Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data
Objective To investigate the extent of geospatial clustering of reported deaths during the Ebola outbreak in Liberia and the covariates associated with the observed clustering.Design Cross-sectional study.Participants Male and female respondents from the 2019–2020 Liberia Demographic and Health Surv...
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BMJ Publishing Group
2022-06-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/12/6/e054095.full |
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| author | Fiifi Amoako Johnson Barbara Sakyi |
| author_facet | Fiifi Amoako Johnson Barbara Sakyi |
| author_sort | Fiifi Amoako Johnson |
| collection | DOAJ |
| description | Objective To investigate the extent of geospatial clustering of reported deaths during the Ebola outbreak in Liberia and the covariates associated with the observed clustering.Design Cross-sectional study.Participants Male and female respondents from the 2019–2020 Liberia Demographic and Health Survey. The analysis covered 11 928 (women=7854 and men=4074) respondents for whom complete data were available.Outcome measures The outcome variable was the death of a household member or relative during the Ebola outbreak in Liberia, coded 1 if the respondent reported death and 0 otherwise.Methods We applied the Bayesian geoadditive semiparametric regression to examine the extent of geospatial clustering of deaths at the district-level and community-level development and socioeconomic factors associated with the observed clustering.Results Almost a quarter (24.8%) of all respondents reported the death of a household member or relative during the Ebola outbreak. The results show that deaths were clustered within districts in six (Grand Cape Mount, Bomi, Monsterrado, Margibi, Gbarpolu and Lofa) of the 15 counties in Liberia. Districts with high death clustering were all near or shared borders with Sierra Leone and Guinea. The community-level development indicators (global human footprint, gross cell production and population density) had a non-linear associative effect with the observed spatial clustering. Also, respondents’ characteristics (respondent’s age (non-linear effect), educational attainment and urban-rural place of residence) were associated with the observed clustering. The results show that death clustering during outbreaks was constrained to poor settings and impacts areas of moderate and high socioeconomic development.Conclusion Reported deaths during the Ebola outbreak in Liberia were not randomly distributed at the district level but clustered. The findings highlight the need to identify at-risk populations during epidemics and respond with the needed interventions to save lives. |
| format | Article |
| id | doaj-art-fb16b5980f7049d091dfd40bf46d4a2e |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2022-06-01 |
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| spelling | doaj-art-fb16b5980f7049d091dfd40bf46d4a2e2025-01-24T08:30:09ZengBMJ Publishing GroupBMJ Open2044-60552022-06-0112610.1136/bmjopen-2021-054095Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey dataFiifi Amoako Johnson0Barbara Sakyi1Department of Population and Health, University of Cape Coast Faculty of Social Sciences, Cape Coast, Ghana7 Department of Population and Health, University of Cape Coast, Cape Coast, GhanaObjective To investigate the extent of geospatial clustering of reported deaths during the Ebola outbreak in Liberia and the covariates associated with the observed clustering.Design Cross-sectional study.Participants Male and female respondents from the 2019–2020 Liberia Demographic and Health Survey. The analysis covered 11 928 (women=7854 and men=4074) respondents for whom complete data were available.Outcome measures The outcome variable was the death of a household member or relative during the Ebola outbreak in Liberia, coded 1 if the respondent reported death and 0 otherwise.Methods We applied the Bayesian geoadditive semiparametric regression to examine the extent of geospatial clustering of deaths at the district-level and community-level development and socioeconomic factors associated with the observed clustering.Results Almost a quarter (24.8%) of all respondents reported the death of a household member or relative during the Ebola outbreak. The results show that deaths were clustered within districts in six (Grand Cape Mount, Bomi, Monsterrado, Margibi, Gbarpolu and Lofa) of the 15 counties in Liberia. Districts with high death clustering were all near or shared borders with Sierra Leone and Guinea. The community-level development indicators (global human footprint, gross cell production and population density) had a non-linear associative effect with the observed spatial clustering. Also, respondents’ characteristics (respondent’s age (non-linear effect), educational attainment and urban-rural place of residence) were associated with the observed clustering. The results show that death clustering during outbreaks was constrained to poor settings and impacts areas of moderate and high socioeconomic development.Conclusion Reported deaths during the Ebola outbreak in Liberia were not randomly distributed at the district level but clustered. The findings highlight the need to identify at-risk populations during epidemics and respond with the needed interventions to save lives.https://bmjopen.bmj.com/content/12/6/e054095.full |
| spellingShingle | Fiifi Amoako Johnson Barbara Sakyi Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data BMJ Open |
| title | Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data |
| title_full | Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data |
| title_fullStr | Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data |
| title_full_unstemmed | Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data |
| title_short | Geospatial clustering and correlates of deaths during the Ebola outbreak in Liberia: a Bayesian geoadditive semiparametric analysis of nationally representative cross-sectional survey data |
| title_sort | geospatial clustering and correlates of deaths during the ebola outbreak in liberia a bayesian geoadditive semiparametric analysis of nationally representative cross sectional survey data |
| url | https://bmjopen.bmj.com/content/12/6/e054095.full |
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