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PMC:7050133 / 23700-34413 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
189 317-325 Species denotes patients Tax:9606
190 124-132 Disease denotes COVID-19 MESH:C000657245
191 133-142 Disease denotes infection MESH:D007239
192 343-352 Disease denotes infection MESH:D007239
193 529-537 Disease denotes COVID-19 MESH:C000657245
195 827-835 Disease denotes COVID-19 MESH:C000657245
201 1581-1586 Species denotes Ebola Tax:1570291
202 1642-1646 Species denotes H1N1 Tax:114727
203 889-897 Disease denotes COVID-19 MESH:C000657245
204 1046-1054 Disease denotes COVID-19 MESH:C000657245
205 1529-1533 Disease denotes SARS MESH:D045169
209 2455-2459 Species denotes H1N1 Tax:114727
210 1874-1882 Disease denotes COVID-19 MESH:C000657245
211 2576-2584 Disease denotes COVID-19 MESH:C000657245
215 3356-3362 Species denotes people Tax:9606
216 2831-2839 Disease denotes COVID-19 MESH:C000657245
217 3157-3163 Disease denotes stress MESH:D000079225
220 3490-3498 Disease denotes COVID-19 MESH:C000657245
221 3499-3508 Disease denotes infection MESH:D007239
227 4022-4031 Disease denotes infection MESH:D007239
228 4226-4234 Disease denotes COVID-19 MESH:C000657245
229 4379-4397 Disease denotes infectious disease MESH:D003141
230 4435-4444 Disease denotes infection MESH:D007239
231 4528-4537 Disease denotes infection MESH:D007239
233 4968-4976 Disease denotes infected MESH:D007239
237 5456-5464 Disease denotes infected MESH:D007239
238 5764-5772 Disease denotes COVID-19 MESH:C000657245
239 5773-5782 Disease denotes infection MESH:D007239
247 6938-6944 Species denotes people Tax:9606
248 6310-6318 Disease denotes COVID-19 MESH:C000657245
249 6448-6456 Disease denotes COVID-19 MESH:C000657245
250 6613-6621 Disease denotes COVID-19 MESH:C000657245
251 6622-6631 Disease denotes infection MESH:D007239
252 6811-6821 Disease denotes infections MESH:D007239
253 6874-6892 Disease denotes infectious disease MESH:D003141
255 7412-7421 Disease denotes mortality MESH:D003643
259 7741-7751 Disease denotes infections MESH:D007239
260 7808-7818 Disease denotes infections MESH:D007239
261 7986-7996 Disease denotes infections MESH:D007239
265 8938-8944 Species denotes people Tax:9606
266 9106-9117 Species denotes Coronavirus Tax:11118
267 9317-9324 Species denotes patient Tax:9606
274 10354-10360 Species denotes people Tax:9606
275 9729-9737 Disease denotes infected MESH:D007239
276 9766-9776 Disease denotes infections MESH:D007239
277 9988-9996 Disease denotes COVID-19 MESH:C000657245
278 10406-10414 Disease denotes COVID-19 MESH:C000657245
279 10586-10594 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T2 4849-4854 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T58 124-132 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T59 133-142 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T60 343-352 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T61 529-537 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T62 827-835 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T63 889-897 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T64 1046-1054 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T65 1529-1533 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T66 1581-1586 Disease denotes Ebola http://purl.obolibrary.org/obo/MONDO_0005737
T67 1680-1687 Disease denotes measles http://purl.obolibrary.org/obo/MONDO_0004619
T68 1762-1765 Disease denotes flu http://purl.obolibrary.org/obo/MONDO_0005812
T69 1874-1882 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T70 2576-2584 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T71 2831-2839 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T72 3490-3498 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T73 3499-3508 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T74 4022-4031 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T75 4226-4234 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T76 4379-4397 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T77 4435-4444 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T78 4528-4537 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T79 5764-5772 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T80 5773-5782 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T81 6310-6318 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T82 6448-6456 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T83 6613-6621 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T84 6622-6631 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T85 6811-6821 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T86 6874-6892 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T87 7741-7751 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T88 7808-7818 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T89 7986-7996 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T90 9766-9776 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T91 9988-9996 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T92 10406-10414 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T93 10586-10594 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T87 35-36 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T88 231-232 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T89 331-332 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T90 399-404 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T91 472-473 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T92 1135-1136 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T93 1425-1426 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T94 1614-1618 http://purl.obolibrary.org/obo/CLO_0053799 denotes 4, 5
T95 1766-1769 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T96 1790-1791 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T97 1813-1815 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T98 2076-2084 http://purl.obolibrary.org/obo/PR_000001898 denotes called a
T99 3004-3005 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T100 3713-3721 http://purl.obolibrary.org/obo/CLO_0001658 denotes actively
T101 4660-4663 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T102 5495-5497 http://purl.obolibrary.org/obo/CLO_0050507 denotes 22
T103 5710-5719 http://purl.obolibrary.org/obo/CLO_0001658 denotes activated
T104 6353-6354 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T105 7001-7002 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T106 7173-7174 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T107 7430-7431 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T108 8505-8506 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T109 8857-8858 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T110 8920-8921 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T111 9296-9297 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T112 10124-10125 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T113 10172-10180 http://purl.obolibrary.org/obo/OBI_0100026 denotes organism
T114 10172-10180 http://purl.obolibrary.org/obo/UBERON_0000468 denotes organism
T115 10521-10522 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T116 10660-10661 http://purl.obolibrary.org/obo/CLO_0001020 denotes a

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T22 2219-2225 Chemical denotes silver http://purl.obolibrary.org/obo/CHEBI_30512|http://purl.obolibrary.org/obo/CHEBI_9141

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T142 0-11 Sentence denotes Disscussion
T143 12-143 Sentence denotes In this study, we used a novel approach to distill information from the cumulative number of diagnosed cases of COVID-19 infection.
T144 144-303 Sentence denotes Among various types of surveillance data, this data often reported the earliest and on a continuous basis with high completeness and are most widely available.
T145 304-415 Sentence denotes In addition, patients with a diagnosed infection are those with high likelihoods to spread the virus to others.
T146 416-556 Sentence denotes Findings from this study provided useful information in a real time manner to monitor, evaluate and forecast the COVID-19 epidemic in China.
T147 557-789 Sentence denotes The methods used in this study although somewhat mathematical, are easy to follow while information extracted from the commonly used data with the methods are highly useful and more sensitive than the daily new and cumulative cases.
T148 791-844 Sentence denotes Nonlinear and chaotic nature of the COVID-19 outbreak
T149 845-1098 Sentence denotes Although an analytical demonstration of the COVID-19 outbreak as nonlinear, chaotic and catastrophic requires more time to wait till the epidemic ends, evidence in the first 2 months suggests that the COVID-19 outbreak in China is nonlinear and chaotic.
T150 1099-1259 Sentence denotes The epidemic emerged suddenly after a long latent period without dramatic changes as revealed from the cumulative cases, and their first and second derivatives.
T151 1260-1461 Sentence denotes The high responsiveness of the epidemic to interventions adds additional evidence supporting the chaotic and catastrophic nature, and demonstrating the selection of a good timing to start intervention.
T152 1462-1736 Sentence denotes Many of these characters are similar to those observed in the 2003 SARS epidemic started in Hong Kong [2], the 2013–16 Ebola spread in the West Africa [4, 5], the 2009 pandemic of H1N1 started in the US [6–8], and the measles outbreaks over 80 cities in the US recently [9].
T153 1737-1821 Sentence denotes Even the seasonal common flu has been proved to have a nonlinear component [11, 12].
T154 1822-2037 Sentence denotes The significance of nonlinear and chaotic nature of COVID-19 means that no methods are available to predict exactly at what point in time the epidemic will emerge as an outbreak, just like volcanoes and earthquakes.
T155 2038-2135 Sentence denotes Therefore, practically there is no so-called a best time or missed the best time to take actions.
T156 2136-2206 Sentence denotes There will also no so-called rational analysis and rational responses.
T157 2207-2364 Sentence denotes There is no silver bullet to use, no standard-operating-procedure (SOP) to follow, and no measures without negative consequences to control the epidemic [2].
T158 2365-2493 Sentence denotes For example, it took more than 6 months for both the US and the WHO to determine the 2009 H1N1 pandemic as an outbreak [13, 14].
T159 2494-2771 Sentence denotes Therefore, knowing the nonlinear and chaotic nature of an epidemic outbreak, like COVID-19, for all stockholders will be essential to the mobilization of resources, working together, taking all actions possible to control the epidemic, and minimizing the negative consequences.
T160 2772-3363 Sentence denotes Specifically, what we can do to deal with an outbreak like COVID-19 would be to (1) collect information as early as possible, (2) monitor the epidemic as close as possible just like we do for an earthquake and make preparations for a hurricane and (3) communicate with the society and use confirmed data appropriately reframed not causing or exacerbating fear and panic in the public, stress and distress among medical and public health professionals, as well as administrators to make right decisions and take the right strategies at the right time in the right places for the right people.
T161 3364-3509 Sentence denotes Knowing the nonlinear and chaotic nature is also essential for taking actions to control the outbreak of an epidemic like the COVID-19 infection.
T162 3510-3903 Sentence denotes As soon as an outbreak is confirmed, the follow measures should be in position immediately 1) closely and carefully monitor the epidemic; 2) take evidence-based interventions to control the epidemic, 3) actively assess responses of the epidemic to the interventions; 4) allow errors in the intervention, particularly during the early period of the epidemic, 5) always prepare for alternatives.
T163 3904-3976 Sentence denotes Another confusion is, when an epidemic starts, everyone asks what it is?
T164 3977-3996 Sentence denotes How does it happen?
T165 3997-4032 Sentence denotes How should I do to avoid infection?
T166 4033-4066 Sentence denotes Is there any effective treatment?
T167 4067-4194 Sentence denotes Answering these questions takes time, but there is no need to wait till all these questions are resolved before taking actions.
T168 4195-4292 Sentence denotes We can take actions to prevent COVID-19 immediately while waiting for answers to these questions.
T169 4293-4445 Sentence denotes This is because we have the evidence-based strategy for control and prevention of any infectious disease without complete understanding of an infection.
T170 4446-4634 Sentence denotes That is so-called Tri-Component Strategy: locating and controlling the sources of infection, identifying and blocking the transmission paths, and protecting those who are susceptible [10].
T171 4635-4714 Sentence denotes This was just what China has done, is doing, and will continue to do this time.
T172 4715-4977 Sentence denotes Typical examples of control and prevention measures include locking down of cities, communities, and villages with potential of large scale transmission, massive environment sterilization, promotion of mask use, efforts to locate, isolate and treat the infected.
T173 4978-5164 Sentence denotes More importantly, most of these actions are initiated, mobilized, coordinated and supported by the government from central to local, and enhanced by volunteers and international support.
T174 5166-5205 Sentence denotes Highly effective of the national effort
T175 5206-5385 Sentence denotes Another important piece of findings is that we detected the effect of the national efforts taken by China from the beginning when they were in position till the end of this study.
T176 5386-5577 Sentence denotes For example, from the second derivative, we observed increases in the infected through the action on January 22, 2020, the next day after the massive intervention started on January 21, 2020.
T177 5578-5637 Sentence denotes This result was also picked up by the exponential modeling.
T178 5638-5783 Sentence denotes From day one on January 21, 2020 when the massive intervention measures activated to February 4, 2020 is the latent period of COVID-19 infection.
T179 5784-6015 Sentence denotes The second derivative precisely recorded the change in newly diagnosed cases in response to the massive measures, reflected as the rapid increase in detection rate, consistent with the result from the exponential modeling analysis.
T180 6016-6264 Sentence denotes The detected responsiveness of the epidemic to the intervention provided data to predict the occurrence of deceleration of the epidemic on February 4, 2020 if the same measures persist, which was exactly what we observed from the second derivative.
T181 6265-6344 Sentence denotes Based on the findings from our analysis, the COVID-19 in China may end up soon.
T182 6345-6566 Sentence denotes Despite a delay of 43 days from the first confirmed cases on December 8, 2019 to January 20, 2020, the COVID-19 epidemic was highly responsive to massive interventions, supporting the effectiveness of these interventions.
T183 6567-6954 Sentence denotes It is our prediction that the outbreak of the COVID-19 infection will be brought under control by the end of February 2020, given the effective control measures known to everyone, increases in immune level in the total population due to latent infections, and most widely spread of knowledge and skills for infectious disease control and prevention among the 1.4 billion people in China.
T184 6956-6990 Sentence denotes Effective methods for surveillance
T185 6991-7071 Sentence denotes There are a number of advantages of methods we developed and used in this study.
T186 7072-7391 Sentence denotes First, framing the diagnosed cases as the cumulative, the first and the second derivative constructs a system to gauge the epidemic, with the cumulative cases showing the overall level of the epidemic, the first derivative to reflect the change of the epidemic, and the second derivative to monitor the speed of change.
T187 7392-7683 Sentence denotes By inclusion of the mortality rate as a reference, results from our approach will be (1) comprehensive to inform the public to be prepared, not scared and not to blame others; (2) useful for administrators to make decisions; (3) valuable for medical and health professionals to take actions.
T188 7684-7997 Sentence denotes Second, we conceptually separated (1) the true number of infections, which will never be practically detected, from (2) the infections that are practically detectable if services are available and accessible and detection technologies are sensitive and reliable, and (3) the actually detected cases of infections.
T189 7998-8236 Sentence denotes This classification greatly improved our understanding of the observed data as well as findings from the two derivatives, and aided us in assessing the responsiveness to the massive interventions, and predicting of the epidemic over time.
T190 8237-8452 Sentence denotes The clarification also enhanced our analytical approach by adding an exponential model to evaluate the detection rate and to bring more data assessing the responsiveness of the epidemic to the massive interventions.
T191 8453-8583 Sentence denotes We highly recommend the inclusion of the methods as a part of routine surveillance in disease control and prevention institutions.
T192 8585-8612 Sentence denotes Limitations and future plan
T193 8613-8635 Sentence denotes There are limitations.
T194 8636-8702 Sentence denotes First, this study covered only the first 2 months of the epidemic.
T195 8703-8804 Sentence denotes We will continue to evaluate the utility of this method as we follow the development of the epidemic.
T196 8805-8876 Sentence denotes Second, the methods used in this study was based on a close population.
T197 8877-9017 Sentence denotes This hypothesis may not be true because of a large number of people with potential history of exposure in China traveled to other countries.
T198 9018-9200 Sentence denotes Up to February 8, 2020, the total cases diagnosed were 37,552 worldwide (Worldometer on Coronavirus) with 37,198 in China, which accounted for 99.1% of the total number of the world.
T199 9201-9278 Sentence denotes Therefore, the impact of close-population assumption would be rather limited.
T200 9279-9358 Sentence denotes Third, there was a lack of individual patient-level data for detailed analysis.
T201 9359-9532 Sentence denotes Fourth, our model can be further improved with other data, such as cases by severity, number of the suspected, number of those who received treatments and treatment results.
T202 9533-9647 Sentence denotes We will follow the epidemic closely and prepare for further research on the topic when more data become available.
T203 9648-10006 Sentence denotes Despite the limitations, this study provided new data to encourage those who are infected to better fight against the infections; to inform and encourage the general public, the medical and health professionals and the government to continue their current measures and to think of more measures that are innovative and effective to end the COVID-19 epidemic.
T204 10007-10388 Sentence denotes One of the greatest motivations for this study is to attempt to provide right information at the population level in a real manner to complement the data from micro-organism centered and laboratory-based biological, molecular, pharmacological and clinical information in both the academic and the mass media that often scare rather than encourage people, even health professionals.
T205 10389-10447 Sentence denotes Of the diagnosed COVID-19 cases, less than 20% are severe.
T206 10448-10560 Sentence denotes Findings from our study indicated that there is no need to be panic from a public health population perspective.
T207 10561-10713 Sentence denotes Although the total cases COVID-19 reached to big numbers, but the 2-month incidence rate was about a half of the natural death rate for Wuhan residents.

2_test

Id Subject Object Predicate Lexical cue
32158961-20379852-45094803 1666-1667 20379852 denotes 6
32158961-23407581-45094803 1666-1667 23407581 denotes 6
32158961-26845437-45094804 1733-1734 26845437 denotes 9
32158961-23729996-45094805 2485-2487 23729996 denotes 13