Vector-borne diseases

This indicator tracks the environmental suitability for the transmission of arboviruses (dengue, chikungunya, and Zika). It uses an improved model to capture the influence of temperature and rainfall on vectorial capacity and vector abundance, and overlays it with human population density data to estimate the R0 (the expected number of secondary infections resulting from one infected person).

The model depends on climatic factors for explaining disease dynamics. It excludes humidity and socioeconomic elements. The indicator exclusively focuses on Aedes aegypti and Aedes albopictus and their spatial dispersion, excluding other Aedes species which are proven to be important for dengue transmission. The model computes R_0 independently for both vectors and does not assess overall transmission risk in regions where these vectors overlaps. The R_0 values predicted by this model represent potential outbreak risks rather than actual transmission rates, since real-world R_0 values result from complex interactions between socioeconomic conditions and climatic factors, which the current model does not encompass.

Malaria is widely recognised as a climate-sensitive infectious disease, because both the Anopheles mosquitoes that transmit it and the Plasmodium parasites that cause infection are strongly affected by climate. Temperature, precipitation, and relative humidity influence the abundance and feeding cycle of Anopheles mosquitoes, while temperature also affects the development of Plasmodium parasites inside the mosquito. This indicator tracks historical climatic suitability for malaria transmission by Anopheles mosquitoes, focusing on the two main malaria-causing parasites: Plasmodium falciparum and Plasmodium vivax. Suitability is defined as the coincidence of key climatic conditions: monthly precipitation above 80 mm, relative humidity above 60%, and average temperatures of 16–32°C for P. vivax and 18–32°C for P. falciparum.

This indicator measures climatic suitability for malaria transmission, not actual malaria cases, Anopheles mosquito presence, or direct disease risk. It should therefore be interpreted as showing where and when climate conditions are becoming more or less suitable for malaria transmission by the vector and parasites. The analysis does not currently capture the effects of land-use or land-cover change, which can influence Anopheles mosquito distribution. It also treats Anopheles as a broad mosquito group, although different species may have different climatic and habitat preferences. Finally, the indicator does not account for population immunity, malaria control measures, or healthcare interventions, all of which can strongly affect real-world malaria risk.

This indicator tracks the temperature suitability of WNV taking into account the species-specific responses of mosquito-pathogen traits to temperature. The temperature suitability index is based on a relative version of the basic reproduction number (R0) incorporating the mosquito-pathogen traits and parameterized from laboratory experimental data for Culex pipiens, Culex quinquefasciatus, and Culex tarsalis. The species-specific temperature suitability values are scaled to range from 0 to 1, where 1 represents optimal temperature conditions for transmission and 0 represents temperatures outside the lower and upper temperature limits for transmission. Species-specific temperature suitability is calculated within each species’ distribution range desribed by approximate distribution maps.

The indicator is limited to three WNV vectors and their approximate spatial distribution. Local intra-species variation of temperature responses is not considered. In addition, the indicator only isolates the effects of temperature on WNV transmission potential via the mosquito-pathogen traits. Effects of temperature on other processes and effects of other drivers of transmission are currently not incorporated. Since the temperature suitability index is build on a relative version of R0, it cannot be interpreted as an absolute measure of secondary infections and, without additional information, cannot be used as a threshold parameter for the occurrence of outbreaks.