Nasarawa State climate-informed malaria incidence modelling: Dataset and R workflow

This repository contains the aggregated, de-identified malaria surveillance dataset and reproducible R analysis workflow supporting the study “Modelling Seasonal Trends of Malaria Incidence in Nasarawa State, Nigeria Using Health Facility Surveillance Data.” The dataset comprises monthly aggregated malaria surveillance data from 13 Local Government Areas of Nasarawa State, Nigeria, covering January 2021 to December 2025. Population denominators used to calculate malaria incidence were derived from the 2006 Nigerian population census and projected using an annual population growth rate of 3.0%. The repository also contains the climatic data and/or derived climatic variables used in the analysis, together with R scripts for data quality assessment, incidence calculation, seasonal decomposition, stationarity assessment, rainfall and temperature cross-correlation analysis, time-series model development and validation, final SARIMAX model fitting, diagnostic assessment, and 2026 forecasting. The final malaria forecasting model uses seasonal ARIMA errors with rainfall as an exogenous predictor. The repository includes the code and model outputs required to reproduce the principal analyses and 2026 forecasts reported in the associated manuscript. The underlying non-aggregated DHIS2 surveillance records are not included because they remain under the stewardship of the National Malaria Elimination Programme and are subject to applicable data-use and governance requirements. The publicly deposited dataset is aggregated and de-identified and contains no individual-level patient information. NASA POWER climatic data are publicly available from the NASA POWER data portal. The deposited R workflow documents the processing and modelling procedures applied to the study data.