Seasonal model of Brauner et al.: COVID-19 Nonpharmaceutical Interventions Effectiveness

TThis repository contains one part of the code used in the paper Gavenčiak et al.: Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions, PLOS Comp. Bio., 2022. The 2021 preprint can be found here.

This repository contains the seasonal variant of the model of Brauner et al. Inferring the effectiveness of government interventions against COVID-19 and has been forked from epidemics/COVIDNPIs; please see that repo for further information.

For the seasonal variant of the model of Sharma et al. (2021), Understanding the effectiveness of government interventions in Europe’s second wave of COVID-19, see the repository gavento/covid_seasonal_Sharma.

Data

The main data files used in the model are data/modelBrauner_dataBrauner.csv and data/modelBrauner_dataBrauner.csv which are derived from data/data_final_nov_temperate_europe.csv from Brauner et al. except for number formatting, leaving out unused features and limiting to temperate Europe for *BraunerTE* (see the paper for details).

The data files data/modelBrauner_dataBraunerTE_mobility_*.csv are enriched with Google community mobility reports. The column Mobility decrease is a mean of indicated mobility categories remapped to range from 0.0 (no mobility) to 1.0 (pre-pandemic mobility), as described in the paper.

Running the model

Instructions for a recent linux distribution (E.g. Ubuntu 20.04+)

• Install poetry in case you don't already have it (follow instructions at https://python-poetry.org for non-default install).

curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python - --version 1.1.6
source $HOME/.poetry/env

• Install dependencies into a poetry virtualenv

poetry install

• Run all or selected the inferences

Adjust the number of parralel runs: each paralllel run uses 4-8 CPU cores.

poetry run python scripts/sensitivity_dispatcher.py --max_processes 4 \
  --categories default_Brauner default_BraunerTE basic_R_normal_Brauner basic_R_normal_BraunerTE \
  seasonality_basic_R_normal_BraunerTE seasonality_maxRday_normal_BraunerTE seasonality_maxRday_fixed_BraunerTE \
  seasonality_mobility_1 

• To plot the results, use the notebooks from notebooks/final_results in the repository gavento/covid_seasonal_Sharma (move the resulting data in sensitivity_analysis/ there).

Changelog

• Preprint v1 (tag preprint-v1)

  • Add seasonality model, customized and extended plotters
  • Added filtered temperate Europe data subset has been added as merged_data/data_final_nov_temperate_europe.csv.
  • Runners and configs for sensitivity analyses
  • Extended trace storage with Arviz netcdf export and JSON for plotting
    • Plotting code in repository gavento/covid_seasonal_Sharma)
  • Minor updates and fixes

• Preprint v2 (tag preprint-v2)

  • Added mobility sensitivity analysis, data and plotters
  • Added data files exactly as used
  • Updated configs and readme for easier reproduction

• Plos Comp. Bio v1 (tag submitted-1)

  • No changes in this repository

Questions?

Please email Tomáš Gavenčiak (gavento at ucw dot cz) or Mrinank Sharma (mrinank at robots dot ac dot uk, only questions regarding their code) for questions regarding the codebase.