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PMC:7224658 / 2206-6290 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
33 466-474 Species denotes patients Tax:9606
34 33-41 Disease denotes COVID-19 MESH:C000657245
35 75-92 Disease denotes 2019, the disease MESH:C000657245
36 404-412 Disease denotes COVID-19 MESH:C000657245
37 486-492 Disease denotes deaths MESH:D003643
38 611-619 Disease denotes COVID-19 MESH:C000657245
39 1141-1149 Disease denotes COVID-19 MESH:C000657245
44 2476-2484 Species denotes patients Tax:9606
45 2559-2567 Species denotes patients Tax:9606
46 1662-1670 Disease denotes COVID-19 MESH:C000657245
47 2550-2558 Disease denotes COVID-19 MESH:C000657245
55 2632-2640 Species denotes patients Tax:9606
56 2623-2631 Disease denotes COVID-19 MESH:C000657245
57 2703-2711 Disease denotes COVID-19 MESH:C000657245
58 3117-3125 Disease denotes COVID-19 MESH:C000657245
59 3297-3305 Disease denotes COVID-19 MESH:C000657245
60 3402-3421 Disease denotes infectious diseases MESH:D003141
61 3484-3502 Disease denotes infectious disease MESH:D003141
64 3954-3962 Disease denotes COVID-19 MESH:C000657245
65 4045-4063 Disease denotes infectious disease MESH:D003141

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 2124-2129 Body_part denotes joint http://purl.org/sig/ont/fma/fma7490

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T10 33-41 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T11 404-412 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T12 611-619 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T13 1141-1149 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T14 1662-1670 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T15 1709-1719 Disease denotes Infectious http://purl.obolibrary.org/obo/MONDO_0005550
T16 2550-2558 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T17 2623-2631 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T18 2703-2711 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T19 3117-3125 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T20 3297-3305 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T21 3402-3412 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T22 3484-3502 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T23 3613-3622 Disease denotes influenza http://purl.obolibrary.org/obo/MONDO_0005812
T24 3954-3962 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T25 4045-4063 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T8 175-187 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T9 203-204 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T10 240-242 http://purl.obolibrary.org/obo/CLO_0054055 denotes 71
T11 298-310 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T12 332-344 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T13 366-378 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T14 479-481 http://purl.obolibrary.org/obo/CLO_0001313 denotes 36
T15 1231-1232 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T16 1264-1270 http://purl.obolibrary.org/obo/CLO_0001658 denotes active
T17 2124-2129 http://purl.obolibrary.org/obo/UBERON_0000982 denotes joint
T18 2124-2129 http://purl.obolibrary.org/obo/UBERON_0004905 denotes joint
T19 2486-2487 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T20 2662-2663 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T21 2825-2830 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T22 3127-3135 http://purl.obolibrary.org/obo/CLO_0001658 denotes activity
T23 3273-3274 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T24 3363-3366 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T25 3373-3374 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T26 3654-3655 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T27 3693-3694 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T28 3800-3801 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 834-837 Chemical denotes Lin http://purl.obolibrary.org/obo/CHEBI_32386
T2 2350-2362 Chemical denotes disinfectant http://purl.obolibrary.org/obo/CHEBI_48219

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T1 1613-1622 http://purl.obolibrary.org/obo/GO_0006810 denotes transport

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T25 0-12 Sentence denotes Introduction
T26 13-143 Sentence denotes Following the first COVID-19 case in Wuhan, China in December 2019, the disease spread rapidly to over 60 countries in early 2020.
T27 144-387 Sentence denotes Consequently, the World Health Organization (WHO) declared a pandemic on March 12, 2020, within 71 days of the first case (Zhu et al., 2020, World Health Organization, 2020c, World Health Organization, 2020d, World Health Organization, 2020e).
T28 388-516 Sentence denotes As of March 31, COVID-19 was present in 206 countries, with 770 138 confirmed patients and 36 796 deaths worldwide (WHO, 2020b).
T29 517-633 Sentence denotes Different countries are employing diverse methods to manage and prevent the further spread of COVID-19 (WHO, 2020a).
T30 634-852 Sentence denotes Most countries are limiting contact between citizens, most notably China, where Wuhan was placed under lockdown within just 23 days of the outbreak, and contact with neighboring cities was forbidden (Lin et al., 2020).
T31 853-1173 Sentence denotes France, Switzerland, and Austria closed their borders on March 17, while France, Spain, Italy, Germany, and some states in the US have been implementing strict policies to limit contact between citizens, including nationwide stay-at-home orders, thereby preventing the domestic spread of COVID-19 (Kinross et al., 2020).
T32 1174-1324 Sentence denotes South Korea’s total population is 51.8 million, of which a large proportion resides or is active in the capital and the surrounding Gyeonggi Province.
T33 1325-1498 Sentence denotes Of the total population, 13.28 million (26.0%), 9.73 million (18.7%), and 2.95 million (5.7%) reside in Gyeonggi Province, Seoul, and Incheon, respectively (Resident, 2020).
T34 1499-1778 Sentence denotes Several studies have indicated that these densely populated urban environments and the heavy dependence on public transport could increase the potential spread of COVID-19 (Choi and Ki, 2020, Korean Society of Infectious Diseases et al., 2020, BBC News, 2020, Shim et al., 2020).
T35 1779-2015 Sentence denotes On March 2, the South Korean government initially postponed the commencement of elementary, middle, and high schools for 4 weeks until April 6, and of university classes until March 16, before switching to online classes until April 16.
T36 2016-2116 Sentence denotes Some schools decided to conduct online classes for the entire first semester (Koh and Hoenig, 2020).
T37 2117-2568 Sentence denotes Due to joint efforts, including public institutions, private enterprises, and other companies implementing work-from-home systems to minimize travel, preventive education for citizens via social distancing campaigns, availability of disinfectant in every building and street, and transparency of information regarding the movements and locations of confirmed patients, a decreasing trend is being observed in the daily number of new COVID-19 patients.
T38 2569-2956 Sentence denotes Based on existing studies, although the number of new COVID-19 patients in South Korea shows a decreasing trend, the global number of COVID-19 cases, including South Korea, is forecast to eventually increase again, possibly due to genetic mutations in the virus, re-influx from overseas, and decreasing compliance by the public (Liu et al., 2020, Verity et al., 2020, Zhan et al., 2020).
T39 2957-3062 Sentence denotes In particular, unlike in Spain, the US, and the UK, outdoor excursions are not restricted in South Korea.
T40 3063-3326 Sentence denotes Therefore, it is predicted that, as citizens adapt to COVID-19, activity levels will increase and adherence will decrease for measures such as staying indoors, social distancing, and mask wearing, resulting in a secondary outbreak of COVID-19 (Zhan et al., 2020).
T41 3327-3585 Sentence denotes Research analyzing 10 years of data has found a strong correlation between infectious diseases and traffic volume; specifically, increased traffic during an infectious disease outbreak is associated with greater spread (Meloni et al., 2009, Wu et al., 2019).
T42 3586-3692 Sentence denotes An analysis of 10 types of influenza from the last 300 years showed a very close association with traffic.
T43 3693-3861 Sentence denotes A disease that took 1 year to spread 300 years ago would now be able to reach anywhere in the world within a day, due to developments in travel (Rodrigue et al., 2020).
T44 3862-4084 Sentence denotes This study investigated the association between changes in traffic volume and the spread of COVID-19 in South Korea, and provides predictive data that may be required to guide future infectious disease prevention policies.

2_test

Id Subject Object Predicate Lexical cue
32417247-31978945-50052990 279-283 31978945 denotes 2020
32417247-32145465-50052991 846-850 32145465 denotes 2020
32417247-32174069-50052992 1737-1741 32174069 denotes 2020
32417247-32198088-50052993 1772-1776 32198088 denotes 2020
32417247-19805184-50052994 3562-3566 19805184 denotes 2009
T86182 279-283 31978945 denotes 2020
T65872 846-850 32145465 denotes 2020
T20249 1737-1741 32174069 denotes 2020
T9156 1772-1776 32198088 denotes 2020
T48213 3562-3566 19805184 denotes 2009