PMC:7510993 / 28903-29838 JSONTXT

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T168","span":{"begin":176,"end":184},"obj":"Disease"},{"id":"T169","span":{"begin":216,"end":225},"obj":"Disease"},{"id":"T170","span":{"begin":364,"end":371},"obj":"Disease"},{"id":"T171","span":{"begin":458,"end":466},"obj":"Disease"},{"id":"T172","span":{"begin":630,"end":638},"obj":"Disease"},{"id":"T173","span":{"begin":754,"end":762},"obj":"Disease"},{"id":"T174","span":{"begin":820,"end":828},"obj":"Disease"},{"id":"T175","span":{"begin":829,"end":838},"obj":"Disease"}],"attributes":[{"id":"A168","pred":"mondo_id","subj":"T168","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A169","pred":"mondo_id","subj":"T169","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"},{"id":"A170","pred":"mondo_id","subj":"T170","obj":"http://purl.obolibrary.org/obo/MONDO_0005136"},{"id":"A171","pred":"mondo_id","subj":"T171","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A172","pred":"mondo_id","subj":"T172","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A173","pred":"mondo_id","subj":"T173","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A174","pred":"mondo_id","subj":"T174","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A175","pred":"mondo_id","subj":"T175","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"}],"text":"l, were countries with high temperature and humidity that are characterized by lower cross-border mobility and more BCG vaccination. The type D countries, with less than 1,000 COVID-19 cases per million in which the infection spread peaked after mid-June, were mostly tropical developing countries with lower population density, less cross-border mobility, higher malaria incidence, and less BCG vaccination. These country-specific factors indicate that the COVID-19 spread is not simply driven by specific environmental variables, and the underlying mechanisms are complicated (Table 1). Therefore, evaluating the drivers of the COVID-19 spread at the present phase of disease expansion is a challenging task.\nThe absence of population-wide testing for COVID-19 makes it difficult to investigate the growth dynamics of COVID-19 infection. The case data include a selection bias due to surveillance focusing mainly on symptomatic perso"}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T160","span":{"begin":691,"end":692},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T161","span":{"begin":742,"end":749},"obj":"http://purl.obolibrary.org/obo/UBERON_0000473"},{"id":"T162","span":{"begin":862,"end":863},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T163","span":{"begin":899,"end":907},"obj":"http://purl.obolibrary.org/obo/CLO_0009985"}],"text":"l, were countries with high temperature and humidity that are characterized by lower cross-border mobility and more BCG vaccination. The type D countries, with less than 1,000 COVID-19 cases per million in which the infection spread peaked after mid-June, were mostly tropical developing countries with lower population density, less cross-border mobility, higher malaria incidence, and less BCG vaccination. These country-specific factors indicate that the COVID-19 spread is not simply driven by specific environmental variables, and the underlying mechanisms are complicated (Table 1). Therefore, evaluating the drivers of the COVID-19 spread at the present phase of disease expansion is a challenging task.\nThe absence of population-wide testing for COVID-19 makes it difficult to investigate the growth dynamics of COVID-19 infection. The case data include a selection bias due to surveillance focusing mainly on symptomatic perso"}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T73","span":{"begin":116,"end":119},"obj":"Chemical"},{"id":"T74","span":{"begin":392,"end":395},"obj":"Chemical"}],"attributes":[{"id":"A73","pred":"chebi_id","subj":"T73","obj":"http://purl.obolibrary.org/obo/CHEBI_41001"},{"id":"A74","pred":"chebi_id","subj":"T74","obj":"http://purl.obolibrary.org/obo/CHEBI_41001"}],"text":"l, were countries with high temperature and humidity that are characterized by lower cross-border mobility and more BCG vaccination. The type D countries, with less than 1,000 COVID-19 cases per million in which the infection spread peaked after mid-June, were mostly tropical developing countries with lower population density, less cross-border mobility, higher malaria incidence, and less BCG vaccination. These country-specific factors indicate that the COVID-19 spread is not simply driven by specific environmental variables, and the underlying mechanisms are complicated (Table 1). Therefore, evaluating the drivers of the COVID-19 spread at the present phase of disease expansion is a challenging task.\nThe absence of population-wide testing for COVID-19 makes it difficult to investigate the growth dynamics of COVID-19 infection. The case data include a selection bias due to surveillance focusing mainly on symptomatic perso"}

{"project":"LitCovid-PubTator","denotations":[{"id":"435","span":{"begin":116,"end":119},"obj":"Species"},{"id":"436","span":{"begin":392,"end":395},"obj":"Species"},{"id":"443","span":{"begin":176,"end":184},"obj":"Disease"},{"id":"444","span":{"begin":216,"end":225},"obj":"Disease"},{"id":"445","span":{"begin":364,"end":371},"obj":"Disease"},{"id":"446","span":{"begin":458,"end":466},"obj":"Disease"},{"id":"447","span":{"begin":630,"end":638},"obj":"Disease"},{"id":"462","span":{"begin":754,"end":762},"obj":"Disease"},{"id":"463","span":{"begin":820,"end":828},"obj":"Disease"},{"id":"464","span":{"begin":829,"end":838},"obj":"Disease"}],"attributes":[{"id":"A435","pred":"tao:has_database_id","subj":"435","obj":"Tax:33892"},{"id":"A436","pred":"tao:has_database_id","subj":"436","obj":"Tax:33892"},{"id":"A443","pred":"tao:has_database_id","subj":"443","obj":"MESH:C000657245"},{"id":"A444","pred":"tao:has_database_id","subj":"444","obj":"MESH:D007239"},{"id":"A445","pred":"tao:has_database_id","subj":"445","obj":"MESH:D008288"},{"id":"A446","pred":"tao:has_database_id","subj":"446","obj":"MESH:C000657245"},{"id":"A447","pred":"tao:has_database_id","subj":"447","obj":"MESH:C000657245"},{"id":"A462","pred":"tao:has_database_id","subj":"462","obj":"MESH:C000657245"},{"id":"A463","pred":"tao:has_database_id","subj":"463","obj":"MESH:C000657245"},{"id":"A464","pred":"tao:has_database_id","subj":"464","obj":"MESH:D007239"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"l, were countries with high temperature and humidity that are characterized by lower cross-border mobility and more BCG vaccination. The type D countries, with less than 1,000 COVID-19 cases per million in which the infection spread peaked after mid-June, were mostly tropical developing countries with lower population density, less cross-border mobility, higher malaria incidence, and less BCG vaccination. These country-specific factors indicate that the COVID-19 spread is not simply driven by specific environmental variables, and the underlying mechanisms are complicated (Table 1). Therefore, evaluating the drivers of the COVID-19 spread at the present phase of disease expansion is a challenging task.\nThe absence of population-wide testing for COVID-19 makes it difficult to investigate the growth dynamics of COVID-19 infection. The case data include a selection bias due to surveillance focusing mainly on symptomatic perso"}

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T4","span":{"begin":801,"end":807},"obj":"http://purl.obolibrary.org/obo/GO_0040007"}],"text":"l, were countries with high temperature and humidity that are characterized by lower cross-border mobility and more BCG vaccination. The type D countries, with less than 1,000 COVID-19 cases per million in which the infection spread peaked after mid-June, were mostly tropical developing countries with lower population density, less cross-border mobility, higher malaria incidence, and less BCG vaccination. These country-specific factors indicate that the COVID-19 spread is not simply driven by specific environmental variables, and the underlying mechanisms are complicated (Table 1). Therefore, evaluating the drivers of the COVID-19 spread at the present phase of disease expansion is a challenging task.\nThe absence of population-wide testing for COVID-19 makes it difficult to investigate the growth dynamics of COVID-19 infection. The case data include a selection bias due to surveillance focusing mainly on symptomatic perso"}

{"project":"LitCovid-sentences","denotations":[{"id":"T149","span":{"begin":133,"end":408},"obj":"Sentence"},{"id":"T150","span":{"begin":409,"end":588},"obj":"Sentence"},{"id":"T151","span":{"begin":589,"end":710},"obj":"Sentence"},{"id":"T152","span":{"begin":711,"end":839},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"l, were countries with high temperature and humidity that are characterized by lower cross-border mobility and more BCG vaccination. The type D countries, with less than 1,000 COVID-19 cases per million in which the infection spread peaked after mid-June, were mostly tropical developing countries with lower population density, less cross-border mobility, higher malaria incidence, and less BCG vaccination. These country-specific factors indicate that the COVID-19 spread is not simply driven by specific environmental variables, and the underlying mechanisms are complicated (Table 1). Therefore, evaluating the drivers of the COVID-19 spread at the present phase of disease expansion is a challenging task.\nThe absence of population-wide testing for COVID-19 makes it difficult to investigate the growth dynamics of COVID-19 infection. The case data include a selection bias due to surveillance focusing mainly on symptomatic perso"}