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LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T112 1139-1152 Disease denotes infections in http://purl.obolibrary.org/obo/MONDO_0005550
T113 1306-1314 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T114 1927-1930 Disease denotes inv http://purl.obolibrary.org/obo/MONDO_0043678
T115 1996-1999 Disease denotes inv http://purl.obolibrary.org/obo/MONDO_0043678
T116 2071-2074 Disease denotes inv http://purl.obolibrary.org/obo/MONDO_0043678
T117 2147-2150 Disease denotes inv http://purl.obolibrary.org/obo/MONDO_0043678
T118 2212-2215 Disease denotes inv http://purl.obolibrary.org/obo/MONDO_0043678
T119 2280-2283 Disease denotes inv http://purl.obolibrary.org/obo/MONDO_0043678
T120 4664-4674 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T209 508-509 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T210 823-824 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T211 1324-1329 http://purl.obolibrary.org/obo/CLO_0001302 denotes 3) (4
T212 1870-1873 http://purl.obolibrary.org/obo/CLO_0001003 denotes 163
T213 3308-3320 http://purl.obolibrary.org/obo/OBI_0000968 denotes instrumental
T214 3365-3377 http://purl.obolibrary.org/obo/OBI_0000968 denotes instrumental
T215 4039-4049 http://purl.obolibrary.org/obo/CLO_0001658 denotes activities
T216 4650-4651 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T8 4007-4026 Phenotype denotes social interactions http://purl.obolibrary.org/obo/HP_0008763|http://purl.obolibrary.org/obo/HP_0008763
T8 4007-4026 Phenotype denotes social interactions http://purl.obolibrary.org/obo/HP_0008763|http://purl.obolibrary.org/obo/HP_0008763

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T419 0-37 Sentence denotes Social and economic mediating factors
T420 38-166 Sentence denotes We also investigate the mediating impacts of some socioeconomic and environmental characteristics on the transmission rates (3).
T421 167-326 Sentence denotes To ease the comparison between different moderators, we consider the mediating impacts on the influence of the average number of new cases in the past 2 weeks.
T422 327-555 Sentence denotes Regarding own-city transmissions, we examine the mediating effects of population density, GDP per capita, number of doctors, and average temperature, wind speed, precipitation, and a dummy variable of adverse weather conditions.
T423 556-806 Sentence denotes Regarding between-city transmissions, we consider the mediating effects of distance, difference in population density, and difference in GDP per capita since cities that are similar in density or economic development level may be more closely linked.
T424 807-864 Sentence denotes We also include a measure of population flows from Wuhan.
T425 865-926 Sentence denotes Table 6 reports the estimation results of the IV regressions.
T426 927-1239 Sentence denotes To ease the comparison across various moderators, for the mediating variables of within-city transmissions that are significant at 10%, we compute the changes in the variables so that the effect of new confirmed infections in the past 14 days on current new confirmed cases is reduced by 1 (columns (2) and (4)).
T427 1240-1314 Sentence denotes Table 6 Social and economic factors mediating the transmission of COVID-19
T428 1315-1330 Sentence denotes (1) (2) (3) (4)
T429 1331-1356 Sentence denotes Jan 19–Feb 1 Feb 2–Feb 29
T430 1357-1366 Sentence denotes IV Coeff.
T431 1367-1376 Sentence denotes IV Coeff.
T432 1377-1417 Sentence denotes Average # of new cases, previous 14 days
T433 1418-1443 Sentence denotes Own city − 0.251 0.672***
T434 1444-1459 Sentence denotes (0.977) (0.219)
T435 1460-1516 Sentence denotes × population density 0.000164 − 0.000202** + 495 per km2
T436 1517-1538 Sentence denotes (0.000171) (8.91e-05)
T437 1539-1585 Sentence denotes × per capita GDP 0.150*** − 66, 667 RMB 0.0102
T438 1586-1603 Sentence denotes (0.0422) (0.0196)
T439 1604-1644 Sentence denotes × # of doctors − 0.108* + 92, 593 0.0179
T440 1645-1662 Sentence denotes (0.0622) (0.0236)
T441 1663-1704 Sentence denotes × temperature 0.0849* − 11.78∘C − 0.00945
T442 1705-1722 Sentence denotes (0.0438) (0.0126)
T443 1723-1749 Sentence denotes × wind speed − 0.109 0.128
T444 1750-1765 Sentence denotes (0.131) (0.114)
T445 1766-1815 Sentence denotes × precipitation 0.965* − 1.04 mm 0.433* − 2.31 mm
T446 1816-1831 Sentence denotes (0.555) (0.229)
T447 1832-1874 Sentence denotes × adverse weather 0.0846 − 0.614*** + 163%
T448 1875-1890 Sentence denotes (0.801) (0.208)
T449 1891-1920 Sentence denotes Other cities 0.0356 − 0.00429
T450 1921-1959 Sentence denotes wt. = inv. distance (0.0375) (0.00343)
T451 1960-1989 Sentence denotes Other cities 0.00222 0.000192
T452 1990-2035 Sentence denotes wt. = inv. density ratio (0.00147) (0.000891)
T453 2036-2064 Sentence denotes Other cities 0.00232 0.00107
T454 2065-2116 Sentence denotes wt. = inv. per capita GDP ratio (0.00497) (0.00165)
T455 2117-2140 Sentence denotes Wuhan − 0.165 − 0.00377
T456 2141-2178 Sentence denotes wt. = inv. distance (0.150) (0.00981)
T457 2179-2205 Sentence denotes Wuhan − 0.00336 − 0.000849
T458 2206-2250 Sentence denotes wt. = inv. density ratio (0.00435) (0.00111)
T459 2251-2273 Sentence denotes Wuhan − 0.440 − 0.0696
T460 2274-2322 Sentence denotes wt. = inv. per capita GDP ratio (0.318) (0.0699)
T461 2323-2349 Sentence denotes Wuhan 0.00729*** 0.0125***
T462 2350-2391 Sentence denotes wt. = population flow (0.00202) (0.00187)
T463 2392-2414 Sentence denotes Observations 4032 8064
T464 2415-2439 Sentence denotes Number of cities 288 288
T465 2440-2464 Sentence denotes Weather controls Yes Yes
T466 2465-2480 Sentence denotes City FE Yes Yes
T467 2481-2496 Sentence denotes Date FE Yes Yes
T468 2497-2563 Sentence denotes The dependent variable is the number of daily new confirmed cases.
T469 2564-2609 Sentence denotes The sample excludes cities in Hubei province.
T470 2610-2861 Sentence denotes Columns (2) and (4) report the changes in the mediating variables that are needed to reduce the impact of new confirmed cases in the preceding 2 weeks by 1, using estimates with significance levels of at least 0.1 in columns (1) and (3), respectively.
T471 2862-3039 Sentence denotes The endogenous variables include the average numbers of new cases in the own city and nearby cities in the preceding 14 days and their interactions with the mediating variables.
T472 3040-3353 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 neighboring cities, during the preceding third and fourth weeks, are used as instrumental variables in the IV regressions.
T473 3354-3453 Sentence denotes Additional instrumental variables are constructed by interacting them with the mediating variables.
T474 3454-3535 Sentence denotes Weather controls include these variables in the preceding first and second weeks.
T475 3536-3593 Sentence denotes Standard errors in parentheses are clustered by provinces
T476 3594-3630 Sentence denotes *** p < 0.01, ** p < 0.05, * p < 0.1
T477 3631-3805 Sentence denotes In the early phase of the epidemic (January 19 to February 1), cities with more medical resources, which are measured by the number of doctors, have lower transmission rates.
T478 3806-3901 Sentence denotes One standard deviation increase in the number of doctors reduces the transmission rate by 0.12.
T479 3902-4061 Sentence denotes Cities with higher GDP per capita have higher transmission rates, which can be ascribed to the increased social interactions as economic activities increase18.
T480 4062-4208 Sentence denotes In the second sub-sample, these effects become insignificant probably because public health measures and inter-city resource sharing take effects.
T481 4209-4311 Sentence denotes In fact, cities with higher population density have lower transmission rates in the second sub-sample.
T482 4312-4441 Sentence denotes Regarding the environmental factors, we notice different significant mediating variables across the first and second sub-samples.
T483 4442-4540 Sentence denotes The transmission rates are lower with adverse weather conditions, lower temperature, or less rain.
T484 4541-4597 Sentence denotes Further research is needed to identify clear mechanisms.
T485 4598-4771 Sentence denotes In addition, population flow from Wuhan still poses a risk of new infections for other cities even after we account for the above mediating effects on own-city transmission.
T486 4772-4922 Sentence denotes This effect is robust to the inclusion of the proximity measures based on economic similarity and geographic proximity between Wuhan and other cities.
T487 4923-5026 Sentence denotes Nevertheless, we do not find much evidence on between-city transmissions among cities other than Wuhan.

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
277 1338-1349 Gene denotes Feb 1 Feb 2 Gene:2233
278 2087-2090 Chemical denotes GDP MESH:D006153
279 2296-2299 Chemical denotes GDP MESH:D006153
281 1306-1314 Disease denotes COVID-19 MESH:C000657245
284 693-696 Chemical denotes GDP MESH:D006153
285 1139-1149 Disease denotes infections MESH:D007239
288 3921-3924 Chemical denotes GDP MESH:D006153
289 4664-4674 Disease denotes infections MESH:D007239