jpolonsky / International-COVID-IFR

Age-specific mortality and immunity patterns of SARS-CoV-2 https://www.nature.com/articles/s41586-020-2918-0

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International-COVID-IFR

Code and data to reproduce the analysis in "Age-specific mortality and immunity patterns of SARS-CoV-2". https://doi.org/10.1038/s41586-020-2918-0

Code

  • RunModel.R is the main RScript to call all data, functions & model fitting.
  • IFRInternational_ensemble.stan contains the core ensemble model code.
  • IFRInternational_singlesero.stan contains core model code for use when fitting individual serological studies in the model likelihood. For studies with only a single survey time point IFRInternational_singlesero_1.stan should be used.
  • adjust-deaths.R estimates age-specific non-nursing home COVID-19 deaths aged 65+ for a subset of countries.

Data

  • deaths_age.csv contains reported age-specific COVID-19 death data from 45 countries.
  • deaths_location.csv contains the number of COVID-19 deaths associated with nursing home/long-term care facilities for a subset of countries.
  • deaths_age_adjusted.csv is the estimated age-specific number of COVID-19 deaths for a subset of countries where nursing home/long-term care deaths could be excluded.
  • time_series_covid19_deaths_global.csv is the daily time-series of COVID-19 deaths from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (https://github.com/CSSEGISandData/COVID-19).
  • deathsT_region.csv contains daily time-series of COVID-19 deaths for a subset of locations, where unavailable from the Johns Hopkins repository.
  • serostudies.csv are the results from each of the seroprevalence surveys included in the analysis.
  • data_sources.csv contains URL links to sources of age-specific death data for each country.
  • France_NursingHomePop.csv is the nursing home population demographics for France.

About

Age-specific mortality and immunity patterns of SARS-CoV-2 https://www.nature.com/articles/s41586-020-2918-0


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Language:R 61.6%Language:Stan 38.4%