Open forum infectious diseases · 2022
Social Network Analysis of Ebola Virus Disease During the 2014 Outbreak in Sukudu, Sierra Leone.
СтатьяНазвание и аннотация: Перевод в очереди
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Hazel Ashley, Davidson Michelle C, Rogers Abu, Barrie M Bailor, Freeman Adams, Mbayoh Mohamed, Kamara Mohamed, Blumberg Seth, Lietman Thomas M, Rutherford George W, Jones James Holland, Porco Travis C, Richardson Eugene T, Kelly J Daniel
Аннотация
BACKGROUND: Transmission by unreported cases has been proposed as a reason for the 2013-2016 Ebola virus (EBOV) epidemic decline in West Africa, but studies that test this hypothesis are lacking. We examined a transmission chain within social networks in Sukudu village to assess spread and transmission burnout.
METHODS: Network data were collected in 2 phases: (1) serological and contact information from Ebola cases (n = 48, including unreported); and (2) interviews (n = 148), including Ebola survivors (n = 13), to identify key social interactions. Social links to the transmission chain were used to calculate cumulative incidence proportion as the number of EBOV-infected people in the network divided by total network size.
RESULTS: The sample included 148 participants and 1522 contacts, comprising 10 social networks: 3 had strong links (>50% of cases) to the transmission chain: household sharing (largely kinship), leisure time, and talking about important things (both largely non-kin). Overall cumulative incidence for these networks was 37 of 311 (12%). Unreported cases did not have higher network centrality than reported cases.
CONCLUSIONS: Although this study did not find evidence that explained epidemic decline in Sukudu, it excluded potential reasons (eg, unreported cases, herd immunity) and identified 3 social interactions in EBOV transmission.
METHODS: Network data were collected in 2 phases: (1) serological and contact information from Ebola cases (n = 48, including unreported); and (2) interviews (n = 148), including Ebola survivors (n = 13), to identify key social interactions. Social links to the transmission chain were used to calculate cumulative incidence proportion as the number of EBOV-infected people in the network divided by total network size.
RESULTS: The sample included 148 participants and 1522 contacts, comprising 10 social networks: 3 had strong links (>50% of cases) to the transmission chain: household sharing (largely kinship), leisure time, and talking about important things (both largely non-kin). Overall cumulative incidence for these networks was 37 of 311 (12%). Unreported cases did not have higher network centrality than reported cases.
CONCLUSIONS: Although this study did not find evidence that explained epidemic decline in Sukudu, it excluded potential reasons (eg, unreported cases, herd immunity) and identified 3 social interactions in EBOV transmission.