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Analysis code for the article: "SARS-CoV-2 prevalence associated to low socioeconomic status and overcrowding in an LMIC megacity: A population-based seroepidemiological survey in Lima, Peru"

Home Page: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(21)00081-X/fulltext

R 100.00%
serological-surveys prevalence peru lima workflow population

covid_seroprev's Introduction

covid_seroprev

DOI

The goal of covid_seroprev is to register the data management and statistical analysis workflow used for the project and manuscript: “Prevalence of SARS-CoV-2 in Lima, Peru: a population-based seroepidemiological survey”

Project Workflow

Files:

  • Encuesta ESPI_fisico.xlsx: XLSForm used to collect data.
  • 01-clean.R: import, clean and integration of data sources. recategorize and create variables.
  • 06-prevalence.R: estimate prevalence.
  • 07-outputs.R: create tables and figures.
  • 11-sampling_comparison.R: contrast census and sample population.
  • 13-epicurve.R: create epicurve from open data.
  • 15-distributions.R: exploratory ecdf for overcrowding.
  • 16-association.R: calculate association measurements.

Reproducibility:

To reproduce this project from 06-prevalence.R onwards, you need the uu_clean_data.rds file stored in the data/ folder. This data source is not available in this repository.

For reproducible workflow examples of the analysis performed in this project go to the:

  • serosurvey R package website to generate prevalence estimates as in 06-prevalence.R, and
  • epitidy R package repository to calculate association measurements as in 16-association.R.

Required packages:

Call renv::restore() to reinstall all of the packages used in this project. Learn more about renv here.

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