PMC:7062829 / 2896-4499 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"25","span":{"begin":712,"end":721},"obj":"Disease"}],"attributes":[{"id":"A25","pred":"tao:has_database_id","subj":"25","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":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}

{"project":"LitCovid-PD-FMA-UBERON","denotations":[{"id":"T1","span":{"begin":631,"end":635},"obj":"Body_part"}],"attributes":[{"id":"A1","pred":"fma_id","subj":"T1","obj":"http://purl.org/sig/ont/fma/fma9712"}],"text":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}

{"project":"LitCovid-PD-UBERON","denotations":[{"id":"T1","span":{"begin":106,"end":111},"obj":"Body_part"},{"id":"T2","span":{"begin":598,"end":603},"obj":"Body_part"},{"id":"T3","span":{"begin":631,"end":635},"obj":"Body_part"},{"id":"T4","span":{"begin":783,"end":788},"obj":"Body_part"}],"attributes":[{"id":"A1","pred":"uberon_id","subj":"T1","obj":"http://purl.obolibrary.org/obo/UBERON_0002542"},{"id":"A2","pred":"uberon_id","subj":"T2","obj":"http://purl.obolibrary.org/obo/UBERON_0002542"},{"id":"A3","pred":"uberon_id","subj":"T3","obj":"http://purl.obolibrary.org/obo/UBERON_0002398"},{"id":"A4","pred":"uberon_id","subj":"T4","obj":"http://purl.obolibrary.org/obo/UBERON_0002542"}],"text":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T13","span":{"begin":712,"end":721},"obj":"Disease"}],"attributes":[{"id":"A13","pred":"mondo_id","subj":"T13","obj":"http://purl.obolibrary.org/obo/MONDO_0005550"}],"text":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T11","span":{"begin":155,"end":156},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T12","span":{"begin":415,"end":416},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T13","span":{"begin":684,"end":685},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T14","span":{"begin":993,"end":994},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T15","span":{"begin":1141,"end":1144},"obj":"http://purl.obolibrary.org/obo/CLO_0051582"},{"id":"T16","span":{"begin":1431,"end":1432},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}

{"project":"LitCovid-sentences","denotations":[{"id":"T21","span":{"begin":0,"end":126},"obj":"Sentence"},{"id":"T22","span":{"begin":127,"end":269},"obj":"Sentence"},{"id":"T23","span":{"begin":270,"end":454},"obj":"Sentence"},{"id":"T24","span":{"begin":455,"end":590},"obj":"Sentence"},{"id":"T25","span":{"begin":591,"end":728},"obj":"Sentence"},{"id":"T26","span":{"begin":729,"end":868},"obj":"Sentence"},{"id":"T27","span":{"begin":869,"end":912},"obj":"Sentence"},{"id":"T28","span":{"begin":913,"end":1079},"obj":"Sentence"},{"id":"T29","span":{"begin":1080,"end":1229},"obj":"Sentence"},{"id":"T30","span":{"begin":1230,"end":1413},"obj":"Sentence"},{"id":"T31","span":{"begin":1414,"end":1603},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}

{"project":"2_test","denotations":[{"id":"32152361-9623998-138518102","span":{"begin":100,"end":101},"obj":"9623998"},{"id":"32152361-10521342-138518103","span":{"begin":124,"end":125},"obj":"10521342"},{"id":"32152361-27433389-138518104","span":{"begin":586,"end":587},"obj":"27433389"},{"id":"32152361-15466494-138518105","span":{"begin":588,"end":589},"obj":"15466494"},{"id":"32152361-9623998-138518106","span":{"begin":1224,"end":1225},"obj":"9623998"}],"text":"Previous studies on super-spreaders have identified two major types of networks, small-world network5 and scale-free network6. In the small-world network, a small number of shortcuts are discovered either by randomly connecting the nodes or randomly rewiring the links. From the shortcuts, it can be inferred that the average node length between any two individuals is shortened, thereby making geographic distance a causal factor in epidemic outbreaks7. In the small-world network context, thus, it is important to control the super-spreading events to prevent completely new outbreaks8,9. In the scale-free network, on the other hand, the number of contacts per individual exhibits a power-law distribution of infection links. The variation in the connectivity distribution of the scale-free network is infinite, because it does not exhibit the threshold phenomenon. Hence, an outbreak can occur at any time10. It can be inferred from both networks that the average shortest path length and a small degree of separation are important factors in the epidemic network analysis11. Furthermore, the super-spreading characteristic of epidemics has been associated with the spatial proximity of neighbouring nodes in the network5,12. Localised transmission of the epidemic is facilitated by high clustering coefficients, because of the close spatial proximity in node connectivity and its influence on their relation. Thus, nodes with a high spatial proximity tend to intensify super-spreading events within clusters, making it easy for the disease to spread locally over the considered population or areas."}