PMC:7210464 / 15657-16695 JSONTXT

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T3","span":{"begin":683,"end":687},"obj":"Body_part"}],"attributes":[{"id":"A3","pred":"fma_id","subj":"T3","obj":"http://purl.org/sig/ont/fma/fma9712"}],"text":"In Eq. 2, the instrumental variables include averages of daily maximum temperature, total precipitation, average wind speed, and the interaction between precipitation and wind speed, for city c in the preceding third and fourth weeks. Detailed discussion of the selection of weather characteristics as instruments is in Section 3.2. The timeline of key variables are displayed in Fig. 1. The primary assumption on the instrumental variables is that weather conditions before 2 weeks do not affect the likelihood that a person susceptible to the virus contracts the disease, conditional on weather conditions and the number of infectious people within the 2-week window. On the other hand, they affect the number of other persons who have become infectious within the 2-week window, because they may have contracted the virus earlier than 2 weeks. These weather variables are exogenous to the error term and affect the spread of the virus, which have been used by Adda (2016) to instrument flu infections9.\nFig. 1 Timeline of key variables"}

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T3","span":{"begin":683,"end":687},"obj":"Body_part"}],"attributes":[{"id":"A3","pred":"uberon_id","subj":"T3","obj":"http://purl.obolibrary.org/obo/UBERON_0002398"}],"text":"In Eq. 2, the instrumental variables include averages of daily maximum temperature, total precipitation, average wind speed, and the interaction between precipitation and wind speed, for city c in the preceding third and fourth weeks. Detailed discussion of the selection of weather characteristics as instruments is in Section 3.2. The timeline of key variables are displayed in Fig. 1. The primary assumption on the instrumental variables is that weather conditions before 2 weeks do not affect the likelihood that a person susceptible to the virus contracts the disease, conditional on weather conditions and the number of infectious people within the 2-week window. On the other hand, they affect the number of other persons who have become infectious within the 2-week window, because they may have contracted the virus earlier than 2 weeks. These weather variables are exogenous to the error term and affect the spread of the virus, which have been used by Adda (2016) to instrument flu infections9.\nFig. 1 Timeline of key variables"}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T54","span":{"begin":626,"end":636},"obj":"Disease"},{"id":"T55","span":{"begin":745,"end":755},"obj":"Disease"},{"id":"T56","span":{"begin":989,"end":992},"obj":"Disease"}],"attributes":[{"id":"A54","pred":"mondo_id","subj":"T54","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"},{"id":"A55","pred":"mondo_id","subj":"T55","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"},{"id":"A56","pred":"mondo_id","subj":"T56","obj":"http://purl.obolibrary.org/obo/MONDO_0005812"}],"text":"In Eq. 2, the instrumental variables include averages of daily maximum temperature, total precipitation, average wind speed, and the interaction between precipitation and wind speed, for city c in the preceding third and fourth weeks. Detailed discussion of the selection of weather characteristics as instruments is in Section 3.2. The timeline of key variables are displayed in Fig. 1. The primary assumption on the instrumental variables is that weather conditions before 2 weeks do not affect the likelihood that a person susceptible to the virus contracts the disease, conditional on weather conditions and the number of infectious people within the 2-week window. On the other hand, they affect the number of other persons who have become infectious within the 2-week window, because they may have contracted the virus earlier than 2 weeks. These weather variables are exogenous to the error term and affect the spread of the virus, which have been used by Adda (2016) to instrument flu infections9.\nFig. 1 Timeline of key variables"}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T67","span":{"begin":14,"end":26},"obj":"http://purl.obolibrary.org/obo/OBI_0000968"},{"id":"T68","span":{"begin":302,"end":313},"obj":"http://purl.obolibrary.org/obo/OBI_0000968"},{"id":"T69","span":{"begin":418,"end":430},"obj":"http://purl.obolibrary.org/obo/OBI_0000968"},{"id":"T70","span":{"begin":517,"end":518},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T71","span":{"begin":545,"end":550},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T72","span":{"begin":819,"end":824},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T73","span":{"begin":932,"end":937},"obj":"http://purl.obolibrary.org/obo/NCBITaxon_10239"},{"id":"T74","span":{"begin":978,"end":988},"obj":"http://purl.obolibrary.org/obo/OBI_0000968"}],"text":"In Eq. 2, the instrumental variables include averages of daily maximum temperature, total precipitation, average wind speed, and the interaction between precipitation and wind speed, for city c in the preceding third and fourth weeks. Detailed discussion of the selection of weather characteristics as instruments is in Section 3.2. The timeline of key variables are displayed in Fig. 1. The primary assumption on the instrumental variables is that weather conditions before 2 weeks do not affect the likelihood that a person susceptible to the virus contracts the disease, conditional on weather conditions and the number of infectious people within the 2-week window. On the other hand, they affect the number of other persons who have become infectious within the 2-week window, because they may have contracted the virus earlier than 2 weeks. These weather variables are exogenous to the error term and affect the spread of the virus, which have been used by Adda (2016) to instrument flu infections9.\nFig. 1 Timeline of key variables"}

{"project":"LitCovid-sentences","denotations":[{"id":"T101","span":{"begin":0,"end":234},"obj":"Sentence"},{"id":"T102","span":{"begin":235,"end":332},"obj":"Sentence"},{"id":"T103","span":{"begin":333,"end":387},"obj":"Sentence"},{"id":"T104","span":{"begin":388,"end":669},"obj":"Sentence"},{"id":"T105","span":{"begin":670,"end":846},"obj":"Sentence"},{"id":"T106","span":{"begin":847,"end":1005},"obj":"Sentence"},{"id":"T107","span":{"begin":1006,"end":1038},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"In Eq. 2, the instrumental variables include averages of daily maximum temperature, total precipitation, average wind speed, and the interaction between precipitation and wind speed, for city c in the preceding third and fourth weeks. Detailed discussion of the selection of weather characteristics as instruments is in Section 3.2. The timeline of key variables are displayed in Fig. 1. The primary assumption on the instrumental variables is that weather conditions before 2 weeks do not affect the likelihood that a person susceptible to the virus contracts the disease, conditional on weather conditions and the number of infectious people within the 2-week window. On the other hand, they affect the number of other persons who have become infectious within the 2-week window, because they may have contracted the virus earlier than 2 weeks. These weather variables are exogenous to the error term and affect the spread of the virus, which have been used by Adda (2016) to instrument flu infections9.\nFig. 1 Timeline of key variables"}

{"project":"LitCovid-PubTator","denotations":[{"id":"147","span":{"begin":963,"end":967},"obj":"Gene"},{"id":"148","span":{"begin":637,"end":643},"obj":"Species"},{"id":"149","span":{"begin":721,"end":728},"obj":"Species"}],"attributes":[{"id":"A147","pred":"tao:has_database_id","subj":"147","obj":"Gene:118"},{"id":"A148","pred":"tao:has_database_id","subj":"148","obj":"Tax:9606"},{"id":"A149","pred":"tao:has_database_id","subj":"149","obj":"Tax:9606"}],"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":"In Eq. 2, the instrumental variables include averages of daily maximum temperature, total precipitation, average wind speed, and the interaction between precipitation and wind speed, for city c in the preceding third and fourth weeks. Detailed discussion of the selection of weather characteristics as instruments is in Section 3.2. The timeline of key variables are displayed in Fig. 1. The primary assumption on the instrumental variables is that weather conditions before 2 weeks do not affect the likelihood that a person susceptible to the virus contracts the disease, conditional on weather conditions and the number of infectious people within the 2-week window. On the other hand, they affect the number of other persons who have become infectious within the 2-week window, because they may have contracted the virus earlier than 2 weeks. These weather variables are exogenous to the error term and affect the spread of the virus, which have been used by Adda (2016) to instrument flu infections9.\nFig. 1 Timeline of key variables"}