Data and replication files for Study of the Spread of COVID-19 in Saint Petersburg, Russia (NCT04406038, ISRCTN11060415) and Real-world Evidence of COVID-19 Vaccines Effectiveness (NCT04981405).
This repository features the data and replication files for the analysis of the seroprevalence and spread of COVID-19 in St. Petersburg, Russia, as well as for the analysis of COVID-19 vaccine effectiveness.
Seroprevalence study of COVID-19 in Saint Petersburg, Russia is a regional longitudinal cohort study aiming to evaluate the spread dynamics of the COVID-19 disease in the population of Saint Petersburg. Clinically asymptomatic adults are sampled from the population using random digit dialing and tested for the presence of SARS-CoV-2-specific antibodies in the blood serum. Data collection and serial sampling of the same individuals spans four weeks and is conducted every two weeks in order to understand both the spread of the virus in the population.
To replicate our analysis you need to clone this repository to your local machine. Then you need to install the required versions of R dependencies listed in DEPENDENCIES. code/analysis/helper_functions/install_dependencies.r automates this step, but you may still need to install the underlying libraries such as JAGS or gfortran manually with Homebrew or apt-get, depending on your platform. Finally, you need to declare the environment variable SPB_COVID_STUDY_PATH in bash pointing to the repository. Or, better yet, you can add it in your .Renviron with
user:~$ echo 'SPB_COVID_STUDY_PATH="path_to_cloned_repository"' >> ~/.Renviron
We provide an annotated Makefile that documents the data analysis in our papers.
To build the ‘Seroprevalence of SARS-CoV-2 antibodies in Saint Petersburg, Russia: a population-based study’ paper run make scientific_reports_paper when in the repository folder.
To build the ‘Evaluation of the performance of SARS-CoV-2 antibody assays’ run make validation_of_covid_tests_paper.
To build the ‘COVID-19 pandemic in Saint Petersburg, Russia’ paper run make pandemic_course_paper.
To build the ‘Vaccine Effectiveness Against Severe COVID-19 in St. Petersburg, Russia’ paper run make ve_against_covid_paper.
Please note that those commands will not produce any publication-ready output files (e.g. tables or figures): the export statements are commented out in the code. Our intention is to make the analysis pipeline transparent to the readers with the aid of make.
For convenience, we also briefly describe the repository structure below:
DEPENDENCIES -- list of R packages required to reproduce the analysis
data/wave*/phone_survey -- depersonified participant-level data from the phone
survey in the respective wave
data/wave1/paper_survey -- depersonified clinic paper-based survey data from
wave 1
data/wave*/test_results -- depersonified data with SARS-CoV-2 antibody test results
by manufacturer (A — Sugentech, B — Abbott, C — Genetico
Coronapass, D - VectorBest) from the respective wave
data/wave2/other_tests -- depersonified data with other blood test results
(Vitamin D, Helicobacter pylori Immunoglobulin G,
Hemoglobin A0, Cholesterin, Triglycerides, etc.) from
wave 2
data/validation_of_covid_tests -- data for validation of assays' perfomance study:
data/validation_of_covid_tests/full_dataset.rda -- cross-validation sample
data/validation_of_covid_tests/full_*test name*.rda -- full-validation sample for
*test name*
data/validation_of_covid_tests/test_nab.rda -- data with neutralization test results
data/validation_of_covid_tests/functions_for_se_sp.R -- auxiliary functions for
assays' perfomance evaluation
data/validation_of_covid_tests/se_sp_roc_calculation.R -- evaluation of assays'
perfomance code
data/validation_of_covid_tests/nab_analysis.R -- analysis of the data with
neutralization test results
data/variants -- data on the monthly counts of SARS-CoV-2 variants of concern (VOC)
in St. Petersburg from the Smorodintsev Research Institute of
Influenza
data/spb_map -- Saint Petersburg district boundaries shapefile from OpenStreetMap
data/kouzh_2018 -- data from the 2016 round of the Comprehensive Monitoring of Living
Conditions household survey (available at
https://www.gks.ru/free_doc/new_site/KOUZ18/index.html)
data/ve_covid_paper -- depersonified participant-level data on lung injury, oxigen
saturation, referral to hospital and vaccination status from
two triage ceters in St. Petersburg
code/analysis/helper_functions -- auxiliary functions
code/analysis/preliminary -- analysis at the onset of the study
code/analysis/wave* -- analysis of the data from the waves 1 to 3
code/analysis/scientific_reports_paper -- the code required to replicate the Sci.Rep
paper
code/analysis/validation_of_covid_tests_paper -- the code required to replicate the
Journal of Medical Virology paper
code/analysis/pandemic_course_paper -- the code required to replicate the Course of
COVID-19 pandemic paper
code/analysis/ve_covid_paper/minimum_detectable_ve.r -- minimum detectable odds ratio
for the ve paper
code/analysis/ve_covid_paper/create_summary_statistics_table.R -- summary statistics
for the ve dataset
code/analysis/ve_covid_paper/*_models.R -- results of model estimates for ve
code/analysis/ve_covid_paper/create_ve_figure_for_age_vac_status.R -- plot for probability
of referral to hospital
by vaccination status
and age
estimates/wave* -- results of the seroprevalence model estimates from the respective
wave: seroprevalence by model and variable level
estimates/pandemic_course_paper -- results of the auxiliary estimates for the
Course of COVID-19 pandemic paper:
estimates/pandemic_course_paper/prevalence_by_agegroup_sex.rdata -- fine-grained
seroprevalence by
sex and age group
for wave 3
estimates/pandemic_course_paper/sample_*.rdata -- sampling results from the Bayesian
evidence synthesis model
estimates/pandemic_course_paper/ir_irf_results_object.rdata -- estimated per-wave IR/
IFR from the Bayesian
evidence synthesis model
estimates/pandemic_course_paper/ir_irf_agesex_results_object.rdata -- estimated IR/IFR
by age/sex group
from the Bayesian
evidence synthesis
model
The code for the Course of COVID-19 pandemic paper also relies on the data from https://github.com/alexei-kouprianov/COVID-19.SPb repository that gathers the federal and city data on the progress of the pandemic and related indicators.
- Analytics use case(s): Population-Level Estimation
- Study type: Clinical Application
- Study start date: May 27, 2020
- Study end date: Ongoing
- Protocol: Study of the Spread of COVID-19 in Saint Petersburg Protocol in English
- Preprints: COVID-19 pandemic in Saint Petersburg, Russia, Vaccine Effectiveness Against Severe COVID-19 in St. Petersburg, Russia
- Publications: Seroprevalence of SARS-CoV-2 antibodies in Saint Petersburg, Russia: a population-based study, Evaluation of the performance of SARS-CoV-2 antibody assays for the longitudinal population-based study of COVID-19 spread in St. Petersburg, Russia
Creative Commons License Attribution 4.0 International (CC BY 4.0).
Anton Barchuk, MD PhD [email protected]