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Work-related and personal predictors of Covid-19 transmission

Author

Listed:
  • Anand, Paul
  • Allen, Heidi
  • Ferrer, Bob
  • Gold, Natalie
  • Martinez, Roland Manuel Gonzalez
  • Kontopantelis, Evangelos
  • Vergunst, Francis

Abstract

The paper provides new evidence from a survey of 2000 individuals in the US and UK related to predictors of Covid-19 transmission. Specifically, it investigates work and personal predictors of transmission experience reported by respondents using regression models to better understand possible transmission pathways and mechanisms in the community. Three themes emerge from the analysis. Firstly, transport roles and travelling practices are significant predictors of infection. Secondly, evidence from the US especially shows union membership, consultation over safety measures and the need to use public transport to get to work are also significant predictors. This is interpreted as evidence of the role of deprivation and of reactive workplace consultations. Thirdly and finally, there is some, often weaker, evidence that income, car-owership, use of a shared kitchen, university degree type, risk aversion, extraversion and height are predictors of transmission. The comparative nature of the evidence indicates that the less uniformly stringent nature of the US lockdown provides more information about both structural and individual factors that predict transmission. The evidence about height is discussed in the context of the aerosol transmission debate. The paper concludes that both structural and individual factors must be taken into account when predicting transmission or designing effective public health measures and messages to prevent or contain transmission.

Suggested Citation

  • Anand, Paul & Allen, Heidi & Ferrer, Bob & Gold, Natalie & Martinez, Roland Manuel Gonzalez & Kontopantelis, Evangelos & Vergunst, Francis, 2020. "Work-related and personal predictors of Covid-19 transmission," LSE Research Online Documents on Economics 106520, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:106520
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    File URL: http://eprints.lse.ac.uk/106520/
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    References listed on IDEAS

    as
    1. Nicholas W. Papageorge & Matthew V. Zahn & Michèle Belot & Eline Broek-Altenburg & Syngjoo Choi & Julian C. Jamison & Egon Tripodi, 2021. "Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(2), pages 691-738, April.
    2. Klaus Desmet & Romain Wacziarg, 2020. "Understanding Spatial Variation in COVID-19 across the United States," NBER Working Papers 27329, National Bureau of Economic Research, Inc.
    3. Lönnqvist, Jan-Erik & Verkasalo, Markku & Walkowitz, Gari & Wichardt, Philipp C., 2015. "Measuring individual risk attitudes in the lab: Task or ask? An empirical comparison," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 254-266.
    4. Alexander W. Bartik & Zoe B. Cullen & Edward L. Glaeser & Michael Luca & Christopher T. Stanton, 2020. "What Jobs are Being Done at Home During the Covid-19 Crisis? Evidence from Firm-Level Surveys," NBER Working Papers 27422, National Bureau of Economic Research, Inc.
    5. Raphael Auer & Giulio Cornelli & Jon Frost, 2020. "Covid-19, cash, and the future of payments," BIS Bulletins 3, Bank for International Settlements.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    coronavirus; Covid-19; transmission; transport; predictors; workplace; deprivation; risk preference; extraversion; height; US; UK;
    All these keywords.

    JEL classification:

    • I00 - Health, Education, and Welfare - - General - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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