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BACKGROUND: Metadata describe and provide context for other data, playing a pivotal role in enabling findability, accessibility, interoperability, and reusability (FAIR) data principles. By providing comprehensive and machine-readable descriptions of digital resources, metadata empower both machines and human users to seamlessly discover, access, integrate, and reuse data or content across diverse platforms and applications. However, the limited accessibility and machine-interpretability of existing metadata for population health data hinder effective data discovery and reuse. OBJECTIVE: To address these challenges, we propose a comprehensive framework using standardized formats, vocabularies, and protocols to render population health data machine-readable, significantly enhancing their FAIRness and enabling seamless discovery, access, and integration across diverse platforms and research applications. METHODS: The framework implements a 3-stage approach. The first stage is Data Documentation Initiative (DDI) integration, which involves leveraging the DDI Codebook metadata and documentation of detailed information for data and associated assets, while ensuring transparency and comprehensiveness. The second stage is Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardization. In this stage, the data are harmonized and standardized into the OMOP CDM, facilitating unified analysis across heterogeneous data sets. The third stage involves the integration of Schema.org and JavaScript Object Notation for Linked Data (JSON-LD), in which machine-readable metadata are generated using Schema.org entities and embedded within the data using JSON-LD, boosting discoverability and comprehension for both machines and human users. We demonstrated the implementation of these 3 stages using the Integrated Disease Surveillance and Response (IDSR) data from Malawi and Kenya. RESULTS: The implementation of our framework significantly enhanced the FAIRness of population health data, resulting in improved discoverability through seamless integration with platforms such as Google Dataset Search. The adoption of standardized formats and protocols streamlined data accessibility and integration across various research environments, fostering collaboration and knowledge sharing. Additionally, the use of machine-interpretable metadata empowered researchers to efficiently reuse data for targeted analyses and insights, thereby maximizing the overall value of population health resources. The JSON-LD codes are accessible via a GitHub repository and the HTML code integrated with JSON-LD is available on the Implementation Network for Sharing Population Information from Research Entities website. CONCLUSIONS: The adoption of machine-readable metadata standards is essential for ensuring the FAIRness of population health data. By embracing these standards, organizations can enhance diverse resource visibility, accessibility, and utility, leading to a broader impact, particularly in low- and middle-income countries. Machine-readable metadata can accelerate research, improve health care decision-making, and ultimately promote better health outcomes for populations worldwide.
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[This corrects the article DOI: 10.2196/56237.].
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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.
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BACKGROUND: Data anonymization and sharing have become popular topics for individuals, organizations, and countries worldwide. Open-access sharing of anonymized data containing sensitive information about individuals makes the most sense whenever the utility of the data can be preserved and the risk of disclosure can be kept below acceptable levels. In this case, researchers can use the data without access restrictions and limitations. OBJECTIVE: This study aimed to highlight the requirements and possible solutions for sharing health surveillance event history data. The challenges lie in the anonymization of multiple event dates and time-varying variables. METHODS: A sequential approach that adds noise to event dates is proposed. This approach maintains the event order and preserves the average time between events. In addition, a nosy neighbor distance-based matching approach to estimate the risk is proposed. Regarding the key variables that change over time, such as educational level or occupation, we make 2 proposals: one based on limiting the intermediate statuses of the individual and the other to achieve k-anonymity in subsets of the data. The proposed approaches were applied to the Karonga health and demographic surveillance system (HDSS) core residency data set, which contains longitudinal data from 1995 to the end of 2016 and includes 280,381 events with time-varying socioeconomic variables and demographic information. RESULTS: An anonymized version of the event history data, including longitudinal information on individuals over time, with high data utility, was created. CONCLUSIONS: The proposed anonymization of event history data comprising static and time-varying variables applied to HDSS data led to acceptable disclosure risk, preserved utility, and being sharable as public use data. It was found that high utility was achieved, even with the highest level of noise added to the core event dates. The details are important to ensure consistency or credibility. Importantly, the sequential noise addition approach presented in this study does not only maintain the event order recorded in the original data but also maintains the time between events. We proposed an approach that preserves the data utility well but limits the number of response categories for the time-varying variables. Furthermore, using distance-based neighborhood matching, we simulated an attack under a nosy neighbor situation and by using a worst-case scenario where attackers have full information on the original data. We showed that the disclosure risk is very low, even when assuming that the attacker's database and information are optimal. The HDSS and medical science research communities in low- and middle-income country settings will be the primary beneficiaries of the results and methods presented in this paper; however, the results will be useful for anyone working on anonymizing longitudinal event history data with time-varying variables for the purposes of sharing.
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Data Anonymization , Privacy , Demography , Disclosure , Electronic Health Records , HumansABSTRACT
BACKGROUND: A large, double-blind, randomised, placebo-controlled trial of repeat BCG found 49% efficacy against leprosy but no protection against tuberculosis after 6-9 years' follow-up in 1995. We report here additional follow-up, which resulted in greatly increased tuberculosis case numbers, and allowed subgroup analysis. METHODS: Nearly 47â000 individuals of all ages living in northern Malawi with a BCG vaccine scar were randomly assigned (1:1) between 1986 and 1989 to receive a second BCG or placebo. The investigators and project staff remained masked to all interventions. Enhanced passive surveillance ensured ascertainment of tuberculosis and leprosy to the end of 2018. Tuberculosis case definitions included rigorous microbiological or histological confirmation. Prespecified subgroup analyses were by tuberculosis type, age at vaccination, time since vaccination, previous tuberculin reactivity, HIV status and Mycobacterium tuberculosis lineage. The original trial is registered with ISRCTN registry, ISRCTN11311670. FINDINGS: In follow-up until Dec 31, 2018, 824 participants had developed tuberculosis, including 786 with pulmonary disease, of whom 383 (63%) of 607 with known HIV status were HIV positive. There was no effect of a second BCG overall (odds ratio [OR] 0·92; 95% CI 0·80-1·05), or for pulmonary (0·93; 0·81-1·07), or lymph node tuberculosis (0·60; 0·31-1·17). The OR was lower for those with known HIV-negative tuberculosis (0·77; 0·59-1·00), for those vaccinated as children (aged <5 years, 0·74; 0·41-1·35; aged 5-14 years, 0·77; 0·60-0·99), and for cases arising at least 20 years after vaccination (0·79; 0·63-1·01). There were no differences by tuberculin status at vaccination, or lineage. There was no evidence of protection against leprosy beyond 10 years after vaccination (although there have been only nine diagnostically certain cases since 1995). INTERPRETATION: There was no evidence that repeat BCG vaccination provides appreciable protection against overall tuberculosis in this rural African population with a high prevalence of HIV. Subgroup effects should not be overinterpreted given the multiple analyses done. However, the evidence for modest protection against HIV-negative tuberculosis, and for a delayed benefit in those vaccinated as children, is consistent with other observations in the literature. FUNDING: LEPRA, Wellcome Trust, Bill & Melinda Gates Foundation.
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BCG Vaccine , Vaccination , Double-Blind Method , Follow-Up Studies , Humans , Malawi/epidemiologyABSTRACT
BACKGROUND: Trials of BCG vaccination to prevent or reduce severity of COVID-19 are taking place in adults, some of whom have been previously vaccinated, but evidence of the beneficial, non-specific effects of BCG come largely from data on mortality in infants and young children, and from in-vitro and animal studies, after a first BCG vaccination. We assess all-cause mortality following a large BCG revaccination trial in Malawi. METHODS: The Karonga Prevention trial was a population-based, double-blind, randomised controlled in Karonga District, northern Malawi, that enrolled participants between January, 1986, and November, 1989. The trial compared BCG (Glaxo-strain) revaccination versus placebo to prevent tuberculosis and leprosy. 46 889 individuals aged 3 months to 75 years were randomly assigned to receive BCG revaccination (n=23 528) or placebo (n=23 361). Here we report mortality since vaccination as recorded during active follow-up in northern areas of the district in 1991-94, and in a demographic surveillance follow-up in the southern area in 2002-18. 7389 individuals who received BCG (n=3746) or placebo (n=3643) lived in the northern follow-up areas, and 5616 individuals who received BCG (n=2798) or placebo (n=2818) lived in the southern area. Year of death or leaving the area were recorded for those not found. We used survival analysis to estimate all-cause mortality. FINDINGS: Follow-up information was available for 3709 (99·0%) BCG recipients and 3612 (99·1%) placebo recipients in the northern areas, and 2449 (87·5%) BCG recipients and 2413 (85·6%) placebo recipients in the southern area. There was no difference in mortality between the BCG and placebo groups in either area, overall or by age group or sex. In the northern area, there were 129 deaths per 19 694 person-years at risk in the BCG group (6·6 deaths per 1000 person-years at risk [95% CI 5·5-7·8]) versus 133 deaths per 19 111 person-years at risk in the placebo group (7·0 deaths per 1000 person-years at risk [95% CI 5·9-8·2]; HR 0·94 [95% CI 0·74-1·20]; p=0·62). In the southern area, there were 241 deaths per 38 399 person-years at risk in the BCG group (6·3 deaths per 1000 person-years at risk [95% CI 5·5-7·1]) versus 230 deaths per 38 676 person-years at risk in the placebo group (5·9 deaths per 1000 person-years at risk [95% CI 5·2-6·8]; HR 1·06 [95% CI 0·88-1·27]; p=0·54). INTERPRETATION: We found little evidence of any beneficial effect of BCG revaccination on all-cause mortality. The high proportion of deaths attributable to non-infectious causes beyond infancy, and the long time interval since BCG for most deaths, might obscure any benefits. FUNDING: British Leprosy Relief Association (LEPRA); Wellcome Trust.
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BCG Vaccine/administration & dosage , Immunization, Secondary/statistics & numerical data , Mortality , Vaccination/methods , Adolescent , Adult , Aged , BCG Vaccine/immunology , COVID-19/epidemiology , COVID-19/immunology , COVID-19/prevention & control , Child , Child, Preschool , Double-Blind Method , Female , Follow-Up Studies , Humans , Immunogenicity, Vaccine , Leprosy/immunology , Leprosy/mortality , Leprosy/prevention & control , Malawi/epidemiology , Male , Middle Aged , Mycobacterium leprae/immunology , SARS-CoV-2/immunology , Treatment Outcome , Tuberculosis/immunology , Tuberculosis/mortality , Tuberculosis/prevention & control , Vaccination/statistics & numerical data , Young AdultABSTRACT
BACKGROUND: Schistosomiasis affects 218 million people worldwide, with most infections in Africa. Prevalence studies suggest that people with chronic schistosomiasis may have higher risk of HIV-1 acquisition and impaired ability to control HIV-1 replication once infected. We hypothesized that: (1) pre-existing schistosome infection may increase the odds of HIV-1 acquisition and that the effects may differ between men and women, and (2) individuals with active schistosome infection at the time of HIV-1 acquisition may have impaired immune control of HIV-1, resulting in higher HIV-1 viral loads at HIV-1 seroconversion. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a nested case-control study within a large population-based survey of HIV-1 transmission in Tanzania. A population of adults from seven villages was tested for HIV in 2007, 2010, and 2013 and dried blood spots were archived for future studies with participants' consent. Approximately 40% of this population has Schistosoma mansoni infection, and 2% has S. haematobium. We tested for schistosome antigens in the pre- and post-HIV-1-seroconversion blood spots of people who acquired HIV-1. We also tested blood spots of matched controls who did not acquire HIV-1 and calculated the odds that a person with schistosomiasis would become HIV-1-infected compared to these matched controls. Analysis was stratified by gender. We compared 73 HIV-1 seroconverters with 265 controls. Women with schistosome infections had a higher odds of HIV-1 acquisition than those without (adjusted OR = 2.8 [1.2-6.6], p = 0.019). Schistosome-infected men did not have an increased odds of HIV-1 acquisition (adjusted OR = 0.7 [0.3-1.8], p = 0.42). We additionally compared HIV-1 RNA levels in the post-seroconversion blood spots in HIV-1 seroconverters with schistosomiasis versus those without who became HIV-infected in 2010, before antiretroviral therapy was widely available in the region. The median whole blood HIV-1 RNA level in the 15 HIV-1 seroconverters with schistosome infection was significantly higher than in the 22 without schistosomiasis: 4.4 [3.9-4.6] log10 copies/mL versus 3.7 [3.2-4.3], p = 0.017. CONCLUSIONS/SIGNIFICANCE: We confirm, in an area with endemic S. mansoni, that pre-existing schistosome infection increases odds of HIV-1 acquisition in women and raises HIV-1 viral load at the time of HIV-1 seroconversion. This is the first study to demonstrate the effect of schistosome infection on HIV-1 susceptibility and viral control, and to differentiate effects by gender. Validation studies will be needed at additional sites.
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Disease Susceptibility , HIV Infections/etiology , HIV Infections/immunology , HIV Seropositivity , Schistosomiasis/complications , Viral Load/immunology , Adult , Animals , Antigens, Helminth/blood , Antigens, Helminth/immunology , Case-Control Studies , Dried Blood Spot Testing , Female , HIV Infections/epidemiology , Humans , Male , RNA, Viral/blood , Schistosoma haematobium/immunology , Schistosoma haematobium/isolation & purification , Schistosoma mansoni/immunology , Schistosoma mansoni/isolation & purification , Schistosomiasis/immunology , Schistosomiasis/parasitology , Sex Characteristics , Tanzania/epidemiology , Viral Load/methodsSubject(s)
Acquired Immunodeficiency Syndrome/mortality , Population Surveillance/methods , Adolescent , Adult , Africa/epidemiology , Age Distribution , Aged , Aged, 80 and over , Child , Child, Preschool , Databases as Topic , Female , Humans , Infant , Infant, Newborn , Longitudinal Studies , Male , Middle Aged , Sex Distribution , Young AdultABSTRACT
The Apostolic faith, a rapidly growing and increasingly influential force in Zimbabwe, has received attention in the literature due to its potential role in shaping its followers' attitudes and behaviours towards health. Existing literature, however, has only examined small cross-section samples from a few confined survey sites or has failed to adequately control for the many factors that may mediate the effects of religion. This paper examines the effects of the Apostolic faith on the usage of maternal health and child immunization services in Zimbabwe. It is based on a nationally representative sample from the 2009 Multi-Indicator Monitoring Survey and employs the established Andersen model on access to health services. Well controlled multivariate logit regression models derived from these data show that an affiliation with the Apostolic faith is a substantial and significant risk factor in reducing the utilization of both maternal and child health services. Moreover, even when the services were least costly and readily available and when gaps along other social and economic factors were limited, as in the case of Bacillus Calmette-Guérin vaccination and one visit to antenatal care, women and children from Apostolic faith families still fared significantly worse than others in accessing them.
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Child Health Services/statistics & numerical data , Maternal Health Services/statistics & numerical data , Religion , Vaccination/statistics & numerical data , Adolescent , Adult , Child , Female , Humans , Middle Aged , Prenatal Care/statistics & numerical data , Socioeconomic Factors , Young Adult , ZimbabweABSTRACT
BACKGROUND: The Tanzanian national HIV care and treatment programme has provided free antiretroviral therapy (ART) to HIV-positive persons since 2004. ART has been available to participants of the Kisesa open cohort study since 2005, but data to 2007 showed a slow uptake of ART and a modest impact on mortality. Additional data from the 2010 HIV serological survey provide an opportunity to update the estimated impact of ART in this setting. METHODS: The Kisesa Health and Demographic Surveillance Site (HDSS) has collected HIV serological data and demographic data, including verbal autopsy (VA) interviews since 1994. Serological data to the end of 2010 were used to make two estimates of HIV-attributable mortality, the first among HIV positives using the difference in mortality between HIV positives and HIV negatives, and the second in the population using the difference between the observed mortality rate in the whole population and the mortality rate among the HIV negatives. Four time periods (1994-1999, 2000-2004, 2005-2007, and 2008-2010) were used and HIV-attributable mortality estimates were analysed in detail for trends over time. A computer algorithm, InterVA-4, was applied to VA data to estimate the HIV-attributable mortality for the population, and this was compared to the estimates from the serological survey data. RESULTS: Among HIV-positive adults aged 45-59 years, high mortality rates were observed across all time periods in both males and females. In HIV-positive men, the HIV-attributable mortality was 91.6% (95% confidence interval (CI): 84.6%-95.3%) in 2000-2004 and 86.3% (95% CI: 71.1%-93.3%) in 2008-2010, while among women, the HIV-attributable mortality was 87.8% (95% CI: 71.1%-94.3%) in 2000-2004 and 85.8% (95% CI: 59.6%-94.4%) in 2008-2010. In the whole population, using the serological data, the HIV-attributable mortality among men aged 30-44 years decreased from 57.2% (95% CI: 46.9%-65.3%) in 2000-2004 to 36.5% (95% CI: 18.8%-50.1%) in 2008-2010, while among women the corresponding decrease was from 57.3% (95% CI: 49.7%-63.6%) to 38.7% (95% CI: 27.4%-48.2%). The HIV-attributable mortality in the population using estimates from the InterVA model was lower than that from HIV sero-status data in the period prior to ART, but slightly higher once ART became available. DISCUSSION: In the Kisesa HDSS, ART availability corresponds with a decline in adult overall mortality, although not as large as expected. Using InterVA to estimate HIV-attributable mortality showed smaller changes in HIV-related mortality following ART availability than the serological results.
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Anti-HIV Agents/therapeutic use , HIV Infections/mortality , Mortality , Adolescent , Adult , Age Factors , Female , HIV Infections/drug therapy , HIV Infections/epidemiology , Humans , Male , Middle Aged , Population Surveillance , Rural Population/statistics & numerical data , Tanzania/epidemiology , Young AdultABSTRACT
INTRODUCTION: Spectrum epidemiological models are used by UNAIDS to provide global, regional and national HIV estimates and projections, which are then used for evidence-based health planning for HIV services. However, there are no validations of the Spectrum model against empirical serological and mortality data from populations in sub-Saharan Africa. METHODS: Serologic, demographic and verbal autopsy data have been regularly collected among over 30,000 residents in north-western Tanzania since 1994. Five-year age-specific mortality rates (ASMRs) per 1,000 person years and the probability of dying between 15 and 60 years of age (45Q15,) were calculated and compared with the Spectrum model outputs. Mortality trends by HIV status are shown for periods before the introduction of antiretroviral therapy (1994-1999, 2000-2005) and the first 5 years afterwards (2005-2009). RESULTS: Among 30-34 year olds of both sexes, observed ASMRs per 1,000 person years were 13.33 (95% CI: 10.75-16.52) in the period 1994-1999, 11.03 (95% CI: 8.84-13.77) in 2000-2004, and 6.22 (95% CI; 4.75-8.15) in 2005-2009. Among the same age group, the ASMRs estimated by the Spectrum model were 10.55, 11.13 and 8.15 for the periods 1994-1999, 2000-2004 and 2005-2009, respectively. The cohort data, for both sexes combined, showed that the 45Q15 declined from 39% (95% CI: 27-55%) in 1994 to 22% (95% CI: 17-29%) in 2009, whereas the Spectrum model predicted a decline from 43% in 1994 to 37% in 2009. CONCLUSION: From 1994 to 2009, the observed decrease in ASMRs was steeper in younger age groups than that predicted by the Spectrum model, perhaps because the Spectrum model under-estimated the ASMRs in 30-34 year olds in 1994-99. However, the Spectrum model predicted greater 45Q15 mortality than observed in the cohort,although the reasons for this over-estimate are unclear [corrected].
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HIV Infections/epidemiology , Models, Statistical , Mortality/trends , Adolescent , Adult , Age Factors , Cohort Studies , Female , HIV Infections/mortality , Humans , Male , Middle Aged , Rural Population/statistics & numerical data , Tanzania/epidemiology , Young AdultABSTRACT
BACKGROUND: Mortality data are frequently presented at the overall population level, possibly obscuring small-scale variations over time and space and between different population sub-groups. OBJECTIVE: Analysis of mortality data from the Dikgale Health and Demographic Surveillance System, in rural South Africa, over the period 1996-2007, to identify local clustering of mortality among the eight villages in the observed population. DESIGN: Mortality data and person-time of observation were collected annually in an open-cohort population of approximately 8,000 people over 12 years. Poisson regression modelling and space-time clustering analyses were used to identify possible clustering of mortality. RESULTS: Similar patterns of mortality clustering emerged from Poisson regression and space-time clustering analyses after allowing for age and sex. There was no appreciable clustering of mortality among children under 15 years of age nor in adults 50 years and over. For adults aged 15-49 years, there were substantial clustering effects both in time and in space, with mortality increasing during the period observed and particularly so in some locations, which were nearer to local conurbations. Mortality was relatively lower in the vicinity of the local health centre. CONCLUSIONS: Although cause-specific mortality data were not available, the rise in mortality in the 15-49-year age group over time and in areas closer to conurbations strongly suggests that the clustering observed was due to the development of HIV/AIDS-related mortality, as seen similarly elsewhere in South Africa. The HIV/AIDS services offered by the local health centre may have contributed to lower relative mortality around that location.