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DSIR - Data Science Infrastructure for Global Health

Supports global health data analysis, including a publication-ready 'ggplot2' theme, a 'flextable' defaults helper, a thin pie chart wrapper, built-in regional country-code datasets with a WHO region lookup helper, a geometric mean function for indicator aggregation, an average annual rate of reduction function for indicator progress tracking, direct age standardization against the bundled WHO 2026 Standard Population, period life-table construction, a snapshot helper for reproducible data pulls, and convenience clients for the World Health Organization Global Health Observatory (GHO) through its legacy OData API <https://ghoapi.azureedge.net/api/> or the public WHO xMart OData API <https://xmart-api-public.who.int/DATA_>, Global Health Estimates (GHE) through WHO xMart, and the United Nations Sustainable Development Goals (SDG) API <https://unstats.un.org/SDGAPI/swagger/>.

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5.73 score 3 stars 679 downloads

cataScience - Interactive Training App for Data Science and AI Skills

An interactive 'shiny' training companion for people who are new to data, developed for World Health Organization data trainings. Bundles hands-on modules for importing data, missing values, outliers, text cleaning, merging, visualization, and basic statistics, plus a set of AI-skills pages (prompting levels, a prompt gallery, AI safety rules, and a methodology case study) and an interactive quiz with per-session topic filters. Launch the app with run_cata().

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5.43 score 3 stars 362 downloads

exmort - All-Cause and Excess Mortality Calculator

An interactive 'shiny' application that estimates all-cause mortality and excess mortality from country-level weekly or monthly death counts. Users supply observed deaths and an event calendar (for example COVID-19 waves or typhoons); the app fits one or more statistical baseline models (historical average, negative binomial regression, quasi-Poisson regression, zero-inflated Poisson regression, ARIMA (autoregressive integrated moving average) and SARIMA (seasonal ARIMA) models, GAM (generalized additive model) splines, and the model of Karlinsky and Kobak (2021) <doi:10.7554/eLife.69336>) using periods outside the supplied events, estimates expected deaths across the observed series, and reports excess deaths, P-scores (excess deaths as a percentage of expected deaths) and confidence limits with tables, plots and downloadable reports. Launch the application with run_app().

Last updated

4.78 score 418 downloads