Pneumonia Surveillance in Peru: Reproducible Analysis and Visualization Repository (2015-2022)

This repository provides reproducible Python notebooks for analyzing and visualizing pneumonia surveillance data from Peru spanning 2015 to 2022. The code supports the findings reported in the manuscript: "Pneumonia incidence, hospitalizations and mortality before and during the COVID-19 pandemic in Peru: a nationwide observational study" (PLOS ONE, 2026). The repository enables full replication of national time-series trends and departmental-level choropleth maps for pneumonia incidence, hospitalizations, and mortality across pre-pandemic (2015–2019), pandemic (2020–2021), and post-pandemic (2022) periods. Contents: Maps.ipynb: Generates four-panel choropleth maps for children under 5 years and adults aged 60+ years, comparing 2015–2019, 2020, 2021, and 2022 with shared color scales. TimeSeries.ipynb: Creates weekly national time-series plots with 4-week moving averages for both age groups, including markers for COVID-19 onset (March 2020) and post-pandemic period (January 2022). datos/: Contains raw surveillance data from MINSA (datos_abiertos_vigilancia_iras_2000_2023.csv) and Peruvian departmental shapefiles for geospatial mapping. Key Features: National and departmental-level pneumonia trend analysis Age-stratified analysis comparing children under 5 and adults 60+ Temporal comparisons across pre-pandemic, pandemic, and post-pandemic periods Publication-quality figures generated with matplotlib and seaborn Fully reproducible Python workflow using pandas, geopandas, matplotlib, and seaborn Data Source: Peruvian public health surveillance system, CDC Peru, MINSA. Population denominators from INEI. Methods: Study period 2015–2022. Outcomes: incidence, hospitalization, and mortality rates per 100,000 inhabitants. Statistical analysis: annual incidence rates with 95% CI (Poisson) and incidence rate ratios comparing pandemic to pre-pandemic periods. Dependencies: pandas, geopandas, matplotlib, seaborn, numpy, shapely. Citation: Ramírez-Soto MC, Arroyo-Hernandez H, Bogado Machuca JV, Stalder DH, Schaerer CE. (2026). Peru Pneumonia Surveillance: Reproducible Analysis and Visualization Repository (2015-2022) [Data set]. Mendeley Data. Contact: Dr. Max Carlos Ramírez-Soto ([e-mail]) Acknowledgments: Universidad Tecnologica del Peru (Grant P-2025-LIM-26) . D.S. and C.E.S. acknowledge the support of FEEI-CONACYT-ARASY ESTR01-23. Funders had no role in study design, data collection, analysis, decision to publish, or manuscript preparation.