Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-23T21:19:18.708Z Has data issue: false hasContentIssue false
  • English
  • Français

THE GREAT COVID-19 VACCINE ROLLOUT: BEHAVIOURAL AND POLICY RESPONSES

Published online by Cambridge University Press:  30 September 2021

M. Christopher Auld Open the ORCID record for M. Christopher Auld [Opens in a new window]  and
Flavio Toxvaerd
M. Christopher Auld*
Affiliation:
Department of Economics, University of Victoria, Victoria, BC, Canada
Flavio Toxvaerd
Affiliation:
Faculty of Economics, University of Cambridge, Cambridge, United Kingdom Centre for Economic Policy Research, London, United Kingdom
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Using daily data on vaccinations, disease spread and measures of social interaction from Google Mobility reports aggregated at the country level for 112 countries, we present estimates of behavioural responses to the global rollout of COVID-19 vaccines. We first estimate correlates of the timing and intensity of the vaccination rollout, finding that countries which vaccinated more of their population earlier strongly tended to be richer, whereas measures of the state of pandemic or its death toll up to the time of the initial vaccine rollout had little predictive ability after controlling for income. Estimates of models of social distancing and disease spread suggest that countries which vaccinated more quickly also experienced decreases in some measures of social distancing, yet also lower incidence of disease, and in these countries, policy-makers relaxed social distancing measures relative to countries which rolled out vaccinations more slowly.

Keywords

I12C5economic epidemiologyeconometricsCOVID-19vaccination
Type
Research Article
Information
National Institute Economic Review , Volume 257: ECONOMIC CONTRIBUTIONS TO INFECTION CONTROL , Summer 2021 , pp. 14 - 35
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of National Institute Economic Review

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Auld, M.C. (2003), ‘Choices, beliefs, and infectious disease dynamics’, Journal of Health Economics, 22, pp. 361–77.CrossRefGoogle ScholarPubMed
Bellemare, M.F., Masaki, T. and Pepinsky, T.B. (2017), ‘Lagged explanatory variables and the estimation of causal effect’, The Journal of Politics, 79, pp. 949–63.CrossRefGoogle Scholar
Berry, C.R., Fowler, A., Glazer, T., Handel-Meyer, S. and MacMillen, A. (2021), ‘Evaluating the effects of shelter-in-place policies during the COVID-19 pandemic’, Proceedings of the National Academy of Sciences, 118, p. e2019706118.Google ScholarPubMed
Callaway, B. and Sant’Anna, P.H. (forthcoming), ‘Difference-in-differences with multiple time periods’, Journal of Econometrics.Google Scholar
Chen, F. and Toxvaerd, F. (2014), ‘The economics of vaccination’, Journal of Theoretical Biology, 363, pp. 105–17.CrossRefGoogle Scholar
Chen, M.K., Zhuo, Y., Da La Fuente, M., Rohla, R. and Long, E.F. (2020), ‘Causal estimation of stay-at-home orders on sars-cov-2 transmission,’ preprint, arXiv:2005.05469.Google Scholar
Cook, T. and Roberts, J. (2021), ‘Impact of vaccination by priority group on UK deaths, hospital admissions and intensive care admissions from COVID-19’, Anaesthesia, 76, pp. 608–16.CrossRefGoogle Scholar
De-Leon, H., Calderon-Margalit, R., Pederiva, F., Ashkenazy, Y. and Gazit, D. (2021), ‘First indication of the effect of COVID-19 vaccinations on the course of the COVID-19 outbreak in Israel’, medRxiv.CrossRefGoogle Scholar
Driscoll, J.C. and Kraay, A.C. (1998), ‘Consistent covariance matrix estimation with spatially dependent panel data’, Review of Economics and Statistics, 80, pp. 549–60.CrossRefGoogle Scholar
Fenichel, E.P., Castillo-Chavez, C., Ceddia, M.G., Chowell, G., Parra, P.A.G., Hickling, G.J., Holloway, G., Horan, R., Morin, B., Perrings, C., Springborn, M., Velazquez, L. and Villalobos, C. (2011), ‘Adaptive human behavior in epidemiological models’, Proceedings of the National Academy of Sciences, 108, pp. 6306–11.CrossRefGoogle ScholarPubMed
Ferguson, N.M., Laydon, D., Nedjati-Gilani, G., et al. (2020), ‘Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand’, Imperial College COVID-19 Response Team Report 9, March 16.Google Scholar
Forni, G. and Mantovani, A. (2021), ‘COVID-19 vaccines: Where we stand and challenges ahead’, Cell Death & Differentiation, 28, pp. 626–39.CrossRefGoogle ScholarPubMed
Galanti, M., Pei, S., Yamana, T.K., Angulo, F.J., Charos, A., Swerdlow, D.L. and Shaman, J. (2021), ‘Social distancing remains key during vaccinations’, Science, 371, pp. 473–4.CrossRefGoogle ScholarPubMed
Gavi: The Vaccine Alliance (2021), ‘The COVAX facility: Interim distribution forecast latest as of February 3, 2021’.Google Scholar
Geoffard, P.-Y. and Philipson, T. (1997), ‘Disease eradication: Private versus public vaccination’, The American Economic Review, 87, pp. 222–30.Google Scholar
Goodman-Bacon, A. (2018), ‘Difference-in-differences with variation in treatment timing’, Technical Report, National Bureau of Economic Research.CrossRefGoogle Scholar
Goolsbee, A. and Syverson, C. (2021), ‘Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020’, Journal of Public Economics, 193, p. 104311.CrossRefGoogle ScholarPubMed
Hale, T., Angrist, N., Goldszmidt, R., et al. (2021), ‘A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)’, Nature Human Behaviour, 6, pp. 529–538.CrossRefGoogle Scholar
Iboi, E.A., Ngonghala, C.N. and Gumel, A.B. (2020), ‘Will an imperfect vaccine curtail the COVID-19 pandemic in the US?’, Cambridge Working Papers in Economics 2097, Faculty of Economics, University of Cambridge. Infectious Disease Modelling, 5, pp. 510–24.CrossRefGoogle Scholar
Kremer, M. (1996), ‘Integrating behavioral choice into epidemiological models of AIDS’, Quarterly Journal of Economics, 111, pp. 549–73.CrossRefGoogle Scholar
Lee, J.Y. and Solon, G. (2011), ‘The fragility of estimated effects of unilateral divorce laws on divorce rates’, The BE Journal of Economic Analysis & Policy, 11.Google Scholar
Makris, M. and Toxvaerd, F. (2020), ‘Great expectations: Social distancing in anticipation of pharmaceutical innovations’, Cambridge Working Papers in Economics 2097, Faculty of Economics, University of Cambridge.Google Scholar
McAdams, D. (2020), ‘Economic epidemiology in the wake of COVID-19’, Economics, 82120, pp. 1–40.Google Scholar
McKee, M. and Rajan, S. (2021), ‘What can we learn from Israel’s rapid roll out of COVID 19 vaccination?’, Israel Journal of Health Policy Research, 10, p. 12.CrossRefGoogle ScholarPubMed
Mecenas, P., Bastos, R.T.D.R.M., Vallinoto, A.C.R. and Normando, D. (2020), ‘Effects of temperature and humidity on the spread of COVID-19: A systematic review’, PLoS one, 15, p. e0238339.CrossRefGoogle ScholarPubMed
Pearl, J. (2013), ‘Linear models: A useful “microscope” for causal analysis’, Journal of Causal Inference, 1, pp. 155–70.CrossRefGoogle Scholar
Philipson, T. (2000), ‘Economic epidemiology and infectious diseases’, Handbook of Health Economics, 1, pp. 1761–99.CrossRefGoogle Scholar
Public Health England (2021a), ‘Impact of COVID-19 vaccines on mortality in England: December 2020 to March 2021’.Google Scholar
Public Health England (2021b), ‘Public Health England vaccine effectiveness report, March 2021’.Google Scholar
Rambachan, A. and Roth, J. (2019), ‘An honest approach to parallel trends’, Unpublished manuscript, Harvard University.Google Scholar
So, A.D. and Woo, J. (2020), ‘Reserving coronavirus disease 2019 vaccines for global access: Cross sectional analysis’, British Medical Journal, 371.Google ScholarPubMed
Talamas, E. and Vohra, R. (2018), ‘Go big or go home: a free and perfectly safe but only partially effective vaccine can make everyone worse off’, Technical Report, Penn Institute for Economic Research, Department of Economics.CrossRefGoogle Scholar
Toxvaerd, F. (2019), ‘Rational disinhibition and externalities in prevention’, International Economic Review, 60, pp. 1737–55.CrossRefGoogle Scholar
Toxvaerd, F. and Rowthorn, R. 2020, ‘On the management of population immunity’, Technical Report, Faculty of Economics & Cambridge-INET Institute, University of Cambridge.Google Scholar
Twohey, M., Collins, K. and Thomas, K. (2020), ‘With First Dibs on Vaccines, Rich Countries Have ‘Cleared the Shelves’”, The New York Times.Google Scholar
Wright, A.L., Sonin, K., Driscoll, J. and Wilson, J. (2020), ‘Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols’, Journal of Economic Behavior & Organization, 180, pp. 544–54.CrossRefGoogle ScholarPubMed
Yan, Y., Malik, A.A., Bayham, J., Fenichel, E.P., Couzens, C. and Omer, S.B. (2021), ‘Measuring voluntary and policy-induced social distancing behavior during the COVID-19 pandemic’, Proceedings of the National Academy of Sciences, 118, p. e2008814118.Google ScholarPubMed
Zanin, L. and Marra, G. (2012), ‘Rolling regression versus time-varying coefficient modelling: An empirical investigation of the Okun’s law in some Euro area countries’, Bulletin of Economic Research, 64, pp. 91–108.CrossRefGoogle Scholar