LitCovid-sentences  

PMC:7210464 / 78514-99584 JSONTXT 9 Projects

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Id Subject Object Predicate Lexical cue
T694 0-8 Sentence denotes Appendix
T695 9-49 Sentence denotes The Appendix consists of three sections.
T696 50-203 Sentence denotes Section A provides details on the first stage of the IV regressions and the selection of the instrumental variables for the local public health policies.
T697 204-338 Sentence denotes Section B shows that our main findings are not sensitive to the adjustment in COVID-19 case definitions in Hubei province in February.
T698 339-408 Sentence denotes Section A contains details on the computation of the counterfactuals.
T699 410-421 Sentence denotes Appendix A.
T700 422-445 Sentence denotes First stage regressions
T701 446-623 Sentence denotes Weather conditions affect disease transmissions either directly if the virus can more easily survive and spread in certain environment, or indirectly by changing human behavior.
T702 624-721 Sentence denotes Table 9 reports results of the first stage of the IV regressions (Table 4) using the full sample.
T703 722-890 Sentence denotes In columns (1) and (2), the dependent variables are the numbers of newly confirmed COVID-19 cases in the own city in the preceding first and second weeks, respectively.
T704 891-1096 Sentence denotes In columns (3) and (4), the dependent variables are the sum of inverse log distance weighted numbers of newly confirmed COVID-19 cases in other cities in the preceding first and second weeks, respectively.
T705 1097-1154 Sentence denotes These are the endogenous variables in the IV regressions.
T706 1155-1255 Sentence denotes The weather variables in the preceding first and second weeks are included in the control variables.
T707 1256-1397 Sentence denotes The weather variables in the preceding third and fourth weeks are the excluded instruments, and their coefficients are reported in the table.
T708 1398-1543 Sentence denotes Because the variables are averages in 7-day moving windows, the error term may be serially correlated, and we include city by week fixed effects.
T709 1544-1734 Sentence denotes Also included in the control variables are the average numbers of new cases in Wuhan in the preceding first and second weeks, interacted with the inverse log distance or the population flow.
T710 1735-1766 Sentence denotes Table 9 First stage regressions
T711 1767-1808 Sentence denotes Dependent variable Average # of new cases
T712 1809-1830 Sentence denotes Own city Other cities
T713 1831-1874 Sentence denotes 1-week lag 2-week lag 1-week lag 2-week lag
T714 1875-1890 Sentence denotes (1) (2) (3) (4)
T715 1891-1899 Sentence denotes Own City
T716 1900-1966 Sentence denotes Maximum temperature, 3-week lag 0.200*** − 0.0431 0.564 − 2.022***
T717 1967-2000 Sentence denotes (0.0579) (0.0503) (0.424) (0.417)
T718 2001-2057 Sentence denotes Precipitation, 3-week lag − 0.685 − 0.865* 4.516 − 1.998
T719 2058-2089 Sentence denotes (0.552) (0.480) (4.045) (3.982)
T720 2090-2141 Sentence denotes Wind speed, 3-week lag 0.508** 0.299 − 0.827 3.247*
T721 2142-2173 Sentence denotes (0.256) (0.223) (1.878) (1.849)
T722 2174-2244 Sentence denotes Precipitation × wind speed, 3-week lag − 0.412** 0.122 − 1.129 − 2.091
T723 2245-2276 Sentence denotes (0.199) (0.173) (1.460) (1.437)
T724 2277-2343 Sentence denotes Maximum temperature, 4-week lag 0.162*** 0.125** 1.379*** 1.181***
T725 2344-2377 Sentence denotes (0.0560) (0.0487) (0.410) (0.404)
T726 2378-2433 Sentence denotes Precipitation, 4-week lag 0.0250 − 0.503 2.667 8.952***
T727 2434-2465 Sentence denotes (0.440) (0.383) (3.224) (3.174)
T728 2466-2514 Sentence denotes Wind speed, 4-week lag 0.179 0.214 − 1.839 1.658
T729 2515-2546 Sentence denotes (0.199) (0.173) (1.458) (1.435)
T730 2547-2620 Sentence denotes Precipitation × wind speed, 4-week lag − 0.354** − 0.0270 1.107 − 2.159**
T731 2621-2652 Sentence denotes (0.145) (0.126) (1.059) (1.043)
T732 2653-2692 Sentence denotes Other cities, weight = inverse distance
T733 2693-2762 Sentence denotes Maximum temperature, 3-week lag − 0.0809*** − 0.00633 0.0520 1.152***
T734 2763-2796 Sentence denotes (0.0203) (0.0176) (0.149) (0.146)
T735 2797-2862 Sentence denotes Precipitation, 3-week lag 4.366*** − 2.370*** 17.99*** − 72.68***
T736 2863-2894 Sentence denotes (0.639) (0.556) (4.684) (4.611)
T737 2895-2955 Sentence denotes Wind speed, 3-week lag 0.326*** − 0.222** − 1.456 − 11.02***
T738 2956-2987 Sentence denotes (0.126) (0.110) (0.926) (0.912)
T739 2988-3066 Sentence denotes Precipitation × wind speed, 3-week lag − 1.780*** 0.724*** − 6.750*** 27.73***
T740 3067-3098 Sentence denotes (0.227) (0.197) (1.663) (1.637)
T741 3099-3170 Sentence denotes Maximum temperature, 4-week lag − 0.0929*** − 0.0346* − 0.518*** 0.0407
T742 3171-3204 Sentence denotes (0.0220) (0.0191) (0.161) (0.159)
T743 3205-3267 Sentence denotes Precipitation, 4-week lag 3.357*** − 0.578 46.57*** − 25.31***
T744 3268-3299 Sentence denotes (0.504) (0.438) (3.691) (3.633)
T745 3300-3359 Sentence denotes Wind speed, 4-week lag 0.499*** 0.214** 4.660*** − 4.639***
T746 3360-3392 Sentence denotes (0.107) (0.0934) (0.787) (0.774)
T747 3393-3471 Sentence denotes Precipitation × wind speed, 4-week lag − 1.358*** − 0.0416 − 17.26*** 8.967***
T748 3472-3503 Sentence denotes (0.178) (0.155) (1.303) (1.282)
T749 3504-3538 Sentence denotes F statistic 11.41 8.46 19.10 36.32
T750 3539-3574 Sentence denotes p value 0.0000 0.0000 0.0000 0.0000
T751 3575-3615 Sentence denotes Observations 12,768 12,768 12,768 12,768
T752 3616-3648 Sentence denotes Number of cities 304 304 304 304
T753 3649-3681 Sentence denotes # cases in Wuhan Yes Yes Yes Yes
T754 3682-3730 Sentence denotes Contemporaneous weather controls Yes Yes Yes Yes
T755 3731-3754 Sentence denotes City FE Yes Yes Yes Yes
T756 3755-3778 Sentence denotes Date FE Yes Yes Yes Yes
T757 3779-3810 Sentence denotes City by week FE Yes Yes Yes Yes
T758 3811-3874 Sentence denotes This table shows the results of the first stage IV regressions.
T759 3875-3943 Sentence denotes The weather variables are weekly averages of daily weather readings.
T760 3944-4082 Sentence denotes Coefficients of the weather variables which are used as excluded instrumental variables are reported. *** p < 0.01, ** p < 0.05, * p < 0.1
T761 4083-4278 Sentence denotes Because the spread of the virus depends on both the number of infectious people and the weather conditions, the coefficients in the first stage regressions do not have structural interpretations.
T762 4279-4398 Sentence denotes The Wald tests on the joint significance of the excluded instruments are conducted and their F statistics are reported.
T763 4399-4451 Sentence denotes The excluded instruments have good predictive power.
T764 4452-4673 Sentence denotes The implementation of local public health measures is likely correlated with the extent of the virus spread, so weather conditions that affect virus transmissions may also affect the likelihood that the policy is adopted.
T765 4674-4956 Sentence denotes The influence of weather conditions on policy adoption may be complicated, so we use the Cluster-Lasso method of Belloni et al. (2016) to select the weather variables that have good predictive power on the adoption of closed management of communities or family outdoor restrictions.
T766 4957-5468 Sentence denotes Let dct be the dummy variable of the adoption of the local public health measure, i.e., dct = 1 if the policy is in place in city c at day t. qct is a vector of candidate weather variables, including weekly averages of daily mean temperature, maximum temperature, minimum temperature, dew point, station-level pressure, sea-level pressure, visibility, wind speed, maximum wind speed, snow depth, precipitation, dummy for adverse weather conditions, squared terms of these variables, and interactions among them.
T767 5469-5581 Sentence denotes First, city and day fixed effects are removed. d¨ct=dct−1n∑cdct−1T∑tdct+1nT∑ctdct and q¨ct is defined similarly.
T768 5582-5649 Sentence denotes The Cluster-Lasso method solves the following minimization problem:
T769 5650-5712 Sentence denotes 1nT∑ctd¨ct−q¨ct′b2+λnT∑kϕk|bk|.λ and ϕ are penalty parameters.
T770 5713-5769 Sentence denotes A larger penalty value forces more coefficients to zero.
T771 5770-5858 Sentence denotes The penalty parameters are picked using the theoretical result of Belloni et al. (2016).
T772 5859-5921 Sentence denotes The estimation uses the Stata package by Ahrens et al. (2019).
T773 5922-6014 Sentence denotes Table 10 lists the selected weather variables, which are used as the instruments in Table 8.
T774 6015-6042 Sentence denotes Table 10 Variables selected
T775 6043-6095 Sentence denotes Dependent variable: closed management of communities
T776 6096-6116 Sentence denotes Dew point 1-week lag
T777 6117-6153 Sentence denotes Diurnal temperature range 1-week lag
T778 6154-6174 Sentence denotes Dew point 2-week lag
T779 6175-6204 Sentence denotes Sea-level pressure 2-week lag
T780 6205-6225 Sentence denotes Dew point 3-week lag
T781 6226-6247 Sentence denotes Visibility 4-week lag
T782 6248-6272 Sentence denotes Precipitation 4-week lag
T783 6273-6320 Sentence denotes Dependent variable: family outdoor restrictions
T784 6321-6348 Sentence denotes Station pressure 1-week lag
T785 6349-6427 Sentence denotes Dummy for adverse weather conditions such as fog, rain, and drizzle 1-week lag
T786 6428-6458 Sentence denotes Maximum temperature 2-week lag
T787 6459-6488 Sentence denotes Sea-level pressure 2-week lag
T788 6489-6519 Sentence denotes Average temperature 3-week lag
T789 6520-6550 Sentence denotes Minimum temperature 3-week lag
T790 6551-6572 Sentence denotes Visibility 3-week lag
T791 6573-6648 Sentence denotes This table shows the weather variables selected by lassopack (Ahrens et al.
T792 6649-6723 Sentence denotes 2019), which implements the Cluster-Lasso method of Belloni et al. (2016).
T793 6724-6765 Sentence denotes City and date fixed effects are included.
T794 6766-7104 Sentence denotes Candidate variables include weekly averages of daily mean temperature, maximum temperature, minimum temperature, dew point, station-level pressure, sea-level pressure, visibility, wind speed, maximum wind speed, snow depth, precipitation, dummy for adverse weather conditions, squared terms of these variables, and interactions among them
T795 7106-7117 Sentence denotes Appendix B.
T796 7118-7161 Sentence denotes Exclude clinically diagnosed cases in Hubei
T797 7162-7250 Sentence denotes COVID-19 case definitions were changed in Hubei province on February 12 and February 20.
T798 7251-7404 Sentence denotes Starting on February 12, COVID-19 cases could also be confirmed based on clinical diagnosis in Hubei province, in addition to molecular diagnostic tests.
T799 7405-7524 Sentence denotes This resulted in a sharp increase in the number of daily new cases reported in Hubei, and in particular Wuhan (Fig. 2).
T800 7525-7596 Sentence denotes The use of clinical diagnosis in confirming cases ended on February 20.
T801 7597-7779 Sentence denotes The numbers of cases that are confirmed based on clinical diagnosis for February 12, 13, and 14 are reported by the Health Commission of Hubei Province and are displayed in Table 11.
T802 7780-7891 Sentence denotes As a robustness check, we re-estimate the model after removing these cases from the daily case counts (Fig. 8).
T803 7892-7932 Sentence denotes Our main findings still hold (Table 12).
T804 7933-8014 Sentence denotes The transmission rates are significantly lower in February compared with January.
T805 8015-8146 Sentence denotes Population flow from the epidemic source increases the infections in destinations, and this effect is slightly delayed in February.
T806 8147-8261 Sentence denotes Fig. 8 Number of daily new confirmed cases of COVID-19 in mainland China and revised case counts in Hubei Province
T807 8262-8327 Sentence denotes Table 11 Number of cumulative clinically diagnosed cases in Hubei
T808 8328-8353 Sentence denotes City Feb 12 Feb 13 Feb 14
T809 8354-8371 Sentence denotes Ezhou 155 168 189
T810 8372-8386 Sentence denotes Enshi 19 21 27
T811 8387-8408 Sentence denotes Huanggang 221 306 306
T812 8409-8426 Sentence denotes Huangshi 12 26 42
T813 8427-8448 Sentence denotes Jingmen 202 155‡ 150‡
T814 8449-8471 Sentence denotes Jingzhou 287 269‡ 257‡
T815 8472-8488 Sentence denotes Qianjiang 0 9 19
T816 8489-8502 Sentence denotes Shiyan 3 4 3‡
T817 8503-8517 Sentence denotes Suizhou 0 6 4‡
T818 8518-8535 Sentence denotes Tianmen 26 67 65‡
T819 8536-8559 Sentence denotes Wuhan 12364 14031 14953
T820 8560-8573 Sentence denotes Xiantao 2 2 2
T821 8574-8592 Sentence denotes Xianning 6 189 286
T822 8593-8608 Sentence denotes Xiangyang 0 0 4
T823 8609-8626 Sentence denotes Xiaogan 35 80 148
T824 8627-8642 Sentence denotes Yichang 0 51 67
T825 8643-8732 Sentence denotes ‡The reductions in cumulative case counts are due to revised diagnosis from further tests
T826 8733-8830 Sentence denotes Table 12 Within- and between-city transmission of COVID-19, revised case counts in Hubei Province
T827 8831-8870 Sentence denotes Jan 19–Feb 29 Jan 19–Feb 1 Feb 2–Feb 29
T828 8871-8894 Sentence denotes (1) (2) (3) (4) (5) (6)
T829 8895-8915 Sentence denotes OLS IV OLS IV OLS IV
T830 8916-9006 Sentence denotes Model A: lagged variables are averages over the preceding first and second week separately
T831 9007-9041 Sentence denotes Average # of new cases, 1-week lag
T832 9042-9104 Sentence denotes Own city 0.747*** 0.840*** 0.939*** 2.456*** 0.790*** 1.199***
T833 9105-9156 Sentence denotes (0.0182) (0.0431) (0.102) (0.638) (0.0211) (0.0904)
T834 9157-9219 Sentence denotes Other cities 0.00631** 0.0124 0.0889 0.0412 − 0.00333 − 0.0328
T835 9220-9293 Sentence denotes wt. = inv. dist. (0.00289) (0.00897) (0.0714) (0.0787) (0.00601) (0.0230)
T836 9294-9347 Sentence denotes Wuhan 0.0331*** 0.0277 − 0.879 − 0.957 0.0543* 0.0840
T837 9348-9416 Sentence denotes wt. = inv. dist. (0.0116) (0.0284) (0.745) (0.955) (0.0271) (0.0684)
T838 9417-9490 Sentence denotes Wuhan 0.00365*** 0.00408*** 0.00462*** 0.00471*** − 0.000882 − 0.00880***
T839 9491-9571 Sentence denotes wt. = pop. flow (0.000282) (0.000287) (0.000326) (0.000696) (0.000797) (0.00252)
T840 9572-9606 Sentence denotes Average # of new cases, 2-week lag
T841 9607-9670 Sentence denotes Own city − 0.519*** − 0.673*** 2.558 − 1.633 − 0.286*** − 0.141
T842 9671-9722 Sentence denotes (0.0138) (0.0532) (2.350) (2.951) (0.0361) (0.0899)
T843 9723-9792 Sentence denotes Other cities − 0.00466 − 0.0208 − 0.361 − 0.0404 − 0.00291 − 0.0235**
T844 9793-9863 Sentence denotes wt. = inv. dist. (0.00350) (0.0143) (0.371) (0.496) (0.00566) (0.0113)
T845 9864-9913 Sentence denotes Wuhan − 0.0914* 0.0308 3.053 3.031 − 0.154 0.0110
T846 9914-9982 Sentence denotes wt. = inv. dist. (0.0465) (0.0438) (2.834) (3.559) (0.0965) (0.0244)
T847 9983-10051 Sentence denotes Wuhan 0.00827*** 0.00807*** 0.00711*** − 0.00632 0.0119*** 0.0112***
T848 10052-10131 Sentence denotes wt. = pop. flow (0.000264) (0.000185) (0.00213) (0.00741) (0.000523) (0.000627)
T849 10132-10197 Sentence denotes Model B: lagged variables are averages over the preceding 2 weeks
T850 10198-10260 Sentence denotes Own city 0.235*** 0.983*** 1.564*** 2.992*** 0.391*** 0.725***
T851 10261-10310 Sentence denotes (0.0355) (0.158) (0.174) (0.892) (0.0114) (0.101)
T852 10311-10372 Sentence denotes Other cities 0.00812 − 0.0925* 0.0414 0.0704 0.0181 − 0.00494
T853 10373-10444 Sentence denotes wt. = inv. dist. (0.00899) (0.0480) (0.0305) (0.0523) (0.0172) (0.0228)
T854 10445-10502 Sentence denotes Wuhan − 0.172* − 0.114** − 0.309 − 0.608 − 0.262 − 0.299*
T855 10503-10568 Sentence denotes wt. = inv. dist. (0.101) (0.0472) (0.251) (0.460) (0.161) (0.169)
T856 10569-10633 Sentence denotes Wuhan 0.0133*** 0.0107*** 0.00779*** 0.00316 0.0152*** 0.0143***
T857 10634-10714 Sentence denotes wt. = pop. flow (0.000226) (0.000509) (0.000518) (0.00276) (0.000155) (0.000447)
T858 10715-10765 Sentence denotes Observations 12,768 12,768 4,256 4,256 8,512 8,512
T859 10766-10806 Sentence denotes Number of cities 304 304 304 304 304 304
T860 10807-10847 Sentence denotes Weather controls Yes Yes Yes Yes Yes Yes
T861 10848-10879 Sentence denotes City FE Yes Yes Yes Yes Yes Yes
T862 10880-10911 Sentence denotes Date FE Yes Yes Yes Yes Yes Yes
T863 10912-10968 Sentence denotes The dependent variable is the number of daily new cases.
T864 10969-11189 Sentence denotes The endogenous explanatory variables include the average numbers of new confirmed cases in the own city and nearby cities in the preceding first and second weeks (model A) and averages in the preceding 14 days (model B).
T865 11190-11497 Sentence denotes Weekly averages of daily maximum temperature, precipitation, wind speed, the interaction between precipitation and wind speed, and the inverse log distance weighted sum of these variables in other cities, during the preceding third and fourth weeks, are used as instrumental variables in the IV regressions.
T866 11498-11597 Sentence denotes Weather controls include contemporaneous weather variables in the preceding first and second weeks.
T867 11598-11693 Sentence denotes Standard errors in parentheses are clustered by provinces. *** p < 0.01, ** p < 0.05, * p < 0.1
T868 11695-11706 Sentence denotes Appendix C.
T869 11707-11737 Sentence denotes Computation of counterfactuals
T870 11738-11755 Sentence denotes Our main model is
T871 11756-11890 Sentence denotes 4 yct=∑τ=12∑k=1Kwithinαwithin,τkh¯ctkτy¯ctτ+∑τ=12∑k=1Kbetween∑r≠cαbetween,τkm¯crtkτy¯rtτ+∑τ=12∑k=1KWuhanρτkm¯c,Wuhan,tkτz¯tτ+xctβ+𝜖ct.
T872 11891-12006 Sentence denotes It is convenient to write it in vector form, 5 Ynt=∑s=114Hnt,s(αwithin)+Mnt,s(αbetween)Yn,t−s+∑τ=12Zntτρτ+Xntβ+𝜖nt,
T873 12007-12052 Sentence denotes where Ynt=y1t⋯ynt′ and 𝜖nt are n × 1 vectors.
T874 12053-12214 Sentence denotes Assuming that Yns = 0 if s ≤ 0, because our sample starts on January 19, and no laboratory confirmed case was reported before January 19 in cities outside Wuhan.
T875 12215-12274 Sentence denotes Xnt=x1t′⋯xnt′′ is an n × k matrix of the control variables.
T876 12275-12411 Sentence denotes Hnt,s(αwithin) is an n × n diagonal matrix corresponding to the s-day time lag, with parameters αwithin={αwithin,τk}k=1,⋯,Kwithin,τ=1,2.
T877 12412-12623 Sentence denotes For example, for s = 1,⋯ , 7, the i th diagonal element of Hnt,s(αwithin) is 17∑k=1Kwithinαwithin,1kh¯ct,ik1, and for s = 8,⋯ , 14, the i th diagonal element of Hnt,s(αwithin) is 17∑k=1Kwithinαwithin,2kh¯ct,ik2.
T878 12624-12665 Sentence denotes Mnt,s(αbetween) is constructed similarly.
T879 12666-12777 Sentence denotes For example, for s = 1,⋯ , 7 and i≠j, the ij th element of Mnt,s(αbetween) is 17∑k=1Kbetweenαbetween,1km¯ijtk1.
T880 12778-12852 Sentence denotes Zntτ is an n × KWuhan matrix corresponding to the transmission from Wuhan.
T881 12853-12913 Sentence denotes For example, the ik th element of Znt1 is m¯i,Wuhan,tk1z¯t1.
T882 12914-13001 Sentence denotes We first estimate the parameters in Eq. 4 by 2SLS and obtain the residuals 𝜖^n1,⋯,𝜖^nT.
T883 13002-13091 Sentence denotes Let ⋅^ denote the estimated value of parameters and ⋅~ denote the counterfactual changes.
T884 13092-13334 Sentence denotes The counterfactual value of Ynt is computed recursively, Y~n1=∑τ=12Z~n1τρ^τ+Xn1β^+𝜖^n1,Y~n2=∑s=11H~n2,s(α^within)+M~n2,s(α^between)Y~n,2−s+∑τ=12Z~n2τρ^τ+Xn2β^+𝜖^n2,Y~n3=∑s=12H~n3,s(α^within)+M~n3,s(α^between)Y~n,3−s+∑τ=12Z~n3τρ^τ+Xn3β^+𝜖^n3,⋮
T885 13335-13389 Sentence denotes The counterfactual change for date t is ΔYnt=Y~nt−Ynt.
T886 13390-13460 Sentence denotes The standard error of ΔYnt is obtained from 1000 bootstrap iterations.
T887 13461-13578 Sentence denotes In each bootstrap iteration, cities are sampled with replacement and the model is estimated to obtain the parameters.
T888 13579-13746 Sentence denotes The counterfactual predictions are obtained using the above equations with the estimated parameters and the counterfactual scenario (e.g., no cities adopted lockdown).
T889 13747-13843 Sentence denotes 1 COVID-19 is also known as novel coronavirus pneumonia or 2019-nCoV acute respiratory disease.
T890 13844-13893 Sentence denotes 2 In 2020, the Lunar New Year was on January 25.
T891 13894-14116 Sentence denotes 3 Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6).
T892 14117-14256 Sentence denotes 4 For instance, using data on the first 425 COVID-19 patients by January 22, Li et al. (2020) estimate a basic reproduction number of 2.2.
T893 14257-14451 Sentence denotes Based on time-series data on the number of COVID-19 cases in mainland China from January 10 to January 24, Zhao et al. (2020) estimate that the mean reproduction number ranges from 2.24 to 3.58.
T894 14452-14535 Sentence denotes 5 We assume a case fatality rate of 4%, the same as China’s current average level.
T895 14536-14809 Sentence denotes Of course, the eventual case fatality rate may be different from the current value, and it depends on many key factors, such as the preparedness of health care systems and the demographic structure of the population outside Hubei province in comparison to China as a whole.
T896 14810-15030 Sentence denotes Also importantly, among patients who have died from COVID-19, the time from symptom onset to outcome ranges from 2 to 8 weeks (World Health Organization 2020b), which is partially beyond the time window of this analysis.
T897 15031-15116 Sentence denotes Therefore, we defer more rigorous estimates about avoided fatality to future studies.
T898 15117-15190 Sentence denotes 6 Li et al. (2020) document the exposure history of the first 425 cases.
T899 15191-15290 Sentence denotes It is suspected that the initial cases were linked to the Huanan Seafood Wholesale Market in Wuhan.
T900 15291-15452 Sentence denotes 7 The COVID-19 epidemic is still ongoing at the time of writing, and the estimates are revised from time to time in the literature as new data become available.
T901 15453-15497 Sentence denotes The current estimates include the following.
T902 15498-15615 Sentence denotes The incubation period is estimated to be between 2 and 10 days (World Health Organization 2020a), 5.2 days (Li et al.
T903 15616-15662 Sentence denotes 2020), or 3 days (median, Guan et al. (2020)).
T904 15663-15731 Sentence denotes The average infectious period is estimated to be 1.4 days (Wu et al.
T905 15732-15739 Sentence denotes 2020a).
T906 15740-16008 Sentence denotes 8 On February 12, cities in Hubei province include clinically diagnosed cases in the confirmed cases, in addition to cases that are confirmed by nucleic acid tests, which results in a sharp increase in the number of confirmed cases for cities in Hubei on February 12.
T907 16009-16085 Sentence denotes The common effect on other cities is controlled for by the day fixed effect.
T908 16086-16139 Sentence denotes 9 Flu viruses are easier to survive in cold weather.
T909 16140-16252 Sentence denotes Adverse weather conditions also limit outdoor activities which can decrease the chance of contracting the virus.
T910 16253-16298 Sentence denotes For details, see Adda (2016) and Section 3.2.
T911 16299-16402 Sentence denotes 10 Hong Kong and Macao are excluded from our analysis due to the lack of some socioeconomic variables.
T912 16403-16450 Sentence denotes 11 Baidu migration (https://qianxi.baidu.com).
T913 16451-16516 Sentence denotes 12 The 100-km circle is consistent with the existing literature.
T914 16517-16678 Sentence denotes Most studies on the socioeconomic impacts of climate change have found that estimation results are insensitive to the choice of the cutoff distance (Zhang et al.
T915 16679-16685 Sentence denotes 2017).
T916 16686-16767 Sentence denotes 13 These cities are Xiaogan, Huanggang, Jingzhou, Suizhou, Ezhou, and Xiangyang.
T917 16768-16821 Sentence denotes 14 The shares of top 100 destinations are available.
T918 16822-16949 Sentence denotes The starting and ending dates of the average shares released by Baidu do not precisely match the period of the analysis sample.
T919 16950-17095 Sentence denotes 15 It is estimated that 14,925,000 people traveled out of Wuhan in 2019 during the Lunar New Year holiday (http://www.whtv.com.cn/p/17571.html).
T920 17096-17284 Sentence denotes The sum of Baidu’s migration index for population flow out of Wuhan during the 40 days around the 2019 Lunar New Year is 203.3, which means one index unit represents 0.000013621 travelers.
T921 17285-17324 Sentence denotes The destination share is in percentage.
T922 17325-17460 Sentence denotes With one more case in Wuhan, the effect on a city receiving 10,000 travelers from Wuhan is 0.00471 × 0.000013621 × 100 × 10000 = 0.064.
T923 17461-17500 Sentence denotes 16 http://www.whtv.com.cn/p/17571.html
T924 17501-17663 Sentence denotes 17 From mid February, individual specific health codes such as Alipay Health Code and WeChat Health Code are being used in many cities to aid quarantine efforts.
T925 17664-17724 Sentence denotes 18 Disease prevalence can also affect economic development.
T926 17725-17872 Sentence denotes One channel is the fertility decision which leads to changes in the demographic structure (e.g., Durevall and Lindskog 2011; Chin and Wilson 2018).
T927 17873-18147 Sentence denotes Fogli and Veldkamp (forthcoming) show that because a dense network spreads diseases faster and higher income is positively correlated with more closely connected social network, infectious diseases can reduce long-run economic growth by limiting the size of social networks.
T928 18148-18244 Sentence denotes 19 There was insufficient hospital capacity in Hubei (and Wuhan in particular) in late January.
T929 18245-18417 Sentence denotes Most patients in Wuhan were hospitalized and isolated around mid February with the completion of new hospitals, makeshift health facilities, and increased testing capacity.
T930 18418-18446 Sentence denotes See Section 5.1 for details.
T931 18447-18544 Sentence denotes 20 We should note that the summary of China’s policy responses here is not a comprehensive list.
T932 18545-18622 Sentence denotes Other entities have also made efforts to help curtail the spread of COVID-19.
T933 18623-18800 Sentence denotes For example, on January 27, the State Grid Corporation of China declared that it would continue supplying electricity to resident users even if payment was not received on time.
T934 18801-18880 Sentence denotes School and universities were closed already because of Lunar New Year holidays.
T935 18881-19048 Sentence denotes 21 According to Law of the People’s Republic of China on Prevention and Treatment of Infectious Diseases, class A infectious diseases only include plague and cholera.
T936 19049-19223 Sentence denotes 22 For a list of quarantine measures, see 2020 Hubei lockdowns (https://en.wikipedia.org/w/index.php?title=2020_Hubei_lockdowns&oldid=946423465), last visited April 2, 2020.
T937 19224-19291 Sentence denotes 23 Wenzhou, Zhengzhou, Hangzhou, Zhumadian, Ningbo, Harbin, Fuzhou
T938 19292-19351 Sentence denotes 24 This restriction varies from 1 to 5 days across cities.
T939 19352-19535 Sentence denotes In most cities, such restrictions are once every 2 days. “Closed management of communities” and “family outdoor restrictions” were mostly announced in city-level government documents.
T940 19536-19691 Sentence denotes There are some cities in which only part of their counties declared to implement “closed management of communities” or “family outdoor restriction” policy.
T941 19692-19768 Sentence denotes However, other counties in the same city may have quickly learned from them.
T942 19769-19946 Sentence denotes Thus, as long as one county in a city has implemented “closed management of communities” or “family outdoor restrictions,” we treat the whole city as having the policy in place.
T943 19947-19963 Sentence denotes Publisher’s note
T944 19964-20082 Sentence denotes Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
T945 20084-20238 Sentence denotes We are grateful to Editor Klaus Zimmermann and three anonymous referees for valuable comments and suggestions which have helped greatly improve the paper.
T946 20239-20461 Sentence denotes We received helpful comments and suggestions from Hanming Fang and seminar participants at Institute for Economic and Social Research of Jinan University and VoxChina Covid-19 Public Health and Public Policy Virtual Forum.
T947 20462-20522 Sentence denotes Pei Yu and Wenjie Wu provided excellent research assistance.
T948 20523-20546 Sentence denotes All errors are our own.
T949 20548-20567 Sentence denotes Funding Information
T950 20568-20652 Sentence denotes Qiu and Shi acknowledge the support from the 111 Project of China (Grant No.B18026).
T951 20653-20787 Sentence denotes Chen thanks the following funding sources: US PEPPER Center Scholar Award (P30AG021342) and NIH/NIA grants (R03AG048920; K01AG053408).
T952 20788-20952 Sentence denotes Shi thanks the National Natural Science Foundation of China (Grant No.71803062) and the Ministry of Education of China (Grant No.18YJC790138) for financial support.
T953 20954-20987 Sentence denotes Compliance with ethical standards
T954 20989-21010 Sentence denotes Conflict of interests
T955 21011-21070 Sentence denotes The authors declare that they have no conflict of interest.