Modeling climate drivers of the current and future spread of sand flies in Europe and neighboring countries with the use of wavelet transform analysis

We used wavelet transform cross-correlation analysis to inform the model of the number of sand flies as a function of meteorological and environmental variables. To that end we used historical sand fly monitoring datasets from several past and ongoing collaborations in Europe, Turkey and Israel (projects EDENext, VectorNet, CLIMOS and PLANET4HEALTH), and correlated those with the corresponding temperature, precipitation, and soil moisture data.

We were looking into how the number of these disease vectors depends on all these variables and were interested to define the time lags between the changes of the meteorological and environmental drivers and change (particularly rise) in numbers of sand flies. We were additionally interested in how the change in climatic suitability for sand fly development will influence their spread in Europe. Finally, we researched if the modelled behavior can be universal across the sand fly species, or should be developed separately by species, and climatic regions.

Our results should assist development of the early warning systems for the spread of sand fly borne diseases that can be used by public health authorities for efficient and effective preparedness.

 

Funding: The CLIMOS consortium is co-funded by the European Commission grant 101057690 and UKRI grants 10038150 and 10039289. The six Horizon Europe projects, BlueAdapt, CATALYSE, CLIMOS, HIGH Horizons, IDAlert, and TRIGGER, form the Climate Change and Health Cluster. The PLANET4HEALTH consortium is co-funded by the European Commission grant 101136652. The five Horizon Europe projects, GO GREEN NEXT, MOSAIC, PLANET4HEALTH, SPRINGS, and TULIP, form the Planetary Health Cluster.