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ABSTRACT
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.
Paper Context
Main findings: For humanitarian organizations it is imperative to document the methodological limitations of cluster surveys and discuss the utility.
Added knowledge: This paper adds new knowledge on cluster surveys for highly clustered data such us in Ebola virus disease.
Global health impact of policy and action: We provided empirical estimates and discuss design improvements to inform future study.
Responsible Editor Stig Wall
Responsible Editor Stig Wall
Acknowledgments
This work is based on Dr Grazia Caleo’s thesis from the London School of Hygiene and Tropical Medicine, which is available informally online, but has not been traditionally published anywhere else.
We thank the households who contributed and participated in this study. We also extend our thanks to Rob Broeder for his contributions to the preparation of the study.
Author contributions
GC, KL, JG, conceived the idea, KK, JB and GC implemented the study, GC wrote the first and late draft. GC, FG, GDT and HAW contributed to the analysis. HAW, KL, KD and AS reviewed early drafts. All authors contributed to later drafts and approved the final submission.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Ethics and consent
The study protocol was approved by the Ethics Review Board of MSF, the Internal Review Board of the Sierra Leone MoHS, and the London School of Hygiene & Tropical Medicine (LSHTM). Approval to conduct the study was obtained from traditional authorities in all study sites prior to data collection. Participation was voluntary. Verbal informed consent for participation was obtained from the head of each household after a briefing about the aim of the study, the questions, survey and how their answers would be recorded, stored and used, duration of the questionnaire, and the option to end the interview or withdraw from the research at any time if wished. Confidentiality was protected during data collection and analysis. No personal identifying information was collected.
Data availability statement
Data are available under the MSF data sharing policy. Requests to access data can be made to [email protected].