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PMC:7224658 / 17709-25940 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
155 123-130 Species denotes patient Tax:9606
156 89-97 Disease denotes COVID-19 MESH:C000657245
157 114-122 Disease denotes COVID-19 MESH:C000657245
163 246-253 Species denotes patient Tax:9606
164 383-390 Species denotes peoples Tax:9606
165 604-612 Disease denotes COVID-19 MESH:C000657245
166 782-790 Disease denotes COVID-19 MESH:C000657245
167 969-987 Disease denotes infectious disease MESH:D003141
171 1281-1289 Species denotes patients Tax:9606
172 1272-1280 Disease denotes COVID-19 MESH:C000657245
173 2359-2367 Disease denotes COVID-19 MESH:C000657245
179 2959-2967 Species denotes patients Tax:9606
180 2482-2490 Disease denotes COVID-19 MESH:C000657245
181 2608-2616 Disease denotes COVID-19 MESH:C000657245
182 2753-2761 Disease denotes COVID-19 MESH:C000657245
183 2950-2958 Disease denotes COVID-19 MESH:C000657245
186 3624-3630 Species denotes people Tax:9606
187 3546-3554 Disease denotes COVID-19 MESH:C000657245
193 3839-3847 Species denotes patients Tax:9606
194 3876-3883 Species denotes persons Tax:9606
195 3830-3838 Disease denotes COVID-19 MESH:C000657245
196 4064-4072 Disease denotes COVID-19 MESH:C000657245
197 4123-4131 Disease denotes fatigued MESH:D005221
199 4523-4531 Disease denotes COVID-19 MESH:C000657245
201 4940-4948 Disease denotes COVID-19 MESH:C000657245
203 5042-5048 Species denotes people Tax:9606
211 6361-6369 Species denotes patients Tax:9606
212 5392-5400 Disease denotes COVID-19 MESH:C000657245
213 5651-5659 Disease denotes COVID-19 MESH:C000657245
214 5888-5896 Disease denotes COVID-19 MESH:C000657245
215 6200-6208 Disease denotes COVID-19 MESH:C000657245
216 6352-6360 Disease denotes COVID-19 MESH:C000657245
217 6418-6426 Disease denotes COVID-19 MESH:C000657245
225 7060-7068 Disease denotes COVID-19 MESH:C000657245
226 7119-7127 Disease denotes COVID-19 MESH:C000657245
227 7222-7230 Disease denotes COVID-19 MESH:C000657245
228 7389-7397 Disease denotes COVID-19 MESH:C000657245
229 7703-7712 Disease denotes infection MESH:D007239
230 7927-7935 Disease denotes COVID-19 MESH:C000657245
231 8060-8068 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T58 89-97 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T59 114-122 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T60 604-612 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T61 782-790 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T62 969-987 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T63 1272-1280 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T64 2359-2367 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T65 2482-2490 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T66 2608-2616 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T67 2753-2761 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T68 2950-2958 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T69 3546-3554 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T70 3830-3838 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T71 4064-4072 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T72 4523-4531 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T73 4940-4948 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T74 5392-5400 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T75 5651-5659 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T76 5888-5896 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T77 6200-6208 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T78 6352-6360 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T79 6418-6426 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T80 7060-7068 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T81 7119-7127 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T82 7222-7230 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T83 7389-7397 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T84 7703-7712 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T85 7927-7935 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T86 8060-8068 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T70 369-370 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T71 414-424 http://purl.obolibrary.org/obo/CLO_0001658 denotes activities
T72 428-429 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T73 884-885 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T74 916-926 http://purl.obolibrary.org/obo/CLO_0001658 denotes activities
T75 1023-1025 http://purl.obolibrary.org/obo/CLO_0050509 denotes 27
T76 1027-1028 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T77 1134-1136 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T78 1384-1394 http://purl.obolibrary.org/obo/CLO_0001658 denotes activities
T79 1409-1410 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T80 1443-1456 http://purl.obolibrary.org/obo/OBI_0000245 denotes organizations
T81 1478-1491 http://purl.obolibrary.org/obo/OBI_0000245 denotes organizations
T82 1982-1992 http://purl.obolibrary.org/obo/CLO_0001658 denotes activities
T83 2074-2075 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T84 2432-2433 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T85 2649-2650 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T86 2869-2870 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T87 3534-3535 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T88 3606-3611 http://purl.obolibrary.org/obo/CLO_0001236 denotes (2) a
T89 4720-4721 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T90 4980-4981 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T91 5022-5025 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T92 5026-5027 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T93 5205-5215 http://purl.obolibrary.org/obo/CLO_0001658 denotes activities
T94 5724-5727 http://purl.obolibrary.org/obo/CLO_0002421 denotes Cho
T95 5724-5727 http://purl.obolibrary.org/obo/CLO_0052479 denotes Cho
T96 5724-5727 http://purl.obolibrary.org/obo/CLO_0052480 denotes Cho
T97 5724-5727 http://purl.obolibrary.org/obo/CLO_0052483 denotes Cho
T98 5724-5727 http://purl.obolibrary.org/obo/CLO_0052484 denotes Cho
T99 5724-5727 http://purl.obolibrary.org/obo/CLO_0052485 denotes Cho
T100 5872-5873 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T101 6287-6288 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T102 6406-6407 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T103 6902-6903 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T104 6932-6933 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T105 7038-7041 http://purl.obolibrary.org/obo/NCBITaxon_9596 denotes Pan
T106 7439-7442 http://purl.obolibrary.org/obo/CLO_0001003 denotes 163
T107 7665-7666 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T108 7903-7904 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T109 7993-7994 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T3 305-307 Chemical denotes TV http://purl.obolibrary.org/obo/CHEBI_75193
T4 7254-7257 Chemical denotes Lin http://purl.obolibrary.org/obo/CHEBI_32386

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T2 4787-4796 http://purl.obolibrary.org/obo/GO_0006810 denotes transport
T3 4816-4821 http://purl.obolibrary.org/obo/GO_0042330 denotes taxis
T4 4905-4914 http://purl.obolibrary.org/obo/GO_0006810 denotes transport

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T162 0-10 Sentence denotes Discussion
T163 11-160 Sentence denotes This study analyzed the relationship between traffic trends and the spread of COVID-19 after the first COVID-19 patient was confirmed in South Korea.
T164 161-219 Sentence denotes This was carried out at both national and regional levels.
T165 220-733 Sentence denotes Since the first confirmed patient in South Korea on January 19, the mass media (e.g. TV news, newspapers, the Internet) and other studies have shown a decrease in peoples’ engagement in outdoor activities as a result of self-isolation, working from home, voluntarily staying indoors, delaying the commencement of schools and universities, and the delivery of educational messages for COVID-19 prevention (e.g. via the Internet, broadcast media, and written articles) (Chinazzi et al., 2020, Magal and Webb, 2020).
T166 734-927 Sentence denotes Similarly, our study showed that, following the COVID-19 outbreak in South Korea, nationwide traffic decreased by 9.7% compared with 2019, indicating a decrease in citizens’ outdoor activities.
T167 928-1079 Sentence denotes In particular, after the KCDC raised the infectious disease alert level to ‘orange’ on January 27, a large decrease was observed in nationwide traffic.
T168 1080-1225 Sentence denotes After the alert level was raised to ‘red’ on February 22, traffic in the fourth week of February was down by 26.1% compared with 2019 (Figure 4).
T169 1226-1697 Sentence denotes To counteract the rapid increase in confirmed COVID-19 patients, the South Korean government implemented policies such as advising the restriction of outdoor activities, implementing a work-from-home system in public organizations, encouraging private organizations to employ work-from-home systems, advising educational institutions (kindergartens, after-school academies, etc.) to close, and delaying the commencement of elementary/middle/high schools and universities.
T170 1698-1786 Sentence denotes The effectiveness of these policies was evidenced by the decrease in nationwide traffic.
T171 1787-1993 Sentence denotes In particular, the data show that although the Korean government did not forcefully prohibit public excursions, citizens voluntarily adhered to the government’s guidelines and restricted outdoor activities.
T172 1994-2241 Sentence denotes Various studies and media opinions have suggested that these results are due to a high level of existing public health education, good information accessibility due to the rapid Internet environment, and effective delivery of educational messages.
T173 2242-2377 Sentence denotes It would be valuable for future research to identify the most effective measures among the South Korean government’s COVID-19 policies.
T174 2378-2549 Sentence denotes Although the nationwide traffic in South Korea showed a continuously decreasing trend after the initial COVID-19 outbreak, it shifted to an increasing trend after March 7.
T175 2550-2783 Sentence denotes This was the day after the numbers of daily new confirmed COVID-19 cases in South Korea shifted to a decreasing trend on March 6, when the Korean press and media had begun reporting decreasing trends in COVID-19 (The Briefing, 2020).
T176 2784-3211 Sentence denotes Moreover, immediately after the WHO Director-General, Tedros Adhanom Ghebreyesus, at a foreign media briefing on March 5, reported that ‘the numbers of new confirmed COVID-19 patients in South Korea are decreasing, and there are encouraging signs’, corresponding news articles were published on March 6 in Korean Standard Time – the day before the nationwide traffic shifted to an increasing trend (The Associated Press, 2020).
T177 3212-3438 Sentence denotes In the cases of Daegu, Cheongdo, and Gyeongsan city, the KCDC recommended that citizens in these areas undergo self-isolation for prevention from 23 February to 8 March, which contributed to the subsequent increase in traffic.
T178 3439-3758 Sentence denotes The shift to an increasing trend in nationwide traffic from March may have been caused by: (1) a change in COVID-19 prevention attitudes toward decreasing compliance; (2) a decrease in people working from home; (3) increased usage of personal vehicles; and (4) an increase in outdoor excursions due to seasonal changes.
T179 3759-3785 Sentence denotes These are discussed below.
T180 3786-4002 Sentence denotes First, as the number of new daily confirmed COVID-19 patients decreased and the number of persons released from isolation increased, it is likely that the attitudes of the public shifted toward decreasing compliance.
T181 4003-4244 Sentence denotes According to previous research, 2 months following the first COVID-19 case in South Korea, citizens became increasingly fatigued by the preventive measures, and their attitudes to prevention became less stringent (Remuzzi and Remuzzi, 2020).
T182 4245-4404 Sentence denotes For instance, analysis of public data from Seoul showed that the number of Seoul Metro passengers in March increased by 3.3% compared with March 2 (Won, 2020).
T183 4405-4590 Sentence denotes Second, employees following work-from-home policies since February started commuting to work again once the spread of COVID-19 had decreased in March, and this led to increased traffic.
T184 4591-4739 Sentence denotes Indeed, employees working from home reached their highest levels of movement in the first week of March, after which they showed a decreasing trend.
T185 4740-4956 Sentence denotes Third, citizens who had previously used public transport (the Metro, buses, taxis, etc.) showed increased use of their personal vehicles for outings to avoid public transport, which is susceptible to COVID-19 spread.
T186 4957-5085 Sentence denotes Fourth, South Korea is a country with four distinct seasons, and has a culture where people frequently go out in the springtime.
T187 5086-5373 Sentence denotes The culture, sports, and tourism ministries in individual cities, provinces, and counties attempted to prevent outdoor activities by closing or reducing the operating hours of major tourism sites; however, the number of tourists visiting these sights increased as the weather got warmer.
T188 5374-5548 Sentence denotes When the regional COVID-19 and traffic trends were analyzed in this study, the traffic in Seoul, Gyeonggi, and Incheon showed smaller changes compared with the other regions.
T189 5549-5735 Sentence denotes This is because the Korean citizens, including overseas students, started returning to the country as COVID-19 began rapidly spreading overseas, such as in Europe and the US (Cho, 2020).
T190 5736-5915 Sentence denotes The number of Korean citizens returning from overseas and requiring control was estimated to be 210 000 individuals, making the risk of a resurgence of COVID-19 considerably high.
T191 5916-6055 Sentence denotes Indeed, 23.8% of the confirmed cases in Seoul in the third week of March were individuals returning from abroad (Young-kyung et al., 2020).
T192 6056-6256 Sentence denotes Thus, Seoul, Gyeonggi, and Incheon, which are closer to the airport and the residences of many citizens returning from abroad, showed increased COVID-19 and traffic trends compared with other regions.
T193 6257-6472 Sentence denotes In particular, Incheon showed a positive linear relationship between traffic and new confirmed COVID-19 patients, prompting increasing concern about a secondary COVID-19 outbreak in this region compared with others.
T194 6473-6505 Sentence denotes This study had some limitations.
T195 6506-6660 Sentence denotes First, it did not collect data on the total national traffic volume, instead relying on VDS data, although these are representative of the national trend.
T196 6661-6772 Sentence denotes Moreover, the data collected included drive-through traffic, which would need to be excluded in future studies.
T197 6773-6901 Sentence denotes Second, this study did not preclude the causal effects of regional influences, such as public policy, the media, education, etc.
T198 6902-7049 Sentence denotes A future study should include a comparison of experiences in each city with those in other outbreak cities pursuing different policies (Pan, 2020).
T199 7050-7092 Sentence denotes Globally, COVID-19 is an ongoing pandemic.
T200 7093-7292 Sentence denotes At present, the spread of COVID-19 is concentrated in Europe and the US, with WHO declaring Europe to be the second epicenter of COVID-19 (Johnson et al., 2020, Lin et al., 2020, Qasim et al., 2020).
T201 7293-7550 Sentence denotes As of March 31, 2020, outside of Asia, the five countries with the highest numbers of confirmed COVID-19 cases were, in descending order, the US (163 479 cases), Italy (101 739 cases), Spain (87 956 cases), Germany (66 885 cases), and France (44 550 cases).
T202 7551-7785 Sentence denotes All these countries allow Koreans to freely travel there and, consequently, South Korea is currently experiencing a persistent increase in the cases of infection re-entering the country from overseas regions such as Europe and the US.
T203 7786-7951 Sentence denotes Preparing various physical and institutional measures, including social distancing, will be necessary to prepare for a secondary outbreak of COVID-19 in South Korea.
T204 7952-8101 Sentence denotes In particular, increased traffic implies a rise in outdoor excursions, which elevates the risk of spread of COVID-19 due to increased social contact.
T205 8102-8231 Sentence denotes The government needs to devise policies similar to social distancing to restrict citizens’ excursions and other risks of contact.

2_test

Id Subject Object Predicate Lexical cue
32417247-32178769-50052995 4238-4242 32178769 denotes 2020
32417247-32275295-50052996 7043-7047 32275295 denotes 2020
32417247-32145465-50052997 7266-7270 32145465 denotes 2020
T59111 4238-4242 32178769 denotes 2020
T38357 7043-7047 32275295 denotes 2020
T47335 7266-7270 32145465 denotes 2020