Background In The Gambia, national estimates of under-five mortality (U5M) were from censuses and multiple indicator cluster surveys (MICS). The country’s first demographic and health survey (DHS) conducted in 2013 provided empirical disaggregated national estimates of neonatal, post-neonatal and child mortality trends. Objective To assess the consistency and accuracy of the estimates of U5M from the existing data sources and its age-specific components in rural Gambia and produce reliable up-to-date estimates. Methods Available national data on under-five mortality from 2000 onwards were extracted. Additionally, data from two DHS regions were compared to those from two health and demographic surveillance systems (HDSS) located within them. Indirect and direct estimates from the data were compared and flexible parametric survival methods used to predict mortality rates for all empirical data points up to 2015. Findings Internal consistency checks on data quality for indirect estimation of U5M suggest that the data were plausible at national level once information from women aged 15–19 years was excluded. The DHS and HDSS data used to make direct U5M estimates were plausible, however HDSS data were of better quality. For 2009–2013, the DHS estimates agreed well with the 2013 census and 2010 MICS reports of U5M but was less accurate about the early births of older women. The most recent estimates from the 2013 DHS, which refer to 2011–12, are an U5M rate of 54/1000 livebirths (95% CI: 43–64) and a neonatal mortality rate of 21/1000 livebirths (95% CI: 15–27), contributing almost 40% of U5M in The Gambia. The DHS showed that for the decade prior to the survey, child mortality dropped by 55% and neonatal mortality by 31%. This indicates the importance of neonatal mortality in The Gambia, and the need to focus on neonatal survival, while maintaining currently successful strategies to further reduce U5M.

Objective To assess whether an adapted Demographic and Health Survey (DHS) like cross-sectional household survey with full pregnancy histories can demonstrate the validity of health and demographic surveillance (HDSS) data by producing similar population structural characteristics and childhood mortality indicators at two HDSS sites in The Gambia–Farafenni and Basse. Methods A DHS-type survey was conducted of 2,580 households in the Farafenni HDSS, and 2,907 in the Basse HDSS. Household members were listed and pregnancy histories obtained for all women aged 15–49. HDSS datasets were extracted for the same households including residency episodes for all current and former members and compared with the survey data. Neonatal (0–28 days), infant (<1 year), child (1–4 years) and under-5 (< 5 years) mortality rates were derived from each source by site and five-year periods from 2001–2015 and by calendar year between 2011 and 2015 using Kaplan–Meier failure probabilities. Survey-HDSS rate ratios were determined using the Mantel-Haenszel method. Results The selected households in Farafenni comprised a total population of 27,646 in the HDSS, compared to 26,109 captured in the household survey, implying higher coverage of 94.4% (95% CI: 94.1–94.7; p<0.0001) against a hypothesised proportion of 90% in the HDSS. All population subgroups were equally covered by the HDSS except for the Wollof ethnic group. In Basse, the total HDSS population was 49,287, compared to 43,538 enumerated in the survey, representing an undercount of the HDSS by the survey with a coverage of 88.3% (95% CI: 88.0–88.6; p = 1). All sub-population groups were also under-represented by the survey. Except for the neonatal mortality rate for Farafenni, the childhood mortality indicators derived from pregnancy histories and HDSS data compare reasonably well by 5-year periods from 2001–2015. Annual estimates from the two data sources for the most recent quinquennium, 2011–2015, were similar in both sites, except for an excessively high neonatal mortality rate for Farafenni in 2015. Conclusion Overall, the adapted DHS-type survey has reasonably represented the Farafenni HDSS database using population size and structure; and both databases using childhood mortality indicators. If the hypothetical proportion is lowered to 85%, the survey would adequately validate both HDSS databases in all considered aspects. The adapted DHS-type sample household survey therefore has potential for validation of HDSS data.

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Background A community’s cultural beliefs, attitudes and discourse can affect their responses in surveys. Knowledge of these cultural factors and how to comply with them or adjust for them during data collection can improve data quality. Objective This study describes implications of features of Gambian culture related to women’s reproductive health, and mortality, when collecting data in surveys. Methods 13 in-depth interviews of female interviewers and a focus group discussion among male interviewers were conducted in two rural health and demographic surveillance systems as well as three key informant interviews in three regions in The Gambia. Results From the fieldworker’s viewpoint, questions relating to reproduction were best asked by women as culturally pregnancies should be concealed, and menstruation is considered a sensitive topic. Gambians were reluctant to speak about decedents and the Fula did not like to be counted, potentially affecting estimation of mortality. Asking about siblings proved problematic among the Fula and Serahule communities. Proposals made to overcome these challenges were that culturally-appropriate metaphors and symbols should be used to discuss sensitive matters and to enumerating births/deaths singly instead of collecting summary totals, which had threatening connotations. This was as opposed to training interviewers to ask standardised and precise verbatim questions. Contribution This paper presents indigenous Gambian solutions by fieldworkers to culturally sensitive topics when collecting pregnancy outcomes and mortality data in demographic and health surveys. For researchers collecting maternal mortality data, it highlights the potential shortcomings of the sibling history methodology.