tetano
Editor, Senior Moderator
Oncotarget. 2017 Feb 3. doi: 10.18632/oncotarget.15076. [Epub ahead of print]
[h=1]Use of social network analysis and global sensitivity and uncertainty analyses to better understand an influenza outbreak.[/h] Liu J[SUP]1,[/SUP][SUP]2[/SUP], Jiang H[SUP]3[/SUP], Zhang H[SUP]2[/SUP], Guo C[SUP]1[/SUP], Wang L[SUP]1,[/SUP][SUP]2[/SUP], Yang J[SUP]2[/SUP], Nie S[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] In the summer of 2014, an influenza A(H3N2) outbreak occurred in Yichang city, Hubei province, China. A retrospective study was conducted to collect and interpret hospital and epidemiological data on it using social network analysis and global sensitivity and uncertainty analyses. Results for degree (χ2=17.6619, P<0.0001) and betweenness(χ2=21.4186, P<0.0001) centrality suggested that the selection of sampling objects were different between traditional epidemiological methods and newer statistical approaches. Clique and network diagrams demonstrated that the outbreak actually consisted of two independent transmission networks. Sensitivity analysis showed that the contact coefficient (k) was the most important factor in the dynamic model. Using uncertainty analysis, we were able to better understand the properties and variations over space and time on the outbreak. We concluded that use of newer approaches were significantly more efficient for managing and controlling infectious diseases outbreaks, as well as saving time and public health resources, and could be widely applied on similar local outbreaks.
[h=4]KEYWORDS:[/h] control of infectious diseases; field epidemiology; global sensitivity and uncertainty analyses; social network analysis
PMID: 28177887 DOI: 10.18632/oncotarget.15076
[PubMed - as supplied by publisher] Free full text
[h=1]Use of social network analysis and global sensitivity and uncertainty analyses to better understand an influenza outbreak.[/h] Liu J[SUP]1,[/SUP][SUP]2[/SUP], Jiang H[SUP]3[/SUP], Zhang H[SUP]2[/SUP], Guo C[SUP]1[/SUP], Wang L[SUP]1,[/SUP][SUP]2[/SUP], Yang J[SUP]2[/SUP], Nie S[SUP]1[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] In the summer of 2014, an influenza A(H3N2) outbreak occurred in Yichang city, Hubei province, China. A retrospective study was conducted to collect and interpret hospital and epidemiological data on it using social network analysis and global sensitivity and uncertainty analyses. Results for degree (χ2=17.6619, P<0.0001) and betweenness(χ2=21.4186, P<0.0001) centrality suggested that the selection of sampling objects were different between traditional epidemiological methods and newer statistical approaches. Clique and network diagrams demonstrated that the outbreak actually consisted of two independent transmission networks. Sensitivity analysis showed that the contact coefficient (k) was the most important factor in the dynamic model. Using uncertainty analysis, we were able to better understand the properties and variations over space and time on the outbreak. We concluded that use of newer approaches were significantly more efficient for managing and controlling infectious diseases outbreaks, as well as saving time and public health resources, and could be widely applied on similar local outbreaks.
[h=4]KEYWORDS:[/h] control of infectious diseases; field epidemiology; global sensitivity and uncertainty analyses; social network analysis
PMID: 28177887 DOI: 10.18632/oncotarget.15076
[PubMed - as supplied by publisher] Free full text