Stillbirth and early neonatal mortality rates may be underestimated using recall information: A comparison of demographic surveillance methodologies

OBJECTIVE

Child mortality and stillbirth rates (SBR) remain high in low-income countries but may be underestimated due to incomplete reporting of child deaths in retrospective pregnancy/birth histories. The aim of this study is to compare stillbirth and mortality estimates derived using two different methods: the method assuming full information and the prospective method.

METHODS

Bandim Health Project's Health and Demographic Surveillance Systems (HDSS) follows women of reproductive age and children under five through routine home visits every 1, 2 or 6 months. Between 2012 and 2020, we estimated and compared early neonatal (ENMR, <7 days), neonatal (NMR, <28 days), and infant mortality (IMR, <1 year) per 1000 live births and SBR per 1000 births. Risk time for children born to registered women was calculated from birth (the method assuming full information) versus date of first observation in the HDSS (the prospective method), either at birth (for pregnancy registration) or registration. Rates were calculated using the Kaplan-Meier estimator and compared in generalised linear models allowing for within-child correlation obtaining relative risks (RR).

RESULTS

We registered and followed 29,413 infants (1380 deaths; 1459 stillbirths) prospectively. An additional 164 infant deaths and 129 stillbirths were registered retrospectively and included in the method assuming full information. The ENMR was 24.5 (95%CI: 22.6-26.4) for the method assuming full information and 25.8 (23.7-27.8) for the prospective method, RR = 0.96 (0.93-0.99). Differences were smaller for the NMRs and IMRs. For SBRs, the estimates were 53.5 (50.9-56.0) and 58.6 (55.7-61.5); RR = 0.91 (0.90-0.93). The difference between methods became more pronounced when the analysis was limited to areas visited every 6 months: RR for ENMR: 0.91 (0.86-0.96) and RR for SBR: 0.85 (0.83-0.87).

CONCLUSIONS

Assuming full information underestimates SBR and ENMR. Accounting for omissions of stillbirths and early neonatal deaths may lead to more accurate estimates and improved ability to monitor mortality.

Local mortality impacts due to future air pollution under climate change scenarios

The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM_2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM_2.5 levels. PM_2.5 levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM_2.5 linking local population and mortality data with PM_2.5-mortality relationships from the literature, and incorporating population projections under the SSPs. PM_2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM_2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM_2.5 attributable burdens mid-century. Our analysis of local PM_2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM_2.5 mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.

Measuring population health: costs of alternative survey approaches in the Nouna Health and Demographic Surveillance System in rural Burkina Faso

BACKGROUND

There are more than 40 Health and Demographic Surveillance System (HDSS) sites in 19 different countries. The running costs of HDSS sites are high. The financing of HDSS activities is of major importance, and adding external health surveys to the HDSS is challenging. To investigate the ways of improving data quality and collection efficiency in the Nouna HDSS in Burkina Faso, the stand-alone data collection activities of the HDSS and the Household Morbidity Survey (HMS) were integrated, and the paper-based questionnaires were consolidated into a single tablet-based questionnaire, the Comprehensive Disease Assessment (CDA).

OBJECTIVE

The aims of this study are to estimate and compare the implementation costs of the two different survey approaches for measuring population health.

DESIGN

All financial costs of stand-alone (HDSS and HMS) and integrated (CDA) surveys were estimated from the perspective of the implementing agency. Fixed and variable costs of survey implementation and key cost drivers were identified. The costs per household visit were calculated for both survey approaches.

RESULTS

While fixed costs of survey implementation were similar for the two survey approaches, there were considerable variations in variable costs, resulting in an estimated annual cost saving of about US$45,000 under the integrated survey approach. This was primarily because the costs of data management for the tablet-based CDA survey were considerably lower than for the paper-based stand-alone surveys. The cost per household visit from the integrated survey approach was US$21 compared with US$25 from the stand-alone surveys for collecting the same amount of information from 10,000 HDSS households.

CONCLUSIONS

The CDA tablet-based survey method appears to be feasible and efficient for collecting health and demographic data in the Nouna HDSS in rural Burkina Faso. The possibility of using the tablet-based data collection platform to improve the quality of population health data requires further exploration.

Monitoring the millennium development goals: the potential role of the INDEPTH Network

The Millennium Declaration, adopted by the United Nations (UN) in 2000, set a series of Millennium Development Goals (MDGs) as priorities for UN member countries, committing governments to realising eight major MDGs and 18 associated targets by 2015. Progress towards these goals is being assessed by tracking a series of 48 technical indicators that have since been unanimously adopted by experts. This concept paper outlines the role member Health and Demographic Surveillance Systems (HDSSs) of the INDEPTH Network could play in monitoring progress towards achieving the MDGs. The unique qualities of the data generated by HDSSs lie in the fact that they provide an opportunity to measure or evaluate interventions longitudinally, through the long-term follow-up of defined populations.

First experiences in the implementation of biometric technology to link data from Health and Demographic Surveillance Systems with health facility data

Background

In developing countries, Health and Demographic Surveillance Systems (HDSSs) provide a framework for tracking demographic and health dynamics over time in a defined geographical area. Many HDSSs co-exist with facility-based data sources in the form of Health Management Information Systems (HMIS). Integrating both data sources through reliable record linkage could provide both numerator and denominator populations to estimate disease prevalence and incidence rates in the population and enable determination of accurate health service coverage.

Objective

To measure the acceptability and performance of fingerprint biometrics to identify individuals in demographic surveillance populations and those attending health care facilities serving the surveillance populations.

Methodology

Two HDSS sites used fingerprint biometrics for patient and/or surveillance population participant identification. The proportion of individuals for whom a fingerprint could be successfully enrolled were characterised in terms of age and sex.

Results

Adult (18–65 years) fingerprint enrolment rates varied between 94.1% (95% CI 93.6–94.5) for facility-based fingerprint data collection at the Africa Centre site to 96.7% (95% CI 95.9–97.6) for population-based fingerprint data collection at the Agincourt site. Fingerprint enrolment rates in children under 1 year old (Africa Centre site) were only 55.1% (95% CI 52.7–57.4). By age 5, child fingerprint enrolment rates were comparable to those of adults.

Conclusion

This work demonstrates the feasibility of fingerprint-based individual identification for population-based research in developing countries. Record linkage between demographic surveillance population databases and health care facility data based on biometric identification systems would allow for a more comprehensive evaluation of population health, including the ability to study health service utilisation from a population perspective, rather than the more restrictive health service perspective.