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PMC:7047374 / 14259-17052 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
219 288-291 Disease denotes ω’P MESH:C000656865
221 567-575 Species denotes patients Tax:9606
223 827-836 Disease denotes infection MESH:D007239
227 987-996 Disease denotes infection MESH:D007239
228 1051-1060 Disease denotes infection MESH:D007239
229 1095-1104 Disease denotes infection MESH:D007239
234 1493-1499 Species denotes people Tax:9606
235 1644-1650 Species denotes people Tax:9606
236 2091-2097 Species denotes people Tax:9606
237 2304-2310 Species denotes people Tax:9606
239 2596-2606 Species denotes SARS-CoV-2 Tax:2697049

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T5 1307-1311 Body_part denotes body http://purl.org/sig/ont/fma/fma256135
T6 1520-1524 Body_part denotes body http://purl.org/sig/ont/fma/fma256135
T7 2613-2616 Body_part denotes RNA http://purl.org/sig/ont/fma/fma67095

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T74 701-711 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T75 827-836 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T76 987-996 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T77 1051-1060 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T78 1095-1104 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T79 1147-1156 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T80 2596-2604 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T81 2596-2600 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T132 311-312 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T133 381-382 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T134 564-566 http://purl.obolibrary.org/obo/CLO_0053799 denotes 45
T135 634-635 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T136 844-849 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T137 1158-1160 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T138 1209-1211 http://purl.obolibrary.org/obo/CLO_0001547 denotes AP
T139 1286-1289 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T140 1463-1464 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T141 1509-1515 http://purl.obolibrary.org/obo/UBERON_0000473 denotes tested
T142 2043-2045 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T143 2068-2072 http://purl.obolibrary.org/obo/CLO_0001185 denotes 2018
T144 2148-2150 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T145 2373-2375 http://purl.obolibrary.org/obo/CLO_0008192 denotes nP
T146 2552-2557 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T147 2617-2622 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T148 2679-2680 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T149 2718-2719 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T112 1209-1211 Chemical denotes AP http://purl.obolibrary.org/obo/CHEBI_28971|http://purl.obolibrary.org/obo/CHEBI_73393|http://purl.obolibrary.org/obo/CHEBI_81686
T115 1224-1226 Chemical denotes IP http://purl.obolibrary.org/obo/CHEBI_74076

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T118 0-20 Sentence denotes Parameter estimation
T119 21-96 Sentence denotes The parameters were estimated based on the following facts and assumptions:
T120 97-167 Sentence denotes The mean incubation period was 5.2 days (95% confidence interval [CI]:
T121 168-181 Sentence denotes 4.1–7.0) [3].
T122 182-276 Sentence denotes We set the same value (5.2 days) of the incubation period and the latent period in this study.
T123 277-301 Sentence denotes Thus, ωP = ω’P = 0.1923.
T124 302-500 Sentence denotes There is a mean 5-day delay from symptom onset to detection/hospitalization of a case (the cases detected in Thailand and Japan were hospitalized from 3 to 7 days after onset, respectively) [19–21].
T125 501-661 Sentence denotes The duration from illness onset to first medical visit for the 45 patients with illness onset before January 1 was estimated to have a mean of 5.8 days (95% CI:
T126 662-675 Sentence denotes 4.3–7.5) [3].
T127 676-744 Sentence denotes In our model, we set the infectious period of the cases as 5.8 days.
T128 745-768 Sentence denotes Therefore, γP = 0.1724.
T129 769-915 Sentence denotes Since there was no data on the proportion of asymptomatic infection of the virus, we simulated the baseline value of proportion of 0.5 (δP = 0.5).
T130 916-1162 Sentence denotes Since there was no evidence about the transmissibility of asymptomatic infection, we assumed that the transmissibility of asymptomatic infection was 0.5 times that of symptomatic infection (κ = 0.5), which was the similar value as influenza [22].
T131 1163-1235 Sentence denotes We assumed that the relative shedding rate of AP compared to IP was 0.5.
T132 1236-1250 Sentence denotes Thus, c = 0.5.
T133 1251-1444 Sentence denotes Since 14 January, 2020, Wuhan City has strengthened the body temperature detection of passengers leaving Wuhan at airports, railway stations, long-distance bus stations and passenger terminals.
T134 1445-1542 Sentence denotes As of January 17, a total of nearly 0.3 million people had been tested for body temperature [23].
T135 1543-1605 Sentence denotes In Wuhan, there are about 2.87 million mobile population [24].
T136 1606-1847 Sentence denotes We assumed that there was 0.1 million people moving out to Wuhan City per day since January 10, 2020, and we believe that this number would increase (mainly due to the winter vacation and the Chinese New Year holiday) until 24 January, 2020.
T137 1848-1929 Sentence denotes This means that the 2.87 million would move out from Wuhan City in about 14 days.
T138 1930-2002 Sentence denotes Therefore, we set the moving volume of 0.2 million per day in our model.
T139 2003-2160 Sentence denotes Since the population of Wuhan was about 11 million at the end of 2018 [25], the rate of people traveling out from Wuhan City would be 0.018 (0.2/11) per day.
T140 2161-2273 Sentence denotes However, we assumed that the normal population mobility before January 1 was 0.1 times as that after January 10.
T141 2274-2391 Sentence denotes Therefore, we set the rate of people moving into and moving out from Wuhan City as 0.0018 per day (nP = mP = 0.0018).
T142 2392-2477 Sentence denotes The parameters bP and bW were estimated by fitting the model with the collected data.
T143 2478-2585 Sentence denotes At the beginning of the simulation, we assumed that the prevalence of the virus in the market was 1/100000.
T144 2586-2777 Sentence denotes Since the SARS-CoV-2 is an RNA virus, we assumed that it could be died in the environment in a short time, but it could be stay for a longer time (10 days) in the unknown hosts in the market.
T145 2778-2793 Sentence denotes We set ε = 0.1.

2_test

Id Subject Object Predicate Lexical cue
32111262-16079251-47462513 1158-1160 16079251 denotes 22
T95670 1158-1160 16079251 denotes 22