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