The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Breeanna Lorenzen - One of the best experts on this subject based on the ideXlab platform.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: John Ly, Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
Gaurab Basu - One of the best experts on this subject based on the ideXlab platform.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: John Ly, Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
Eric F Lambin - One of the best experts on this subject based on the ideXlab platform.
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impact of macroeconomic change on deforestation in south cameroon integration of Household Survey and remotely sensed data
2001Co-Authors: Benoit Mertens, William D Sunderlin, Ousseynou Ndoye, Eric F LambinAbstract:The integration of information from Household Surveys and data on land-cover changes derived from remote sensing improves our understanding of the causes and processes of land-use/land-cover changes. A Household Survey covering 552 Households in 33 villages was carried out in the East Province of Cameroon. This Survey focused on land-use changes since the 1970s. Those data were related to time series of remote sensing satellite data. A major interest of the field data lies in the longitudinal framework of the Survey. It highlighted the evolution of the Household and its land-use over three periods related to the key macroeconomic periods, and corresponding to the dates of acquisition of the remote sensing data. The research results demonstrate that macroeconomic changes affecting Cameroon have played a fundamental role in the way land-use practices influence the forest cover. The results show that the annual rate of deforestation increased after the economic crisis as compared to the previous period. The Household Survey information enables identification of the causal relationships and the processes of land-use and land-cover changes. Observations reveal that the beginning of the economic crisis (1986) is associated in time with a strong increase of the deforestation rate related to population growth, increased marketing of food crops, modification of farming systems, and colonization of new agricultural areas in remote forest zones.
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impact of macroeconomic change on deforestation in south cameroon integration of Household Survey and remotely sensed data
World Development, 2000Co-Authors: Benoit Mertens, William D Sunderlin, Ousseynou Ndoye, Eric F LambinAbstract:Integration of information from Household Surveys and data on land-cover changes derived from remote sensing helps to understand the causes and processes of land-use/land-cover changes. A Household Survey covering 552 Households in 33 villages was carried out in the East Province of Cameroon. This Survey focused on land-use changes since the 1970s. Data were related to time series of remote sensing satellite data. A major interest of the filed data lies in the longitudinal framework of Survey. It highlighted the evolution of the Household and its land-use over three periods related to the key of macroeconomic periods, and corresponding to the dates of acquisition of the remote sensing data. The research results demonstrate that macroeconomic changes affecting Cameroon have played a fundamental role in the way land-use practices influence the forest cover. The results show that the annual rate of deforestation increased after the economic crisis as compared to the previous period. The Household Survey information enables identification of the casual relationships and the processes of land-use and land-cover changes. Observations reveal that the beginning of the economic crisis (1986) is associated in time with a strong increase of the deforestation rate related to population growth, increased marketing of food crops, modification of farming systems, and colonisation of new agricultural areas in remote forest zones.
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impact of macroeconomic change on deforestation in south cameroon integration of Household Survey and remotely sensed data
World Development, 2000Co-Authors: Benoit Mertens, William D Sunderlin, Ousseynou Ndoye, Eric F LambinAbstract:Summary. — The integration of information from Household Surveys and data on land-cover changes derived from remote sensing improves our understanding of the causes and processes of land-use/land-cover changes. A Household Survey covering 552 Households in 33 villages was carried out in the East Province of Cameroon. This Survey focused on land-use changes since the 1970s. Those data were related to time series of remote sensing satellite data. A major interest of the field data lies in the longitudinal framework of the Survey. It highlighted the evolution of the Household and its land-use over three periods related to the key macroeconomic periods, and corresponding to the dates of acquisition of the remote sensing data. The research results demonstrate that macroeconomic changes aAecting Cameroon have played a fundamental role in the way land-use practices influence the forest cover. The results show that the annual rate of deforestation increased after the economic crisis as compared to the previous period. The Household Survey information enables identification of the causal relationships and the processes of land-use and land-cover changes. Observations reveal that the beginning of the economic crisis (1986) is associated in time with a strong increase of the deforestation rate related to population growth, increased marketing of food crops, modification of farming systems, and colonization of new agricultural areas in remote forest zones. ” 2000 Elsevier Science Ltd. All rights reserved.
Vidiya Sathananthan - One of the best experts on this subject based on the ideXlab platform.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: John Ly, Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
Zahir Kanjee - One of the best experts on this subject based on the ideXlab platform.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
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facility based delivery during the ebola virus disease epidemic in rural liberia analysis from a cross sectional population based Household Survey
PLOS Medicine, 2016Co-Authors: John Ly, Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna LorenzenAbstract:BACKGROUND: 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. METHODS AND FINDINGS: 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. CONCLUSIONS: 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.
