ArticleScientific reports2019
A climate-driven and field data-assimilated population dynamics model of sand flies.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Chandipura Virus: An Emerging Neurological Threat Transmitted by Sandflies in India.Immunity, inflammation and disease · 2026Review
- Vectors on the Move: How Climate Change Fuels the Spread of Arboviruses in Europe.Microorganisms · 2025Review
- Chandipura Virus Resurgence in India: Insights Into Diagnostic Tools, Antiviral Development, and Public Health Implications.Global health, epidemiology and genomics · 2025Review
- Mitigating climate change impacts on health: a comparative analysis of strategies in Saudi Arabia and Lebanon.Frontiers in public health · 2025Article
- Toscana virus - an emerging Mediterranean arbovirus transmitted by sand flies.The Journal of general virology · 2024Review
- The potential of climatic suitability indicator for Leishmania transmission modelling in Europe: insights and suggested directions.The Lancet regional health. Europe · 2024Article
- Mapping the distribution of sandflies and sandfly-associated pathogens in China.PLoS neglected tropical diseases · 2024Article
- Modelling spatiotemporal patterns of visceral leishmaniasis incidence in two endemic states in India using environment, bioclimatic and demographic data, 2013-2022.PLoS neglected tropical diseases · 2024Article
- Current Status of Omics Studies Elucidating the Features of Reproductive Biology in Blood-Feeding Insects.Insects · 2023Review
- Entomological surveillance and spatiotemporal risk assessment of sand fly-borne diseases in Cyprus.Current research in parasitology & vector-borne diseases · 2023Article
- A dynamically structured matrix population model for insect life histories observed under variable environmental conditions.Scientific reports · 2022Article
- Sand flies: Basic information on the vectors of leishmaniasis and their interactions with Leishmania parasites.Communications biology · 2022Review
- Climate change and infectious disease in Europe: Impact, projection and adaptation.The Lancet regional health. Europe · 2021Review
- Climate change impacts on infectious diseases in the Eastern Mediterranean and the Middle East (EMME)-risks and recommendations.Climatic change · 2021Article
- Influence of Temperature on the Life-Cycle Dynamics ofInsects · 2020Article
- Species diversity and molecular insights into phlebotomine sand flies in Sardinia (Italy)-an endemic region for leishmaniasis.Parasitology research · 2020Article
- The changing distribution of Leishmania infantum Nicolle, 1908 and its Mediterranean sandfly vectors in the last 140 kys.Scientific reports · 2019Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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