Data for the analysis of mosquito bites in Catalonia (2022-2024)

This project aims to analyse mosquito bite patterns across Catalonia using real-world data from multiple open sources. Mosquito activity is shaped by environmental and demographic conditions, and understanding these relationships can help identify risk factors and support public health initiatives. Our central hypothesis is that bite frequency varies with environmental variables such as temperature and humidity, as well as demographic characteristics like population density and geographic region. We also examine whether certain mosquito species are reported more frequently than others. To address these questions, we built a complete data-processing pipeline that integrates, cleans, and analyses information from several open datasets. It is important to note that the primary source of bite information (Mosquito Alert) is based on user-reported bites and sightings. These reports are not uniformly distributed across Catalonia and are particularly concentrated in the Barcelona metropolitan area. This uneven spatial distribution introduces potential biases in the dataset and limits the representativeness of the observations. For a more accurate and comprehensive analysis, a targeted data-collection campaign focused on mosquito bites and sightings across under-represented regions would be necessary. Codebook Variable Description id Unique user identifier that refers to the person who reported the mosquito bite (uuid) code A four‑digit code used to identify the person who reported the mosquito bite (????) date Date where the bite was reported (dd/mm/yyyy) b_longitude Longitude of the bite (decimal degrees) b_latitude Latitude of the bite (decimal degrees) b_altitude Altitude of the bite (m) b_province Province where the bite was reported b_county County where the bite was reported b_municipality City/town where the bite was reported b_m_population Municipality population b_count Bite counts for each entry b_location Bite location (outdoors, inside building, inside car, don’t know b_time Bite registered day part (Morning, midday, afternoon, night) prob_tiger Probability for the mosquito to be tiger prob_culex Probability for the mosquito to be culex s_id Nearest station with data available s_altitude Weather station altitude (m) s_temp Station registered mean temperature (ºC) s_humidity Station registered mean humidity (%) distance Haversine distance from the two points (bite and meteorological station) (km) alt_diff Altitude difference between bite and station coordinates (m) temp_correction Temperature deviation (ºC) temp_adjusted Corrected temperature (ºC) temp_range Temperature intervals