january-msemakweli/AMR: Pandemic Disruptions and Post-COVID Patterns of Antimicrobial Resistance-Associated Infections in Sweden

AMR-Associated Infections Analysis (Sweden 2015–2025) Analysis of pandemic disruptions and post-COVID patterns of antimicrobial resistance–associated infections in Sweden: regional incidence for ESBL/CARBA, VRE, and MRSA. Overview Pre-COVID (2015–2019): baseline COVID (2020–2021): pandemic period Post-COVID (2022–2025): recovery The analysis uses negative binomial regression (period-based IRR and interrupted time-series) with region fixed effects and log-population offset. Population denominators come from Statistics Sweden (SCB) via the PxWeb API. Data | File | Description | |------|-------------| | AMR_Associated_Infections.csv | Regional case counts and incidence rates (per 100,000) by year. Source: Swedish Public Health Agency (Folkhälsomyndigheten) / SmiNet. | Population data are fetched from SCB (annual table BefolkningNy for 2015–2024; 2025 uses the monthly table BefolkManadCKM if needed). Results are cached under the project or parent folder (e.g. ../scb_population_county_2015_2024.csv). Project structure | File / folder | Purpose | |---------------|---------| | AMR_Associated_Infections_Analysis.R | Main script: load data, fetch SCB population, build long-format data, run period and ITS models, produce summary and IRR/ITS tables, optional figures (if pre-generated). | | make_amr_its_counterfactual_plots.R | Build ITS counterfactual figures (observed vs fitted vs no-interruption) and write CSVs + PNGs into amr_its_plots/. | | make_amr_its_counterfactual_panel.R | Single panel figure combining ESBL/CARBA, VRE, and MRSA counterfactual plots. | | create_amr_maps.R | Choropleth maps of mean regional incidence by period (Pre-COVID, COVID, Post-COVID) for ESBL-CARBA, VRE, MRSA; outputs map_amr_infections_combined.png. | | amr_its_plots/ | Output folder for ITS national series CSVs and counterfactual PNGs. | Requirements R (tested with a recent R 4.x). R packages: tidyverse, MASS, broom, pxweb, knitr, kableExtra for the main script; make_amr_its_counterfactual_*.R also use patchwork and cowplot; create_amr_maps.R uses sf, rnaturalearth, ggspatial, RColorBrewer, patchwork, ggrepel. Install from CRAN if needed, e.g.: install.packages(c("tidyverse", "MASS", "broom", "pxweb", "knitr", "kableExtra", "patchwork", "cowplot", "sf", "rnaturalearth", "ggspatial", "RColorBrewer", "ggrepel")) How to run Set working directory to the folder that contains AMR_Associated_Infections.csv (the AMR folder). Main analysis (tables and model objects): source("AMR_Associated_Infections_Analysis.R") This loads data, fetches/caches SCB population, runs period and ITS models, and prints/formats tables (e.g. summary stats, IRR table, ITS effects, AIC). If amr_its_plots/ and map_amr_infections_combined.png already exist, it will include those figures. ITS counterfactual figures and CSVs (optional; creates or updates amr_its_plots/): Rscript make_amr_its_counterfactual_plots.R Or the combined panel: Rscript make_amr_its_counterfactual_panel.R Maps (optional; creates map_amr_infections_combined.png): source("create_amr_maps.R") Or from the shell: Rscript create_amr_maps.R Recommended order: run make_amr_its_counterfactual_plots.R (and optionally create_amr_maps.R) if you want the main script to display the pre-generated figures; otherwise the main script still runs all models and tables. Outputs Console / R environment: summary_stats, national_trends, all_irr, its_effects, aic_tbl, regional_summary, and formatted kable tables. amr_its_plots/: CSVs: its_national_series_esbl_carba.csv, its_national_series_vre.csv, its_national_series_mrsa.csv (observed and fitted/counterfactual series). PNGs: counterfactual plots per pathogen (and panel if you ran the panel script). Root: map_amr_infections_combined.png (from create_amr_maps.R). References Swedish Public Health Agency. Sjukdomsstatistik / Disease statistics. Statistics Sweden (SCB). PxWeb API.