Lyme borreliosis surveillance and climate data for Poland, 2009–2024: harmonised voivodeship-quarter panel and analytical code
Description
This deposit contains the harmonised analytical dataset and analytical code accompanying Grzybek et al., "Climate signal or surveillance artefact? A planetary-health framework for interpreting vector-borne disease notifications, tested with Lyme borreliosis in Poland, 2009–2024" (The Lancet Planetary Health). The core dataset is a voivodeship-quarter panel covering all 16 Polish administrative regions across 16 consecutive years (1,024 voivodeship-quarter observations; 259,003 reported Lyme borreliosis cases). Each row combines quarterly case counts, annual case counts, incidence per 100,000 population, hospitalisation counts, and hospitalisation proportion, sourced from the National Institute of Public Health NIH – National Research Institute (NIZP-PZH-PIB) epidemiological bulletins, with quarterly climate variables — mean air temperature, total cloud cover, relative humidity, wind speed, total precipitation, days with snowfall, and maximum daily precipitation — aggregated from two IMGW-PIB station networks (klimat: 28 stations across 12 voivodeships; opad: 1,135 stations across all 16 voivodeships). A station-to-voivodeship crosswalk and the station-quarter intermediate dataset are included to document the aggregation pipeline. Analytical code is provided in Python (NumPy, SciPy) and reproduces every table, figure, and statistical model reported in the paper: the Stage 2 lag-structure analysis, the Stage 3 multivariable negative binomial models (Models A, B, E, J, P), sensitivity analyses, and the ordinary-least-squares hospitalisation-proportion validation model testing the constant-severity assumption. The deposit also includes a data dictionary defining every field with units and source, the pre-specified statistical analysis plan, and a README with reproduction instructions. Released under CC BY 4.0 (data) and MIT (code). Raw source data remain publicly available at their authoritative primary sources: NIZP-PZH-PIB (http://wwwold.pzh.gov.pl/oldpage/epimeld/index_p.html) and IMGW-PIB (https://danepubliczne.imgw.pl).