Pregnancy reporting and biases in under-five mortality in three African HDSSs

Health and Demographic Surveillance Systems (HDSS) are important sources of population health data in sub-Saharan Africa, but the recording of pregnancies, pregnancy outcomes, and early mortality is often incomplete. This study assessed HDSS pregnancy reporting completeness and identified predictors of unreported pregnancies that likely ended in adverse outcomes. The analysis utilized individually-linked HDSS and antenatal care (ANC) data from Siaya, Kenya for pregnancies in 2018-2020. We cross-checked ANC records with HDSS pregnancy registrations and outcomes. Pregnancies observed in the ANC that were missing reports in the HDSS despite a data collection round following the expected delivery date were identified as likely adverse outcomes, and we investigated the characteristics of such individuals. Clinical data were used to investigate the timing of HDSS pregnancy registration relative to care seeking and gestational age, and examine misclassification of miscarriages and stillbirths. From an analytical sample of 2,475 pregnancies observed in the ANC registers, 46% had pregnancy registrations in the HDSS, and 89% had retrospectively reported pregnancy outcomes. 1% of registered pregnancies were missing outcomes, compared to 10% of those lacking registration. Registered pregnancies had higher rates of stillbirth and perinatal mortality than those lacking registration. In 77% of cases, women accessed ANC prior to registering the pregnancy in the HDSS. Half of reported miscarriages were misclassified stillbirths. We identified 141 unreported pregnancies that likely ended in adverse outcomes. Such cases were more common among those who visited ANC clinics during the first trimester, made fewer overall visits, were HIV-positive, and outside of formal union. Record linkage with ANC clinics revealed pregnancy underreporting in HDSS, resulting in biased measurement of perinatal mortality. Integrating records of ANC usage into routine data collection can augment HDSS pregnancy surveillance and improve monitoring of adverse pregnancy outcomes and early mortality.

Background: Health and Demographic Surveillance Systems (HDSS) collect independent mortality data that could be used for assessing the quality of mortality data in national civil registration (CR) systems in low- and middle-income countries. However, the use of HDSS data for such purposes depends on the quality of record linkage between the two data sources. We describe and evaluate the quality of record linkage between HDSS and CR mortality data in South Africa with HDSS data from Agincourt HDSS. Methods: We applied deterministic and probabilistic record linkage approaches to mortality records from 2006 to 2009 from the Agincourt HDSS and those in the CR system. Quality of the matches generated by the probabilistic approach was evaluated using sensitivity and positive predictive value (PPV) calculated from a subset of records that were linked using national identity number. Matched and unmatched records from the Agincourt HDSS were compared to identify characteristics associated with successful matching. In addition, the distribution of background characteristics in all deaths that occurred in 2009 and those linked to CR records was compared to assess systematic bias in the resulting record-linked dataset in the latest time period. Results: Deterministic and probabilistic record linkage approaches combined linked a total of 2264 out of 3726 (60.8%) mortality records from the Agincourt HDSS to those in the CR system. Probabilistic approaches independently linked 1969 (87.0%) of the linked records. In a subset of 708 records that were linked using national identity number, the probabilistic approaches yielded sensitivity of 90.0% and PPV of 98.5%. Records belonging to more vulnerable people, including poorer persons, young children, and non-South Africans were less likely to be matched. Nevertheless, distribution of most background characteristics was similar between all Agincourt HDSS deaths and those matched to CR records in the latest time period. Conclusion: This study shows that record linkage of mortality data from HDSS and CR systems is possible and can be useful in South Africa. The study identifies predictors for death registration and data items and registration system characteristics that could be improved to achieve more optimal future matching possibilities.

Reliable civil registration and vital statistics (CRVSs) are essential for estimating mortality rates and population changes, and are critical for public health and socio-economic planning. CRVSs are largely incomplete in Africa, thus Health and Demographic Surveillance Systems (HDSSs) fill gaps in CRVSs, albeit existing HDSSs in South Africa are in rural areas. This limits the generalisability of such data in a country such as South Africa where over 60% live in urban areas, and where there are limitations to access health and social services. We describe the approaches, achievements, challenges and lessons learned in setting up a HDSS site in Soweto and Thembelihle (SaT-HDSS), Johannesburg; which is the first urban-based HDSS in Southern Africa. We also highlight a number of studies being implemented in the HDSS. In 2017–2020, the HDSS has enrolled 124,169 individuals and followed up 95% of this population through 3 rounds of data collection. Several challenges were encountered during the initiation of the HDSS, including difficulties in community mobilisation and entry, stakeholders’ engagement and participation, inaccessibility problems and concerns about safety of fieldworkers, and difficulty in getting/recruiting technical staff with requisite experience. Nevertheless, the SaT-HDSS was successfully established through application of several strategies, including continuous community engagement and stakeholders’ mobilisation; in-depth training and retraining of all study staff; technical support from well-established HDSS sites across Africa, and international academic collaborations. Despite the challenges of undertaking routine surveillance of a hard-to-reach and highly mobile population, the SaT-HDSS was successfully established with a high-retention rate. The HDSS offers an important lens on morbidity and mortality and serves as a platform for pilots of interventions and programmes aimed at improving health and well-being of an urban population.

Assessing malaria attributed mortality in west and southern Africa

BackgroundSeveral low and middle-income countries (LMIC) use Demographic and Health Surveys (DHS) and/or Health and Demographic Surveillance System (HDSS) to monitor the health of their population. The level and trends of under-five mortality rates could be different in the HDSS sites compared to the DHS reports. In this study, we investigated the change in under-five mortality rates overtime in the HDSS sites and the corresponding DHS reports in eight countries and 13 sites.MethodsUnder-five mortality rates in the HDSS sites were determined using number of under-five deaths (numerator) and live births (denominator). The trends and annualized rate of change (ARC) of under-five mortality rates in the HDSS sites and the DHS reports were compared by fitting exponential function.ResultsUnder-five mortality rates declined substantially in most of the sites during the last 10–15 years. Ten out of 13 (77 %) HDSS sites have consistently lower under-five mortality rates than the DHS under-five mortality rates. In the Kilifi HDSS in Kenya, under-five mortality rate declined by 65.6 % between 2003 and 2014 with ARC of 12.2 % (95 % CI: 9.4–15.0). In the same period, the DHS under-five mortality rate in the Coastal region of Kenya declined by 50.8 % with ARC of 6 % (95 % CI: 2.0–9.0). The under-five mortality rate reduction in the Mlomp (78.1 %) and Niakhar (80.8 %) HDSS sites in Senegal during 1993–2012 was significantly higher than the mortality decline observed in the DHS report during the same period. On the other hand, the Kisumu HDSS in Kenya had lower under-five mortality reduction (15.8 %) compared to the mortality reduction observed in the DHS report (27.7 %) during 2003–2008. Under-five mortality rate rose by 27 % in the Agincourt HDSS in South Africa between 1998 to 2003 that was contrary to the 18 % under-five mortality reduction in the DHS report during the same period.ConclusionsThe inconsistency between HDSS and DHS approaches could have global implication on the estimation of child mortality and ethical issues on mortality inequalities. Further studies should be conducted to investigate the reasons of child mortality variation between the HDSS and the DHS approaches.

Health and Demographic Surveillance Systems (HDSS) have been developed in several low- and middle-income countries (LMICs) in Africa and Asia. This paper reviews their history, state of the art and future potential and highlights substantial areas of contribution by the late Professor Peter Byass. Historically, HDSS appeared in the second half of the twentieth century, responding to a dearth of accurate population data in poorly resourced settings to contextualise the study of interventions to improve health and well-being. The progress of the development of this network is described starting with Pholela, and progressing through Gwembe, Balabgarh, Niakhar, Matlab, Navrongo, Agincourt, Farafenni, and Butajira, and the emergence of the INDEPTH Network in the early 1990’s The paper describes the HDSS methodology, data, strengths, and limitations. The strengths are particularly their temporal coverage, detail, dense linkage, and the fact that they exist in chronically under-documented populations in LMICs where HDSS sites operate. The main limitations are generalisability to a national population and a potential Hawthorne effect, whereby the project itself may have changed characteristics of the population. The future will include advances in HDSS data harmonisation, accessibility, and protection. Key applications of the data are to validate and assess bias in other datasets. A strong collaboration between a national HDSS network and the national statistics office is modelled in South Africa and Sierra Leone, and it is possible that other low- to middle-income countries will see the benefit and take this approach.

Background: Data about data, metadata, for describing Health and Demographic Surveillance System (HDSS) data have often received insufficient attention. This thesis studied how to develop provenance metadata within the context of HDSS data harmonisation - the network for Analysing Longitudinal Population-based HIV/ AIDS data on Africa (ALPHA). Technologies from the data documentation community were customised, among them: A process model - Generic Longitudinal Business Process Model (GLBPM), two metadata standards - Data Documentation Initiative (DDI) and Standard for Data and Metadata eXchange (SDMX) and a data transformations description language - Structured Data Transform Language (SDTL). Methods: A framework with three complementary facets was used: Creating a recipe for annotating primary HDSS data using the GLBPM and DDI; Approaches for documenting data transformations. At a business level, prospective and retrospective documentation using GLBPM and DDI and retrospectively recovering the more granular details using SDMX and SDTL; Requirements analysis for a user-friendly provenance metadata browser. Results: A recipe for the annotation of HDSS data was created outlining considerations to guide HDSS on metadata entry, staff training and software costs. Regarding data transformations, at a business level, a specialised process model for the HDSS domain was created. It has algorithm steps for each data transformation sub-process and data inputs and outputs. At a lower level, the SDMX and SDTL captured about 80% (17/21) of the variable level transformations. The requirements elicitation study yielded requirements for a provenance metadata browser to guide developers. Conclusions: This is a first attempt ever at creating detailed metadata for this resource or any other similar resources in this field. HDSS can implement these recipes to document their data. This will increase transparency and facilitate reuse thus potentially bringing down costs of data management. It will arguably promote the longevity and wide and accurate use of these data.

Investigating clinical transfers of HIV patients is important for accurate estimates of retention and informing interventions to support patients. We investigate transfers for adults reported as lost to follow-up (LTFU) from eight HIV care facilities in the Agincourt health and demographic surveillance system (HDSS), South Africa. Using linked clinic and HDSS records, outcomes of adults more than 90 days late for their last scheduled clinic visit were determined through clinic and routine tracing record reviews, HDSS data, and supplementary tracing. Factors associated with transferring to another clinic were determined through Cox regression models. Transfers were graphically and geospatially visualised. Transfers were more common for women, patients living further from the clinic, and patients with higher baseline CD4 cell counts. Transfers to clinics within the HDSS were more likely to be undocumented and were significantly more likely for women pregnant at ART initiation. Transfers outside the HDSS clustered around economic hubs. Patients transferring to health facilities within the HDSS may be shopping for better care, whereas those who transfer out of the HDSS may be migrating for work. Treatment programmes should facilitate transfer processes for patients, ensure continuity of care among those migrating, and improve tracking of undocumented transfers.

Investigating clinical transfers of HIV patients is important for accurate estimates of retention and informing interventions to support patients. We investigate transfers for adults reported as lost to follow-up (LTFU) from eight HIV care facilities in the Agincourt health and demographic surveillance system (HDSS), South Africa. Using linked clinic and HDSS records, outcomes of adults more than 90 days late for their last scheduled clinic visit were determined through clinic and routine tracing record reviews, HDSS data, and supplementary tracing. Factors associated with transferring to another clinic were determined through Cox regression models. Transfers were graphically and geospatially visualised. Transfers were more common for women, patients living further from the clinic, and patients with higher baseline CD4 cell counts. Transfers to clinics within the HDSS were more likely to be undocumented and were significantly more likely for women pregnant at ART initiation. Transfers outside the HDSS clustered around economic hubs. Patients transferring to health facilities within the HDSS may be shopping for better care, whereas those who transfer out of the HDSS may be migrating for work. Treatment programmes should facilitate transfer processes for patients, ensure continuity of care among those migrating, and improve tracking of undocumented transfers.

IntroductionHealth and Demographic Surveillance Systems (HDSS) collect data on births, deaths and migration from relatively small, geographically defined populations primarily in Africa and Asia. HDSS occupy a grey area between...

Background: Accurate data on perinatal and neonatal mortality in sub-Saharan Africa are scarce. This thesis assesses methods for their estimation in The Gambia. Methods: Under-five mortality was estimated, comparing the results of the first Demographic Health Survey in 2013 with previous inquiries. Three studies collecting primary data were conducted to assess and develop systems to improve estimation of perinatal and neonatal mortality. First, a pregnancy history survey that employed female interviewers was conducted and the results were compared with those from routine health and demographic surveillance in Basse. A second study linked records of women visiting antenatal clinics (ANC) to the Health and Demographic Surveillance System (HDSS) and used the augmented data to re-estimate neonatal, infant mortality and stillbirth rates. Third, a qualitative study was embedded in the retrospective survey to explore reasons for under-reporting of neonatal deaths and stillbirths. Findings: The DHS estimates of mortality for the recent past were consistent with those from other surveys. Age-disaggregated estimates for 2010-11 reveal that neonatal mortality constitutes 40% of under-five deaths in The Gambia. Women reported significantly more pregnancies in the pregnancy history survey than the HDSS and, in particular, more adverse pregnancy outcomes. Thus, while collecting data prospectively in HDSS generally limits omissions of deaths and age/date reporting errors, it may yield less complete data than pregnancy histories on adverse perinatal outcomes. However, the ANC-HDSS linkage study improved the capture of pregnancies. Women whose pregnancy was only detected in the clinic were 2.5 times more likely to have had a stillbirth than women whose pregnancies were picked up by the HDSS. The qualitative study showed that the cultural practice of pregnancy concealment, reluctance to speak of the deceased and to be counted affect the accuracy of data on pregnancy outcomes and mortality in The Gambia. It also revealed the importance of identification and use of culturally-appropriate metaphors and idioms to discuss sensitive matters compared to training interviewers to ask standardised verbatim questions.

Sampling rules do not apply in a Health and Demographic Surveillance System (HDSS) that covers exhaustively a district-level population and is not meant to be representative of a national population. We highlight the advantages of HDSS data for causal analysis and identify in the literature the principles of conditional generalisation that best apply to HDSS. A probabilistic view on HDSS data is still justified by the need to model complex causal inference. Accounting for contextual knowledge, reducing omitted-variable bias, detailing order of events, and high statistical power brings credence to HDSS data. Generalisation of causal mechanisms identified in HDSS data is consolidated through systematic comparison and triangulation with national or international data.

BackgroundIn the developed world, information on vital events is routinely collected nationally to inform population and health policies. However, in many low-and middle-income countries, especially those in sub-Saharan Africa (SSA), there is a lack of effective and comprehensive national civil registration and vital statistics system. In the past decades, the number of Health and Demographic Surveillance Systems (HDSSs) has increased throughout SSA. An HDSS monitors births, deaths, causes of death, migration, and other health and socio-economic indicators within a defined population over time. Currently, the International Network for the Continuous Demographic Evaluation of Populations and Their Health (INDEPTH) brings together 38 member research centers which run 44 HDSS sites from 20 countries in Africa, Asia and Oceana. Thirty two of these HDSS sites are in SSA.DiscussionThis paper argues that, in the absence of an adequate national CRVS, HDSSs should be more effectively utilised to generate relevant public health data, and also to create local capacity for longitudinal data collection and management systems in SSA. If HDSSs get strategically located to cover different geographical regions in a country, data from these sites could be used to provide a more complete national picture of the health of the population. They provide useful data that can be extrapolated for national estimates if their regional coverage is well planned. HDSSs are however resource-intensive. Efforts are being put towards getting them linked to local or national policy contexts and to reduce their dependence on external funding. Increasing their number in SSA to cover a critical proportion of the population, especially urban populations, must be carefully planned. Strategic planning is needed at national levels to geographically locate HDSS sites and to support these through national funding mechanisms.SummaryThe paper does not suggest that HDSSs should be seen as a replacement for civil registration systems. Rather, they should serve as a short- to medium-term measure to provide data for health and population planning at regional levels with possible extrapolation to national levels. HDSSs can also provide useful lessons for countries that intend to set up nationally representative sample vital registration systems in the long term.

Bayesian spatio-temporal modelling of the relationship between mortality and malaria transmission in rural western Kenya

To evaluate the contributions of the INDEPTH Network of health and demographic surveillance system (HDSS) members to research efforts and interventions on reproductive health in low- and middle-income countries (LMICs). Review of peer-reviewed published papers on sexual and reproductive health (SRH) that use the HDSS framework through (i) an online search for publications using terminology related to HDSS, HIV, Maternal health, adolescent sexual and reproductive health, family planning/contraceptives and fertility, and (ii) asking INDEPTH member centres for information on their published papers on SRH publications that used the HDSS framework. A paper was included in the review only if it used HDSS data, dealt with SRH issues, and had been published in a peer-reviewed international journal. Most of the papers in the review focused on HIV, maternal health, family planning and adolescent sexual and reproductive health (ASRH). Generally, people are knowledgeable about HIV. School attendance considerably delays entry into motherhood and reduces the probability of entering into early marriage or sexual union. The general decline in maternal mortality over the last decade is partly due to better access to emergency obstetric services, improved education of women and reduction in fertility. Sexual and reproductive health is a significant public health need, yet little research has been published in this area to inform policy. The HDSS framework is ideal for SRH research, as it offers the advantage to track and monitor progress of relevant health and demographic indicators, especially in family planning, marriage and fertility studies.