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LitCovid-PD-CHEBI

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T1","span":{"begin":3446,"end":3448},"obj":"Chemical"}],"attributes":[{"id":"A1","pred":"chebi_id","subj":"T1","obj":"http://purl.obolibrary.org/obo/CHEBI_73613"}],"text":"Methods\n\nData\nThe dataset contains records of all 186 people, across 43 hospitals, who were infected with the MERS virus between May 20 and July 4, 2015 in Korea. The data is publicly available on press mentions from the Korea Centers for Disease Control \u0026 Prevention. The data includes diagnosis and reporting date, sex, age at diagnosis, source of infection, transmission route, and stage of MERS. Scholarly papers in various journals and news media also provided current issues of the MERS event. The use of multiple sources of evidence allows us to validate the research findings. In this study, the contact patterns coming from Marquetoux et al.25 are established by tracing the relationship matrix of individuals and hospitals. The data for the analysis contains two types of contacts: personal and hospital. A personal contact is defined as the person-to-person route. The format for a personal contact is a daily record. For every pair of individual hosts between whom infectious contacts occurred on a given date, there is a daily record including the source (infector) and target individuals (infected) presented with the spread of the MERS infection. A hospital contact is defined as a hospital-acquired infection, also known as nosocomial infection. A contact occurs when an infected individual visits healthcare facilities for a limited time period for MERS diagnosis, treatment, and follow-up visit records. Each hospital contact corresponds to an actual visit of the individual hosts and includes the date on which the contact event occurred.\nWe construct a matrix of contact patterns of individuals and hospitals. The number of observations for the personal contacts are 161(source: n) and 31(target: k), and those for the hospital contacts are 186 (infected host: n) and 43(hospital: k). Among the 186 confirmed cases (including one case confirmed by China), the rates of infection were confirmed to be as follows: 44.1% (82 cases) among in- or out-patients sharing wards with the MERS patient; 34.4% (64 cases) among the hospitalised MERS patient’s cohabiting family members or visitors; and 21.0% (39 cases) among the healthcare workers or staff employed at the MERS-affected hospital26. Based on this data, we use an adjacency matrix to construct contact networks consisting of all recorded transmission routes of MERS infections from May 20 to July 4. In the personal contact network, each pair of individuals, p, is examined to determine whether the infection was passed from a source individual i to a target individual j. Thus, Rij:p is equal to 1 if there is an infectious contact between individuals i and j; the personal contact network is as follows: Rp = 1 if Rij:p = 1 and 0 otherwise. In the hospital contact network, we first use a two-mode incidence matrix to form individual host-by-hospital contact relations, in which Rij:h = 1 if individual host i visited hospital j, and Rij:h = 0 otherwise. Next, we construct a bipartite graph consisting of the union of the individual hosts and hospitals as nodes with the edges only connecting individual hosts with hospitals. For hospital-acquired infection, therefore, individual hosts are connected only by co-presence in hospitals, and hospitals are connected only by having individual hosts in common. Thus, the exposed contacts through which the infection can spread are represented by the co-presence of two individual hosts in the same hospitals. All the data in MS Excel, network measures, and visual displays of disease contact relations are produced using UCINET 627, Net-Draw28, and VOSviewer29.\n\nAnalytical techniques\nThis study examines the 2015 MERS outbreak in Korea using network analysis tools such as the indicators of centrality, egocentric network, core-periphery, and cut-points. First, centrality pertains to the node’s (as unit of analysis: individual host) position in a network through specific analysis that is preoccupied with the degree, betweenness, closeness, and eigenvector of the geodesic distances30. Then, the egocentric network is used to identify the topologies of the contact networks in which single individual hosts are bound with their neighbouring individual hosts to reveal the link between direct contact and the spread of the MERS infection31. Furthermore, the core-periphery structures in a given network can reveal how the infection is transmitted locally or globally through the interaction of the core and periphery32. Finally, a cut-point approach is used to identify the key hosts whose removal from the network would divide the network into un-connected parts, indicating a potential weakness in the network or disruption of the infection transmission flow33. The comprehensive analysis can reveal how a disease contact network can be formed among individuals exposed to nosocomial infections, and the impact of the super-spreaders on the prevalence of infectious diseases within a relatively short period."}

LitCovid-sentences

2_test

{"project":"2_test","denotations":[{"id":"32152361-26883965-138518112","span":{"begin":650,"end":652},"obj":"26883965"},{"id":"32152361-20585380-138518113","span":{"begin":3579,"end":3581},"obj":"20585380"}],"text":"Methods\n\nData\nThe dataset contains records of all 186 people, across 43 hospitals, who were infected with the MERS virus between May 20 and July 4, 2015 in Korea. The data is publicly available on press mentions from the Korea Centers for Disease Control \u0026 Prevention. The data includes diagnosis and reporting date, sex, age at diagnosis, source of infection, transmission route, and stage of MERS. Scholarly papers in various journals and news media also provided current issues of the MERS event. The use of multiple sources of evidence allows us to validate the research findings. In this study, the contact patterns coming from Marquetoux et al.25 are established by tracing the relationship matrix of individuals and hospitals. The data for the analysis contains two types of contacts: personal and hospital. A personal contact is defined as the person-to-person route. The format for a personal contact is a daily record. For every pair of individual hosts between whom infectious contacts occurred on a given date, there is a daily record including the source (infector) and target individuals (infected) presented with the spread of the MERS infection. A hospital contact is defined as a hospital-acquired infection, also known as nosocomial infection. A contact occurs when an infected individual visits healthcare facilities for a limited time period for MERS diagnosis, treatment, and follow-up visit records. Each hospital contact corresponds to an actual visit of the individual hosts and includes the date on which the contact event occurred.\nWe construct a matrix of contact patterns of individuals and hospitals. The number of observations for the personal contacts are 161(source: n) and 31(target: k), and those for the hospital contacts are 186 (infected host: n) and 43(hospital: k). Among the 186 confirmed cases (including one case confirmed by China), the rates of infection were confirmed to be as follows: 44.1% (82 cases) among in- or out-patients sharing wards with the MERS patient; 34.4% (64 cases) among the hospitalised MERS patient’s cohabiting family members or visitors; and 21.0% (39 cases) among the healthcare workers or staff employed at the MERS-affected hospital26. Based on this data, we use an adjacency matrix to construct contact networks consisting of all recorded transmission routes of MERS infections from May 20 to July 4. In the personal contact network, each pair of individuals, p, is examined to determine whether the infection was passed from a source individual i to a target individual j. Thus, Rij:p is equal to 1 if there is an infectious contact between individuals i and j; the personal contact network is as follows: Rp = 1 if Rij:p = 1 and 0 otherwise. In the hospital contact network, we first use a two-mode incidence matrix to form individual host-by-hospital contact relations, in which Rij:h = 1 if individual host i visited hospital j, and Rij:h = 0 otherwise. Next, we construct a bipartite graph consisting of the union of the individual hosts and hospitals as nodes with the edges only connecting individual hosts with hospitals. For hospital-acquired infection, therefore, individual hosts are connected only by co-presence in hospitals, and hospitals are connected only by having individual hosts in common. Thus, the exposed contacts through which the infection can spread are represented by the co-presence of two individual hosts in the same hospitals. All the data in MS Excel, network measures, and visual displays of disease contact relations are produced using UCINET 627, Net-Draw28, and VOSviewer29.\n\nAnalytical techniques\nThis study examines the 2015 MERS outbreak in Korea using network analysis tools such as the indicators of centrality, egocentric network, core-periphery, and cut-points. First, centrality pertains to the node’s (as unit of analysis: individual host) position in a network through specific analysis that is preoccupied with the degree, betweenness, closeness, and eigenvector of the geodesic distances30. Then, the egocentric network is used to identify the topologies of the contact networks in which single individual hosts are bound with their neighbouring individual hosts to reveal the link between direct contact and the spread of the MERS infection31. Furthermore, the core-periphery structures in a given network can reveal how the infection is transmitted locally or globally through the interaction of the core and periphery32. Finally, a cut-point approach is used to identify the key hosts whose removal from the network would divide the network into un-connected parts, indicating a potential weakness in the network or disruption of the infection transmission flow33. The comprehensive analysis can reveal how a disease contact network can be formed among individuals exposed to nosocomial infections, and the impact of the super-spreaders on the prevalence of infectious diseases within a relatively short period."}