Search

Abstract Background Sentinel surveillance for HIV in ante-natal clinics (ANC) remains the primary method for collecting timely trend data on HIV prevalence in most of sub-Saharan Africa. We describe prevalence of HIV and syphilis infection and trends over time in HIV prevalence among women attending ante-natal clinics (ANC) in Magu district and Mwanza city, part of Mwanza region in Northern Tanzania. HIV prevalence from ANC surveys in 2000 and 2002 was 10.5% and 10.8% respectively. In previous rounds urban residence, residential mobility, the length of time sexually active before marriage, time since marriage and age of the partner were associated with HIV infection. Methods A third round of HIV sentinel surveillance was conducted at ante-natal clinics in Mwanza region, Tanzania during 2006. We interviewed women attending 27 ante-natal clinics. In 15 clinics we also anonymously tested women for syphilis and HIV infection and linked these results to the questionnaire data. Results HIV prevalence was 7.6% overall in 2006 and 7.4% at the 11 clinics used in previous rounds. Geographical variations in HIV prevalence, apparent in previous rounds, have largely disappeared but syphilis prevalence is still higher in rural clinics. HIV prevalence has declined in urban clinics and is stable in rural clinics. The correlates of HIV infection have changed over time. In this round older age, lower gravidity, remarriage, duration of marriage, sexual activity before marriage, long interval between last birth and pregnancy and child death were all associated with infection. Conclusions HIV prevalence trends concur with results from a community-based cohort in the region. Correlates of HIV infection have also changed and more proximate, individual level factors are now more important, in line with the changing epidemiology of infection in this population.

Objectives: To evaluate quality of sexual debut and first marriage data, measure trends and study the association of risky sexual behaviour in youth with adult risk behaviour. Methods: Reports on age at first sex (AFS) and age at first marriage (AFM) from the Kisesa cohort study, 1994–2004, were evaluated for consistency and used to describe trends in median age-at-event and time spent single but sexually active in different birth cohorts. The association of these variables with marital stability and numbers of partners at later ages was explored using statistical regression techniques. Results: AFS and AFM were inconsistently reported by 32% and 33% of respondents, respectively, but there was no general tendency to report lower or higher ages at a later report date. In 10-year birth cohorts born between 1950–9 and 1980–9, male median AFS declined from 18.1 to 17.0 years and female median AFM rose from 16.2 to 16.6 years. Young people of both sexes currently spend longer sexually active but unmarried than previously. Early marriage is statistically associated with remarriage and polygamy; longer time between sexual debut and marriage is associated with higher numbers of partners at later stages of life. Conclusion: Inconsistent reporting of age-at-event introduces noise but does not bias estimates of population level indicators. Lengthening time spent single and sexually active suggests that men and women entering first marriage will have been exposed to increased numbers of non-marital partners. Successful youth interventions may also influence adult behaviour. [ABSTRACT FROM PUBLISHER]

Background: The absence of high-quality comprehensive civil registration and vital statistics systems across many settings in Africa has led to little empirical data on causes of death in the region. We aimed to use verbal autopsy data to provide comparative, population-based estimates of cause-specific mortality among adolescents and adults in eastern and southern Africa., Methods: In this surveillance study, we harmonised verbal autopsy and residency data from nine health and demographic surveillance system (HDSS) sites in Kenya, Malawi, Tanzania, South Africa, Uganda, and Zimbabwe, each with variable coverage from Jan 1, 1995, to Dec 31, 2019. We included all deaths to adolescents and adults aged 12 or over that were residents of the study sites and had a verbal autopsy conducted. InSilicoVA, a probabilistic model, was used to assign cause of death on the basis of the signs and symptoms reported in the verbal autopsy. Levels and trends in all-cause and cause-specific mortality rates and cause-specific mortality fractions were calculated, stratified by HDSS site, sex, age, and calendar periods., Findings: 52 484 deaths and 5 157 802 person-years were reported among 1 071 913 individuals across the nine sites during the study period. 47 961 (91·4%) deaths had a verbal autopsy, of which 46 570 (97·1%) were assigned a cause of death. All-cause mortality generally decreased across the HDSS sites during this period, particularly for adults aged 20-59 years. In many of the HDSS sites, these decreases were driven by reductions in HIV and tuberculosis-related deaths. In 2010-14, the top causes of death were: road traffic accidents, HIV or tuberculosis, and meningitis or sepsis in adolescents (12-19 years); HIV or tuberculosis in adults aged 20-59 years; and neoplasms and cardiovascular disease in adults aged 60 years and older. There was greater between-HDSS and between-sex variation in causes of death for adolescents compared with adults., Interpretation: This study shows progress in reducing mortality across eastern and southern Africa but also highlights age, sex, within-HDSS, and between-HDSS differences in causes of adolescent and adult deaths. These findings highlight the importance of detailed local data to inform health needs to ensure continued improvements in survival., Funding: National Institute of Child Health and Human Development of the US National Institutes of Health., Competing Interests: Declaration of interests LM reports research grants from Wellcome Trust, the US National Institutes of Health (NIH), and Medical Research Council Centre for Global Infectious Disease Analysis funding from the UK Medical Research Council (MRC) and the UK Department for International Development. SG reports research grants from Wellcome Trust, NIH, Bill & Melinda Gates Foundation, and WHO; financial support for attending meetings and travel from Imperial College London; and participation on a Data Safety Monitoring Board at Kings College London and as a board member at Biomedical Research Training Institute, Harare, Zimbabwe. CC reports research grants from NIH. SJC reports research grants from NIH; and acting as a paid consultant on verbal autopsy implementation methods and software for two non-governmental organisations (Vital Strategies and CDC Foundation). All other authors declare no competing interests. LM, CN, and SG have received funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK MRC and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC and FCDO Concordat agreement and this centre is also part of the European and Developing Countries Clinical Trials Partnership programme supported by the EU; and LM, CN, and SG have received funding by Community Jameel., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Proximity to family, household composition, and structure are often studied as outcomes and as explanatory factors in a wide range of scientific disciplines. Here, we describe a large longitudinal dataset (currently including data from over 70,000 individuals from 2004 to 2017), including data on household structure, proximity to kin, population density, and other socio-demographic factors derived from data from the Karonga Health and Demographic Surveillance Site (HDSS) in Northern Malawi. We present how the dataset is generated, list some examples of how it can be used, and provide information on the limitations that affect the types of analyses that can be carried out., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 McLean E et al.)

Background: In sub-Saharan Africa, migration of young people is common and occurs for a variety of reasons. Research focus is often on international or long-distance internal migration; however, shorter moves also affect people's lives and can reveal important information about cultures and societies. In rural sub-Saharan Africa, migration may be influenced by cultural norms and family considerations: these may be changing due to demographic shifts, urbanisation, and increased media access., Methods: We used longitudinal data from a Health and Demographic Surveillance Site in rural northern Malawi to present a detailed investigation of migration in young people between 2004-2017. Our focus is on the cultural effects of gender and family, and separate migrations into short and long distance, and independent and accompanied, as these different move types are likely to represent very different events in a young person's life. We use descriptive analyses multi-level multinomial logistic regression modelling., Results & Conclusions: We found two key periods of mobility 1) in very young childhood and 2) in adolescence/young adulthood. In this traditionally patrilocal area, we found that young women move longer distances to live with their spouse, and also were more likely to return home after a marriage ends, rather than remain living independently. Young people living close to relatives tend to have lower chances of moving, and despite the local patrilineal customs, we found evidence of the importance of the maternal family. Female and male children may be treated differently from as young as age 4, with girls more likely to migrate long distances independently, and more likely to accompany their mothers in other moves., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 McLean E et al.)

Background: Knowing levels and determinants of partnership acquisition will help inform interventions that try to reduce transmission of sexually transmitted infections (STIs) including HIV., Methods: We used population-based, cross-sectional data from 47 Demographic and Health Surveys to calculate rates of partner acquisition among men and women (15-49years), and identified socio-demographic correlates for partner acquisition. Partner acquisition rates were estimated as the total number of acquisitions divided by the person-time in the period covered by the survey. For each survey and by sex, we estimated age-specific partner acquisition rates and used age-adjusted piecewise exponential survival models to explore whether there was any association between wealth, HIV status and partner status with partner acquisition rates., Results: Across countries, the median partner acquisition rates were 30/100 person-years for men (interquartile range 21-45) and 13/100 person-years for women (interquartile range 6-18). There were substantial variations in partner acquisition rates by age. Associations between wealth and partner acquisition rates varied across countries. People with a cohabiting partner were less likely to acquire a new one, and this effect was stronger for women than men and varied substantially between countries. Women living with HIV had higher partner acquisition rates than HIV-negative women but this association was less apparent for men. At a population level, partner acquisition rates were correlated with HIV incidence., Conclusions: Partner acquisition rates are variable and are associated with important correlates of STIs and thus could be used to identify groups at high risk of STIs.

Introduction: Population health data integration remains a critical challenge in low- and middle-income countries (LMIC), hindering the generation of actionable insights to inform policy and decision-making. This paper proposes a pan-African, Findable, Accessible, Interoperable, and Reusable (FAIR) research architecture and infrastructure named the INSPIRE datahub. This cloud-based Platform-as-a-Service (PaaS) and on-premises setup aims to enhance the discovery, integration, and analysis of clinical, population-based surveys, and other health data sources., Methods: The INSPIRE datahub, part of the Implementation Network for Sharing Population Information from Research Entities (INSPIRE), employs the Observational Health Data Sciences and Informatics (OHDSI) open-source stack of tools and the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to harmonise data from African longitudinal population studies. Operating on Microsoft Azure and Amazon Web Services cloud platforms, and on on-premises servers, the architecture offers adaptability and scalability for other cloud providers and technology infrastructure. The OHDSI-based tools enable a comprehensive suite of services for data pipeline development, profiling, mapping, extraction, transformation, loading, documentation, anonymization, and analysis., Results: The INSPIRE datahub's "On-ramp" services facilitate the integration of data and metadata from diverse sources into the OMOP CDM. The datahub supports the implementation of OMOP CDM across data producers, harmonizing source data semantically with standard vocabularies and structurally conforming to OMOP table structures. Leveraging OHDSI tools, the datahub performs quality assessment and analysis of the transformed data. It ensures FAIR data by establishing metadata flows, capturing provenance throughout the ETL processes, and providing accessible metadata for potential users. The ETL provenance is documented in a machine- and human-readable Implementation Guide (IG), enhancing transparency and usability., Conclusion: The pan-African INSPIRE datahub presents a scalable and systematic solution for integrating health data in LMICs. By adhering to FAIR principles and leveraging established standards like OMOP CDM, this architecture addresses the current gap in generating evidence to support policy and decision-making for improving the well-being of LMIC populations. The federated research network provisions allow data producers to maintain control over their data, fostering collaboration while respecting data privacy and security concerns. A use-case demonstrated the pipeline using OHDSI and other open-source tools., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Bhattacharjee, Kiwuwa-Muyingo, Kanjala, Maoyi, Amadi, Ochola, Kadengye, Gregory, Kiragga, Taylor, Greenfield, Slaymaker, Todd and INSPIRE Network.)

Objective: To compare HIV prevalence estimates from routine programme data in antenatal care (ANC) clinics in western Kenya with HIV prevalence estimates in a general population sample in the era of universal test and treat (UTT)., Methods: The study was conducted in the area covered by the Siaya Health Demographic Surveillance System (Siaya HDSS) in western Kenya and used data from ANC clinics and the general population. ANC data (n = 1,724) were collected in 2018 from 13 clinics located within the HDSS. The general population was a random sample of women of reproductive age (15-49) who reside in the Siaya HDSS and participated in an HIV sero-prevalence survey in 2018 (n = 2,019). Total and age-specific HIV prevalence estimates were produced from both datasets and demographic decomposition methods were used to quantify the contribution of the differences in age distributions and age-specific HIV prevalence to the total HIV prevalence estimates., Results: Total HIV prevalence was 18.0% (95% CI 16.3-19.9%) in the ANC population compared with 18.4% (95% CI 16.8-20.2%) in the general population sample. At most ages, HIV prevalence was higher in the ANC population than in the general population. The age distribution of the ANC population was younger than that of the general population, and because HIV prevalence increases with age, this reduced the total HIV prevalence among ANC attendees relative to prevalence standardised to the general population age distribution., Conclusion: In the era of UTT, total HIV prevalence among ANC attendees and the general population were comparable, but age-specific HIV prevalence was higher in the ANC population in most age groups. The expansion of treatment may have led to changes in both the fertility of women living with HIV and their use of ANC services, and our results lend support to the assertion that the relationship between ANC and general population HIV prevalence estimates are highly dynamic., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ambia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)