Seasonal variation in airborne infection risk in schools due to changes in ventilation inferred from monitored carbon dioxide

Indoor Air. 2021 Jul;31(4):1154-1163. doi: 10.1111/ina.12818. Epub 2021 Mar 8.

Abstract

The year 2020 has seen the world gripped by the effects of the COVID-19 pandemic. It is not the first time, nor will it be last, that our increasingly globalized world has been significantly affected by the emergence of a new disease. In much of the Northern Hemisphere, the academic year begins in September, and for many countries, September 2020 marked the return to full schooling after some period of enforced closure due to COVID-19. In this paper, we focus on the airborne spread of disease and investigate the likelihood of transmission in school environments. It is crucial to understand the risk airborne infection from COVID-19 might pose to pupils, teachers, and their wider social groups. We use monitored CO2 data from 45 classrooms in 11 different schools from within the UK to estimate the likelihood of infection occurring within classrooms regularly attended by the same staff and pupils. We determine estimates of the number of secondary infections arising via the airborne route over pre/asymptomatic periods on a rolling basis. Results show that, assuming relatively quiet desk-based work, the number of secondary infections is likely to remain reassuringly below unity; however, it can vary widely between classrooms of the same school even when the same ventilation system is present. Crucially, the data highlight significant variation with the seasons with January being nearly twice as risky as July. We show that such seasonal variations in risk due to changes in ventilation rates are robust and our results hold for wide variations in disease parameterizations, suggesting our results may be applied to a number of different airborne diseases.

Keywords: COVID-19; SARS-CoV-2; airborne infection risk; infection modeling; monitored CO2; school.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • COVID-19 / transmission*
  • Carbon Dioxide / analysis
  • Humans
  • Inhalation Exposure*
  • Risk Assessment
  • Schools / statistics & numerical data*
  • Seasons
  • Ventilation*

Substances

  • Carbon Dioxide