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Industrial mining projects can play an important role in global sustainable development if associated health risks are minimised and opportunities maximised. While a broad body of evidence from quantitative studies exists that establishes the interlinkages between mining operations and effects on public health, little research has been conducted investigating health impacts from the perspective of affected communities. This is particularly true in sub-Saharan Africa, where about a third of the remaining global mineral resources are endowed and health-related indicators for sustainable development are lagging behind. In this multi-country qualitative study, we explore community perceptions regarding impacts of industrial mining on their health and well-being. In nine study sites in Burkina Faso, Mozambique and Tanzania, we conducted 83 participatory focus group discussions with a total of 791 participants (385 men, 406 women). Our findings reveal a broad range of perceived impacts on environmental, economic and social determinants of health, with secondary health implications related to morbidity, mortality and well-being. Overall, perceived negative impacts prevailed, mainly related to environmental pollution, change in livelihoods or social disruption. Perceived positive impacts on health and well-being were related to interventions implemented by the mines such as new or improved water sources, health care facilities, roads and schools. The consistency of these findings across countries and study sites suggests a structural problem and indicates a pressing need to address health by acting on the wider determinants of health in mining regions. Participatory health impact assessment should be strengthened in host countries to foster strategic interventions, include marginalised population groups, and protect and promote the health of local communities. By including community perspectives on health before and during project implementation, policymakers can take advantage of economic opportunities while avoiding the pitfalls, bringing their communities closer to achieving good health and well-being goals by 2030 and beyond.

While a substantial amount of literature addresses the relationship between natural resources and economic growth, relatively little is known regarding the relationship between natural resource endowment and health at the population level. We construct a 5-year cross-country panel to assess the impact of natural resource rents on changes in life expectancy at birth as a proxy indicator for population health during the period 1970–2015. To estimate the causal effects of interest, we use global commodity prices as instrumental variables for natural resource rent incomes in two-stage-least squares regressions. Controlling for country and year fixed effects, we show that each standard deviation increase in resource rents results in life expectancy increase of 6.72% (CI: 2.01%, 11.44%). This corresponds to approximately one additional year of life expectancy gained over five years. We find a larger positive effect of rents on life expectancy in sub-Saharan Africa (SSA) compared to other world regions. We do not find short-term effects of rents on economic growth, but show that increases in resource rents result in sizeable increases in government revenues in the short run, which likely translate into increased spending across government sectors. This suggests that natural resources can help governments finance health and other development-oriented programs needed to improve population health.

High quality health data as collected by health management information systems (HMIS) is an important building block of national health systems. District Health Information System 2 (DHIS2) software is an innovation in data management and monitoring for strengthening HMIS that has been widely implemented in low and middle-income countries in the last decade. However, analysts and decision-makers still face significant challenges in fully utilizing the capabilities of DHIS2 data to pursue national and international health agendas. We aimed to (i) identify the most relevant health indicators captured by DHIS2 for tracking progress towards the Sustainable Development goals in sub-Saharan African countries and (ii) present a clear roadmap for improving DHIS2 data quality and consistency, with a special focus on immediately actionable solutions. We identified that key indicators in child and maternal health (e.g. vaccine coverage, maternal deaths) are currently being tracked in the DHIS2 of most countries, while other indicators (e.g. HIV/AIDS) would benefit from streamlining the number of indicators collected and standardizing case definitions. Common data issues included unreliable denominators for calculation of incidence, differences in reporting among health facilities, and programmatic differences in data quality. We proposed solutions for many common data pitfalls at the analysis level, including standardized data cleaning pipelines, k-means clustering to identify high performing health facilities in terms of data quality, and imputation methods. While we focus on immediately actionable solutions for DHIS2 analysts, improvements at the point of data collection are the most rigorous. By investing in improving data quality and monitoring, countries can leverage the current global attention on health data to strengthen HMIS and progress towards national and international health priorities.

BackgroundVerbal autopsy (VA) plays a vital role in providing cause-of-death information in places where such information is not available. Many low-/middle-income countries (LMICs) including Tanzania are still struggling to yield quality and adequate cause-of-death data for Civil Registration and Vital Statistics (CRVS).ObjectiveTo highlight challenges and recommendations for VA implementation to support LMICs yield quality and adequate mortality statistics for informed decisions on healthcare interventions.DesignCross-sectional study.Study settingIringa region in Tanzania.Participants41 people including 33 community health workers, 1 VA national coordinator, 5 national task force members, 1 VA regional coordinator and 1 member of the VA data management team.ResultsThe perceived challenges of key informants include a weak death notification system, lengthy VA questionnaire, poor data quality and inconsistent responses, lack of clarity in the inclusion criteria, poor commitment to roles and responsibilities, poor coordination, poor financial mechanism and no or delayed feedback to VA implementers. Based on these findings, we recommend the following strategies for effective adaptation and use of VAs: (1) reinforce or implement legislative procedures towards the legal requirement for death notification. (2) Engage key stakeholders in the overall implementation of VAs. (3) Build capacity for data collection, monitoring, processing and use of VA data. (4) Improve the VA questionnaire and quality control mechanism for optimal use in data collection. (5) Create sustainable financing mechanisms and institutionalisation of VA implementation. (6) Integrating VA Implementation in CRVS.ConclusionEffective VA implementation demands through planning, stakeholder engagement, upskilling of local experts and fair compensation for interviewers. Such coordinated endeavours will overcome systemic, technical and behavioural challenges hindering VA’s successful implementation.

BackgroundApproximately 70% of deaths in Tanzania occur outside health facilities and are often unreported or lack cause of death (COD) information. Consequently, health planning relies on data representing only 10%–15% of the population. To address this gap, Tanzania integrated verbal autopsy (VA) into its civil registration and vital statistics (CRVS) to generate more comprehensive COD data for mortality reporting. This manuscript shares Tanzania’s VA implementation experience from 2017 to 2020, focusing on its integration into the CRVS system, and assesses its capacity to generate accurate and representative mortality data to guide health policies and planning.MethodsVA implementation followed a phased approach: (1) a pilot and pretest phase covering 10 wards (urban-to-rural ratio 1:3) and achieving 38.3% data completeness, (2) a demonstration phase covering 106 wards (urban-to-rural ratio 1:3), with data completeness at 22.7% and (3) a national scale-up phase, which is currently underway. Data were collected using a standardised WHO VA questionnaire administered via tablets. CODs were determined using physician- and computer-coded methods.ResultsThe concordance (R-squared) between physician-coded and computer-coded VA (PCVA and CCVA) for cause specific-mortality fraction was 0.83 for InsilicoVA, 0.70 for InterVA5 and 0.47 for Tariff. Communicable diseases accounted for 45.6% of deaths, with a higher burden in rural areas, whereas non-communicable diseases (40.2%) were more prevalent in urban areas. The leading CODs were HIV/AIDS, cardiac diseases, malaria, tuberculosis and diabetes.ConclusionsVA plays a pivotal role in generating comprehensive mortality statistics, particularly in low-resource settings. Its integration into CRVS systems with support from CCVA provides a scalable and sustainable solution to address critical data gaps and improve public health interventions, thus better enabling evidence-based health policies and planning in Tanzania.

Rural households in East Africa rely on local markets, but the influence of market food diversity and household food purchase diversity on diets has not been well‐characterized. We quantify the associations among market food diversity, household food purchase diversity and dietary diversity of mothers, fathers and children in rural Tanzania. This study uses baseline data from a randomized controlled trial, Engaging Fathers for Effective Child Nutrition and Development in Tanzania. We used the 10 food groups for women's dietary diversity to assess the seasonal availability of nutritious foods in 79 markets. Using data from 957 rural households in two districts in Mara, Tanzania, we measured household food purchase diversity over the previous month and dietary diversity among children (6–23 months), mothers and fathers. Overall, 63% of markets sold all 10 food groups throughout the year, indicating high‐market food diversity and minimal seasonality. However, only 33% of women and 35% of children met dietary diversity recommendations. Households that reported higher purchasing power (0.14, p < 0.001), lived within 30 min of a market (0.36, p = 0.001) and had access to a highly diverse market (0.37, p = 0.01) purchased a higher diversity of foods. In turn, food purchase diversity was positively associated with the dietary diversity of mothers (p < 0.001) and children 9–23 months (p < 0.001) but not fathers (p = 0.56). Interventions must account for food availability and access in local markets, and promoting diverse food purchases may be an effective strategy to improve women's and children's diets in rural areas. We quantified the association between market food diversity, household food purchase diversity and the diets of mothers, fathers and children in rural Tanzania. Market food diversity was associated with higher food purchase diversity, which in turn was associated with improved dietary diversity for mothers and children but not fathers. Key messages Local markets in rural Mara, Tanzania, had unexpectedly high food diversity with minimal seasonality. Physical and economic access to diverse food markets was associated with households' food purchase, which was in turn associated with women's and children's consumption of diverse diets. Fathers' diets were more diverse and not associated with the diversity of food purchases for consumption at home. The metric developed here—household food purchase diversity—captures food diversity that could contribute to nutrient intake of children and adults. Intervention design must account for the broader food environment in rural settings.

Background Monitoring medically certified causes of death is essential to shape national health policies, track progress to Sustainable Development Goals, and gauge responses to epidemic and pandemic disease. The combination of electronic health information systems with new methods for data quality monitoring can facilitate quality assessments and help target quality improvement. Since 2015, Tanzania has been upgrading its Civil Registration and Vital Statistics system including efforts to improve the availability and quality of mortality data. Methods We used a computer application (ANACONDA v4.01) to assess the quality of medical certification of cause of death (MCCD) and ICD-10 coding for the underlying cause of death for 155,461 deaths from health facilities from 2014 to 2018. From 2018 to 2019, we continued quality analysis for 2690 deaths in one large administrative region 9 months before, and 9 months following MCCD quality improvement interventions. Interventions addressed governance, training, process, and practice. We assessed changes in the levels, distributions, and nature of unusable and insufficiently specified codes, and how these influenced estimates of the leading causes of death. Results 9.7% of expected annual deaths in Tanzania obtained a medically certified cause of death. Of these, 52% of MCCD ICD-10 codes were usable for health policy and planning, with no significant improvement over 5 years. Of certified deaths, 25% had unusable codes, 17% had insufficiently specified codes, and 6% were undetermined causes. Comparing the before and after intervention periods in one Region, codes usable for public health policy purposes improved from 48 to 65% within 1 year and the resulting distortions in the top twenty cause-specific mortality fractions due to unusable causes reduced from 27.4 to 13.5%. Conclusion Data from less than 5% of annual deaths in Tanzania are usable for informing policy. For deaths with medical certification, errors were prevalent in almost half. This constrains capacity to monitor the 15 SDG indicators that require cause-specific mortality. Sustainable quality assurance mechanisms and interventions can result in rapid improvements in the quality of medically certified causes of death. ANACONDA provides an effective means for evaluation of such changes and helps target interventions to remaining weaknesses.

Over the past 70 years, significant advances have been made in determining the causes of death in populations not served by official medical certification of cause at the time of death using a technique known as Verbal Autopsy (VA). VA involves an interview of the family or caregivers of the deceased after a suitable bereavement interval about the circumstances, signs and symptoms of the deceased in the period leading to death. The VA interview data are then interpreted by physicians or, more recently, computer algorithms, to assign a probable cause of death. VA was originally developed and applied in field research settings. This paper traces the evolution of VA methods with special emphasis on the World Health Organization's (WHO)'s efforts to standardize VA instruments and methods for expanded use in routine health information and vital statistics systems in low- and middle-income countries (LMICs). These advances in VA methods are culminating this year with the release of the 2022 WHO Standard Verbal Autopsy (VA) Toolkit. This paper highlights the many contributions the late Professor Peter Byass made to the current VA standards and methods, most notably, the development of InterVA, the most commonly used automated computer algorithm for interpreting data collected in the WHO standard instruments, and the capacity building in low- and middle-income countries (LMICs) that he promoted. This paper also provides an overview of the methods used to improve the current WHO VA standards, a catalogue of the changes and improvements in the instruments, and a mapping of current applications of the WHO VA standard approach in LMICs. It also provides access to tools and guidance needed for VA implementation in Civil Registration and Vital Statistics Systems at scale.

Industrial mining transforms local landscapes, including important health determinants like clean water and sanitation. In this paper, we combined macro-level quantitative and micro-level qualitative data to show how mining projects affect water infrastructures and ultimately the health of affected communities. Although we observed a positive trend of water infrastructure in mining settings, surrounding communities are also characterized by water scarcity and degradation of water quality. The video at the core of this publication showcases inter-linkages of the findings obtained at both the macro- and the micro-levels, embedding our results in a geospatial context. While mining projects can have positive impacts on the development of local water infrastructure, improved management of negative impacts of mining projects is needed for promoting ‘Good health and well-being’ and ‘Clean water and sanitation’ as promulgated by the Sustainable Development Goals of the 2030 Agenda.

It is well established that social determinants influence people’s health and well-being. Yet, limited attention is given to the fact that social determinants are, in turn, the result of political determinants. The political struggle between different ideas, interests and power over public policies, that is, how societies shall function, results in formal and informal structures that work as a ‘sorting machine’: they determine how societies (re)distribute material resources and opportunities among their members, creating societal classes that face disparate health outcomes. Their visible and measurable characteristics are then labelled ‘social determinants’. Improving public health, therefore, needs engaging with the political determinants.We contribute to this broader vision with a process-oriented, interdisciplinary framework. It first operationalises the analysis of political determinants of health to understand how, in a specific public health concern, politics shapes policy processes and causes differential health outcomes. Building on these insights, the framework then supports strategic engagement with the politics of policy processes, using agile methods to identify and promote more equitable and politically feasible policy options.We illustrate our approach by reporting on an interdisciplinary 6-year research project in Burkina Faso, Ghana, Mozambique and Tanzania, examining how structural determinants contribute to unequal public health outcomes in industrial mining areas. Trade-offs between attracting mining firms and safeguarding public health have led to a patchwork of national legislation, global governance regimes and voluntary commitments, inviting an eclectic consideration of public health industrial mining. For instance, among over 560 mining projects across Africa, more than 90% of impact assessments were inaccessible. In the few that were, public health is only marginally considered, disproportionately harming vulnerable populations.To strengthen the ‘structural competence’ and policy relevance of the public health discipline, our results suggest an institutionalised cooperation with political science in curricula, training and applied research.