Modelling the spatial risk of malaria through probability distribution of Anopheles maculipennis s.l. and imported cases (Q10766)

Malaria remains one of the most important infectious diseases globally due to its high incidence and mortality rates. Theinflux of infected cases from endemic to non-endemic malaria regions like Europe has resulted in a public health concernover sporadic local outbreaks. This is facilitated by the continued presence of competent Anopheles vectors in non-endemic countries.We modelled the potential distribution of the main malaria vector across Spain using the ensemble of eightmodelling techniques based on environmental parameters and the Anopheles maculipennis s.l. presence/absence datacollected from 2000 to 2020. We then combined this map with the number of imported malaria cases in eachmunicipality to detect the geographic hot spots with a higher risk of local malaria transmission.The malaria vector occurred preferentially in irrigated lands characterized by warm climate conditions and moderateannual precipitation. Some areas surrounding irrigated lands in northern Spain (e.g. Zaragoza, Logroo), mainland areas(e.g. Madrid, Toledo) and in the South (e.g. Huelva), presented a significant likelihood of A. maculipennis s.l. occurrence,with a large overlap with the presence of imported cases of malaria.While the risk of malaria re-emergence in Spain is low, it is not evenly distributed throughout the country. The fourrecorded local cases of mosquito-borne transmission occurred in areas with a high overlap of imported cases andmosquito presence. Integrating mosquito distribution with human incidence cases provides an effective tool for thequantification of large-scale geographic variation in transmission risk and pinpointing priority areas for targetedsurveillance and prevention.