Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey

The Ebola virus disease (EVD) epidemic has threatened access to basic health services through facility closures, resource diversion, and decreased demand due to community fear and distrust. While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilize...

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Veröffentlicht in:PLoS medicine 2016-08, Vol.13 (8), p.e1002096-e1002096
Hauptverfasser: Ly, John, Sathananthan, Vidiya, Griffiths, Thomas, Kanjee, Zahir, Kenny, Avi, Gordon, Nicholas, Basu, Gaurab, Battistoli, Dale, Dorr, Lorenzo, Lorenzen, Breeanna, Thomson, Dana R, Waters, Ami, Moore, Uriah G, Roberts, Ruth, Smith, Wilmot L, Siedner, Mark J, Kraemer, John D
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container_issue 8
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container_title PLoS medicine
container_volume 13
creator Ly, John
Sathananthan, Vidiya
Griffiths, Thomas
Kanjee, Zahir
Kenny, Avi
Gordon, Nicholas
Basu, Gaurab
Battistoli, Dale
Dorr, Lorenzo
Lorenzen, Breeanna
Thomson, Dana R
Waters, Ami
Moore, Uriah G
Roberts, Ruth
Smith, Wilmot L
Siedner, Mark J
Kraemer, John D
description The Ebola virus disease (EVD) epidemic has threatened access to basic health services through facility closures, resource diversion, and decreased demand due to community fear and distrust. While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data. We conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias. We detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may und
doi_str_mv 10.1371/journal.pmed.1002096
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While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data. We conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias. We detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may under-approximate the effect seen in the most heavily affected areas. These are the first population-based survey data to show collateral disruptions to facility-based delivery caused by the West African EVD epidemic, and they reinforce the need to consider the full spectrum of implications caused by public health emergencies.</description><identifier>ISSN: 1549-1676</identifier><identifier>ISSN: 1549-1277</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.1002096</identifier><identifier>PMID: 27482706</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Births ; Care and treatment ; Cluster Analysis ; Community ; Confidence intervals ; Datasets ; Delivery, Obstetric - statistics &amp; numerical data ; Ebola hemorrhagic fever ; Ebola virus ; Ebolavirus ; Epidemics ; Family Characteristics ; Female ; Global positioning systems ; GPS ; Health facilities ; Health services ; Hemorrhagic Fever, Ebola - epidemiology ; Households ; Humans ; Liberia - epidemiology ; Management ; Maternal Health Services - statistics &amp; numerical data ; Maternal Health Services - supply &amp; distribution ; Medical care ; Medicine and Health Sciences ; People and Places ; Population ; Pregnancy ; Research and Analysis Methods ; Rural Health Services - statistics &amp; numerical data ; Rural Health Services - supply &amp; distribution ; Studies ; Surveys ; Surveys and Questionnaires ; Wellness programs ; Womens health ; Young Adult</subject><ispartof>PLoS medicine, 2016-08, Vol.13 (8), p.e1002096-e1002096</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Ly J, Sathananthan V, Griffiths T, Kanjee Z, Kenny A, Gordon N, et al. (2016) Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey. PLoS Med 13(8): e1002096. doi:10.1371/journal.pmed.1002096</rights><rights>2016 Ly et al 2016 Ly et al</rights><rights>2016 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Ly J, Sathananthan V, Griffiths T, Kanjee Z, Kenny A, Gordon N, et al. (2016) Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey. 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While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data. We conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias. We detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may under-approximate the effect seen in the most heavily affected areas. These are the first population-based survey data to show collateral disruptions to facility-based delivery caused by the West African EVD epidemic, and they reinforce the need to consider the full spectrum of implications caused by public health emergencies.</description><subject>Adult</subject><subject>Births</subject><subject>Care and treatment</subject><subject>Cluster Analysis</subject><subject>Community</subject><subject>Confidence intervals</subject><subject>Datasets</subject><subject>Delivery, Obstetric - statistics &amp; numerical data</subject><subject>Ebola hemorrhagic fever</subject><subject>Ebola virus</subject><subject>Ebolavirus</subject><subject>Epidemics</subject><subject>Family Characteristics</subject><subject>Female</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Health facilities</subject><subject>Health services</subject><subject>Hemorrhagic Fever, Ebola - epidemiology</subject><subject>Households</subject><subject>Humans</subject><subject>Liberia - epidemiology</subject><subject>Management</subject><subject>Maternal Health Services - statistics &amp; numerical data</subject><subject>Maternal Health Services - supply &amp; distribution</subject><subject>Medical care</subject><subject>Medicine and Health Sciences</subject><subject>People and Places</subject><subject>Population</subject><subject>Pregnancy</subject><subject>Research and Analysis Methods</subject><subject>Rural Health Services - statistics &amp; numerical data</subject><subject>Rural Health Services - supply &amp; distribution</subject><subject>Studies</subject><subject>Surveys</subject><subject>Surveys and Questionnaires</subject><subject>Wellness programs</subject><subject>Womens health</subject><subject>Young Adult</subject><issn>1549-1676</issn><issn>1549-1277</issn><issn>1549-1676</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqVk9Fu0zAUhiMEYmPwBggsTUIgkWI7ThxzgTS6jk2aGFrRbi0nPmk9uXGxk4q-Bw-Mu2XTinoxlIsk9nd-27__kySvCR6RjJNP1673rbKj5QL0iGBMsSieJPskZyIlBS-ePvjeS16EcB0ZgQV-nuxRzkrKcbGf_DlRtbGmW6dfVQCNjsGaFfg10r037Qx1c0CTylmFrozvAzo2ASKIJkujYWFqZFp02Xtl0bmpwBv1GR3FXa2DCajxboEUGnsXQjqFujMuTn1EP9yyt2rzNyx66voAc2c1mvZ-BeuXybNG2QCvhvdBMj2Z_ByfpucX387GR-dpzQXvUlKVJehK00rRohS0EVpDyUhGNMlrXDHOc1JxhWtNtRacFZxlqiyzTGiqsoPk7a3q0rogBzuDJCXFtCwIziJxdktop67l0puF8mvplJE3A87PpPKdqS1IQSnWjDJcCcJIoytcQkHrChpgRZ7rqPVlWK2v4o3V0HbRtS3R7ZnWzOXMrSQTHJekiALvBwHvfvUQOrkwoQZrVQvRv7hvIkhW8pw-Ao0xiAmgOKKH_6C7jRiomYpnNW3j4hbrjag8YlxEywXJI5XuoGbQQjyPa6ExcXiLH-3g43OTrJ0FH7YKItPB726m-hDk2fTyP9jvj2cvrrbZdw_YOSjbzYOz_SbOYRtkt2C9yb-H5v6uCZabDr5zWm46WA4dHMvePMzJfdFdy2Z_AX0uP34</recordid><startdate>20160802</startdate><enddate>20160802</enddate><creator>Ly, John</creator><creator>Sathananthan, Vidiya</creator><creator>Griffiths, Thomas</creator><creator>Kanjee, Zahir</creator><creator>Kenny, Avi</creator><creator>Gordon, Nicholas</creator><creator>Basu, Gaurab</creator><creator>Battistoli, Dale</creator><creator>Dorr, Lorenzo</creator><creator>Lorenzen, Breeanna</creator><creator>Thomson, Dana R</creator><creator>Waters, Ami</creator><creator>Moore, Uriah G</creator><creator>Roberts, Ruth</creator><creator>Smith, Wilmot L</creator><creator>Siedner, Mark J</creator><creator>Kraemer, John D</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>7T2</scope><scope>7U2</scope><scope>7U9</scope><scope>C1K</scope><scope>H94</scope><scope>5PM</scope><scope>DOA</scope><scope>CZK</scope><orcidid>https://orcid.org/0000-0002-9822-8796</orcidid><orcidid>https://orcid.org/0000-0003-3506-842X</orcidid><orcidid>https://orcid.org/0000-0002-9570-3168</orcidid><orcidid>https://orcid.org/0000-0002-7531-4886</orcidid><orcidid>https://orcid.org/0000-0002-9465-7307</orcidid></search><sort><creationdate>20160802</creationdate><title>Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey</title><author>Ly, John ; Sathananthan, Vidiya ; Griffiths, Thomas ; Kanjee, Zahir ; Kenny, Avi ; Gordon, Nicholas ; Basu, Gaurab ; Battistoli, Dale ; Dorr, Lorenzo ; Lorenzen, Breeanna ; Thomson, Dana R ; Waters, Ami ; Moore, Uriah G ; Roberts, Ruth ; Smith, Wilmot L ; Siedner, Mark J ; Kraemer, John D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c797t-1b88edbd2ba26892f9dde84131d15c0b47751b7a0cd2dd9746743a88339d2a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Adult</topic><topic>Births</topic><topic>Care and treatment</topic><topic>Cluster Analysis</topic><topic>Community</topic><topic>Confidence intervals</topic><topic>Datasets</topic><topic>Delivery, Obstetric - statistics &amp; numerical data</topic><topic>Ebola hemorrhagic fever</topic><topic>Ebola virus</topic><topic>Ebolavirus</topic><topic>Epidemics</topic><topic>Family Characteristics</topic><topic>Female</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>Health facilities</topic><topic>Health services</topic><topic>Hemorrhagic Fever, Ebola - epidemiology</topic><topic>Households</topic><topic>Humans</topic><topic>Liberia - epidemiology</topic><topic>Management</topic><topic>Maternal Health Services - statistics &amp; numerical data</topic><topic>Maternal Health Services - supply &amp; distribution</topic><topic>Medical care</topic><topic>Medicine and Health Sciences</topic><topic>People and Places</topic><topic>Population</topic><topic>Pregnancy</topic><topic>Research and Analysis Methods</topic><topic>Rural Health Services - statistics &amp; numerical data</topic><topic>Rural Health Services - supply &amp; distribution</topic><topic>Studies</topic><topic>Surveys</topic><topic>Surveys and Questionnaires</topic><topic>Wellness programs</topic><topic>Womens health</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ly, John</creatorcontrib><creatorcontrib>Sathananthan, Vidiya</creatorcontrib><creatorcontrib>Griffiths, Thomas</creatorcontrib><creatorcontrib>Kanjee, Zahir</creatorcontrib><creatorcontrib>Kenny, Avi</creatorcontrib><creatorcontrib>Gordon, Nicholas</creatorcontrib><creatorcontrib>Basu, Gaurab</creatorcontrib><creatorcontrib>Battistoli, Dale</creatorcontrib><creatorcontrib>Dorr, Lorenzo</creatorcontrib><creatorcontrib>Lorenzen, Breeanna</creatorcontrib><creatorcontrib>Thomson, Dana R</creatorcontrib><creatorcontrib>Waters, Ami</creatorcontrib><creatorcontrib>Moore, Uriah G</creatorcontrib><creatorcontrib>Roberts, Ruth</creatorcontrib><creatorcontrib>Smith, Wilmot L</creatorcontrib><creatorcontrib>Siedner, Mark J</creatorcontrib><creatorcontrib>Kraemer, John D</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints In Context</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health &amp; Medical Collection (Proquest)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Safety Science and Risk</collection><collection>Virology and AIDS Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals (DOAJ)</collection><collection>PLoS Medicine</collection><jtitle>PLoS medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ly, John</au><au>Sathananthan, Vidiya</au><au>Griffiths, Thomas</au><au>Kanjee, Zahir</au><au>Kenny, Avi</au><au>Gordon, Nicholas</au><au>Basu, Gaurab</au><au>Battistoli, Dale</au><au>Dorr, Lorenzo</au><au>Lorenzen, Breeanna</au><au>Thomson, Dana R</au><au>Waters, Ami</au><au>Moore, Uriah G</au><au>Roberts, Ruth</au><au>Smith, Wilmot L</au><au>Siedner, Mark J</au><au>Kraemer, John D</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey</atitle><jtitle>PLoS medicine</jtitle><addtitle>PLoS Med</addtitle><date>2016-08-02</date><risdate>2016</risdate><volume>13</volume><issue>8</issue><spage>e1002096</spage><epage>e1002096</epage><pages>e1002096-e1002096</pages><issn>1549-1676</issn><issn>1549-1277</issn><eissn>1549-1676</eissn><abstract>The Ebola virus disease (EVD) epidemic has threatened access to basic health services through facility closures, resource diversion, and decreased demand due to community fear and distrust. While modeling studies have attempted to estimate the impact of these disruptions, no studies have yet utilized population-based survey data. We conducted a two-stage, cluster-sample household survey in Rivercess County, Liberia, in March-April 2015, which included a maternal and reproductive health module. We constructed a retrospective cohort of births beginning 4 y before the first day of survey administration (beginning March 24, 2011). We then fit logistic regression models to estimate associations between our primary outcome, facility-based delivery (FBD), and time period, defined as the pre-EVD period (March 24, 2011-June 14, 2014) or EVD period (June 15, 2014-April 13, 2015). We fit both univariable and multivariable models, adjusted for known predictors of facility delivery, accounting for clustering using linearized standard errors. To strengthen causal inference, we also conducted stratified analyses to assess changes in FBD by whether respondents believed that health facility attendance was an EVD risk factor. A total of 1,298 women from 941 households completed the survey. Median age at the time of survey was 29 y, and over 80% had a primary education or less. There were 686 births reported in the pre-EVD period and 212 in the EVD period. The unadjusted odds ratio of facility-based delivery in the EVD period was 0.66 (95% confidence interval [CI] 0.48-0.90, p-value = 0.010). Adjustment for potential confounders did not change the observed association, either in the principal model (adjusted odds ratio [AOR] = 0.70, 95%CI 0.50-0.98, p = 0.037) or a fully adjusted model (AOR = 0.69, 95%CI 0.50-0.97, p = 0.033). The association was robust in sensitivity analyses. The reduction in FBD during the EVD period was observed among those reporting a belief that health facilities are or may be a source of Ebola transmission (AOR = 0.59, 95%CI 0.36-0.97, p = 0.038), but not those without such a belief (AOR = 0.90, 95%CI 0.59-1.37, p = 0.612). Limitations include the possibility of FBD secular trends coincident with the EVD period, recall errors, and social desirability bias. We detected a 30% decreased odds of FBD after the start of EVD in a rural Liberian county with relatively few cases. Because health facilities never closed in Rivercess County, this estimate may under-approximate the effect seen in the most heavily affected areas. These are the first population-based survey data to show collateral disruptions to facility-based delivery caused by the West African EVD epidemic, and they reinforce the need to consider the full spectrum of implications caused by public health emergencies.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27482706</pmid><doi>10.1371/journal.pmed.1002096</doi><orcidid>https://orcid.org/0000-0002-9822-8796</orcidid><orcidid>https://orcid.org/0000-0003-3506-842X</orcidid><orcidid>https://orcid.org/0000-0002-9570-3168</orcidid><orcidid>https://orcid.org/0000-0002-7531-4886</orcidid><orcidid>https://orcid.org/0000-0002-9465-7307</orcidid><oa>free_for_read</oa></addata></record>
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subjects Adult
Births
Care and treatment
Cluster Analysis
Community
Confidence intervals
Datasets
Delivery, Obstetric - statistics & numerical data
Ebola hemorrhagic fever
Ebola virus
Ebolavirus
Epidemics
Family Characteristics
Female
Global positioning systems
GPS
Health facilities
Health services
Hemorrhagic Fever, Ebola - epidemiology
Households
Humans
Liberia - epidemiology
Management
Maternal Health Services - statistics & numerical data
Maternal Health Services - supply & distribution
Medical care
Medicine and Health Sciences
People and Places
Population
Pregnancy
Research and Analysis Methods
Rural Health Services - statistics & numerical data
Rural Health Services - supply & distribution
Studies
Surveys
Surveys and Questionnaires
Wellness programs
Womens health
Young Adult
title Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey
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