[1] Haug N, Geyrhofer L, Londei A, Dervic E, Desvars-Larrive A, Loreto V, et al. Ranking the effectiveness of worldwide COVID-19 government interventions. Nat Hum Behav 2020;4(12):1303 − 12. http://dx.doi.org/10.1038/s41562-020-01009-0.
[2] Tian HY, Liu YH, Li YD, Wu CH, Chen B, Kraemer MUG, et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 2020;368(6491):638 − 42. http://dx.doi.org/10.1126/science.abb6105.
[3] Chetty R, Friedman JN, Hendren N, Stepner M, The Opportunity Insights Team. The economic impacts of COVID-19: evidence from a new public database built using private sector data. 2020 Jun. NBER Working Paper No. w27431. https://www.nber.org/papers/w27431.
[4] Guan DB, Wang DP, Hallegatte S, Davis SJ, Huo JW, Li SP, et al. Global supply-chain effects of COVID-19 control measures. Nat Hum Behav 2020;4(6):577 − 87. http://dx.doi.org/10.1038/s41562-020-0896-8.
[5] Bonaccorsi G, Pierri F, Cinelli M, Flori A, Galeazzi A, Porcelli F, et al. Economic and social consequences of human mobility restrictions under COVID-19. Proc Natl Acad Sci USA 2020;117(27):15530 − 5. http://dx.doi.org/10.1073/pnas.2007658117.
[6] Gimbrone C, Rutherford C, Kandula S, Martínez-Alés G, Shaman J, Olfson M, et al. Associations between COVID-19 mobility restrictions and economic, mental health, and suicide-related concerns in the US using cellular phone GPS and Google search volume data. PLoS One 2021;16(12):e0260931. http://dx.doi.org/10.1371/journal.pone.0260931.
[7] Hatchett RJ, Mecher CE, Lipsitch M. Public health interventions and epidemic intensity during the 1918 influenza pandemic. Proc Natl Acad Sci USA 2007;104(18):7582 − 7. http://dx.doi.org/10.1073/pnas.0610941104.
[8] Chowell G, Echevarría-Zuno S, Viboud C, Simonsen L, Tamerius J, Miller MA, et al. Characterizing the epidemiology of the 2009 influenza A/H1N1 pandemic in mexico. PLoS Med 2011;8(5):e1000436. http://dx.doi.org/10.1371/journal.pmed.1000436.
[9] National Health Commission of the People’s Republic of China. Latest situation on the COVID-19. 2022. http://www.nhc.gov.cn/cms-search/xxgk/getManuscriptXxgk.htm?id=0c63639099e64612993590e0b2b329e8. [2022-5-31]. (In Chinese).
[10] Baud D, Qi XL, Nielsen-Saines K, Musso D, Pomar L, Favre G. Real estimates of mortality following COVID-19 infection. Lancet Infect Dis 2020;20(7):773. http://dx.doi.org/10.1016/S1473-3099(20)30195-X.
[11] National Bureau of Statistics of China. China Statistical Yearbook 2018. 2018. http://www.stats.gov.cn/tjsj/ndsj/2018/indexeh.htm. [2020-6-20]. (In Chinese).
[12] Imbens GW, Rubin DB. Causal inference for statistics, social, and biomedical sciences: an introduction. Cambridge: Cambridge University Press. 2015. http://dx.doi.org/10.1017/CBO9781139025751.
[13] Basu D. Randomization analysis of experimental data: the fisher randomization test. J Am Stat Assoc 1980;75(371):575 − 82. http://dx.doi.org/10.1080/01621459.1980.10477512.
[14] Rubin DB, Stroud TWF. Bayesian break-point forecasting in parallel time series, with application to university admissions. Can J Stat 1987;15(1):1 − 19. http://dx.doi.org/10.2307/3314857.
[15] Han SS, Rubin DB. Contrast-specific propensity scores. Biostat Epidemiol 2021;5(1):1 − 8. http://dx.doi.org/10.1080/24709360.2021.1936421.