IDEAS home Printed from https://ideas.repec.org/p/ehl/lserod/106520.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: http://eprints.lse.ac.uk/106520/
    File Function: Open access version.
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anand, Paul & Allen, Heidi & Ferrer, Robert & Gold, Natalie & Gonzales Martinez, Rolando & Kontopantelis, Evan & Krause, Melanie & Vergunst, Francis, 2020. "Work-Related and Personal Predictors of COVID-19 Transmission," IZA Discussion Papers 13493, Institute of Labor Economics (IZA).
    2. Brandily, Paul & Brébion, Clément & Briole, Simon & Khoury, Laura, 2021. "A poorly understood disease? The impact of COVID-19 on the income gradient in mortality over the course of the pandemic," European Economic Review, Elsevier, vol. 140(C).
    3. Abel Brodeur & David Gray & Anik Islam & Suraiya Bhuiyan, 2021. "A literature review of the economics of COVID‐19," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1007-1044, September.
    4. Johannes S. Kunz & Carol Propper, 2022. "Is Hospital Quality Predictive of Pandemic Deaths? Evidence from US Counties," Papers 2022-01, Centre for Health Economics, Monash University.
    5. Hevia, Constantino & Macera, Manuel & Neumeyer, Pablo Andrés, 2022. "Covid-19 in unequal societies," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    6. Aditya Goenka & Lin Liu & Manh-Hung Nguyen, 2021. "Modeling optimal quarantines with waning immunity," Discussion Papers 21-10, Department of Economics, University of Birmingham.
    7. Menon, Nidhiya, 2021. "Does BMI predict the early spatial variation and intensity of Covid-19 in developing countries? Evidence from India," Economics & Human Biology, Elsevier, vol. 41(C).
    8. Paul Brandily & Clément Brébion & Simon Briole & Laura Khoury, 2021. "A Poorly Understood Disease? The Evolution of the Income Gradient in Excess Mortality Due to COVID-19 within Urban Areas," Working Papers halshs-03154551, HAL.
    9. Kunz, Johannes S. & Propper, Carol, 2023. "JUE Insight: Is hospital quality predictive of pandemic deaths? Evidence from US counties," Journal of Urban Economics, Elsevier, vol. 133(C).
    10. R. Jason Faberman & Daniel Hartley, 2020. "The Relationship Between Race, Type of Work, and Covid-19 Infection Rates," Working Paper Series WP2020-18, Federal Reserve Bank of Chicago.
    11. Aditya Goenka & Lin Liu & Manh-Hung Nguyen, 2020. "Modeling optimal quarantines under infectious disease related mortality," Working Papers 202025, University of Liverpool, Department of Economics.
    12. François Desmoulins-Lebeault & Jean-François Gajewski & Luc Meunier, 2018. "Personality and Risk Aversion," Economics Bulletin, AccessEcon, vol. 38(1), pages 472-489.
    13. Ranganathan, Kavitha & Lejarraga, Tomás, 2021. "Elicitation of risk preferences through satisficing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    14. Goytom Abraha Kahsay & Daniel Osberghaus, 2018. "Storm Damage and Risk Preferences: Panel Evidence from Germany," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 301-318, September.
    15. Wu, WenTing & Chen, XiaoQian & Zvarych, Roman & Huang, WeiLun, 2024. "The Stackelberg duel between Central Bank Digital Currencies and private payment titans in China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    16. Graham, James & Ozbilgin, Murat, 2021. "Age, industry, and unemployment risk during a pandemic lockdown," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    17. 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.
    18. de Palma, André & Vosough, Shaghayegh & Liao, Feixiong, 2022. "An overview of effects of COVID-19 on mobility and lifestyle: 18 months since the outbreak," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 372-397.
    19. Sophie Massin & Antoine Nebout & Bruno Ventelou, 2018. "Predicting medical practices using various risk attitude measures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(6), pages 843-860, July.
    20. Nicolai J. Foss, 2021. "The Impact of the Covid‐19 Pandemic on Firms’ Organizational Designs," Journal of Management Studies, Wiley Blackwell, vol. 58(1), pages 270-274, January.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:106520. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.