Mapping child growth failure in Africa between 2000 and 2015.

Insufficient growth during childhood is associated with poor health outcomes and an increased risk of death. Between 2000 and 2015, nearly all African countries demonstrated improvements for children under 5 years old for stunting, wasting, and underweight, the core components of child growth failure. Here we show that striking subnational heterogeneity in levels and trends of child growth remains. If current rates of progress are sustained, many areas of Africa will meet the World Health Organization Global Targets 2025 to improve maternal, infant and young child nutrition, but high levels of growth failure will persist across the Sahel. At these rates, much, if not all of the continent will fail to meet the Sustainable Development Goal target-to end malnutrition by 2030. Geospatial estimates of child growth failure provide a baseline for measuring progress as well as a precision public health platform to target interventions to those populations with the greatest need, in order to reduce health disparities and accelerate progress.

Mapping diphtheria-pertussis-tetanus vaccine coverage in Africa, 2000-2016: a spatial and temporal modelling study.

BACKGROUND: Routine childhood vaccination is among the most cost-effective, successful public health interventions available. Amid substantial investments to expand vaccine delivery throughout Africa and strengthen administrative reporting systems, most countries still require robust measures of local routine vaccine coverage and changes in geographical inequalities over time. METHODS: This analysis drew from 183 surveys done between 2000 and 2016, including data from 881 268 children in 49 African countries. We used a Bayesian geostatistical model calibrated to results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017, to produce annual estimates with high-spatial resolution (5 ×    5 km) of diphtheria-pertussis-tetanus (DPT) vaccine coverage and dropout for children aged 12-23 months in 52 African countries from 2000 to 2016. FINDINGS: Estimated third-dose (DPT3) coverage increased in 72·3% (95% uncertainty interval [UI] 64·6-80·3) of second-level administrative units in Africa from 2000 to 2016, but substantial geographical inequalities in DPT coverage remained across and within African countries. In 2016, DPT3 coverage at the second administrative (ie, district) level varied by more than 25% in 29 of 52 countries, with only two (Morocco and Rwanda) of 52 countries meeting the Global Vaccine Action Plan target of 80% DPT3 coverage or higher in all second-level administrative units with high confidence (posterior probability ≥95%). Large areas of low DPT3 coverage (≤50%) were identified in the Sahel, Somalia, eastern Ethiopia, and in Angola. Low first-dose (DPT1) coverage (≤50%) and high relative dropout (≥30%) together drove low DPT3 coverage across the Sahel, Somalia, eastern Ethiopia, Guinea, and Angola. INTERPRETATION: Despite substantial progress in Africa, marked national and subnational inequalities in DPT coverage persist throughout the continent. These results can help identify areas of low coverage and vaccine delivery system vulnerabilities and can ultimately support more precise targeting of resources to improve vaccine coverage and health outcomes for African children. FUNDING: Bill & Melinda Gates Foundation.

Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories.

BACKGROUND: Understanding potential trajectories in health and drivers of health is crucial to guiding long-term investments and policy implementation. Past work on forecasting has provided an incomplete landscape of future health scenarios, highlighting a need for a more robust modelling platform from which policy options and potential health trajectories can be assessed. This study provides a novel approach to modelling life expectancy, all-cause mortality and cause of death forecasts -and alternative future scenarios-for 250 causes of death from 2016 to 2040 in 195 countries and territories. METHODS: We modelled 250 causes and cause groups organised by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) hierarchical cause structure, using GBD 2016 estimates from 1990-2016, to generate predictions for 2017-40. Our modelling framework used data from the GBD 2016 study to systematically account for the relationships between risk factors and health outcomes for 79 independent drivers of health. We developed a three-component model of cause-specific mortality: a component due to changes in risk factors and select interventions; the underlying mortality rate for each cause that is a function of income per capita, educational attainment, and total fertility rate under 25 years and time; and an autoregressive integrated moving average model for unexplained changes correlated with time. We assessed the performance by fitting models with data from 1990-2006 and using these to forecast for 2007-16. Our final model used for generating forecasts and alternative scenarios was fitted to data from 1990-2016. We used this model for 195 countries and territories to generate a reference scenario or forecast through 2040 for each measure by location. Additionally, we generated better health and worse health scenarios based on the 85th and 15th percentiles, respectively, of annualised rates of change across location-years for all the GBD risk factors, income per person, educational attainment, select intervention coverage, and total fertility rate under 25 years in the past. We used the model to generate all-cause age-sex specific mortality, life expectancy, and years of life lost (YLLs) for 250 causes. Scenarios for fertility were also generated and used in a cohort component model to generate population scenarios. For each reference forecast, better health, and worse health scenarios, we generated estimates of mortality and YLLs attributable to each risk factor in the future. FINDINGS: Globally, most independent drivers of health were forecast to improve by 2040, but 36 were forecast to worsen. As shown by the better health scenarios, greater progress might be possible, yet for some drivers such as high body-mass index (BMI), their toll will rise in the absence of intervention. We forecasted global life expectancy to increase by 4·4 years (95% UI 2·2 to 6·4) for men and 4·4 years (2·1 to 6·4) for women by 2040, but based on better and worse health scenarios, trajectories could range from a gain of 7·8 years (5·9 to 9·8) to a non-significant loss of 0·4 years (-2·8 to 2·2) for men, and an increase of 7·2 years (5·3 to 9·1) to essentially no change (0·1 years [-2·7 to 2·5]) for women. In 2040, Japan, Singapore, Spain, and Switzerland had a forecasted life expectancy exceeding 85 years for both sexes, and 59 countries including China were projected to surpass a life expectancy of 80 years by 2040. At the same time, Central African Republic, Lesotho, Somalia, and Zimbabwe had projected life expectancies below 65 years in 2040, indicating global disparities in survival are likely to persist if current trends hold. Forecasted YLLs showed a rising toll from several non-communicable diseases (NCDs), partly driven by population growth and ageing. Differences between the reference forecast and alternative scenarios were most striking for HIV/AIDS, for which a potential increase of 120·2% (95% UI 67·2-190·3) in YLLs (nearly 118 million) was projected globally from 2016-40 under the worse health scenario. Compared with 2016, NCDs were forecast to account for a greater proportion of YLLs in all GBD regions by 2040 (67·3% of YLLs [95% UI 61·9-72·3] globally); nonetheless, in many lower-income countries, communicable, maternal, neonatal, and nutritional (CMNN) diseases still accounted for a large share of YLLs in 2040 (eg, 53·5% of YLLs [95% UI 48·3-58·5] in Sub-Saharan Africa). There were large gaps for many health risks between the reference forecast and better health scenario for attributable YLLs. In most countries, metabolic risks amenable to health care (eg, high blood pressure and high plasma fasting glucose) and risks best targeted by population-level or intersectoral interventions (eg, tobacco, high BMI, and ambient particulate matter pollution) had some of the largest differences between reference and better health scenarios. The main exception was sub-Saharan Africa, where many risks associated with poverty and lower levels of development (eg, unsafe water and sanitation, household air pollution, and child malnutrition) were projected to still account for substantive disparities between reference and better health scenarios in 2040. INTERPRETATION: With the present study, we provide a robust, flexible forecasting platform from which reference forecasts and alternative health scenarios can be explored in relation to a wide range of independent drivers of health. Our reference forecast points to overall improvements through 2040 in most countries, yet the range found across better and worse health scenarios renders a precarious vision of the future-a world with accelerating progress from technical innovation but with the potential for worsening health outcomes in the absence of deliberate policy action. For some causes of YLLs, large differences between the reference forecast and alternative scenarios reflect the opportunity to accelerate gains if countries move their trajectories toward better health scenarios-or alarming challenges if countries fall behind their reference forecasts. Generally, decision makers should plan for the likely continued shift toward NCDs and target resources toward the modifiable risks that drive substantial premature mortality. If such modifiable risks are prioritised today, there is opportunity to reduce avoidable mortality in the future. However, CMNN causes and related risks will remain the predominant health priority among lower-income countries. Based on our 2040 worse health scenario, there is a real risk of HIV mortality rebounding if countries lose momentum against the HIV epidemic, jeopardising decades of progress against the disease. Continued technical innovation and increased health spending, including development assistance for health targeted to the world's poorest people, are likely to remain vital components to charting a future where all populations can live full, healthy lives. FUNDING: Bill & Melinda Gates Foundation.

Zero-Dose Childhood Vaccination Status in Rural Democratic Republic of Congo: Quantifying the Relative Impact of Geographic Accessibility and Attitudes toward Vaccination.

Despite efforts to increase childhood vaccination coverage in the Democratic Republic of the Congo (DRC), approximately 20% of infants have not started their routine immunization schedule (zero-dose). The present study aims to evaluate the relative influence of geospatial access to health facilities and caregiver perceptions of vaccines on the vaccination status of children in rural DRC. Pooled data from two consecutive nationwide immunization surveys conducted in 2022 and 2023 were used. Geographic accessibility was assessed based on travel time from households to their nearest health facility using the AccessMod 5 model. Caregiver attitudes to vaccination were assessed using the survey question "How good do you think vaccines are for your child?" We used logistic regression to assess the relationship between geographic accessibility, caregiver attitudes toward vaccination, and their child's vaccination status. Geographic accessibility to health facilities was high in rural DRC, with 88% of the population living within an hour's walk to a health facility. Responding that vaccines are "Bad, Very Bad, or Don't Know" relative to "Very Good" for children was associated with a many-fold increased odds of a zero-dose status (ORs 69.3 [95%CI: 63.4-75.8]) compared to the odds for those living 60+ min from a health facility, relative to <5 min (1.3 [95%CI: 1.1-1.4]). Similar proportions of the population fell into these two at-risk categories. We did not find evidence of an interaction between caregiver attitude toward vaccination and travel time to care. While geographic access to health facilities is crucial, caregiver demand appears to be a more important driver in improving vaccination rates in rural DRC.

A consolidated and geolocated facility list in Senegal from triangulating secondary data.

Having a geolocated list of all facilities in a country - a "master facility list" (MFL) - can provide critical inputs for health program planning and implementation. To the best of our knowledge, Senegal has never had a centralized MFL, though many data sources currently exist within the broader Senegalese data landscape that could be leveraged and consolidated into a single database - a critical first step toward building a full MFL. We collated 12,965 facility observations from 16 separate datasets and lists in Senegal, and applied matching algorithms, manual checking and revisions as needed, and verification processes to identify unique facilities and triangulate corresponding GPS coordinates. Our resulting consolidated facility list has a total of 4,685 facilities, with 2,423 having at least one set of GPS coordinates. Developing approaches to leverage existing data toward future MFL establishment can help bridge data demands and inform more targeted approaches for completing a full facility census based on areas and facility types with the lowest coverage. Going forward, it is crucial to ensure routine updates of current facility lists, and to strengthen government-led mechanisms around such data collection demands and the need for timely data for health decision-making.

Innovations in social health delivery to advance equitable pediatric and adolescent life course health development: A review and roadmap forward.

Recognizing the influence of social determinants on health and development, health care has increasingly advocated for interventions that target upstream factors as part of routine pediatric care delivery. In response, clinic-based social risk screening and referral programs have proliferated wherein patients are screened for health-related social needs (HRSNs, such as food and housing insecurity) and referred to community-based organizations (CBOs) and social service providers to address those needs. In recent years, an array of digital platforms, known as Social Health Access and Referral Platforms (SHARPs), have emerged to facilitate the scale and implementation of these models amidst growing system demand. Recent evidence on the effectiveness of social risk screen and refer models and SHARPs has been mixed, giving researchers pause and calling for more nuanced understanding of the limitations of such models, especially for promoting child and family health. Design thinking informed by the Life-Course Health Development (LCHD) framework provides a particularly useful lens for synthesizing emerging limitations of such models in the pediatric context, given the dynamic and developmentally-driven circumstances that shape family health and well-being in the early life course. By (1) focusing on addressing deficits-based social risks, (2) scoping to act upon narrow, downstream needs, (3) timing to react to social needs that have already caused harm rather than preventing them, and (4) limiting scale to individual-by-individual responses rather than structural and population-wide interventions, the current design of prevailing social risk screen and refer programs fundamentally limits their potential impact and misses opportunities to improve health equity over the life course. How can health care, social care, and technology partners move forward in collaboration with families and communities to better support equitable lifelong health and social development? In this narrative review, we will summarize the current design, implementation, and limitations of the predominant social risk screen and refer approach in the context of early childhood and adolescent care delivery. We then will apply LCHD principles to advance and improve on this approach from a reactionary focus towards a Family Journey Model that better supports life course health development.

Implementation of cross-sector partnerships: a description of implementation factors related to addressing social determinants to reduce racial disparities in adverse birth outcomes.

Introduction: Traditional perinatal care alone cannot address the social and structural determinants that drive disparities in adverse birth outcomes. Despite the wide acceptance of partnerships between healthcare systems and social service agencies to address this challenge, there needs to be more research on the implementation factors that facilitate (or hinder) cross-sector partnerships, particularly from the perspective of community-based organizations. This study aimed to integrate the views of healthcare staff and community-based partner organizations to describe the implementation of a cross-sector partnership designed to address social and structural determinants in pregnancy. Methods: We used a mixed methods design (in-depth interviews and social network analysis) to integrate the perspectives of healthcare clinicians and staff with those of community-based partner organizations to identify implementation factors related to cross-sector partnerships. Results: We identified seven implementation factors related to three overarching themes: relationship-centered care, barriers and facilitators of cross-sector partnerships, and strengths of a network approach to cross-sector collaboration. Findings emphasized establishing relationships between healthcare staff, patients, and community-based partner organizations. Conclusion: This study provides practical insights for healthcare organizations, policymakers, and community organizations that aim to improve access to social services among historically marginalized perinatal populations.

A Framework for Cross-Sector Partnerships to Address Childhood Adversity and Improve Life Course Health.

Childhood adversity and its structural causes drive lifelong and intergenerational inequities in health and well-being. Health care systems increasingly understand the influence of childhood adversity on health outcomes but cannot treat these deep and complex issues alone. Cross-sector partnerships, which integrate health care, food support, legal, housing, and financial services among others, are becoming increasingly recognized as effective approaches address health inequities. What principles should guide the design of cross-sector partnerships that address childhood adversity and promote Life Course Health Development (LCHD)? The complex effects of childhood adversity on health development are explained by LCHD concepts, which serve as the foundation for a cross-sector partnership that optimizes lifelong health. We review the evolution of cross-sector partnerships in health care to inform the development of an LCHD-informed partnership framework geared to address childhood adversity and LCHD. This framework outlines guiding principles to direct partnerships toward life course-oriented action: (1) proactive, developmental, and longitudinal investment; (2) integration and codesign of care networks; (3) collective, community and systemic impact; and (4) equity in praxis and outcomes. Additionally, the framework articulates foundational structures necessary for implementation: (1) a shared cross-sector theory of change; (2) relational structures enabling shared leadership, trust, and learning; (3) linked data and communication platforms; and (4) alternative funding models for shared savings and prospective investment. The LCHD-informed cross-sector partnership framework presented here can be a guide for the design and implementation of cross-sector partnerships that effectively address childhood adversity and advance health equity through individual-, family-, community-, and system-level intervention.

International COVID-19 mortality forecast visualization: covidcompare.io.

COVID-19 mortality forecasting models provide critical information about the trajectory of the pandemic, which is used by policymakers and public health officials to guide decision-making. However, thousands of published COVID-19 mortality forecasts now exist, many with their own unique methods, assumptions, format, and visualization. As a result, it is difficult to compare models and understand under which circumstances a model performs best. Here, we describe the construction and usability of covidcompare.io, a web tool built to compare numerous forecasts and offer insight into how each has performed over the course of the pandemic. From its launch in December 2020 to June 2021, we have seen 4600 unique visitors from 85 countries. A study conducted with public health professionals showed high usability overall as formally assessed using a Post-Study System Usability Questionnaire. We find that covidcompare.io is an impactful tool for the comparison of international COVID-19 mortality forecasting models.

Interest in Clinic-Based Financial Services among Low-Income Prenatal Patients and its Association with Health-Related Social Risk Factors.

BACKGROUND: Poverty and financial stress affect prenatal health and well-being as well as early childhood development. This study sought to examine interest in clinic-based financial services to address financial stress in low-income, Medicaid-enrolled prenatal patients and its relationship with self-reported social risks. METHODS: We conducted a cross-sectional study of patients at a large safety-net prenatal clinic. Participants completed a written survey on interest in linkage to financial services, poverty-related financial stress, difficulty affording social needs, and interest in services to address material hardships. We compared interest in financial and social needs services by level of financial stress using multivariate regression. RESULTS: Respondents (N = 108) were entirely Medicaid-enrolled, with a majority identifying as Hispanic/Latinx (57%) or Black/African American (20%). Sixty-four percent indicated interest in connection to any of the financial services surveyed. Interest was highest in employment (52%), savings and budgeting (49%), job training/adult education (49%), and financial counseling (48%) services. Individuals with high financial stress, compared to those with low financial stress, expressed a higher level of interest in financial services (aRR = 1.61 [95% CI 1.12-2.39]). Interest in financial services was associated with difficulty affording social needs (aRR = 2.24 [95% CI 1.33-4.43]) and interest in services addressing social needs (aRR = 1.45 [95% CI 1.13-1.92]). CONCLUSION: In this study of low-income, Medicaid-insured prenatal patients, there was a high degree of interest in clinic-based financial services. Integrating financial services into prenatal health care appears to be an approach that low-income patients would be interested in to directly address poverty and financial stress.

Pediatric Household Transmission of Severe Acute Respiratory Coronavirus-2 Infection-Los Angeles County, December 2020 to February 2021.

This brief report presents transmission rates from a prospective study of 15 households with pediatric index cases of severe acute respiratory coronavirus-2 in Los Angeles County from December 2020 to February 2021. Our findings support ongoing evidence that transmission from pediatric index cases to household contacts is frequent but can be mitigated with practicing well-documented control measures at home, including isolation, masking and good hand hygiene.