Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020;33(4):1127-1172.
doi: 10.1007/s00148-020-00778-2. Epub 2020 May 9.

Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China

Yun Qiu  1 , Xi Chen  2   3 , Wei Shi  1
Affiliations

Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China

Yun Qiu et al. J Popul Econ. 2020.

Abstract

This study models local and cross-city transmissions of the novel coronavirus in China between January 19 and February 29, 2020. We examine the role of various socioeconomic mediating factors, including public health measures that encourage social distancing in local communities. Weather characteristics 2 weeks prior are used as instrumental variables for causal inference. Stringent quarantines, city lockdowns, and local public health measures imposed in late January significantly decreased the virus transmission rate. The virus spread was contained by the middle of February. Population outflow from the outbreak source region posed a higher risk to the destination regions than other factors, including geographic proximity and similarity in economic conditions. We quantify the effects of different public health measures in reducing the number of infections through counterfactual analyses. Over 1.4 million infections and 56,000 deaths may have been avoided as a result of the national and provincial public health measures imposed in late January in China.

Keywords: 2019 novel coronavirus; Quarantine; Transmission.

PubMed Disclaimer

Conflict of interest statement

Conflict of interestsThe authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Timeline of key variables
Fig. 2
Fig. 2
Number of daily new confirmed cases of COVID-19 in mainland China
Fig. 3
Fig. 3
Baidu index of population flow from Wuhan
Fig. 4
Fig. 4
Destination shares in population flow from Wuhan
Fig. 5
Fig. 5
Rolling window analysis of within- and between-city transmission of COVID-19. This figure shows the estimated coefficients and 95% CIs from the instrumental variable regressions. The specification is the same as the IV regression models in Table 4. Each estimation sample contains 14 days with the starting date indicated on the horizontal axis
Fig. 6
Fig. 6
Timeline of China’s public health policies in curtailing the spread of COVID-19
Fig. 7
Fig. 7
Counterfactual policy simulations. This figure displays the daily differences between the total predicted number and the actual number of daily new COVID-19 cases for each of the four counterfactual scenarios for cities outside Hubei province in mainland China. The spike on February 12 in scenario C is due to a sharp increase in daily case counts in Wuhan resulting from changes in case definitions in Hubei province (see Appendix B for details)
Fig. 8
Fig. 8
Number of daily new confirmed cases of COVID-19 in mainland China and revised case counts in Hubei Province
See this image and copyright information in PMC

Update of

References

    1. Adda J. Economic activity and the spread of viral diseases: evidence from high frequency data. Q J Econ. 2016;131(2):891–941. doi: 10.1093/qje/qjw005. - DOI
    1. Ahrens A, Hansen C, Schaffer ME (2019) lassopack: model selection and prediction with regularized regression in Stata, arXiv:1901.05397
    1. Barmby T, Larguem M. Coughs and sneezes spread diseases: an empirical study of absenteeism and infectious illness. J Health Econ. 2009;28:1012–1017. doi: 10.1016/j.jhealeco.2009.06.006. - DOI - PubMed
    1. Belloni A, Chernozhukov V, Hansen C, Kozbur D. Inference in high-dimensional panel models with an application to gun control. J Bus Econ Stat. 2016;34:590–605. doi: 10.1080/07350015.2015.1102733. - DOI
    1. Chin Y-M, Wilson N. Disease risk and fertility: evidence from the HIV/AIDS pandemic. J Popul Econ. 2018;31:429–451. doi: 10.1007/s00148-017-0669-5. - DOI

LinkOut - more resources