This metadata refer to the dataset presenting the annual change in the estimated West Nile Virus transmission risk between 1950 and 2020 by country. The risk varies between 0 (no risk) and 1 (very high risk). This indicator uses machine learning models incorporating WNV reported cases and climate variables (temperature, precipitation) to estimate WNV transmission probability. West Nile virus is a climate-sensitive multi-host and multi-vector pathogen. Human infection is associated with severe disease risk and death. In the past few decades, European countries have had a large increase in the intensity, frequency, and geographical expansion of West Nile virus outbreaks. The 2018 outbreak has been the largest yet, with 11 European countries reporting 1584 locally acquired infections. Increasing ambient temperatures are increasing the vectorial capacity of the Culex mosquito vector, and thus increasing the outbreak probability.
This metadata refer to the dataset presenting the annual change in the percentage of coastal area per European country that is suitable for infections from vibrio species between 2003 and 2021. Vibrio bacteria can lead to severe gastrointestinal infections, skin and ear infections, and more severe health outcomes, including necrotising fasciitis, amputation, sepsis, and death. In Europe, cases have steadily increased over the years in countries with national surveillance; however, vibriosis is not a notifiable disease in the EU. Increasing sea temperatures have led to higher percentages of coastal areas with brackish waters in Europe showing suitable conditions for the transmission for non-cholerae Vibrio bacteria.
This metadata refer to the dataset presenting the annual change in the number of months suitable for the transmission of the Plasmodium vivax parasite causing malaria. The suitable months are those with precipitation above 80 mm, average temperature between 14.5°C and 33°C, and relative humidity above 60%, in land types highly suitable for Anopheles mosquitoes.
This metadata refer to the dataset presenting the annual change in the basic reproduction number (R0) for zika transmission in the period 1951-2021. The basic reproduction number of zika from Aedes mosquitos is calculated using a model to capture the influence of temperature and rainfall on mosquito vectorial capacity and mosquito abundance, and overlaying it with human population density data to estimate the R0 (i.e., the expected number of secondary infections resulting from one infected person).
This metadata refer to the dataset presenting the annual change in the basic reproduction number (R0) for dengue transmission in the period 1951-2021. The basic reproduction number of dengue from Aedes mosquitos is calculated using a model to capture the influence of temperature and rainfall on mosquito vectorial capacity and mosquito abundance, and overlaying it with human population density data to estimate the R0 (i.e., the expected number of secondary infections resulting from one infected person).
This series refers to datasets related to climate change impacts, exposures, and vulnerabilities in Europe based on the Lancet Countdown indicators on health and heat; extreme events and health; and climate-sensitive infectious disease.