Within-city transmission
Table 3 reports the estimation results of the OLS and IV regressions of Eq. 2, in which only within-city transmission is considered. After controlling for time-invariant city fixed effects and time effects that are common to all cities, on average, one new infection leads to 1.142 more cases in the next week, but 0.824 fewer cases 1 week later. The negative effect can be attributed to the fact that both local authorities and residents would have taken more protective measures in response to a higher perceived risk of contracting the virus given more time. Information disclosure on newly confirmed cases at the daily level by official media and information dissemination on social media throughout China may have promoted more timely actions by the public, resulting in slower virus transmissions. We then compare the transmission rates in different time windows. In the first sub-sample, one new infection leads to 2.135 more cases within a week, implying a fast growth in the number of cases. However, in the second sub-sample, the effect decreases to 1.077, suggesting that public health measures imposed in late January were effective in limiting a further spread of the virus. Similar patterns are also observed in model B.
Table 3 Within-city transmission of COVID-19
Jan 19–Feb 29 Jan 19–Feb 1 Feb 2–Feb 29
(1) (2) (3) (4) (5) (6)
OLS IV OLS IV OLS IV
All cities excluding Wuhan
Model A: lagged variables are averages over the preceding first and second week separately
Average # of new cases 0.873*** 1.142*** 1.692*** 2.135*** 0.768*** 1.077***
1-week lag (0.00949) (0.0345) (0.0312) (0.0549) (0.0120) (0.0203)
Average # of new cases − 0.415*** − 0.824*** 0.860 − 6.050*** − 0.408*** − 0.796***
2-week lag (0.00993) (0.0432) (2.131) (2.314) (0.00695) (0.0546)
Model B: lagged variables are averages over the preceding 2 weeks
Average # of new case 0.474*** 0.720*** 3.310*** 3.860*** 0.494*** 1.284***
Previous 14 days (0.0327) (0.143) (0.223) (0.114) (0.00859) (0.107)
Observations 12,768 12,768 4256 4256 8512 8512
Number of cities 304 304 304 304 304 304
Weather controls Yes Yes Yes Yes Yes Yes
City FE Yes Yes Yes Yes Yes Yes
Date FE Yes Yes Yes Yes Yes Yes
All cities excluding cities in Hubei Province
Model A: lagged variables are averages over the preceding first and second week separately
Average # of new cases 0.725*** 1.113*** 1.050*** 1.483*** 0.620*** 0.903***
1-week lag (0.141) (0.0802) (0.0828) (0.205) (0.166) (0.0349)
Average # of new cases − 0.394*** − 0.572*** 0.108 − 3.664 − 0.228*** − 0.341***
2-week lag (0.0628) (0.107) (0.675) (2.481) (0.0456) (0.121)
Model B: lagged variables are averages over the preceding 2 weeks
Average # of new cases 0.357*** 0.631*** 1.899*** 2.376*** 0.493*** 0.745***
Previous 14 days (0.0479) (0.208) (0.250) (0.346) (0.122) (0.147)
Observations 12,096 12,096 4032 4032 8064 8064
Number of cities 288 288 288 288 288 288
Weather controls Yes Yes Yes Yes Yes Yes
City FE Yes Yes Yes Yes Yes Yes
Date FE Yes Yes Yes Yes Yes Yes
The dependent variable is the number of daily new cases. The endogenous explanatory variables include the average numbers of new confirmed cases in the own city in the preceding first and second weeks (model A) and the average number in the preceding 14 days (model B). Weekly averages of daily maximum temperature, precipitation, wind speed, the interaction between precipitation and wind speed, and the inverse log distance weighted sum of each of these variables in other cities, during the preceding third and fourth weeks, are used as instrumental variables in the IV regressions. Weather controls include contemporaneous weather variables in the preceding first and second weeks. Standard errors in parentheses are clustered by provinces. *** p < 0.01, ** p < 0.05, * p < 0.1
Many cases were also reported in other cities in Hubei province apart from Wuhan, where six of them reported over 1000 cumulative cases by February 1513. Their overstretched health care system exacerbates the concern over delayed reporting of confirmed cases in these cities. To mitigate the effect of such potential measurement errors on our estimates, we re-estimate (2) excluding all cities in Hubei province. The bottom panel of Table 3 reports these estimates. Comparing the IV estimates in columns (4) and (6) between the upper and lower panels, we find that the transmission rates are lower in cities outside Hubei. In the January 19–February 1 sub-sample, one new case leads to 1.483 more cases in the following week, and this is reduced to 0.903 in the February 2–February 29 sub-sample. We also find a similar pattern when comparing the estimates from model B.