Improving retrospective data on recent household deaths: a multi-arm randomized trial in Guinea-Bissau

Abstract

Background: In countries with limited civil registration and vital statistics systems, assessing the impact of health crises requires precise retrospective mortality data. We tested whether calendar methods improve survey or census data on dates of recent household deaths registered in a Health and Demographic Surveillance System (HDSS).

Methods: Between April and June 2023, we randomized 578 households with HDSS-registered deaths in Guinea-Bissau to interviews by using (i) a standard questionnaire with close-ended questions about dates of deaths, or similar questionnaires supplemented with (ii) a physical calendar of local events printed on paper or (iii) a digital calendar implemented on tablets. We evaluated the accuracy of reported dates through record linkages to HDSS data.

Results: No deaths were reported in 11.8% of the 508 participating households. In other households (n = 448), informants reported 574 deaths since January 2020. Relative to the standard questionnaire, neither the physical calendar nor the digital calendar improved the proportion of deaths reported in the same month and year as recorded by using surveillance data. The physical and digital calendars reduced the share of missing data on dates of deaths (6.1% and 3.2%, respectively, versus 13.1% with the standard questionnaire). Reported dates of deaths obtained by using the digital calendar were more weakly correlated with surveillance data than those collected in other arms. Using the digital calendar also added 1.15 minutes to the data collection.

Conclusion: Digital calendars do not improve the reporting of dates of deaths in surveys or censuses. Further trials of the use of a physical calendar in retrospective interviews about recent household deaths are warranted.

Keywords: Bandim Health Project; Guinea-Bissau; civil registration and vital statistics; data quality; low- and lower-middle-income countries; mortality; randomized trial; recall; survey.

Figure 1.

Map of Guinea-Bissau and the study area. Source: DIVA-GIS (2023) for shape files.

Figure 2.

Distribution of household deaths reported in the trial, by study arm. Note: χ² test P-values for pairwise comparison between the control arm (Standard questionnaire) and each experimental arm (Physical calendar; Digital calendar).

Figure 3.

Share of linked deaths reported to have occurred in the same month and year as in the Bandim Health Project Health and Demographic Surveillance System (HDSS). Note: Vertical black lines represent 95% confidence intervals estimated from logistic models controlling for stratification variables. P-values are from the same models comparing the control arm (Standard questionnaire) and each experimental arm (Physical calendar; Digital calendar).

Figure 4.

Share of missing data on dates of death components, by study arm. Notes: The survey sample includes only deaths that were ascertained as having occurred from January 2020 onwards (n =574). Vertical black lines represent 95% confidence intervals estimated from logistic models controlling for stratification variables. P-values are from the same models comparing the control arm (Standard questionnaire) and each experimental arm (Physical calendar; Digital calendar).

Figure 5.

Absolute difference in months between Bandim Health Project Health and Demographic Surveillance System (HDSS) and trial-reported dates of death, by study arm. The graph excludes three observations (two in the Digital calendar and one in the Physical calendar) with month differences exceeding 40 months for visualization purposes.

Figure 6.

Number of deaths with complete dates reported in each study arm and the Bandim Health Project Health and Demographic Surveillance System (HDSS).

Figure 7.

Interview duration by study arm and number of reported deaths since January 2020.