Causal effects of vaccine uptake and population mobility on COVID-19 cases and deaths in Russia

  • Иван Гордеев Национальный исследовательский университет «Высшая школа экономики», НИУ ВШЭ

Аннотация

This paper analyzes short-run COVID-19 dynamics in Russia using a weekly panel of 12 regions over 54 weeks. Growth rates of cases and deaths are modeled as functions of vaccination uptake  and behavioral activity, with region fixed effects and a set of controls. Identification uses three  sources of exogenous variation: the timing of regional QR-code mandates as an instrument for Retail & Recreation mobility, news about potential WHO approval of Sputnik V interacted with  the mandate indicator, and a short post-mandate window as instruments for vaccination. First-stage diagnostics show strong relevance (the homoskedastic partial F-statistics are 519 for mobility and  98 for vaccination), while event-study and placebo checks detect no pre-trends or reverse-timing  effects (future WHO-related news terms do not predict current vaccination). TSLS estimates  indicate a clear protective role of vaccination (particularly full immunization) and a positive causal  impact of mobility. The six-week vaccination lag reduces future growth in cases and deaths, with  the effect more than twice as large as naïve OLS suggests. The impact of mobility on subsequent  cases and deaths is about twice as large as suggested by OLS and remains robust across different  specifications. Overall, under standard IV assumptions, completing full vaccination and reducing  high-contact leisure activity substantially reduce short-run transmission and mortality.

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Литература

Andrews, N., Stowe, J., Kirsebom, F., Toffa, S., Rickeard, T., Gallagher, E., Gower, C., Kall, M., Groves, N., O’Connell, A.-M., Simons, D., Blomquist, P. B., Zaidi, A., Nash, S., Abdul Aziz, N. I. B., Thelwall, S., Dabrera, G., Myers, R., Amirthalingam, G., … Lopez Bernal, J. (2022). COVID-19 vaccine effectiveness against the Omicron (B.1.1.529) variant. The New England Journal of Medicine, 386, 1532–1546. https://doi.org/10.1056/NEJMoa2119451

Chernozhukov, V., Kasahara, H., & Schrimpf, P. (2021). Causal impact of masks, policies, behavior on early COVID-19 pandemic in the U.S. Journal of Econometrics, 220(1), 23-62. https://doi.org/10.1016/j.jeconom.2020.09.003

Egorov, G., Enikolopov, R., Makarin, A., & Petrova, M. (2021). Divided we stay home: Social distancing and ethnic diversity. Journal of Public Economics, 194, 104328. https://doi.org/10.1016/j.jpubeco.2020.104328

Ellison, G. (2024). Implications of heterogeneous SIR models for analyses of COVID-19. Review of Economic Design, 28, 651–687. https://doi.org/10.1007/s10058-024-00355-z

Gans, J. S. (2022). The economic consequences of R=1: Towards a workable behavioural epidemiological model of pandemics. Review of Economic Analysis, 14(1), 3–25. https://doi.org/10.15353/rea.v14i1.4786

Google LLC. (2022). COVID-19 Community Mobility Reports. https://www.google.com/covid19/mobility/

Gordeev, I. (2025a). COVID-19 pandemic in Russia: Behavioral response. Journal of Human Behavior in the Social Environment, 35(2), 179–195. https://doi.org/10.1080/10911359.2023.2289492

Gordeev, I. (2025b). Instrumental variables analysis of COVID-19 vaccination in Moscow. Applied Economics, 1–17. https://doi.org/10.1080/00036846.2025.2559205

Hansen, N. J. H., & Mano, R. C. (2023). COVID-19 vaccines: A shot in the arm for the economy. IMF Economic Review, 71, 148–169. https://doi.org/10.1057/s41308-022-00184-6

Karaivanov, A., Lu, S.E., Shigeoka, H., Chen, C., & Pamplona, S. (2021). Face masks, public policies and slowing the spread of COVID-19: Evidence from Canada. Journal of Health Economics, 78, 102475. https://doi.org/10.1016/j.jhealeco.2021.102475

Karaivanov, A., Kim, D., Lu, S.E., & Shigeoka, H. (2022). COVID-19 vaccination mandates and vaccine uptake. Nature Human Behavior, 6, 1615–1624. https://doi.org/10.1038/s41562-022-01363-1

Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London. Series A, Containing Papers of a Mathematical and Physical Character, 115(772), 700–721. https://doi.org/10.1098/rspa.1927.0118

Linton, N., Kobayashi, T., Yang, Y., Hayashi, K., Akhmetzhanov, A., Jung, S., Yuan, B., Kinoshita, R., & Nishiura, H. (2020). Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: A statistical analysis of publicly available case data. Journal of Clinical Medicine, 9(2), 538. https://doi.org/10.3390/jcm9020538

Rahmani, K., Shavaleh, R., Forouhi, M., Feiz Disfani, H., Kamandi, M., Oskooi, R. K., Foogerdi, M., Soltani, M., Rahchamani, M., Mohaddespour, M., & Dianatinasab, M. (2022). The effectiveness of COVID-19 vaccines in reducing the incidence, hospitalization, and mortality from COVID-19: A systematic review and meta-analysis. Frontiers in Public Health, 10, 873596. https://doi.org/10.3389/fpubh.2022.873596

Shkolnikov, V. M., Klimkin, I., McKee, M., Jdanov, D. A., Alustiza-Galarza, A., Németh, L., Timonin, S. A., Nepomuceno, M. R., Andreev, E. M., & Leon, D. A. (2022). What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks. SSM – Population Health, 18, 101118.https://doi.org/10.1016/j.ssmph.2022.101118

Stock, J. H., & Yogo, M. (2005). Testing for weak instruments in linear IV regression. In: Andrews, D.W.K. and Stock, J.H. (eds), Identification and Inference for Econometric Models: Essays in Honor of Thomas Rothenberg. Cambridge: Cambridge University Press, 80–108. https://doi.org/10.1017/CBO9780511614491.006 Timonin, S., Klimkin, I., Shkolnikov, V. M., Andreev, E. M., McKee, M., & Leon, D. A. (2021).

Excess mortality in Russia and its regions compared to high income countries: An analysis of monthly series of 2020. SSM – Population Health, 17, 101006. https://doi.org/10.1016/j.ssmph.2021.101006

Wu, Y., Kang, L., Guo, Z., Liu, J., Liu, M., & Liang, W. (2022). Incubation period of COVID-19 caused by unique SARS-CoV-2 strains: A systematic review and meta-analysis. JAMA Network Open, 5(8), e2228008. https://doi.org/10.1001/jamanetworkopen.2022.28008

Опубликован
2025-10-09
Как цитировать
ГордеевИ. (2025). Causal effects of vaccine uptake and population mobility on COVID-19 cases and deaths in Russia. Препринты НИУ ВШЭ, 10(1). извлечено от https://preprint.hse.ru/article/view/28594