LitCovid-sentences  

PMC:7210464 / 29770-33549 JSONTXT 6 Projects

Annnotations TAB TSV DIC JSON TextAE

Id Subject Object Predicate Lexical cue
T234 0-132 Sentence denotes Table 3 reports the estimation results of the OLS and IV regressions of Eq. 2, in which only within-city transmission is considered.
T235 133-346 Sentence denotes 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.
T236 347-561 Sentence denotes 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.
T237 562-803 Sentence denotes 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.
T238 804-869 Sentence denotes We then compare the transmission rates in different time windows.
T239 870-1000 Sentence denotes 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.
T240 1001-1187 Sentence denotes 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.
T241 1188-1234 Sentence denotes Similar patterns are also observed in model B.
T242 1235-1279 Sentence denotes Table 3 Within-city transmission of COVID-19
T243 1280-1319 Sentence denotes Jan 19–Feb 29 Jan 19–Feb 1 Feb 2–Feb 29
T244 1320-1343 Sentence denotes (1) (2) (3) (4) (5) (6)
T245 1344-1364 Sentence denotes OLS IV OLS IV OLS IV
T246 1365-1391 Sentence denotes All cities excluding Wuhan
T247 1392-1482 Sentence denotes Model A: lagged variables are averages over the preceding first and second week separately
T248 1483-1559 Sentence denotes Average # of new cases 0.873*** 1.142*** 1.692*** 2.135*** 0.768*** 1.077***
T249 1560-1625 Sentence denotes 1-week lag (0.00949) (0.0345) (0.0312) (0.0549) (0.0120) (0.0203)
T250 1626-1709 Sentence denotes Average # of new cases − 0.415*** − 0.824*** 0.860 − 6.050*** − 0.408*** − 0.796***
T251 1710-1774 Sentence denotes 2-week lag (0.00993) (0.0432) (2.131) (2.314) (0.00695) (0.0546)
T252 1775-1840 Sentence denotes Model B: lagged variables are averages over the preceding 2 weeks
T253 1841-1916 Sentence denotes Average # of new case 0.474*** 0.720*** 3.310*** 3.860*** 0.494*** 1.284***
T254 1917-1984 Sentence denotes Previous 14 days (0.0327) (0.143) (0.223) (0.114) (0.00859) (0.107)
T255 1985-2031 Sentence denotes Observations 12,768 12,768 4256 4256 8512 8512
T256 2032-2072 Sentence denotes Number of cities 304 304 304 304 304 304
T257 2073-2113 Sentence denotes Weather controls Yes Yes Yes Yes Yes Yes
T258 2114-2145 Sentence denotes City FE Yes Yes Yes Yes Yes Yes
T259 2146-2177 Sentence denotes Date FE Yes Yes Yes Yes Yes Yes
T260 2178-2223 Sentence denotes All cities excluding cities in Hubei Province
T261 2224-2314 Sentence denotes Model A: lagged variables are averages over the preceding first and second week separately
T262 2315-2391 Sentence denotes Average # of new cases 0.725*** 1.113*** 1.050*** 1.483*** 0.620*** 0.903***
T263 2392-2453 Sentence denotes 1-week lag (0.141) (0.0802) (0.0828) (0.205) (0.166) (0.0349)
T264 2454-2534 Sentence denotes Average # of new cases − 0.394*** − 0.572*** 0.108 − 3.664 − 0.228*** − 0.341***
T265 2535-2595 Sentence denotes 2-week lag (0.0628) (0.107) (0.675) (2.481) (0.0456) (0.121)
T266 2596-2661 Sentence denotes Model B: lagged variables are averages over the preceding 2 weeks
T267 2662-2738 Sentence denotes Average # of new cases 0.357*** 0.631*** 1.899*** 2.376*** 0.493*** 0.745***
T268 2739-2804 Sentence denotes Previous 14 days (0.0479) (0.208) (0.250) (0.346) (0.122) (0.147)
T269 2805-2851 Sentence denotes Observations 12,096 12,096 4032 4032 8064 8064
T270 2852-2892 Sentence denotes Number of cities 288 288 288 288 288 288
T271 2893-2933 Sentence denotes Weather controls Yes Yes Yes Yes Yes Yes
T272 2934-2965 Sentence denotes City FE Yes Yes Yes Yes Yes Yes
T273 2966-2997 Sentence denotes Date FE Yes Yes Yes Yes Yes Yes
T274 2998-3054 Sentence denotes The dependent variable is the number of daily new cases.
T275 3055-3267 Sentence denotes 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).
T276 3268-3583 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 each of these variables in other cities, during the preceding third and fourth weeks, are used as instrumental variables in the IV regressions.
T277 3584-3683 Sentence denotes Weather controls include contemporaneous weather variables in the preceding first and second weeks.
T278 3684-3779 Sentence denotes Standard errors in parentheses are clustered by provinces. *** p < 0.01, ** p < 0.05, * p < 0.1