Journal Article > ResearchFull Text
Glob Health Action. 25 April 2024; Volume 17 (Issue 1); 2331291.; DOI:10.1080/16549716.2024.2331291
Caleo G, Lokuge K, Kardamanidis K, Greig J, Belava J, et al.
Glob Health Action. 25 April 2024; Volume 17 (Issue 1); 2331291.; DOI:10.1080/16549716.2024.2331291
BACKGROUND
There is a lack of empirical data on design effects (DEFF) for mortality rate for highly clustered data such as with Ebola virus disease (EVD), along with a lack of documentation of methodological limitations and operational utility of mortality estimated from cluster-sampled studies when the DEFF is high.
OBJECTIVES
The objectives of this paper are to report EVD mortality rate and DEFF estimates, and discuss the methodological limitations of cluster surveys when data are highly clustered such as during an EVD outbreak.
METHODS
We analysed the outputs of two independent population-based surveys conducted at the end of the 2014-2016 EVD outbreak in Bo District, Sierra Leone, in urban and rural areas. In each area, 35 clusters of 14 households were selected with probability proportional to population size. We collected information on morbidity, mortality and changes in household composition during the recall period (May 2014 to April 2015). Rates were calculated for all-cause, all-age, under-5 and EVD-specific mortality, respectively, by areas and overall. Crude and adjusted mortality rates were estimated using Poisson regression, accounting for the surveys sample weights and the clustered design.
RESULTS
Overall 980 households and 6,522 individuals participated in both surveys. A total of 64 deaths were reported, of which 20 were attributed to EVD. The crude and EVD-specific mortality rates were 0.35/10,000 person-days (95%CI: 0.23-0.52) and 0.12/10,000 person-days (95%CI: 0.05-0.32), respectively. The DEFF for EVD mortality was 5.53, and for non-EVD mortality, it was 1.53. DEFF for EVD-specific mortality was 6.18 in the rural area and 0.58 in the urban area. DEFF for non-EVD-specific mortality was 1.87 in the rural area and 0.44 in the urban area.
CONCLUSION
Our findings demonstrate a high degree of clustering; this contributed to imprecise mortality estimates, which have limited utility when assessing the impact of disease. We provide DEFF estimates that can inform future cluster surveys and discuss design improvements to mitigate the limitations of surveys for highly clustered data.
There is a lack of empirical data on design effects (DEFF) for mortality rate for highly clustered data such as with Ebola virus disease (EVD), along with a lack of documentation of methodological limitations and operational utility of mortality estimated from cluster-sampled studies when the DEFF is high.
OBJECTIVES
The objectives of this paper are to report EVD mortality rate and DEFF estimates, and discuss the methodological limitations of cluster surveys when data are highly clustered such as during an EVD outbreak.
METHODS
We analysed the outputs of two independent population-based surveys conducted at the end of the 2014-2016 EVD outbreak in Bo District, Sierra Leone, in urban and rural areas. In each area, 35 clusters of 14 households were selected with probability proportional to population size. We collected information on morbidity, mortality and changes in household composition during the recall period (May 2014 to April 2015). Rates were calculated for all-cause, all-age, under-5 and EVD-specific mortality, respectively, by areas and overall. Crude and adjusted mortality rates were estimated using Poisson regression, accounting for the surveys sample weights and the clustered design.
RESULTS
Overall 980 households and 6,522 individuals participated in both surveys. A total of 64 deaths were reported, of which 20 were attributed to EVD. The crude and EVD-specific mortality rates were 0.35/10,000 person-days (95%CI: 0.23-0.52) and 0.12/10,000 person-days (95%CI: 0.05-0.32), respectively. The DEFF for EVD mortality was 5.53, and for non-EVD mortality, it was 1.53. DEFF for EVD-specific mortality was 6.18 in the rural area and 0.58 in the urban area. DEFF for non-EVD-specific mortality was 1.87 in the rural area and 0.44 in the urban area.
CONCLUSION
Our findings demonstrate a high degree of clustering; this contributed to imprecise mortality estimates, which have limited utility when assessing the impact of disease. We provide DEFF estimates that can inform future cluster surveys and discuss design improvements to mitigate the limitations of surveys for highly clustered data.
Journal Article > Case Report/SeriesFull Text
Am J Trop Med Hyg. 10 November 2015; Volume 94 (Issue 2); 417-9.; DOI:10.4269/ajtmh.15-0619
Bower H, Grass JE, Veltus E, Brault AC, Campbell S, et al.
Am J Trop Med Hyg. 10 November 2015; Volume 94 (Issue 2); 417-9.; DOI:10.4269/ajtmh.15-0619
We report the case of an Ebola virus (EBOV) RNA-negative pregnant woman who delivered an EBOV RNA-positive stillborn infant at a community health center in rural Sierra Leone, 1 month after the mother's last possible exposure. The mother was later found to be immunoglobulins M and G positive indicating previous infection. The apparent absence of Ebola symptoms and not recognizing that the woman had previous contact with an Ebola patient led health workers performing the delivery to wear only minimal personal protection, potentially exposing them to a high risk of EBOV infection. This case emphasizes the importance of screening for epidemiological risk factors as well as classic and atypical symptoms of Ebola when caring for pregnant women, even once they have passed the typical time frame for exposure and incubation expected in nonpregnant adults. It also illustrates the need for health-care workers to use appropriate personal protection equipment when caring for pregnant women in an Ebola setting.
Protocol > Research Protocol
Caleo GNC, Kardamanidis K, Broeder R, Belava J, Kremer R, et al.
1 July 2018
2. Objectives
2.1. Primary objectives
The Primary objective of the survey is to:
Estimate mortality in a sample of the population in the urban and rural area of Bo District from the approximate start of the Ebola outbreak in Sierra Leone (mid May 2014) until the day of the survey.
2.2. Secondary objectives
Estimate overall and cause-specific mortality (EVD and non-EVD) in children under the age of 5 years, and the population aged 5 years and older within the study area, with particular attention to the period prior to the MSF Ebola Management Centre (EMC) opening in Bo district (19 September 2014) and the period during which it was receiving cases from the district (last confirmed case exited 26 January 2015);
Estimate overall and cause-specific mortality (EVD and non-EVD) in quarantined and non-quarantined households; and contact-traced and non-contact-traced households;
Describe health seeking behaviour in terms of whether health care was sought, where health care was sought and whether access to health care was possible.
2.1. Primary objectives
The Primary objective of the survey is to:
Estimate mortality in a sample of the population in the urban and rural area of Bo District from the approximate start of the Ebola outbreak in Sierra Leone (mid May 2014) until the day of the survey.
2.2. Secondary objectives
Estimate overall and cause-specific mortality (EVD and non-EVD) in children under the age of 5 years, and the population aged 5 years and older within the study area, with particular attention to the period prior to the MSF Ebola Management Centre (EMC) opening in Bo district (19 September 2014) and the period during which it was receiving cases from the district (last confirmed case exited 26 January 2015);
Estimate overall and cause-specific mortality (EVD and non-EVD) in quarantined and non-quarantined households; and contact-traced and non-contact-traced households;
Describe health seeking behaviour in terms of whether health care was sought, where health care was sought and whether access to health care was possible.
Journal Article > ResearchFull Text
Emerg Infect Dis. 1 February 2016; Volume 22 (Issue 2); 217-23.; DOI:10.3201/eid2202.151250
Crowe SJ, Maenner MJ, Kuah S, Erickson BR, Coffee M, et al.
Emerg Infect Dis. 1 February 2016; Volume 22 (Issue 2); 217-23.; DOI:10.3201/eid2202.151250
To determine whether 2 readily available indicators predicted survival among patients with Ebola virus disease in Sierra Leone, we evaluated information for 216 of the 227 patients in Bo District during a 4-month period. The indicators were time from symptom onset to healthcare facility admission and quantitative real-time reverse transcription PCR cycle threshold (Ct), a surrogate for viral load, in first Ebola virus-positive blood sample tested. Of these patients, 151 were alive when detected and had reported healthcare facility admission dates and Ct values available. Time from symptom onset to healthcare facility admission was not associated with survival, but viral load in the first Ebola virus-positive blood sample was inversely associated with survival: 52 (87%) of 60 patients with a Ct of >24 survived and 20 (22%) of 91 with a Ct of <24 survived. Ct values may be useful for clinicians making treatment decisions or managing patient or family expectations.