Publications by authors named "E Slaymaker"
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.
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.
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- Migration among young people in sub-Saharan Africa is driven by cultural norms, family considerations, and is influenced by changes such as urbanization and increased media access.
- The study utilized longitudinal data from a Health and Demographic Surveillance Site in Malawi to analyze migration patterns between 2004-2017, focusing on gender roles and the impact of family ties.
- Key findings indicate that young women tend to migrate longer distances for marriage and often return home after marital dissolution, while the proximity to relatives can reduce the likelihood of migration, with distinct differences in treatment and migration patterns observed between genders from early childhood.
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.
View Article and Find Full Text PDFBackground: 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.