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LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T160 64-88 Disease denotes coronavirus disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T161 291-304 Disease denotes infections in http://purl.obolibrary.org/obo/MONDO_0005550
T162 453-462 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T163 523-533 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T164 579-589 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T165 698-708 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T166 780-788 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T167 1065-1073 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T168 1181-1189 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T169 1190-1200 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T170 1923-1933 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T171 2070-2080 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T172 2813-2821 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T173 2885-2895 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T285 259-264 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T286 371-376 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T287 789-792 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T288 1660-1661 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T289 1828-1831 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T290 2082-2083 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T291 2265-2266 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T292 2321-2326 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T293 2375-2376 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T294 2650-2651 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T295 2875-2880 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T676 0-10 Sentence denotes Conclusion
T677 11-155 Sentence denotes This paper examines the transmission dynamics of the coronavirus disease 2019 in China, considering both within- and between-city transmissions.
T678 156-386 Sentence denotes Our sample is from January 19 to February 29 and covers key episodes such as the initial spread of the virus across China, the peak of infections in terms of domestic case counts, and the gradual containment of the virus in China.
T679 387-547 Sentence denotes Changes in weather conditions induce exogenous variations in past infection rates, which allow us to identify the causal impact of past infections on new cases.
T680 548-709 Sentence denotes The estimates suggest that the infectious effect of the existing cases is mostly observed within 1 week and people’s responses can break the chain of infections.
T681 710-882 Sentence denotes Comparing estimates in two sub-samples, we observe that the spread of COVID-19 has been effectively contained by mid February, especially for cities outside Hubei province.
T682 883-971 Sentence denotes Data on real-time population flows between cities have become available in recent years.
T683 972-1160 Sentence denotes We show that this new source of data is valuable in explaining between-city transmissions of COVID-19, even after controlling for traditional measures of geographic and economic proximity.
T684 1161-1300 Sentence denotes By April 5 of 2020, COVID-19 infections have been reported in more than 200 countries or territories and more than 64,700 people have died.
T685 1301-1407 Sentence denotes Behind the grim statistics, more and more national and local governments are implementing countermeasures.
T686 1408-1501 Sentence denotes Cross border travel restrictions are imposed in order to reduce the risk of case importation.
T687 1502-1656 Sentence denotes In areas with risks of community transmissions, public health measures such as social distancing, mandatory quarantine, and city lockdown are implemented.
T688 1657-1934 Sentence denotes In a series of counterfactual simulations, we find that based on the experience in China, preventing sustained community transmissions from taking hold in the first place has the largest impact, followed by restricting population flows from areas with high risks of infections.
T689 1935-2081 Sentence denotes Local public health measures such as closed management of communities and family outdoor restrictions can further reduce the number of infections.
T690 2082-2374 Sentence denotes A key limitation of the paper is that we are not able to disentangle the effects from each of the stringent measures taken, as within this 6-week sampling period, China enforced such a large number of densely timed policies to contain the virus spreading, often simultaneously in many cities.
T691 2375-2723 Sentence denotes A second limitation is that shortly after the starting date of the official data release for confirmed infected cases throughout China, i.e., January 19, 2020, many stringent measures were implemented, which prevents researchers to compare the post treatment sub-sample with a pre treatment sub-sample during which no strict policies were enforced.
T692 2724-2918 Sentence denotes Key knowledge gaps remain in the understanding of the epidemiological characteristics of COVID-19, such as individual risk factors for contracting the virus and infections from asymptotic cases.
T693 2919-3065 Sentence denotes Data on the demographics and exposure history for those who have shown symptoms as well as those who have not will help facilitate these research.

LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
404 656-662 Species denotes people Tax:9606
405 64-88 Disease denotes coronavirus disease 2019 MESH:C000657245
406 291-301 Disease denotes infections MESH:D007239
407 453-462 Disease denotes infection MESH:D007239
408 523-533 Disease denotes infections MESH:D007239
409 698-708 Disease denotes infections MESH:D007239
410 780-788 Disease denotes COVID-19 MESH:C000657245
411 1065-1073 Disease denotes COVID-19 MESH:C000657245
418 1283-1289 Species denotes people Tax:9606
419 1181-1189 Disease denotes COVID-19 MESH:C000657245
420 1190-1200 Disease denotes infections MESH:D007239
421 1295-1299 Disease denotes died MESH:D003643
422 1923-1933 Disease denotes infections MESH:D007239
423 2070-2080 Disease denotes infections MESH:D007239
427 2478-2486 Disease denotes infected MESH:D007239
428 2813-2821 Disease denotes COVID-19 MESH:C000657245
429 2885-2895 Disease denotes infections MESH:D007239