Correction: Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study.

[This corrects the article DOI: 10.2196/56237.].

Making Metadata Machine-Readable as the First Step to Providing Findable, Accessible, Interoperable, and Reusable Population Health Data: Framework Development and Implementation Study.

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.

Insights into COVID-19 data collection and management in Malawi: exploring processes, perceptions, and data discrepancies.

Background: The completion of case-based surveillance forms was vital for case identification during COVID-19 surveillance in Malawi. Despite significant efforts, the resulting national data suffered from gaps and inconsistencies which affected its optimal usability. The objectives of this study were to investigate the processes of collecting and reporting COVID-19 data, to explore health workers' perceptions and understanding of the collection tools and processes, and to identify factors contributing to data quality. Methods: A total of 75 healthcare professionals directly involved in COVID-19 data collection from the Malawi Ministry of Health in Lilongwe and Blantyre participated in Focus Group Discussions and In-Depth Interviews. We collected participants' views on the effectiveness of surveillance forms in collecting the intended data, as well as on the data collection processes and training needs. We used MAXQDA for thematic and document analysis. Results: Form design significantly influenced data quality and, together with challenges in applying case definitions, formed 44% of all issues raised. Concerns regarding processes used in data collection and training gaps comprised 49% of all the issues raised. Language issues (2%) and privacy, ethical, and cultural considerations (4%), although mentioned less frequently, offered compelling evidence for further review. Conclusions: Our study highlights the integral connection between data quality and the design and utilization of data collection forms. While the forms were deemed to contain the most relevant fields, deficiencies in format, order of fields, and the absence of an addendum with guidelines, resulted in large gaps and errors. Form design needs to be reviewed so that it appropriately fits into the overall processes and systems that capture surveillance data. This study is the first of its kind in Malawi, offering an in-depth view of the perceptions and experiences of health professionals involved in disease surveillance on the tools and processes they use.

Levels, trends and inequalities in mortality among 5-19-year-olds in Tanzania: Magu Health and Demographic Surveillance Study (1995-2022).

Background: For the past two decades, health priorities in Tanzania have focussed on children under-five, leaving behind the older children and adolescents (5-19 years). Understanding mortality patterns beyond 5 years is important in bridging a healthy gap between childhood to adulthood. We aimed to estimate mortality levels, trends, and inequalities among 5-19-year-olds using population data from the Magu Health and Demographic Surveillance Site (HDSS) in Tanzania and further compare the population level estimates with global estimates. Methods: Using data from the Magu HDSS from 1995 to 2022, from Kaplan Meir survival probabilities, we computed annual mortality probabilities for ages 5-9, 10-14 and 15-19 and determined the average annual rate of change in mortality by fitting the variance weighted least square regression on annual mortality probabilities. We compared 5-19 trends with younger children aged 1-4 years. We further disaggregated mortality by sex, area of residence and wealth tertiles, and we computed age-stratified risk ratios with respective 95% confidence intervals (CIs) using Cox proportional hazard model to determine inequalities. We further compared population-level estimates in all-cause mortality with global estimates from the United Nations Inter-agency Group for Child Mortality Estimation and the Global Burden of Disease study by computing the relative differences to the estimates. Results: Mortality declined steadily among the three age groups from 1995 to 2022, whereby the average annual rate of decline increased with age (2.2%, 2.7%, and 2.9% for 5-9-, 10-14-, and 15-19-year-old age groups, respectively). The pace of this decline was lower than that of younger children aged 1-4 years (4.8% decline). We observed significant mortality inequalities with boys, those residing in rural areas, and those from poorest wealth tertiles lagging behind. While Magu estimates were close to global estimates for the 5-9-year-old age group, we observed divergent results for adolescents (10-19 years), with Magu estimates lying between the global estimates. Conclusion: The pace of mortality decline was lower for the 5-19-year-old age group compared to younger children, with observable inequalities by socio-demographic characteristics. Determining the burden of disease across different strata is important in the development of evidence-based targeted interventions to address the mortality burden and inequalities in this age group, as it is an important transition period to adulthood.

Estimation of cause-specific mortality in Rakai, Uganda, using verbal autopsy 1999-2019.

BACKGROUND: There are scant data on the causes of adult deaths in sub-Saharan Africa. We estimated the level and trends in adult mortality, overall and by different causes, in rural Rakai, Uganda, by age, sex, and HIV status. OBJECTIVES: To estimate and analyse adult cause-specific mortality trends in Rakai, Uganda. METHODOLOGY: Mortality information by cause, age, sex, and HIV status was recorded in the Rakai Community Cohort study using verbal autopsy interviews, HIV serosurveys, and residency data. We estimated the average number of years lived in adulthood. Using demographic decomposition methods, we estimated the contribution of each cause of death to adult mortality based on the average number of years lived in adulthood. RESULTS: Between 1999 and 2019, 63082 adults (15-60 years) were censused, with 1670 deaths registered. Of these, 1656 (99.2%) had completed cause of death data from verbal autopsy. The crude adult death rate was 5.60 (95% confidence interval (CI): 5.33-5.87) per 1000 person-years of observation (pyo). The crude death rate decreased from 11.41 (95% CI: 10.61-12.28) to 3.27 (95% CI: 2.89-3.68) per 1000 pyo between 1999-2004 and 2015-2019. The average number of years lived in adulthood increased in people living with HIV and decreased in HIV-negative individuals between 2000 and 2019. Communicable diseases, primarily HIV and Malaria, had the biggest decreases, which improved the average number of years lived by approximately extra 12 years of life in females and 6 years in males. There were increases in deaths due to non-communicable diseases and external causes, which reduced the average number of years lived in adulthood by 2.0 years and 1.5 years in females and males, respectively. CONCLUSION: There has been a significant decline in overall mortality from 1999 to 2019, with the greatest decline seen in people living with HIV since the availability of antiretroviral therapy in 2004. By 2020, the predominant causes of death among females were non-communicable diseases, with external causes of death dominating in males.

Main findings: There are significant declines in mortality in people living with HIV. However, mortality in HIV-negative people increased due to non-communicable diseases in females, and injuries and external causes of death among males.Added knowledge: In this HIV-endemic area, decreasing adult mortality has been documented over the last 20 years. This paper benchmarks the changes in cause-specific mortality in this area.Global health impact for policy action: As in many African countries, more effort is needed to reduce mortality for non-communicable diseases, injuries, and external causes of death as these seem to have been neglected.

Improving the Barrier and Mechanical Properties of Paper Used for Packing Applications with Renewable Hydrophobic Coatings Derived from Camelina Oil.

This study looked at using modified camelina oil to develop sustainable coatings that could replace those derived from petroleum-based materials for use in packaging and other industrial sectors. Solvent-free synthesis of maleic anhydride grafted camelina oil (MCO) was carried out at two different temperatures (200 and 230 °C) to obtain sustainable hydrophobic coating materials for paper substrates. Maleic anhydride grafting of camelina oil was confirmed with attenuated total reflectance-Fourier transform infrared and NMR spectroscopic techniques, and up to 16% grafting of maleic anhydride was achieved, as determined by the titration method. MCO, obtained at different reaction temperatures, was coated onto cellulosic paper and evaluated for its hydrophobicity, mechanical, oxygen, and water vapor barrier properties. Scanning electron microscopy indicated the homogeneous dispersion of coating material onto the paper substrate. MCO-coated papers (MCO-200C paper and MCO-230C paper) provided a water contact angle of above 90° which indicates that the modified oil was working as a hydrophobic coating. Water vapor permeability (WVP) testing of coated papers revealed a reduction in WVP of up to 94% in comparison to the uncoated paper. Moreover, an improved oxygen barrier property was also observed for paper coated with both types of MCO. Analysis of the mechanical properties showed a greater than 70% retention of tensile strength and up to a five-fold increase in elongation at break of coated versus uncoated papers. Overall, the results show that camelina oil, a renewable resource, can be modified to produce environmentally friendly hydrophobic coating materials with improved mechanical and water vapor barrier properties that can serve as a potential coating material in the packaging industry. The results of this research could find applications in the huge paper packaging industries, specially in food packaging.

Genetic study for seed germination and shattering in Euphorbia lagascae in response to different seed treatments.

Euphorbia lagascae Spreng is a promising emerging oilseed crop, with its seed oil accounting for approximately 50% of the seed weight. Euphorbia oil contains a significant amount of vernolic acid, comprising two-thirds of its composition, which boasts various industrial applications, including acting as a stabilizer-plasticizer and natural dye. However, this species was known to have a high degree of seed-shattering and a low germination rate, which act as two important barriers to large-scale production and exploitation. Therefore, the objective of this study is to determine the genetic control of seed germination and seed-shattering traits in order to develop a reliable pipeline that would be applicable for industries and breeders to select superior E. lagascae lines and design a robust breeding scheme in a short time at reduced labor costs. For this objective, five different wild-type genotypes of E. lagascae that demonstrated high germination potential were crossed with an ethyl methanesulfonate (EMS) mutant genotype that produces non-shattering capsules. The F2 populations from two successful crosses (A and B) were separated into three different treated groups for seed germination evaluation and to study the segregation of 200 individuals per F2 population. The three treatments were: light, gibberellic acid (GA3), and control treatment. Consequently, plants treated with approximately 250 µmol/m2/s of light showed significant improvement in germination up to 75% in cross A and 82.4 % in cross B compared with the control plants and the group treated with 0.05% GA3. According to the chi-square test results, the inheritance pattern of seed germination in response to light treatment follows a 3:1 segregation ratio between germinated and non-germinated seeds, indicating a dominant gene action in the F2 generation. The same conclusion was followed for the shattering trait in the group treated with light, which was also simply inherited as a 3:1 ratio for shattering vs. non-shattering capsules. Our results emphasize the importance and significance of light treatment in producing uniform populations through acceptable germination and shattering resistance of the mutant genotypes of E. lagascae. This is the first report of light treatment that significantly improved seed germination of E. lagascae, which may enhance efforts in the development of this new industrial crop as a feedstock for vernolic acid production.

INSPIRE datahub: a pan-African integrated suite of services for harmonising longitudinal population health data using OHDSI tools.

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.

Improvement of germination rate and hybridization to facilitate breeding of an industrial oil crop, Euphorbia lagascae Spreng.

BACKGROUND: The potential of plant-based sources of vernolic acid to provide agricultural producers with a market diversification opportunity and industrial manufacturers with a renewable, environmentally friendly chemical feedstock is immense. The herbaceous wild spurge or caper spurge (Euphorbia lagascae Spreng) is the most promising source of vernolic acid, containing an average oil content of 50%, of which around 60% is vernolic acid. Its seed yield ranges between 500 and 2000 kg ha-1, and a theoretical yield of 180 kg ha-1 of pure vernolic acid is possible. The objective of this research was to characterize the flower and whole plant morphology so to allow for the development of a method to efficiently hybridize E. lagasce plants for breeding purposes. RESULTS: In this study, we have characterized the flower and whole plant morphology in detail, thereby, developing an efficient method for hybridization of E. lagasce to allow for its breeding and improvement as a novel oil crop. Such method was not described previously in the literature making it difficult to breed this crop. We believe that the method will be of great value to plant breeders working on optimizing the crop, particularly in terms of the development of non-shattering cultivars with enhanced germination potential. CONCLUSIONS: The successful development of this crop through plant breeding could provide substantial economic benefits to farmers by offering them a new industrial oilseed crop. This research could prove invaluable in unlocking the potential of E. lagasce, and in turn, the potential of vernolic acid as a renewable, environmentally friendly source of chemical feedstock.

Mapping regional variability of exclusive breastfeeding and its determinants at different infant's age in Tanzania.

INTRODUCTION: Despite its numerous benefits, exclusive breastfeeding (EBF) remains an underutilized practice. Enhancing EBF uptake necessitates a focused approach targeting regions where its adoption is suboptimal. This study aimed to investigate regional disparities in EBF practices and identify determinants of EBF among infants aged 0-1, 2-3, and 4-5 months in Tanzania. METHODS: This cross-sectional study utilized data from the 2015/16 Tanzania Demographic and Health Survey. A total of 1,015 infants aged 0-5 met the inclusion criteria, comprising 378 aged 0-1 month, 334 at 2-3 months, and 303 at 4-5 months. EBF practices were assessed using a 24-hour recall method. A generalized linear mixed model, with fixed covariates encompassing infant and maternal attributes and clusters for enumeration areas (EAs) and regions, was employed to estimate EBF proportions. RESULTS: Regional disparities in EBF were evident among infants aged 0-1, 2-3, and 4-5 months, with decline in EBF proportions as an infant's age increases. This pattern was observed nationwide. Regional and EA factors influenced the EBF practices at 0-1 and 2-3 months, accounting for 17-40% of the variability at the regional level and 40-63% at the EA level. Literacy level among mothers had a significant impact on EBF practices at 2-3 months (e.g., women who could read whole sentences; AOR = 3.2, 95% CI 1.1,8.8). CONCLUSION: Regional disparities in EBF proportions exist in Tanzania, and further studies are needed to understand their underlying causes. Targeted interventions should prioritize regions with lower EBF proportions. This study highlights the clustering of EBF practices at 0-1 and 2-3 months on both regional and EA levels. Conducting studies in smaller geographical areas may enhance our understanding of the enablers and barriers to EBF and guide interventions to promote recommended EBF practices.

Trends of Exclusive Breastfeeding Practices and Its Determinants in Tanzania from 1999 to 2016.

Introduction: The benefits of exclusive breastfeeding (EBF) are widely reported. However, it is crucial to examine potential disparities in EBF practices across different regions of a country. Our study uses Tanzania demographic and health survey data to report on the trends of EBF across regions from 1999 to 2016, the patterns of the practice based on geographical location and socioeconomic status, and explores its determinants across the years. Methods: Descriptive statistics were used to establish the trends of EBF by geographical location and wealth quintile. A generalized linear mixed model was developed to incorporate both infant and maternal attributes as fixed covariates while considering enumeration areas and regions as clusters. The fitted model facilitated the estimation of EBF proportions at a regional level and identified key determinants influencing EBF practices across the survey periods. Moreover, we designed breastfeeding maps, visually depicting the performance of different regions throughout the surveys. Results: Across the various survey rounds, a notable regional variation in EBF practices was observed, with coastal regions generally exhibiting lower adherence to the practice. There was a linear trend between EBF and geographical residence (p < 0.05) and socioeconomic standing (p < 0.05) across the survey periods. Rural-dwelling women and those from the least affluent backgrounds consistently showcased a higher proportion of EBF. The prevalence of EBF declined as infants aged (p < 0.001), a trend consistent across all survey waves. The associations between maternal attributes and EBF practices displayed temporal variations. Furthermore, a correlation between exclusive breastfeeding and attributes linked to both regional disparities and enumeration areas was observed. The intra-cluster correlation ranged from 18% to 41.5% at the regional level and from 40% to 58.5% at the enumeration area level. Conclusions: While Tanzania's progress in EBF practices is laudable, regional disparities persist, demanding targeted interventions. Sustaining achievements while addressing wealth-based disparities and the decline in EBF with infant age is vital. The study highlights the need for broad national strategies and localized investigations to understand and enhance EBF practices across different regions and socioeconomic contexts.

Unmet need for modern contraception by HIV status: findings from community-based studies implemented before and after earlier ART initiation program in rural Tanzania.

BACKGROUND: Tanzania Health policy insists on the need to provide all women access to contraception despite HIV status. We used data from two HIV epidemiologic serological surveys carried out at different periods of ART provision in rural Tanzania to assess the level of unmet need for modern contraception by HIV status and associated factors. METHODS: We performed secondary data analysis of two surveys conducted at the Magu Health and Demographic Surveillance System site, in Mwanza, Tanzania. Information on unmet need for modern contraception was derived from fertility desire and contraception use. Unmet need, HIV status, and socioeconomic and demographic variables were analysed. The percentage of women with unmet needs for modern contraception by HIV status is presented for the 2012 and 2017 surveys. Bivariate and multivariate analyses using logistic regression were used to investigate associated factors showing adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs). RESULTS: Data from 3352 and 3196 women aged 15-49 years collected in the 2012 and 2017 surveys, respectively, were analysed. The percentages of women with unmet needs for modern contraception in the 2012 and 2017 surveys were 30.9% (95% CI 29.4-32.6) and 31.6% (95% CI 30.0-33.3), respectively. The unmet need for modern contraception was 26% lower in HIV-uninfected women in 2012 (aOR = 0.74; 95% CI 0.569-0.973); p = 0.031). Risk factors for unmet need for modern contraception in 2012 were HIV uninfected (adjusted OR = 0.74; 95% CI 0.569-0.973); p = 0.031), married marital status (adjusted OR = 0.768; 95% CI 0.743-0.794); p < 0.0001), higher education (adjusted OR = 0.768; 95% CI 0.743-0.794); p < 0.0001), and taking alcohol (adjusted OR = 0.768; 95% CI 0.743-0.794); p < 0.0001). Only two factors were associated with unmet need for modern contraception in 2017: married marital status (adjusted OR = 0.46; 95% CI 0.305-0.722); p = 0.001) and women who earned for their families (aOR = 0.66; 95% CI 0.494-0.887); p = 0.006). DISCUSSION: Nearly one-third of women had an unmet need for modern contraception, which was lower in HIV-uninfected women than in WLHIV-infected women. The study has identified women whose demand for contraception has not been met: WLHIV, post marital women, women with low education and women who were reported to earn money for their families. Family planning interventions should be tailored to these groups of women.

Comparison of survival analysis approaches to modelling age at first sex among youth in Kisesa Tanzania.

BACKGROUND: Many studies analyze sexual and reproductive event data using descriptive life tables. Survival analysis has better power to estimate factors associated with age at first sex (AFS), but proportional hazards models may not be right model to use. This study used accelerated failure time (AFT) models, restricted Mean Survival time model (RMST) models, with semi and non-parametric methods to assess age at first sex (AFS), factors associated with AFS, and verify underlying assumptions for each analysis. METHODS: Self-reported sexual debut data was used from respondents 15-24 years in eight cross-sectional surveys between 1994-2016, and from adolescents' survey in an observational community study (2019-2020) in northwest Tanzania. Median AFS was estimated in each survey using non-parametric and parametric models. Cox regression, AFT parametric models (exponential, gamma, generalized gamma, Gompertz, Weibull, log-normal and log-logistic), and RMST were used to estimate and identify factors associated with AFS. The models were compared using Akaike information criterion (AIC) and Bayesian information criterion (BIC), where lower values represent a better model fit. RESULTS: The results showed that in every survey, the Cox regression model had higher AIC and BIC compared to the other models. Overall, AFT had the best fit in every survey round. The estimated median AFS using the parametric and non-parametric methods were close. In the adolescent survey, log-logistic AFT showed that females and those attending secondary and higher education level had a longer time to first sex (Time ratio (TR) = 1.03; 95% CI: 1.01-1.06, TR = 1.05; 95% CI: 1.02-1.08, respectively) compared to males and those who reported not being in school. Cell phone ownership (TR = 0.94, 95% CI: 0.91-0.96), alcohol consumption (TR = 0.88; 95% CI: 0.84-0.93), and employed adolescents (TR = 0.95, 95% CI: 0.92-0.98) shortened time to first sex. CONCLUSION: The AFT model is better than Cox PH model in estimating AFS among the young population.

Enabling data sharing and utilization for African population health data using OHDSI tools with an OMOP-common data model.

The COVID-19 pandemic has spurred the use of AI and DS innovations in data collection and aggregation. Extensive data on many aspects of the COVID-19 has been collected and used to optimize public health response to the pandemic and to manage the recovery of patients in Sub-Saharan Africa. However, there is no standard mechanism for collecting, documenting and disseminating COVID-19 related data or metadata, which makes the use and reuse a challenge. INSPIRE utilizes the Observational Medical Outcomes Partnership (OMOP) as the Common Data Model (CDM) implemented in the cloud as a Platform as a Service (PaaS) for COVID-19 data. The INSPIRE PaaS for COVID-19 data leverages the cloud gateway for both individual research organizations and for data networks. Individual research institutions may choose to use the PaaS to access the FAIR data management, data analysis and data sharing capabilities which come with the OMOP CDM. Network data hubs may be interested in harmonizing data across localities using the CDM conditioned by the data ownership and data sharing agreements available under OMOP's federated model. The INSPIRE platform for evaluation of COVID-19 Harmonized data (PEACH) harmonizes data from Kenya and Malawi. Data sharing platforms must remain trusted digital spaces that protect human rights and foster citizens' participation is vital in an era where information overload from the internet exists. The channel for sharing data between localities is included in the PaaS and is based on data sharing agreements provided by the data producer. This allows the data producers to retain control over how their data are used, which can be further protected through the use of the federated CDM. Federated regional OMOP-CDM are based on the PaaS instances and analysis workbenches in INSPIRE-PEACH with harmonized analysis powered by the AI technologies in OMOP. These AI technologies can be used to discover and evaluate pathways that COVID-19 cohorts take through public health interventions and treatments. By using both the data mapping and terminology mapping, we construct ETLs that populate the data and/or metadata elements of the CDM, making the hub both a central model and a distributed model.

Brief Report: Changes in Nocturnal Heart Rate Variability in People Living With HIV During the First Year of Antiretroviral Therapy Compared With HIV-Uninfected Community Controls.

BACKGROUND: Higher nocturnal heart rate and lower nocturnal heart rate variability (HRV) is associated with increased cardiovascular disease mortality. Longitudinal studies on nocturnal HRV in people living with HIV (PLWH) are lacking. METHODS: We conducted a 1-year prospective cohort study of adult PLWH and HIV-uninfected community controls in northwestern Tanzania. At enrollment, we collected data on cardiovascular risk factors and tested blood samples for hemoglobin, insulin, CD4 cell count, and C-reactive protein. We measured nocturnal HRV and heart rate at baseline and first-year follow-up. Mixed effect linear regression was used to determine predictors of lower HRV. RESULTS: Of the 111 enrolled participants (74 PLWH and 37 HIV-uninfected adults), 57.7% were female and the median age was 40 years. Over 1 year of follow-up, the average nocturnal heart rate was 4.5 beats/minute higher in PLWH ( P = 0.006). In the fully adjusted model (with age, sex, nocturnal heart rate, and diabetes), average nocturnal HRV was 10.5 milliseconds lower in PLWH compared with HIV-uninfected adults ( P = 0.03). Unlike with nocturnal heart rate, nocturnal HRV did not improve after 1 year of ART in PLWH or HIV-uninfected adults (fully adjusted change = -2.5 milliseconds, P = 0.45). Lower educational attainment, lesser pancreatic ß-cell function, and anemia were associated with higher HRV. CONCLUSIONS: Nocturnal parasympathetic nervous system function was persistently lower in PLWH compared with HIV-uninfected adults even after antiretroviral therapy initiation. Improving nocturnal autonomic nervous system function could be a target for cardiovascular disease prevention in PLWH.

Fertility trends by HIV status in a health and demographic surveillance study in Magu District, Tanzania, 1994-2018.

BACKGROUND: Sub-Saharan Africa (SSA) has the highest fertility rates and highest HIV disease burden globally. However, it is not clear how the rapid expansion of anti-retroviral therapy (ART) for HIV has impacted the fertility gap between HIV-infected and uninfected women. We used data from a Health and Demographic Surveillance System (HDSS) in north-western Tanzania to explore trends in fertility rates and the relationship between HIV and fertility over the 25-year period. METHODS: From 1994 to 2018, births and population denominators from the HDSS population were used to obtain age-specific fertility rates (ASFRs) and total fertility rates (TFRs). HIV status was extracted from eight rounds of epidemiologic serological surveillances (1994-2017). Fertility rates by HIV status and in different levels of ART availability were compared over time. Independent risk factors for fertility changes were examined using Cox proportional hazard models. RESULTS: There were 24,662 births from 36,814 women (15-49) who contributed a total of 145,452.5 Person-Years of follow-ups. The TFR declined from 6.5 births per woman in 1994-1998 to 4.3 births per woman in 2014-2018. The number of births per woman was 40% lower in women living with HIV than in HIV-uninfected women (4.4 vs. 6.7), although this difference narrowed over time. The fertility rate in HIV-uninfected women was 36% lower in 2013-2018 than in 1994-1998(age-adjusted HR = 0.641; 95% CI 0.613-0.673). In contrast, the fertility rate in women living with HIV was relatively unchanged over the same follow up period (age-adjusted HR = 1.099; 95% CI 0.870-1.387). CONCLUSIONS: There was a notable fertility decline among women in the study area from 1994 to 2018. Fertility remained lower in women living with HIV than in HIV-uninfected women, but the difference continued to narrow over time. These results highlight the need for more research into fertility changes, fertility desire and family planning use in Tanzanian rural communities.

Valorization of camelina oil to biobased materials and biofuels for new industrial uses: a review.

Global environmental pollution is a growing concern, especially the release of carbon dioxide from the use of petroleum derived materials which negatively impacts our environment's natural greenhouse gas level. Extensive efforts have been made to explore the conversion of renewable raw materials (vegetable oils) into bio-based products with similar or enhanced properties to those derived from petroleum. However, these edible plant oils, commonly used for human food consumption, are often not suitable raw materials for industrial applications. Hence, there is an increasing interest in exploring the use of non-edible plant oils for industrial applications. One such emerging oil seed crop is Camelina sativa, generally known as camelina, which has limited use as a food oil and so is currently being explored as a feedstock for various industrial applications in both Europe and North America. Camelina oil is highly unsaturated, making it an ideal potential AGH feedstock for the manufacture of lower carbon footprint, biobased products that reduce our dependency on petroleum resources and thus help to combat climate change. This review presents a brief description of camelina highlighting its composition and its production in comparison with traditional plant oils. The main focus is to summarize recent data on valorization of camelina oil by various chemical means, with specific emphasis on their industrial applications in biofuels, adhesives and coatings, biopolymers and bio-composites, alkyd resins, cosmetics, and agriculture. The review concludes with a discussion on current challenges and future opportunities of camelina oil valorization into various industrial products.

Role of clusters in exclusive breastfeeding practices in Tanzania: A secondary analysis study using demographic and health survey data (2015/2016).

Background: While the benefits of exclusive breastfeeding are widely acknowledged, it continues to be a rare practice. Determinants of exclusive breastfeeding in Tanzania have been studied; however, the existence and contribution of regional variability to the practice have not been explored. Methods: Tanzania demographic and health survey data for 2015/2016 were used. Information on infants aged up to 6 months was abstracted. Exclusive breastfeeding was defined using a recall of feeding practices in the past 24 h. Enumeration areas and regions were treated as random effects. Models without random effects were compared with those that incorporated random effects using the Akaike information criterion. The determinants of exclusive breastfeeding were estimated using the generalized linear mixed model with enumeration areas nested within the region. Results: The generalized linear mixed model with an enumeration area nested within a region performed better than other models. The intra-cluster variability at region and enumeration area levels was 3.7 and 24.5%, respectively. The odds of practicing exclusive breastfeeding were lower for older and male infants, for mothers younger than 18, among mothers residing in urban areas, among those who were employed by a family member or someone else, those not assisted by a nurse/midwife, and those who were not counseled on exclusive breastfeeding within 2 days post-delivery. There was no statistical evidence of an association between exclusive breastfeeding practices and the frequency of listening to the radio and watching television. When mapping the proportion of exclusive breastfeeding, a variability of the practice is seen across regions. Conclusion: There is room to improve the proportion of those who practice exclusive breastfeeding in Tanzania. Beyond individual and setting factors, this analysis shows that a quarter of the variability in exclusive breastfeeding practices is at the community level. Further studies may explore the causes of variabilities in regional and enumeration area and how it operates. Interventions to protect, promote, and support exclusive breastfeeding in Tanzania may target the environment that shapes the attitude toward exclusive breastfeeding in smaller geographical areas.

Loss to Follow-Up Risk among HIV Patients on ART in Zimbabwe, 2009-2016: Hierarchical Bayesian Spatio-Temporal Modeling.

Loss to follow-up (LTFU) is a risk factor for poor outcomes in HIV patients. The spatio-temporal risk of LTFU is useful to identify hotspots and guide policy. Secondary data on adult HIV patients attending a clinic in provinces of Zimbabwe between 2009 and 2016 were used to estimate the LTFU risk in each of the 10 provinces. A hierarchical Bayesian spatio-temporal Poisson regression model was fitted using the Integrated Nested Laplace Approximation (INLA) package with LTFU as counts adjusting for age, gender, WHO clinical stage, tuberculosis coinfection and duration on ART. The structured random effects were modelled using the conditional autoregression technique and the temporal random effects were modelled using first-order random walk Gaussian priors. The overall rate of LTFU was 22.7% (95%CI: 22.6/22.8) with Harare (50.28%) and Bulawayo (31.11%) having the highest rates. A one-year increase in the average number of years on ART reduced the risk of LTFU by 35% (relative risk (RR) = 0.651; 95%CI: 0.592-0.712). In general, the provinces with the highest exceedance LTFU risk were Matabeleland South and Matabeleland North. LTFU is one of the drawbacks of HIV prevention. Interventions targeting high-risk regions in the southern and northern regions of Zimbabwe are a priority. Community-based interventions and programmes which mitigate LTFU risk remain essential in the global HIV prevention campaign.