Trypanosoma species research and implications、Insect symbiosis and bacterial influences

Sand flies are responsible for the transmission of leishmaniasis, a neglected tropical disease claiming more than 50,000 lives annually. Leishmaniasis is an emerging health risk in tropical and Mediterranean countries as well as temperate regions in North America and Europe. There is an increasing demand for predicting population dynamics and spreading of sand flies to support management and control, yet phenotypic diversity and complex environmental dependence hamper model development. Here, we present the principles for developing predictive species-specific population dynamics models for important disease vectors. Based on these principles, we developed a sand fly population dynamics model with a generic structure where model parameters are inferred using a surveillance dataset collected from Greece and Cyprus. The model incorporates distinct life stages and explicit dependence on a carefully selected set of environmental variables. The model successfully replicates the observations and demonstrates high predictive capacity on the validation dataset from Turkey. The surveillance datasets inform about biological processes, even in the absence of laboratory experiments. Our findings suggest that the methodology can be applied to other vector species to predict abundance, control dispersion, and help to manage the global burden of vector-borne diseases.