Overview of the Lives Saved Tool (LiST)

Constrained optimization: evaluating possible packages of community health interventions with competing resource requirements in Galmudug, Somalia

Investment in community health worker (CHW) programs has allowed health systems to reach previously underserved rural and remote populations. As a result, CHWs are often burdened with responsibilities to deliver large packages of services, at times without sufficient human, financial, or health resources. To design a community-level program that saves maternal and newborn lives while operating within resource limitations, we used constrained optimization (a mathematical process for finding the solution to a stated objective while accounting for listed requirements) to construct a model for select villages in Galmudug State, Somalia. After establishing the resource requirements for delivering 25 evidence-based maternal and neonatal interventions, we used the Lives Saved Tool and optimization techniques to determine the package of care that leads to the most projected lives saved. With a cadre of 1450 female health workers and a budget of $435 000 for maternal and neonatal health commodities and programming over 1 year, we calculated that the optimized set of interventions for Galmudug could avert 15% of the 4132 projected maternal and neonatal deaths in 2024. We also conducted sensitivity analyses to show how the optimal combination of interventions and the number of lives saved change as the resource levels change. The model provides practitioners with a new tool and accompanying approach to evaluate possible packages of community health interventions with competing resource requirements.

An individual-based modelling study estimating the impact of maternity service delivery on health in Malawi

Maternal and perinatal morbidity and mortality remain high in Malawi, partially due to gaps in the coverage and quality of health services. We developed an individual-based model of maternal and perinatal health and healthcare in Malawi, situated in a 'whole-health system, all-disease' framework (Thanzi La Onse). We modelled sixteen scenarios estimating the impact of current and improved coverage and quality of antenatal, intrapartum, and postnatal services from 2023 to 2030. Whilst current service delivery is inferred to avert morbidity and mortality, the largest reductions in the stillbirth, maternal and neonatal mortality rates were observed when the use and quality of all services was maximised concurrently (a 10%, 52% and 57% reduction respectively). When services were considered in isolation, generally, increased coverage without quality improvement did not impact mortality or DALYs. In only three scenarios was a sufficient reduction in neonatal mortality observed to achieve target 3.2 of the United Nation's Sustainable Development Goals (SDG), and in no scenarios was a reduction in maternal mortality sufficient to achieve SDG target 3.1 observed, reaffirming that system wide investments are essential to achieve these goals.

Impact of health intervention coverage on reducing maternal mortality in 126 low- and middle-income countries: a Lives Saved Tool modelling study

BACKGROUND

There is a continued and urgent need to address the stagnation of the global maternal mortality ratio (MMR), especially for low- and middle-income countries (LMICs). We aimed to assess the impact of scaling up health intervention coverage on reducing MMR under four scenarios for 126 LMICs.

METHODS

We conducted the modelling study to estimate MMR and additional maternal lives saved by intervention by 2030 for 126 LMICs using the Lives Saved Tool (LiST). We applied four scenarios to assess the impact of scaling up health intervention coverage with no scale-up (no change), a modest scale-up (increased by 2% per year), a substantial scale-up (increased by 5% per year), and universal coverage (coverage reached 95% by 2030). In sensitivity analysis, with the current trend, we assumed that coverage of each intervention remained unchanged from 2024, with MMR changing according to the annual percentage change (APC) of 2015-2020.

RESULTS

Among the 126 LMICs, 31.7% (40/126) countries showed an increase in MMR, and 38.1% (48/126) stalled on the reduction of MMR from 2015 to 2020. With a modest, substantial, or universal scale-up, the 2030 average MMR would be 172.1 (117.6-262.9), 139.8 (95.6-213.5) or 98.6 (67.8-149.7), not reaching the SDG Target 3.1. Additional maternal lives saved by scaling up the coverage of health interventions were mainly clustered in the African Region, the Southeast Asia Region, and the Eastern Mediterranean Region. Compared with other included interventions, uterotonics for postpartum hemorrhage, assisted vaginal delivery and cesarean delivery played more important roles in reducing maternal mortality.

CONCLUSIONS

The study findings highlighted that even under a substantial scale-up of intervention coverage or scaling up to universal coverage of interventions, it would be difficult for the 126 LMICs to achieve the SDG Target 3.1 on time. Optimizing the allocation of health resources, promoting health equality, taking more decisive national, regional and global actions are urgently needed for LMICs to reduce MMR and reach the SDG Target 3.1.

Projecting the impact of a national strategy to accelerate stunting prevention in East Nusa Tenggara, Indonesia, using the Lives Saved Tool

Stunting remains a critical public health issue in East Nusa Tenggara (ENT), Indonesia, with prevalence rates among the highest in the country despite national efforts to reduce its occurrence. The aim of this study was to project the impact of the 2018-2024 National Strategy to Accelerate Stunting Prevention on children under five years old in ENT, using the Lives Saved Tool. A cross-sectional approach was employed, integrating data from various sources, including the 2020 Census of Indonesia, the Global Data Lab-Area Database, the Central Bureau of Statistics Republic Indonesia, the National Socioeconomic Survey, the 2017 Indonesia Demographic and Health Survey, the 2018 Basic Health Research, and the 2021 Indonesia Nutrition Status Survey. The analysis considered three scenarios: (1) a baseline scenario reflecting ENT's 2017 coverage, maintained through 2028; (2) a scenario assuming Indonesia achieves the Health Plan Action Stunting targets; and (3) a projection of stunting rates based on ENT-specific coverage. Under scenarios 1 and 2, the prevalence of stunting was projected to decrease from 40.04% in 2018 to 39.82% and 39.78%, respectively, by 2028, with scenario 3 reflecting a similar trend. The findings revealed a sharp increase in the number of stunting cases averted among children under five years old between 2017 and 2021, followed by a more gradual decline, culminating in the 2028 projections: 2,249 children (scenario 2), 2,130 children (scenario 3), and 1,966 children (scenario 1). Breastfeeding promotion emerged as the most impactful intervention, accounting for over half of the total stunting cases averted under both Indonesia-wide and ENT-specific coverage scenarios. This was followed by interventions such as multiple micronutrient supplementation and vitamin A supplementation. The study highlights that reducing the prevalence of stunting among children requires a comprehensive prioritization of intervention strategies. The implementation of breastfeeding promotion, combined with appropriate complementary feeding practices, is expected to contribute significantly to achieving the sustainable development goal targets.

Maternal health planning and prioritization in Chad: developing a supportive tool

The Republic of Chad has one of the highest rates of maternal mortality in the world. With scarce resources to respond to competing demands, pragmatic evidence-based planning tools are needed to aid planning and support priority setting. This action research aimed to develop a tool to support maternal health (MH) planning and prioritization decisions and identify priority regions/provinces for intervention in Chad based on aggregate MH coverage gap scores (Target-Coverage = Coverage Gap). A rapid review was conducted to identify key indicators and relevant national targets. The 2019 Multiple Indicator Cluster Survey and other national surveys were the data sources for selected indicators at the provincial level. Aggregate MH coverage gaps were calculated and displayed using geographic information system software to visualize variations by province. Eleven key informant interviews (KIIs) and six focus group discussions (FGDs) were conducted with clinicians and administrators to understand existing MH planning, prioritization, and maternal mortality risks in Chad. Wide provincial variation in aggregate MH coverage gaps was identified (mean score 374.3, SD: 77.4). Indicators contributing the most to coverage gaps include emergency obstetric care, adolescent births, tetanus vaccination, and delivery by skilled health personnel. Two weighting scenarios for the coverage gap scores are also considered. KIIs and FGDs revealed that existing MH planning in Chad differs provincially and by health system level, with no clear prioritization processes identified. Main themes regarding MH risks reported by stakeholders included challenges relating to the health system, policy landscape, country and population-specific factors, along with specific MH threats. Current centralized planning approaches may benefit from greater consideration of provincial differences to support more efficient and equitable resource distribution. This multi-indicator assessment offers an adaptable approach for evidence-based MH resource allocation to prioritize subnational areas with worst health indicators in resource-limited settings, although further research is needed to test its impact.

Optimal allocation of antenatal and young child nutrition interventions: an individual-based global burden of disease calibrated microsimulation

BACKGROUND

Undernutrition remains a global crisis and is a focus of Sustainable Development Goals. While there are multiple known, effective interventions, complex interactions between prevention and treatment and resource constraints can lead to difficulties in allocating funding. Simulation studies that use in silico simulation can help illuminate the interactions between interventions and provide insight into the cost-effectiveness of alternative packages of options.

METHODS

We developed an individual-based microsimulation model based on the Global Burden of Disease (GBD) 2021 study data to test a range of nutrition interventions, including antenatal interventions (iron and folic acid, multiple micronutrients, and balanced energy protein supplementation) and child interventions (treatment for severe acute malnutrition, treatment for moderate acute malnutrition, and wasting prevention with small-quantity lipid-based nutrient supplements). We also developed an analytic approach to process the results of the microsimulation and identify the optimal intervention funding allocation for a given budget size. We use Ethiopia as an example in this paper.

RESULTS

In our illustrative example of Ethiopia, the reallocation of the baseline budget to minimize disability-adjusted life years (DALYs) resulted in first funding the antenatal multiple micronutrients to their maximum coverage and then funding treatment for severe child acute malnutrition. Relative to the baseline allocation, the reallocation optimized to minimizing DALYs resulted in 592,000 fewer annual DALYs, constituting an 8.3% reduction in total DALYs in Ethiopia. For budgets larger than the baseline, our model recommended funding first targeted moderate acute malnutrition treatment, second universal moderate acute malnutrition treatment, third wasting prevention with small-quantity lipid-based nutrient supplements, and fourth balanced energy protein supplementation.

CONCLUSIONS

Our simulation is a novel model for estimating optimal allocation of spending on antenatal and child health nutrition interventions which accounts for the interaction between preventive and therapeutic approaches. Our illustrative results show that an optimized reallocation of current spending can substantially improve pregnancy-related and child health without additional funding. We hope this model can add validity and confidence to prior results to aid stakeholders in funding decisions.

Mathematical modelling to estimate the impact of maternal and perinatal healthcare services and interventions on health in sub-Saharan Africa: A scoping review

INTRODUCTION

Mathematical modelling is a commonly utilised tool to predict the impact of policy on health outcomes globally. Given the persistently high levels of maternal and perinatal morbidity and mortality in sub-Saharan Africa, mathematical modelling is a potentially valuable tool to guide strategic planning for health and improve outcomes.

METHODS

The aim of this scoping review was to explore the characteristics of mathematical models and modelling studies evaluating the impact of maternal and/or perinatal healthcare interventions or services on health-related outcomes in the region. A search across three databases was conducted on 2nd November 2023 which returned 8660 potentially relevant studies, from which 60 were included in the final review. Characteristics of these studies, the interventions which were evaluated, the models utilised, and the analyses conducted were extracted and summarised.

RESULTS

Findings suggest that the popularity of modelling within this field is increasing over time with most studies published after 2015 and that population-based, deterministic, linear models were most frequently utilised, with the Lives Saved Tool being applied in over half of the reviewed studies (n = 34, 57%). Much less frequently (n = 6) models utilising system-thinking approaches, such as individual-based modelling or systems dynamics modelling, were developed and applied. Models were most applied to estimate the impact of interventions or services on maternal mortality (n = 34, 57%) or neonatal mortality outcomes (n = 39, 65%) with maternal morbidity (n = 4, 7%) and neonatal morbidity (n = 6, 10%) outcomes and stillbirth reported on much less often (n = 14, 23%).

DISCUSSION

Going forward, given that healthcare delivery systems have long been identified as complex adaptive systems, modellers may consider the advantages of applying systems-thinking approaches to evaluate the impact of maternal and perinatal health policy. Such approaches allow for a more realistic and explicit representation of the systems- and individual- level factors which impact the effectiveness of interventions delivered within health systems.

Impact of scaling up health intervention coverage on reducing maternal mortality in 26 low- and middle-income countries: A modelling study

BACKGROUND

Prioritising actions is urgently needed to address the stagnation of the global maternal mortality ratio (MMR). As most maternal deaths occur in low- and middle-income countries (LMICs), we aimed to assess the impact of scaling up health intervention coverage on reducing MMR under four scenarios for 26 LMICs.

METHODS

We conducted a modelling study to estimate the MMR and additional maternal lives saved by intervention by 2030 for 26 LMICs using the Lives Saved Tool (LiST). We used four scenarios to assess the impact of scaling up health intervention coverage by no scale-up (no change), modest scale-up (increased by 2% per year), substantial scale-up (increased by 5% per year), and universal coverage (coverage reached 95% by 2030). We divided the selected 26 countries into three groups according to their MMR levels in 2020.

RESULTS

Among 26 LMICs, six (23.1%) countries showed an increase in MMRs and 13 (50.0%) stalled on the reduction of MMR from 2015 to 2020. Under a substantial scale-up of coverage or scaling up to universal coverage, the average MMR in 2030 of 26 LMICs would be 62.8 or 52.8, reaching the Sustainable Development Goal (SDG) 3.1. Caesarean delivery, uterotonics for postpartum haemorrhage, and assisted vaginal delivery had a more important role in this reduction compared to other interventions.

CONCLUSIONS

Scaling up the coverage of health interventions is critical for reducing MMRs. If a substantial scale-up or scaling up to universal coverage of continuous maternity interventions from preconception to postpartum period can be achieved, LMICs in Southeast Asia and Western Pacific regions could reach the SDG 3.1 on time.

Using the Lives Saved Tool to inform global nutrition advocacy

Background

The global nutrition community has been interested in investigating investment strategies that could be used to promote an increased focus and investment in nutrition programming in low- and middle-income countries.

Methods

The Lives Saved Tool (LiST) was used to evaluate lives saved and the costs of nutrition interventions in nine high-burden countries. In this case study, we detail the analyses that were conducted with LiST and how the results were packaged to develop Nourish the Future - a five-year proposal for the US government to scale up lifesaving malnutrition interventions.

Results

Scaling up a proposed package of critical nutrition interventions including micronutrient supplementation for pregnant women, breastfeeding support, Vitamin A supplementation for children, and treatments for moderate and severe acute malnutrition is an effective and cost-effective way to avert millions of child deaths and stillbirths.

Conclusions

This is one of the few case studies that outlines how a nutrition modeling tool (in this case LiST) was used to engage in a prioritisation exercise to inform a US-based advocacy ask. We share reflections and provide practical insights into user motivation and preferences for existing and future modeling tool developers. This case study also emphasises how integral evidence translation and strategic advocacy are to ensure the use of the modeling results.

Association of parental level of education and child factors on length-for-age indicator among socially vulnerable children aged 6-24 months from a Brazilian state using structural equation modelling

This cross-sectional study employs structural equation modelling (sEM) to explore both direct and indirect effects of parental level of education and child individual factors on the length-for-age outcomes in children aged 6-24 months assisted by the Bolsa Família Program in the State of Alagoas. A total of 1448 children were analysed by the sEM technique. A negative standardised direct effect (sDE) of the children's younger age (sDE: -0·06; P = 0·017), the use of bottle feeding (sDE: -0·11; P < 0·001) and lack of a minimum acceptable diet (sDE: -0·09; P < 0·001) on the length-for-age indicator was found. Being female (SDE: 0·08; P = 0·001), a higher birth weight (SDE: 0·33; P < 0·001), being ever breastfed (sdE: 0·07; P = 0·004) and a higher level of parental education (SDE: 0·09; P < 0·001) showed a positive SDE effect on the child's length-for-age. The model also demonstrated a negative standardised indirect effect (SIE) of the sweet beverage consumption (SIE: -0·08; P = 0·003) and a positive effect of being ever breastfed (SIE: 0·06; P = 0·017) on the child's length-for-age through parental level of education as a mediator. This research underscores the crucial role of proper feeding practices and provides valuable insights for the development of targeted interventions, policies and programmes to improve nutritional well-being and promote adequate linear growth and development among young children facing similar challenges.

Adapting the log quadratic model to estimate age- and cause-specific mortality among neonates

INTRODUCTION

Estimates for cause-specific mortality for neonates are generally available for all countries for neonates overall (0 to 28 days). However, cause-specific mortality is generally not being estimated at higher age resolution for neonates, despite evidence of heterogeneity in the causes of deaths during this period. We aimed to use the adapted log quadratic model in a setting where verbal autopsy was the primary means of determining cause of death.

METHODS

We examined the timing and causes of death among a cohort of neonates in rural Nepal followed as part of the Nepal Oil Massage Study (NOMS). We adapted methods defined by Wilmoth et al (2012) and Guillot et al. (2022) to estimate age and cause-specific mortality among neonates. We used cross validation to estimate the accuracy of this model, holding out each three month period. We took the average cross validation across hold out as our measure of model performance and compared to a standard approach which did not account for the heterogeneity in cause-specific mortality rate within this age group.

RESULTS

There were 957 neonates in the NOMS cohort with known age and cause of death. We estimated an average cross-validation error of 0.9 per 1000 live births for mortality due to prematurity in the first week, and 1.1 for mortality due to birth asphyxia, compared to the standard approach, having error 7.4 and 7.8 per 1000 live births, respectively. Generally mortality rates for less common causes such as congenital malformations and pneumonia were estimated with higher cross-validation error.

CONCLUSIONS

The stability and precision of these estimates compare favorably with similar estimates developed with higher quality cause-specific mortality surveillance from China, demonstrating that reliably estimating causes of mortality at high resolution is possible for neonates in low resources areas.

Modeled impacts of bouillon fortification with micronutrients on child mortality in Senegal, Burkina Faso, and Nigeria

Micronutrient interventions can reduce child mortality. By applying Micronutrient Intervention Modeling methods in Senegal, Burkina Faso, and Nigeria, we estimated the impacts of bouillon fortification on apparent dietary adequacy of vitamin A and zinc among children and folate among women. We then used the Lives Saved Tool to predict the impacts of bouillon fortification with ranges of vitamin A, zinc, and folic acid concentrations on lives saved among children 6-59 months of age. Fortification at 250 µg vitamin A/g and 120 µg folic acid/g was predicted to substantially reduce vitamin A- and folate-attributable deaths: 65% for vitamin A and 92% for folate (Senegal), 36% for vitamin A and 74% for folate (Burkina Faso), and >95% for both (Nigeria). Zinc fortification at 5 mg/g would avert 48% (Senegal), 31% (Burkina Faso), and 63% (Nigeria) of zinc-attributable deaths. The addition of all three nutrients at 30% of Codex nutrient reference values in 2.5 g bouillon was predicted to save an annual average of 293 child lives in Senegal (3.5% of deaths from all causes among children 6-59 months of age), 933 (2.1%) in Burkina Faso, and 18,362 (3.7%) in Nigeria. These results, along with evidence on program feasibility and costs, can help inform fortification program design discussions.

Health impact and cost-effectiveness of expanding routine immunization coverage in India through Intensified Mission Indradhanush

Many children do not receive a full schedule of childhood vaccines, yet there is limited evidence on the cost-effectiveness of strategies for improving vaccination coverage. Evidence is even scarcer on the cost-effectiveness of strategies for reaching 'zero-dose children', who have not received any routine vaccines. We evaluated the cost-effectiveness of periodic intensification of routine immunization (PIRI), a widely applied strategy for increasing vaccination coverage. We focused on Intensified Mission Indradhanush (IMI), a large-scale PIRI intervention implemented in India in 2017-2018. In 40 sampled districts, we measured the incremental economic cost of IMI using primary data, and used controlled interrupted time-series regression to estimate the incremental vaccination doses delivered. We estimated deaths and disability-adjusted life years (DALYs) averted using the Lives Saved Tool and reported cost-effectiveness from immunization programme and societal perspectives. We found that, in sampled districts, IMI had an estimated incremental cost of 2021US$13.7 (95% uncertainty interval: 10.6 to 17.4) million from an immunization programme perspective and increased vaccine delivery by an estimated 2.2 (-0.5 to 4.8) million doses over a 12-month period, averting an estimated 1413 (-350 to 3129) deaths. The incremental cost from a programme perspective was $6.21 per dose ($2.80 to dominated), $82.99 per zero-dose child reached ($39.85 to dominated), $327.63 ($147.65 to dominated) per DALY averted, $360.72 ($162.56 to dominated) per life-year saved and $9701.35 ($4372.01 to dominated) per under-5 death averted. At a cost-effectiveness threshold of 1× per-capita GDP per DALY averted, IMI was estimated to be cost-effective with 90% probability. This evidence suggests IMI was both impactful and cost-effective for improving vaccination coverage, though there is a high degree of uncertainty in the results. As vaccination programmes expand coverage, unit costs may increase due to the higher costs of reaching currently unvaccinated children.

Challenges in reducing maternal and neonatal mortality in Niger: an in-depth case study

INTRODUCTION

Recent modelled estimates suggest that Niger made progress in maternal mortality since 2000. However, neonatal mortality has not declined since 2012 and maternal mortality estimates were based on limited data. We researched the drivers of progress and challenges.

METHODS

We reviewed two decades of health policies, analysed mortality trends from United Nations data and six national household surveys between 1998 and 2021 and assessed coverage and inequalities of maternal and newborn health indicators. Quality of care was evaluated from health facility surveys in 2015 and 2019 and emergency obstetric assessments in 2011 and 2017. We determined the impact of intervention coverage on maternal and neonatal lives saved between 2000 and 2020. We interviewed 31 key informants to understand the factors underpinning policy implementation.

RESULTS

Empirical maternal mortality ratio declined from 709 to 520 per 100 000 live births during 2000-2011, while neonatal mortality rate declined from 46 to 23 per 1000 live births during 2000-2012 then increased to 43 in 2018. Inequalities in neonatal mortality were reduced across socioeconomic and demographic strata. Key maternal and newborn health indicators improved over 2000-2012, except for caesarean sections, although the overall levels were low. Interventions delivered during childbirth saved most maternal and newborn lives. Progress came from health centre expansion, emergency care and the 2006 fee exemptions policy. During the past decade, challenges included expansion of emergency care, continued high fertility, security issues, financing and health workforce. Social determinants saw minimal change.

CONCLUSIONS

Niger reduced maternal and neonatal mortality during 2000-2012, but progress has stalled. Further reductions require strategies targeting comprehensive care, referrals, quality of care, fertility reduction, social determinants and improved security nationwide.

Effective multi-sectoral approach for rapid reduction in maternal and neonatal mortality: the exceptional case of Bangladesh

BACKGROUND

Bangladesh experienced impressive reductions in maternal and neonatal mortality over the past several decades with annual rates of decline surpassing 4% since 2000. We comprehensively assessed health system and non-health factors that drove Bangladesh's success in mortality reduction.

METHODS

We operationalised a comprehensive conceptual framework and analysed available household surveys for trends and inequalities in mortality, intervention coverage and quality of care. These include 12 household surveys totalling over 1.3 million births in the 15 years preceding the surveys. Literature and desk reviews permitted a reconstruction of policy and programme development and financing since 1990. These were supplemented with key informant interviews to understand implementation decisions and strategies.

RESULTS

Bangladesh prioritised early population policies to manage its rapidly growing population through community-based family planning programmes initiated in mid-1970s. These were followed in the 1990s and 2000s by priority to increase access to health facilities leading to rapid increases in facility delivery, intervention coverage and access to emergency obstetric care, with large contribution from private facilities. A decentralised health system organisation, from communities to the central level, openness to private for-profit sector growth, and efficient financing allocation to maternal and newborn health enabled rapid progress. Other critical levers included poverty reduction, women empowerment, rural development, and culture of data generation and use. However, recent empirical data suggest a slowing down of mortality reductions.

CONCLUSION

Bangladesh demonstrated effective multi-sectoral approach and persistent programming, testing and implementation to achieve rapid gains in maternal and neonatal mortality reduction. The slowing down of recent mortality trends suggests that the country will need to revise its strategies to achieve the Sustainable Development Goals. As fertility reached replacement level, further gains in maternal and neonatal mortality will require prioritising universal access to quality facility delivery, and addressing inequalities, including reaching the rural poor.

Learning from success: the main drivers of the maternal and newborn health transition in seven positive-outlier countries and implications for future policies and programmes

Currently, about 8% of deaths worldwide are maternal or neonatal deaths, or stillbirths. Maternal and neonatal mortality have been a focus of the Millenium Development Goals and the Sustainable Development Goals, and mortality levels have improved since the 1990s. We aim to answer two questions: What were the key drivers of maternal and neonatal mortality reductions seen in seven positive-outlier countries from 2000 to the present? How generalisable are the findings?We identified positive-outlier countries with respect to maternal and neonatal mortality reduction since 2000. We selected seven, and synthesised experience to assess the contribution of the health sector to the mortality reduction, including the roles of access, uptake and quality of services, and of health system strengthening. We explored the wider context by examining the contribution of fertility declines, and the roles of socioeconomic and human development, particularly as they affected service use, the health system and fertility. We analysed government levers, namely policies and programmes implemented, investments in data and evidence, and political commitment and financing, and we examined international inputs. We contextualised these within a mortality transition framework.We found that strategies evolved over time as the contacts women and neonates had with health services increased. The seven countries tended to align with global recommendations but could be distinguished in that they moved progressively towards implementing their goals and in scaling-up services, rather than merely adopting policies. Strategies differed by phase in the transition framework-one size did not fit all.

Predicting the potential impact of scaling up four pneumonia interventions on under-five pneumonia mortality: A prospective Lives Saved Tool (LiST) analysis for Bangladesh, Chad, and Ethiopia

Background

Pneumonia remains the leading cause of mortality in under-five children outside the neonatal period. Progress has slowed down in the last decade, necessitating increased efforts to scale up effective pneumonia interventions.

Methods

We used the Lives Saved Tool (LiST), a modelling software for child mortality in low- and middle-income settings, to prospectively analyse the potential impact of upscaling pneumonia interventions in Bangladesh, Chad, and Ethiopia from 2023 to 2030. We included Haemophilus influenzae type B (Hib) vaccination, pneumococcal conjugate vaccine (PCV), oral antibiotics, pulse oximetry, and oxygen as pneumonia interventions in our analysis. Outcomes of interest were the number of pneumonia deaths averted, the proportion of deaths averted by intervention, and changes in the under-five mortality rate.

Findings

We found that 19 775 lives of children under-five could be saved in Bangladesh, 76 470 in Chad, and 97 343 in Ethiopia by scaling intervention coverages to ≥90% by 2030. Our estimated reductions in pneumonia deaths among children under five range from 44.61% to 57.91% in the respective countries. Increased coverage of oral antibiotics, pulse oximetry, and oxygen show similar effects in all three countries, averting between 18.80% and 23.65% of expected pneumonia deaths. Scaling-up PCV has a prominent effect, especially in Chad, where it could avert 14.04% of expected pneumonia deaths. Under-five mortality could be reduced by 1.42 per 1000 live births in Bangladesh, 22.52 per 1000 live births in Chad, and 5.48 per 1000 live births in Ethiopia.

Conclusions

This analysis shows the high impact of upscaling pneumonia interventions. The lack of data regarding coverage indicators is a barrier for further research, policy, and implementation, all requiring increased attention.

Barriers to promoting breastfeeding in primary health care in Mexico: a qualitative perspective

Objective

This article aimed to identify the main barriers related to promoting and counseling breastfeeding (BF) at the Primary Health Care (PHC) in Mexico.

Methodology

A qualitative study with a phenomenological approach was carried out in 88 health centers of the Ministry of Health in the states of Chihuahua, Oaxaca, Chiapas, Veracruz, Mexico, and Yucatan. From September to November 2021, we interviewed 88 key health professionals (HPs) (physicians, nurses, nutritionists, and others) from the PHC of the Ministry of Health in Mexico and 80 parents of children under 5 years old. In addition, nine focus groups were conducted with parents and caregivers. The data obtained were triangulated with information from focus groups and semi-structured interviews.

Results

Of the total interviews, 43.2% (n = 38) were nurses, 29.5% (n = 26) were physicians, 19.3% (n = 17) were nutritionists, and the rest were other health professionals. In the group of users, 97.6% (n = 121) were women. We identified contextual barriers, such as the lack of well-trained health professionals and the scarcest nutrition professionals, as material resources in the health units, without mentioning the low user attendance at their control consultations. Furthermore, we identified barriers related to the orientation and promotion of breastfeeding in health units, including a lack of specific strategies, ineffective communication, and the recommendations of commercial milk formulas.

Conclusion

The results presented reflect the reality of Mexico in relation to BF, making it urgent to take immediate action to improve the quality of nutritional care related to the promotion and orientation of BF at the PHC.

Global health economics: The Equitable Impact Sensitive Tool (EQUIST) - development, validation, implementation and evaluation of impact (2011 to 2022)

Background

The Equitable Impact Sensitive Tool (EQUIST) was developed to address the limitations of the traditional cost-effectiveness analysis (CEA) in global health, which often overlooked equity considerations. Its primary aim was to create more effective and efficient health systems by explicitly incorporating equity as a key driver in health policy decisions. This was done in response to the recognition that, while CEA helped reduce mortality rates through interventions like childhood vaccinations, it was insufficient in addressing growing inequalities in health, especially in low-and-middle-income countries (LMICs).

Methods

The development of EQUIST involved a multi-stage process which began in 2011 with the recognition of the need for a more nuanced approach than CEA alone. This led to a proposal for creating a tool that balanced cost-effectiveness with equity. The conceptual framework, developed between March and May 2012, included assessments of intervention efficiency by equity strata, effectiveness, impact, and cost-effectiveness. Key to EQUIST's development was its integration with other data science platforms, notably the Lives Saved Tool and the Marginal Budgeting for Bottlenecks tool, allowing EQUIST to draw on comprehensive data sets and thus enabling a more detailed analysis of health interventions' impacts across different socio-economic strata.

Results

EQUIST was validated in 2012 through applications in five representative countries, demonstrating its ability to identify more equitable and cost-effective health interventions which targeted vulnerable populations, leading to more lives saved compared to traditional methods. It was then used to develop investment cases for the Global Financing Facility, resulting in significant funding being made available for maternal and child health programmes. Consequently, EQUIST directly influenced the development of national health policies and resource allocations in over 26 African countries.

Conclusions

EQUIST has proven to be a valuable tool in developing health policies that are both cost-effective and equitable. In the future, it will be further integrated with other tools and expanded in scope to address broader health issues, including adolescent health and human immunodeficiency virus/acquired immunodeficiency syndrome programme planning. Overall, EQUIST represents a paradigm shift in global health economics, emphasising the importance of equity alongside cost-effectiveness in health policy decisions. Its development and implementation have had a tangible impact on health outcomes, particularly in LMICs, where it has been instrumental in reducing maternal and child mortality while addressing health inequities.

Investment case for small and sick newborn care in Tanzania: systematic analyses

BACKGROUND

Small and sick newborn care (SSNC) is critical for national neonatal mortality reduction targets by 2030. Investment cases could inform implementation planning and enable coordinated resource mobilisation. We outline development of an investment case for Tanzania to estimate additional financing for scaling up SSNC to 80% of districts as part of health sector strategies to meet the country's targets.

METHODS

We followed five steps: (1) reviewed national targets, policies and guidelines; (2) modelled potential health benefits by increased coverage of SSNC using the Lives Saved Tool; (3) estimated setup and running costs using the Neonatal Device Planning and Costing Tool, applying two scenarios: (A) all new neonatal units and devices with optimal staffing, and (B) half new and half modifying, upgrading, or adding resources to existing neonatal units; (4) calculated budget impact and return on investment (ROI) and (5) identified potential financing opportunities.

RESULTS

Neonatal mortality rate was forecast to fall from 20 to 13 per 1000 live births with scale-up of SSNC, superseding the government 2025 target of 15, and close to the 2030 Sustainable Development Goal 3.2 target of <12. At 85% endline coverage, estimated cumulative lives saved were 36,600 by 2025 and 80,000 by 2030. Total incremental costs were estimated at US$166 million for scenario A (US$112 million set up and US$54 million for running costs) and US$90 million for scenario B (US$65 million setup and US$25 million for running costs). Setup costs were driven by infrastructure (83%) and running costs by human resources (60%). Cost per capita was US$0.93 and the ROI is estimated to be between US$8-12 for every dollar invested.

CONCLUSIONS

ROI for SSNC is higher compared to other health investments, noting many deaths averted followed by full lifespan. This is conservative since disability averted is not included. Budget impact analysis estimated a required 2.3% increase in total government health expenditure per capita from US$40.62 in 2020, which is considered affordable, and the government has already allocated additional funding. Our proposed five-step SSNC investment case has potential for other countries wanting to accelerate progress.

Return on investments in the Health Extension Program in Ethiopia

BACKGROUND

Since 2003, the government of Ethiopia has trained and deployed more than 42,000 Health Extension Workers across the country to provide primary healthcare services. However, no research has assessed the return on investments into human resources for health in this setting. This study aims to fill this gap by analyzing the return on investment within the context of the Ethiopian Health Extension Program.

METHODS

We collected data on associated costs and benefits attributed to the Health Extension Program from primary and secondary sources. Primary sources included patient exit interviews, surveys with Health Extension Workers and other health professionals, key informant interviews, and focus groups conducted in the following regions: Amhara, Oromia, Tigray, and the Southern Nations Nationalities and Peoples' Region. Secondary sources consisted of financial and administrative reports gathered from the Ministry of Health and its subsidiaries, as well as data accessed through the Lives Saved Tool. A long-run return on investment analysis was conducted considering program costs (personnel, recurrent, and capital investments) in comparison to benefits gained through improved productivity, equity, empowerment, and employment.

FINDINGS

Between 2008-2017, Health Extension Workers saved 50,700 maternal and child lives. Much of the benefits were accrued by low income, less educated, and rural women who had limited access to services at higher level health centers and hospitals. Regional return ranged from $1.27 to $6.64, with an overall return on investment in the range of $1.59 to $3.71.

CONCLUSION

While evidence of return on investments are limited, results from the Health Extension Program in Ethiopia show promise for similar large, sustainable system redesigns. However, this evidence needs to be contextualized and adapted in different settings to inform policy and practice. The Ethiopian Health Extension Program can serve as a model for other nations of a large-scale human resources for health program containing strong economic benefits and long-term sustainability through successful government integration.

The impact of antibiotic treatment for syphilis, chlamydia, and gonorrhoea during pregnancy on birth outcomes: A systematic review and meta-analysis

Background

Sexually transmissible infections are important causes of loss of health and lives in women and infants worldwide. This paper presents the methods and results of a systematic review that focuses on the impact of antibiotic treatment for syphilis, chlamydia, and gonorrhoea during pregnancy on birth outcomes for the Lives Saved Tool (LiST).

Methods

We searched PubMed, Embase, Cochrane Libraries, Global Health and Global Index Medicus for articles available until May 23rd, 2022. The search criteria focused on the impact of treatment for the three sexually transmitted infection among pregnant women. Nearly all the articles found were non-randomized studies.

Results

Treatment for pregnant women with active syphilis reduced the risk of preterm birth by 52% (95% CI = 42%-61%; 11 043 participants, 15 studies; low quality); stillbirth by 79% (95% CI = 65%-88%; 14 667 participants, eight studies; low quality); and low birth weight by 50% (95% CI = 41%-58%; 9778 participants, seven studies; moderate quality). Treatment for pregnant women with chlamydia infection reduced the risk of preterm birth by 42% (95% CI = 7%-64%; 5468 participants, seven studies; low quality) and might reduce the risk of low birth weight by 40% (95% CI = 0%-64%; 4684 participants, four studies; low quality). No studies provided data on treatment of gonorrhoea therefore no meta-analysis was conducted.

Conclusions

Because few studies adjusted for potential confounding factors, the overall quality of evidence was considered low. However, given the consistent and large effects, we recommend updating the estimated effect of timely detection and treatment for syphilis on preterm birth and stillbirth in the LiST model. More research is required to ascertain the effect of antibiotic treatment for chlamydia and gonorrhoea infection in pregnancy.

Evidence-based antenatal interventions to reduce the incidence of small vulnerable newborns and their associated poor outcomes

A package of care for all pregnant women within eight scheduled antenatal care contacts is recommended by WHO. Some interventions for reducing and managing the outcomes for small vulnerable newborns (SVNs) exist within the WHO package and need to be more fully implemented, but additional effective measures are needed. We summarise evidence-based antenatal and intrapartum interventions (up to and including clamping the umbilical cord) to prevent vulnerable births or improve outcomes, informed by systematic reviews. We estimate, using the Lives Saved Tool, that eight proven preventive interventions (multiple micronutrient supplementation, balanced protein and energy supplementation, low-dose aspirin, progesterone provided vaginally, education for smoking cessation, malaria prevention, treatment of asymptomatic bacteriuria, and treatment of syphilis), if fully implemented in 81 low-income and middle-income countries, could prevent 5·202 million SVN births (sensitivity bounds 2·398-7·903) and 0·566 million stillbirths (0·208-0·754) per year. These interventions, along with two that can reduce the complications of preterm (<37 weeks' gestation) births (antenatal corticosteroids and delayed cord clamping), could avert 0·476 million neonatal deaths (0·181-0·676) per year. If further research substantiates the preventive effect of three additional interventions (supplementation with omega-3 fatty acids, calcium, and zinc) on SVN births, about 8·369 million SVN births (2·398-13·857) and 0·652 million neonatal deaths (0·181-0·917) could be avoided per year. Scaling up the eight proven interventions and two intrapartum interventions would cost about US$1·1 billion in 2030 and the potential interventions would cost an additional $3·0 billion. Implementation of antenatal care recommendations is urgent and should include all interventions that have proven effects on SVN babies, within the context of access to family planning services and addressing social determinants of health. Attaining high effective coverage with these interventions will be necessary to achieve global targets for the reduction of low birthweight births and neonatal mortality, and long-term benefits on growth and human capital.

A simulation-based comparative effectiveness analysis of policies to improve global maternal health outcomes

The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) to less than 70 maternal deaths per 100,000 live births by 2030, with no individual country exceeding 140. However, on current trends the goals are unlikely to be met. We used the empirically calibrated Global Maternal Health microsimulation model, which simulates individual women in 200 countries and territories to evaluate the impact of different interventions and strategies from 2022 to 2030. Although individual interventions yielded fairly small reductions in maternal mortality, integrated strategies were more effective. A strategy to simultaneously increase facility births, improve the availability of clinical services and quality of care at facilities, and improve linkages to care would yield a projected global MMR of 72 (95% uncertainty interval (UI) = 58-87) in 2030. A comprehensive strategy adding family planning and community-based interventions would have an even larger impact, with a projected MMR of 58 (95% UI = 46-70). Although integrated strategies consisting of multiple interventions will probably be needed to achieve substantial reductions in maternal mortality, the relative priority of different interventions varies by setting. Our regional and country-level estimates can help guide priority setting in specific contexts to accelerate improvements in maternal health.

Cost-effectiveness of a direct to beneficiary mobile communication programme in improving reproductive and child health outcomes in India

INTRODUCTION

Kilkari is the largest maternal messaging programme of its kind globally. Between its initiation in 2012 in Bihar and its transition to the government in 2019, Kilkari was scaled to 13 states across India and reached over 10 million new and expectant mothers and their families. This study aims to determine the cost-effectiveness of exposure to Kilkari as compared with no exposure across 13 states in India.

METHODS

The study was conducted from a programme perspective using an analytic time horizon aligned with national scale-up efforts from December 2014 to April 2019. Economic costs were derived from the financial records of implementing partners. Data on incremental changes in the practice of reproductive maternal newborn and child health (RMNCH) outcomes were drawn from an individually randomised controlled trial in Madhya Pradesh and inputted into the Lives Saved Tool to yield estimates of maternal and child lives saved. One-way and probabilistic sensitivity analyses were carried out to assess uncertainty.

RESULTS

Inflation adjusted programme costs were US$8.4 million for the period of December 2014-April 2019, corresponding to an average cost of US$264 298 per year of implementation in each state. An estimated 13 842 lives were saved across 13 states, 96% among children and 4% among mothers. The cost per life saved ranged by year of implementation and with the addition of new states from US$392 ($385-$393) to US$953 ($889-$1092). Key drivers included call costs and incremental changes in coverage for key RMNCH practices.

CONCLUSION

Kilkari is highly cost-effective using a threshold of India's national gross domestic product of US$1998. Study findings provide important evidence on the cost-effectiveness of a national maternal messaging programme in India.

TRIAL REGISTRATION

NCT03576157.

A new mixed agent-based network and compartmental simulation framework for joint modeling of related infectious diseases- application to sexually transmitted infections

Background

A model that jointly simulates infectious diseases with common modes of transmission can serve as a decision-analytic tool to identify optimal intervention combinations for overall disease prevention. In the United States, sexually transmitted infections (STIs) are a huge economic burden, with a large fraction of the burden attributed to HIV. Data also show interactions between HIV and other sexually transmitted infections (STIs), such as higher risk of acquisition and progression of co-infections among persons with HIV compared to persons without. However, given the wide range in prevalence and incidence burdens of STIs, current compartmental or agent-based network simulation methods alone are insufficient or computationally burdensome for joint disease modeling. Further, causal factors for higher risk of coinfection could be both behavioral (i.e., compounding effects of individual behaviors, network structures, and care behaviors) and biological (i.e., presence of one disease can biologically increase the risk of another). However, the data on the fraction attributed to each are limited.

Methods

We present a new mixed agent-based compartmental (MAC) framework for jointly modeling STIs. It uses a combination of a new agent-based evolving network modeling (ABENM) technique for lower-prevalence diseases and compartmental modeling for higher-prevalence diseases. As a demonstration, we applied MAC to simulate lower-prevalence HIV in the United States and a higher-prevalence hypothetical Disease 2, using a range of transmission and progression rates to generate burdens replicative of the wide range of STIs. We simulated sexual transmissions among heterosexual males, heterosexual females, and men who have sex with men (men only and men and women). Setting the biological risk of co-infection to zero, we conducted numerical analyses to evaluate the influence of behavioral factors alone on disease dynamics.

Results

The contribution of behavioral factors to risk of coinfection was sensitive to disease burden, care access, and population heterogeneity and mixing. The contribution of behavioral factors was generally lower than observed risk of coinfections for the range of hypothetical prevalence studied here, suggesting potential role of biological factors, that should be investigated further specific to an STI.

Conclusions

The purpose of this study is to present a new simulation technique for jointly modeling infectious diseases that have common modes of transmission but varying epidemiological features. The numerical analysis serves as proof-of-concept for the application to STIs. Interactions between diseases are influenced by behavioral factors, are sensitive to care access and population features, and are likely exacerbated by biological factors. Social and economic conditions are among key drivers of behaviors that increase STI transmission, and thus, structural interventions are a key part of behavioral interventions. Joint modeling of diseases helps comprehensively simulate behavioral and biological factors of disease interactions to evaluate the true impact of common structural interventions on overall disease prevention. The new simulation framework is especially suited to simulate behavior as a function of social determinants, and further, to identify optimal combinations of common structural and disease-specific interventions.

Reducing inequities in maternal and child health in rural Guatemala through the CBIO+ Approach of Curamericas: 5. Mortality assessment

BACKGROUND

The Curamericas/Guatemala Maternal and Child Health Project, 2011-2015, implemented the Census-Based, Impact-Oriented Approach, the Care Group Approach, and the Community Birthing Center Approach. Together, this expanded set of approaches is known as CBIO+. This is the fifth of 10 papers in our supplement describing the Project and the effectiveness of the CBIO+ Approach. This paper assesses causes, levels, and risk factors for mortality along with changes in mortality.

METHODS

The Project maintained Vital Events Registers and conducted verbal autopsies for all deaths of women of reproductive age and under-5 children. Mortality rates and causes of death were derived from these data. To increase the robustness of our findings, we also indirectly estimated mortality decline using the Lives Saved Tool (LiST).

FINDINGS

The leading causes of maternal and under-5 mortality were postpartum hemorrhage and pneumonia, respectively. Home births were associated with an eight-fold increased risk of both maternal (p = 0.01) and neonatal (p = 0.00) mortality. The analysis of vital events data indicated that maternal mortality declined from 632 deaths per 100,000 live births in Years 1 and 2 to 257 deaths per 100,000 live birth in Years 3 and 4, a decline of 59.1%. The vital events data revealed no observable decline in neonatal or under-5 mortality. However, the 12-59-month mortality rate declined from 9 deaths per 1000 live births in the first three years of the Project to 2 deaths per 1000 live births in the final year. The LiST model estimated a net decline of 12, 5, and 22% for maternal, neonatal and under-5 mortality, respectively.

CONCLUSION

The baseline maternal mortality ratio is one of the highest in the Western hemisphere. There is strong evidence of a decline in maternal mortality in the Project Area. The evidence of a decline in neonatal and under-5 mortality is less robust. Childhood pneumonia and neonatal conditions were the leading causes of under-5 mortality. Expanding access to evidence-based community-based interventions for (1) prevention of postpartum hemorrhage, (2) home-based neonatal care, and (3) management of childhood pneumonia could help further reduce mortality in the Project Area and in similar areas of Guatemala and beyond.

Health and economic benefits of achieving contraceptive and maternal health targets in Small Island Developing States in the Pacific and Caribbean

INTRODUCTION

Reducing unmet need for modern contraception and expanding access to quality maternal health (MH) services are priorities for improving women's health and economic empowerment. To support investment decisions, we estimated the additional cost and expected health and economic benefits of achieving the United Nations targets of zero unmet need for modern contraceptive choices and 95% coverage of MH services by 2030 in select Small Island Developing States.

METHODS

Five Pacific (Kiribati, Samoa, Solomon Islands, Tonga and Vanuatu) and four Caribbean (Barbados, Guyana, Jamaica and Saint Lucia) countries were considered based on population survey data availability. For each country, the Lives Saved Tool was used to model costs, health outcomes and economic benefits for two scenarios: business-as-usual (BAU) (coverage maintained) and coverage-targets-achieved, which scaled linearly from 2022 (following COVID-19 disruptions) coverage of evidence-based family planning and MH interventions to reach United Nations targets, including modern contraceptive methods and access to complete antenatal, delivery and emergency care. Unintended pregnancies, maternal deaths, stillbirths and newborn deaths averted by the coverage-targets-achieved scenario were converted to workforce, education and social economic benefits; and benefit-cost ratios were calculated.

RESULTS

The coverage-targets-achieved scenario required an additional US$12.6M (US$10.8M-US$15.9M) over 2020-2030 for the five Pacific countries (15% more than US$82.4M to maintain BAU). This additional investment was estimated to avert 126 000 (40%) unintended pregnancies, 2200 (28%) stillbirths and 121 (29%) maternal deaths and lead to a 15-fold economic benefit of US$190.6M (US$67.0M-US$304.5M) by 2050. For the four Caribbean countries, an additional US$17.8M (US$15.3M-US$22.4M) was needed to reach the targets (4% more than US$405.4M to maintain BAU). This was estimated to avert 127 000 (23%) unintended pregnancies, 3600 (23%) stillbirths and 221 (25%) maternal deaths and lead to a 24-fold economic benefit of US$426.2M (US$138.6M-US$745.7M) by 2050.

CONCLUSION

Achieving full coverage of contraceptive and MH services in the Pacific and Caribbean is likely to have a high return on investment.

Investing in human development and building state resilience in fragile contexts: A case study of early nutrition investments in Burkina Faso

Maternal and early malnutrition have negative health and developmental impacts over the life-course. Consequently, early nutrition support can provide significant benefits into later life, provided the later life contexts allow. This study examines the limits of siloed investments in nutrition and illustrates how ignoring life-course contextual constraints limits human development benefits and exacerbates inequality, particularly in fragile contexts. This case study focuses on Burkina Faso, a country with high rates of early malnutrition and a fragile state. We modelled the impact of scaling up 10 nutrition interventions to 80% coverage for a single year cohort on stunting, nationally and sub-nationally, using the Lives Saved Tool (LiST), and the consequent impact on earnings, without and with a complementary cash-transfer in later life. The impact on earnings was modelled utilising the well-established pathway between early nutrition, years of completed schooling and, consequent adult earnings. Productivity returns were estimated as the present value of increased income over individuals' working lives, then compared to estimates of the present value of providing the cost of nutrition interventions and cash-transfers. The cost benefit ratio at the national level for scaled nutrition alone is 1:1. Sub-nationally the worst-off region yields the lowest ratio < 0.2 for every dollar spent. The combination of nutrition and cash-transfers national cost benefit is 1:12, still with regional variation but with great improvement in the poorest region. This study shows that early nutrition support alone may not be enough to address inequality and may add to state fragility. Taking a life-course perspective when priority-setting in contexts with multiple constraints on development can help to identify interventions that maximizing returns, without worsening inequality.

Impacts of micronutrient intervention programs on effective coverage and lives saved: Modeled evidence from Cameroon

Policymakers are committed to improving nutritional status and to saving lives. Some micronutrient intervention programs (MIPs) can do both, but not to the same degrees. We apply the Micronutrient Intervention Modeling tool to compare sets of MIPs for (1) achieving dietary adequacy separately for zinc, vitamin A (VA), and folate for children and women of reproductive age (WRA), and (2) saving children's lives via combinations of MIPs. We used 24-h dietary recall data from Cameroon to estimate usual intake distributions of zinc and VA for children 6-59 months and of folate for WRA. We simulated the effects on dietary inadequacy and lives saved of four fortified foods and two VA supplementation (VAS) platforms. We estimated program costs over 10 years. To promote micronutrient-specific dietary adequacy, the economic optimization model (EOM) selected zinc- and folic acid-fortified wheat flour, VA-fortified edible oils, and bouillon cubes, and VAS via Child Health Days in the North macroregion. A different set of cost-effective MIPs emerged for reducing child mortality, shifting away from VA and toward more zinc for children and more folic acid for WRA. The EOM identified more efficient sets of MIPs than the business-as-usual MIPs, especially among programs aiming to save lives.

Evaluation of a comprehensive maternal newborn health intervention in rural Tanzania: single-arm pre-post coverage survey results

Background

In Tanzania, maternal and newborn deaths can be prevented via quality facility-based antenatal care (ANC), delivery, and postnatal care (PNC). Scalable, integrated, and comprehensive interventions addressing demand and service-side care-seeking barriers are needed.

Objective

Assess coverage survey indicators before and after a comprehensive maternal newborn health (MNH) intervention in Misungwi District, Tanzania.

Methods

A prospective, single-arm, pre- (2016) and post-(2019) coverage survey (ClinicalTrials.gov #NCT02506413) was used to assess key maternal and newborn health (MNH) outcomes. The Mama na Mtoto intervention included district activities (planning, leadership training, supportive supervision), health facility activities (training, equipment, infrastructure upgrades), and plus community health worker mobilization. Implementation change strategies, a process model, and a motivational framework incorporated best practices from a similar Ugandan intervention. Cluster sampling randomized hamlets then used ‘wedge sampling’ protocol as an alternative to full household enumeration. Key outcomes included: four or more ANC visits (ANC4+); skilled birth attendant (SBA); PNC for mother within 48 hours (PNC-woman); health facility delivery (HFD); and PNC for newborn within 48 hours (PNC-baby). Trained interviewers administered the ‘Real Accountability: Data Analysis for Results Coverage Survey to women 15–49 years old. Descriptive statistics incorporated design effect; the Lives Saved Tool estimated deaths averted based on ANC4+/HFD.

Results

Between baseline (n = 2,431) and endline (n = 2,070), surveys revealed significant absolute percentage increases for ANC4+ (+11.6, 95% CI [5.4, 17.7], p < 0.001), SBA (+16.6, 95% CI [11.1, 22.0], p < 0.001), PNC-woman (+9.2, 95% CI [3.2, 15.2], p = 0.002), and HFD (+17.2%, 95% CI [11.3, 23.1], p < 0.001). A PNC-baby increase (+6.1%, 95% CI [−0.5, 12.8], p = 0.07) was not statistically significant. An estimated 121 neonatal and 20 maternal lives were saved between 2016 and 2019.

Conclusions

Full-district scale-up of a comprehensive MNH package embedded government health system was successfully implemented over a short time and associated with significant maternal care-seeking improvements and potential for lives saved.

Maternal and child nutrition in the Lives Saved Tool: Results of a recent update

Background

The Lives Saved Tool (LiST) is a mathematical modelling tool for estimating the survival, health, and nutritional impacts of scaling intervention coverage in low- and middle-income countries (LMICs). Various nutrition interventions are included in LiST and are regularly (and independently) reviewed and updated as new data emerge. This manuscript describes our latest in-depth review of nutrition evidence, focusing on intervention efficacy, appropriate population-affected fractions, and new interventions for potential inclusion in the LiST model.

Methods

An external advisory group (EAG) was assembled to review evidence from systematic reviews on intervention-outcome (I-O) pairs for women and children under five years of age. GRADE quality was assigned to each pair based on a LiST-specific checklist to facilitate consistent decisions during the consideration. For existing interventions with new information, the EAG was asked to recommend whether to update the default efficacy values and population-affected fractions. For the new interventions, the EAG decided whether there was sufficient evidence of benefit, and in affirmative cases, information on the efficacy and affected fraction values that could be used. Decisions were based on expert group consensus.

Results

Overall, the group reviewed 53 nutrition-related I-O pairs, including 25 existing and 28 new ones. Efficacy and population-affected fractions were updated for seven I-O pairs; three pairs were updated for efficacy estimates only, three were updated for population-affected fractions only; and nine new I-O pairs were added to the model, bringing the total of nutrition-related I-O pairs to 34. Included in the new I-O pairs were two new nutrition interventions added to LIST: zinc fortification and neonatal vitamin A supplementation.

Conclusions

For modelling tools like LiST to be useful, it is crucial to update interventions, efficacy and population-affected fractions as new evidence becomes available. The present updates will enable LiST users to better estimate the potential health, nutrition, and survival benefits of investing in nutrition.

Progress towards achieving child survival goals in Kenya after devolution: Geospatial analysis with scenario-based projections, 2015-2025

Subnational projections of under-5 mortality (U5M) have increasingly become an essential planning tool to support Sustainable Development Goals (SDGs) agenda and strategies for improving child survival. To support child health policy, planning, and tracking child development goals in Kenya, we projected U5M at units of health decision making. County-specific annual U5M were estimated using a multivariable Bayesian space-time hierarchical model based on intervention coverage from four alternate intervention scale-up scenarios assuming 1) the highest subnational intervention coverage in 2014, 2) projected coverage based on the fastest county-specific rate of change observed in the period between 2003-2014 for each intervention, 3) the projected national coverage based on 2003-2014 trends and 4) the country-specific targets of intervention coverage relative to business as usual (BAU) scenario. We compared the percentage change in U5M based on the four scale-up scenarios relative to BAU and examined the likelihood of reaching SDG 3.2 target of at least 25 deaths/1,000 livebirths by 2022 and 2025. Projections based on 10 factors assuming BAU, showed marginal reductions in U5M across counties with all the counties except Mandera county not achieving the SDG 3.2 target by 2025. Further, substantial reductions in U5M would be achieved based on the various intervention scale-up scenarios, with 63.8% (30), 74.5% (35), 46.8% (22) and 61.7% (29) counties achieving SDG target for scenarios 1,2,3 and 4 respectively by 2025. Scenario 2 yielded the highest reductions of U5M with individual scale-up of access to improved water, recommended treatment of fever and accelerated HIV prevalence reduction showing considerable impact on U5M reduction (≥ 20%) relative to BAU. Our results indicate that sustaining an ambitious intervention scale-up strategy matching the fastest rate observed between 2003-2014 would substantially reduce U5M in Kenya. However, despite this ambitious scale-up scenario, 25% (12 of 47) of the Kenya's counties would still not achieve SDG 3.2 target by 2025.

Estimates of child mortality reductions attributed to vitamin A supplementation in sub-Saharan Africa: scale up, scale back, or refocus?

BACKGROUND

Vitamin A supplementation (VAS) has been implemented in over 82 countries globally, primarily because of its beneficial effect in preventing child mortality. Secular reductions in child mortality and the implementation of alternative programs to promote vitamin A intake have led to questions on the need for national VAS programs.

OBJECTIVES

This study aimed to estimate child mortality changes related to VAS using current, scale-back, and scale-up coverage scenarios.

METHODS

Data related to demographic characteristics, fertility, intervention coverage, anthropometry, child mortality and cause-of-death structure were integrated into the Lives Saved Tool (LiST). We estimated the cause-specific (LiST model) and all-cause mortality reductions related to VAS based on evidence from recent meta-analyses.

RESULTS

Between 2008 and 2018, VAS coverage declined in most sub-Saharan African (SSA) countries. In 2019 alone, 12% and 24% reductions in all-cause mortality related to VAS were expected to avert from 105,332 to 234,704 child deaths, respectively, in SSA; whereas the cause-specific mortality model (LiST) estimated that 141,670 child deaths were averted in 2019. Estimates of VAS-related child mortality reductions were highly variable among countries. Our scaling-back scenario led to highly variable country-level results, with expected increases in mortality rates, from a low of 0.04/1000 live births to as high as 49.3/1000 live births, suggesting that some countries could start considering scaling back, while others need to scale up.

CONCLUSIONS

Excess child mortality that would be preventable by VAS has declined, but is still significant in many SSA countries. While scale-up of VAS is needed for most of the countries, scaling back can also be considered in some countries. Policy decisions, however, should be guided by more recent data on food consumption, vitamin A statuses, child health, and vitamin A fortification coverage.

Healthcare utilization and maternal and child mortality during the COVID-19 pandemic in 18 low- and middle-income countries: An interrupted time-series analysis with mathematical modeling of administrative data

BACKGROUND

The Coronavirus Disease 2019 (COVID-19) pandemic has had wide-reaching direct and indirect impacts on population health. In low- and middle-income countries, these impacts can halt progress toward reducing maternal and child mortality. This study estimates changes in health services utilization during the pandemic and the associated consequences for maternal, neonatal, and child mortality.

METHODS AND FINDINGS

Data on service utilization from January 2018 to June 2021 were extracted from health management information systems of 18 low- and lower-middle-income countries (Afghanistan, Bangladesh, Cameroon, Democratic Republic of the Congo (DRC), Ethiopia, Ghana, Guinea, Haiti, Kenya, Liberia, Madagascar, Malawi, Mali, Nigeria, Senegal, Sierra Leone, Somalia, and Uganda). An interrupted time-series design was used to estimate the percent change in the volumes of outpatient consultations and maternal and child health services delivered during the pandemic compared to projected volumes based on prepandemic trends. The Lives Saved Tool mathematical model was used to project the impact of the service utilization disruptions on child and maternal mortality. In addition, the estimated monthly disruptions were also correlated to the monthly number of COVID-19 deaths officially reported, time since the start of the pandemic, and relative severity of mobility restrictions. Across the 18 countries, we estimate an average decline in OPD volume of 13.1% and average declines of 2.6% to 4.6% for maternal and child services. We projected that decreases in essential health service utilization between March 2020 and June 2021 were associated with 113,962 excess deaths (110,686 children under 5, and 3,276 mothers), representing 3.6% and 1.5% increases in child and maternal mortality, respectively. This excess mortality is associated with the decline in utilization of the essential health services included in the analysis, but the utilization shortfalls vary substantially between countries, health services, and over time. The largest disruptions, associated with 27.5% of the excess deaths, occurred during the second quarter of 2020, regardless of whether countries reported the highest rate of COVID-19-related mortality during the same months. There is a significant relationship between the magnitude of service disruptions and the stringency of mobility restrictions. The study is limited by the extent to which administrative data, which varies in quality across countries, can accurately capture the changes in service coverage in the population.

CONCLUSIONS

Declines in healthcare utilization during the COVID-19 pandemic amplified the pandemic's harmful impacts on health outcomes and threaten to reverse gains in reducing maternal and child mortality. As efforts and resource allocation toward prevention and treatment of COVID-19 continue, essential health services must be maintained, particularly in low- and middle-income countries.

COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery

Over the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as routine immunisation activities resume, it is important to estimate the effectiveness of different approaches for recovery. We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to routine immunisations occurring in the years 2020-2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in routine immunisation coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%. We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020-2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect. Overall, our results show that drops in routine immunisation coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.

The RADAR coverage tool: developing a toolkit for rigorous household surveys for reproductive, maternal, newborn, and child health & nutrition indicators

Population-based intervention coverage data are used to inform the design of projects, programs, and policies and to evaluate their impact. In low- and middle-income countries (LMICs), household surveys are the primary source of coverage data. Many coverage surveys are implemented by organizations with limited experience or resources in population-based data collection. We developed a streamlined survey and set of supporting materials to facilitate rigorous survey design and implementation. The RADAR coverage survey tool aimed to 1) rigorously measure priority reproductive, maternal, newborn, child health & nutrition coverage indicators, and allow for equity and gender analyses; 2) use standard, valid questions, to the extent possible; 3) be as light as possible; 4) be flexible to address users’ needs; and 5) be compatible with the Lives Saved Tool for analysis of program impact. Early interactions with stakeholders also highlighted survey planning, implementation, and analysis as challenging areas. We therefore developed a suite of resources to support implementers in these areas. The toolkit was piloted by implementers in Tanzania and in Burkina Faso. Although the toolkit was successfully implemented in these settings and facilitated survey planning and implementation, we found that implementers must still have access to sufficient resources, time, and technical expertise in order to use the tool appropriately. This potentially limits the use of the tool to situations where high-quality surveys or evaluations have been prioritized and adequately resourced.

Reducing household air pollution exposure to improve early child growth and development; a randomized control trial protocol for the "Poriborton-Extension: The CHANge trial"

Background

Globally, household air pollution (HAP) is a leading environmental cause of morbidity and mortality. Our trial aims to assess the impact of liquefied petroleum gas (LPG) for cooking to reduce household air pollution exposure on child health outcomes, compared to usual cooking practices in Bangladesh. The primary aim is to evaluate if reduced exposure to HAP through the provision of LPG for cooking from early gestation through to age 2 improves child anthropometry, health, and neuro-cognitive developmental outcomes, compared to children exposed to emissions from usual practice.

Methods

Two-arm parallel cluster randomized controlled trial (cCRT). We will extend the intervention and follow-up of our existing “Poriborton” trial. In a subset of the original surviving participants, we will supply LPG cylinders and LPG stoves (intervention) compared to usual cooking practices and extend the follow-up to 24 months of age. The expected final sample size, for both (intervention and control) is 1854 children with follow-up to 2 years of age available for analysis.

Discussion

This trial will answer important research gaps related to HAP and child health and neuro-cognitive developmental outcomes. This evidence will help to understand the impact of a HAP intervention on child health to inform policies for the adoption of clean fuel in Bangladesh and other similar settings.

Trial registration

The Poriborton: Change trial: Household Air Pollution and Perinatal and early Neonatal mortality is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12618001214224, original trial registered on 19th July 2018, extension approved on 23rd June 2021. www.anzctr.org.au.

Estimating additional schooling and lifetime earning obtained from improved linear growth in low- and middle-income countries using the Lives Saved Tool (LiST)

Background

Policymakers seeking to prioritize the use of restricted financial resources need to understand the relative costs and benefits of interventions for improving nutritional status. Improved linear growth can lead to increased education attainment and improved economic productivity in low- and middle-income countries (LMICs), though these non-health-related benefits are not reflected in current long-term modelling efforts, including the Lives Saved Tool (LiST). Our objective was to integrate the effects of improved linear growth on non-health related benefit into LiST by estimating subsequent gains in years of schooling and wage earnings. We then estimated the impacts of reaching the Sustainable Development Goals (SDGs) target for stunting in South Asian countries on lifetime productivity.

Methods

In the first step, we used LiST outputs to estimate the improved linear growth due to scaled-up nutrition interventions and used published estimates to quantify the education gain resulting from an increase in height for age z-score (HAZ). In the second step, we used published country-level estimates on economic returns to schooling to quantify the relative gains in wages that children born today will experience because of their additional education attainment in the future. In the last step, we used country-level data on wages to estimate the net present value of future earnings gained due to early childhood growth improvement per birth cohort.

Results

If South Asia countries reach the SDG target by 2025, an estimated 8.6 million years of schooling will be obtained by six birth cohorts of 2020 to 2025. These six birth cohorts will also gain an estimated US$64 893 million in the present value term, at a 5% discount rate, in lifetime earnings. India has the largest expected gain in years of schooling (7367 years) and lifetime earnings (US$59 390 million in present value terms, at a 5% discount rate).

Conclusions

Two non-health-related benefits of improved linear growth – additional years of schooling and lifetime earnings – are added in LiST. Together with LiST costing, users can now conduct both cost-effective and benefit-cost analyses. Using both analyses will provide more comprehensive insights into nutrition interventions' relative costs and benefits.

Updating the assumptions on the impact of household water, sanitation and hygiene interventions on diarrhea morbidity in young children

Background

The Lives Saved Tool (LiST) is a publicly available and widely used model used to estimate the impact of scaling up interventions on maternal and child health. A strength of the model is that it is continuously updated with country-specific information about intervention coverage, risk factors and causes of death. This paper reports an updated review and meta-analysis on the efficacy of water, sanitation and hygiene (WASH) interventions in reducing diarrhea morbidity among children under the age of five years.

Methods

We updated previous LiST systematic reviews for improved WASH interventions according to standard LiST criteria. We sought to identify more recent WASH studies to update LiST efficacy estimates for each WASH intervention on diarrhea morbidity. In addition, we conducted a search to identify studies that reported an effect size for combined improved WASH interventions. For interventions where we found new studies, we conducted a weighted meta-analysis to produce an updated effect size estimate.

Results

We did not find new studies demonstrating an effect of improved water source alone on diarrhea morbidity among children under 5 years of age. For improved sanitation, we conducted an updated meta-analysis among 4 studies and found no difference between intervention and control arms (weighted mean difference (WMD) = -5% (95% confidence interval (CI) = -11% to 2%). We identified four trials that assessed the effect of combined interventions targeting improved water, sanitation and hygiene. The weighted mean difference also showed no effect on diarrhea morbidity among children under 5 years of age (WMD = -6%, 95% CI = -15% to 4%). Our updated results for handwashing promotion estimate the effects to results in a 17% reduction in childhood diarrhea morbidity (95% CI = 7% to 27%).

Conclusions

Despite widespread acceptance that WASH interventions can improve diarrhea morbidity, the evidence supporting this specifically for children under 5 years of age remains weak. Children interact with the environment in ways that differ from adults and these constant exposures may limit the effect that these WASH interventions can have on diarrhea morbidity.

Nutrition-sensitive agriculture programs increase dietary diversity in children under 5 years: A review and meta-analysis

Background

Low-quality diets contribute to the burden of malnutrition and increase the risk of children not achieving their developmental potential. Nutrition-sensitive agriculture programs address the underlying determinants of malnutrition, though their contributions to improving diets do not factor into current nutrition impact modeling tools.

Objective

To synthesize the evidence on the effectiveness of nutrition-sensitive agriculture programs in improving dietary diversity in young children (6-23.9 months and 6-60 months).

Methods

A literature search was conducted for published trials through existing systematic reviews and individual database search of the ISI Web of Science. All dietary diversity measures in the studies selected to be in the analysis were extracted. Estimation of main pooled effects were conducted on outcomes of minimum diet diversity (MDD) and diet diversity score (DDS) using random-effects meta-regression models. We report pooled effect sizes as standardized mean differences (SMDs) or odds ratios (ORs).

Results

Nutrition-sensitive agricultural interventions have a significant positive impact on the diet diversity scores of children aged 6-23.9 months (SMD = 0.22, 95% confidence interval (CI) = 0.09-0.36) and on the odds of reaching minimum diet diversity (OR = 1.45, 95% CI = 1.20, 1.76). Similar impacts are found when analyses are expanded to include studies for children aged 6-60 months (DDS SMD = 0.22, 95% CI = 0.12-0.32) (MDD OR = 1.64, 95% CI:  = 1.38-1.94).

Conclusion

Nutrition-sensitive agriculture interventions consistently have a positive impact on child dietary diversity. Incorporating this evidence in nutrition modeling tools can contribute to decision-making on the relative benefits of nutrition-sensitive interventions as compared with other maternal, newborn, child health and nutrition (MNCHN) interventions.

Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation

BACKGROUND

The Sustainable Development Goals (SDGs), set in 2015 by the UN General Assembly, call for all countries to reach an under-5 mortality rate (U5MR) of at least as low as 25 deaths per 1000 livebirths and a neonatal mortality rate (NMR) of at least as low as 12 deaths per 1000 livebirths by 2030. We estimated levels and trends in under-5 mortality for 195 countries from 1990 to 2019, and conducted scenario-based projections of the U5MR and NMR from 2020 to 2030 to assess country progress in, and potential for, reaching SDG targets on child survival and the potential under-5 and neonatal deaths over the next decade.

METHODS

Levels and trends in under-5 mortality are based on the UN Inter-agency Group for Child Mortality Estimation (UN IGME) database on under-5 mortality, which contains around 18 000 country-year datapoints for 195 countries-nearly 10 000 of those datapoints since 1990. The database includes nationally representative mortality data from vital registration systems, sample registration systems, population censuses, and household surveys. As with previous sets of national UN IGME estimates, a Bayesian B-spline bias-reduction model (B3) that considers the systematic biases associated with the different data source types was fitted to these data to generate estimates of under-5 (age 0-4 years) mortality with uncertainty intervals for 1990-2019 for all countries. Levels and trends in the neonatal mortality rate (0-27 days) are modelled separately as the log ratio of the neonatal mortality rate to the under-5 mortality rate using a Bayesian model. Estimated mortality rates are combined with livebirths data to calculate the number of under-5 and neonatal deaths. To assess the regional and global burden of under-5 deaths in the present decade and progress towards SDG targets, we constructed several scenario-based projections of under-5 mortality from 2020 to 2030 and estimated national, regional, and global under-5 mortality trends up to 2030 for each scenario.

FINDINGS

The global U5MR decreased by 59% (90% uncertainty interval [UI] 56-61) from 93·0 (91·7-94·5) deaths per 1000 livebirths in 1990 to 37·7 (36·1-40·8) in 2019, while the annual number of global under-5 deaths declined from 12·5 (12·3-12·7) million in 1990 to 5·2 (5·0-5·6) million in 2019-a 58% (55-60) reduction. The global NMR decreased by 52% (90% UI 48-55) from 36·6 (35·6-37·8) deaths per 1000 livebirths in 1990, to 17·5 (16·6-19·0) in 2019, and the annual number of global neonatal deaths declined from 5·0 (4·9-5·2) million in 1990, to 2·4 (2·3-2·7) million in 2019, a 51% (47-54) reduction. As of 2019, 122 of 195 countries have achieved the SDG U5MR target, and 20 countries are on track to achieve the target by 2030, while 53 will need to accelerate progress to meet the target by 2030. 116 countries have reached the SDG NMR target with 16 on track, leaving 63 at risk of missing the target. If current trends continue, 48·1 million under-5 deaths are projected to occur between 2020 and 2030, almost half of them projected to occur during the neonatal period. If all countries met the SDG target on under-5 mortality, 11 million under-5 deaths could be averted between 2020 and 2030.

INTERPRETATION

As a result of effective global health initiatives, millions of child deaths have been prevented since 1990. However, the task of ending all preventable child deaths is not done and millions more deaths could be averted by meeting international targets. Geographical and economic variation demonstrate the possibility of even lower mortality rates for children under age 5 years and point to the regions and countries with highest mortality rates and in greatest need of resources and action.

FUNDING

Bill & Melinda Gates Foundation, US Agency for International Development.

Adapting and validating the log quadratic model to derive under-five age- and cause-specific mortality (U5ACSM): a preliminary analysis

BACKGROUND

The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0-27 days), infants (0-11 months), and children age 12-59 months.

METHODS

We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known.

RESULTS

We estimate U5ACSM within 0.1-0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios.

CONCLUSION

The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.

Breastfeeding in the Modern World

BACKGROUND

Social changes in the 20th century resulted in substantial reductions in the prevalence of breastfeeding in many countries but especially in those with high and increasing wealth. Concerns about this decline prompted widespread research to quantify the benefits of breastfeeding and the mechanisms by which it exerts protective effects for mothers and children. Pro-breastfeeding advocacy resulted in the WHO International Code of Marketing of Breastmilk Substitutes in 1981 and the Innocenti Declaration on Breastfeeding in 1990, which, together with numerous other initiatives, have helped to turn the tide.

SUMMARY

A tranche of recent meta-analyses of dozens of individual studies provide very strong evidence that breastfeeding has substantial benefits to babies, infants, and young children. The benefits and strengths of association vary according to the background environmental and hygiene conditions in different settings. In low-income settings, the chief measurable benefits for the child are in respect of reductions in diarrhea and respiratory infections, and in mortality. In high-income settings, breastfeeding protects against otitis media, likely protects against type 2 diabetes and overweight and obesity, and possibly protects against type 1 diabetes. It likely improves IQ by 2-3 percentage points. In mothers, breastfeeding reduces a mother's likelihood of breast and ovarian cancers. Feeding these data into the Lives Saved Tool suggests that these benefits could prevent 823,000 deaths in children and 22,000 among women.

Prevalence and factors associated with no intention to exclusively breastfeed for the first 6 months of life

OBJECTIVE

To investigate the prevalence and factors associated with no intention to exclusively breastfeed for the first 6 months of life in a sample of women in the first 24 h postpartum during the hospital stay.

METHODS

Cross-sectional study with data from screening phase of a birth cohort. The proportion of mothers who did not intend to breastfeed exclusively for 6 months (primary outcome) derived from a negative response to the question "Would you be willing to try to breastfeed exclusively for the first 6 months?", in an interview conducted by previously trained interviewers. Crude and adjusted prevalence ratios (PR) with 95% confidence intervals were obtained by Poisson regression with robust variance.

RESULTS

A total of 2964 postpartum women were interviewed. The overall prevalence of mothers who did not intend to breastfeed exclusively for 6 months was 17.8% (16.4-19.1%). After adjusting for maternal age and type of pregnancy (singleton or multiple), no intention to exclusively breastfeed was higher in mothers with a monthly household income < 3 minimum wages (PR, 1.64; 1.35-1.98) and in those who intended to smoke 4-7 days/week after delivery (PR, 1.42; 1.11-1.83). The presence of significant newborn morbidity (PR, 0.32; 0.19-0.54) and intention to breastfeed up to 12 months (PR, 0.46; 0.38-0.55) had a protective effect against not intending to breastfeed exclusively for 6 months.

CONCLUSIONS

Approximately 1 in every 5 mothers did not intend to breastfeed exclusively for 6 months. Strategies aimed at promoting exclusive breastfeeding should focus attention on mothers from lower economic strata and smokers.

Impact of mass distribution of insecticide-treated nets in Mozambique, 2012 to 2025: Estimates of child lives saved using the Lives Saved Tool

Malaria was the leading cause of post-neonatal deaths in Mozambique in 2017. The use of insecticide treated nets (ITNs) is recognized as one of the most effective ways to reduce malaria mortality in children. No previous analyses have estimated changes in mortality attributable to the scale-up of ITNs, accounting for provincial differences in mortality rates and coverage of health interventions. Based upon annual provincial ownership coverage of ITNs, the Lives Saved Tool (LiST), a multi-cause mathematical model, estimated under-5 lives saved attributable to increased household ITN coverage in 10 provinces of Mozambique between 2012 and 2018, and projected lives saved from 2019 to 2025 if 2018 coverage levels are sustained. An estimated 14,040 under-5 child deaths were averted between 2012 and 2018. If 2018 coverage levels are maintained until 2025, an additional 33,277 child deaths could be avoided. If coverage reaches at least 85% in all ten provinces by 2022, then a projected 36,063 child lives can be saved. From 2012 to 2018, the estimated number of lives saved was highest in Zambezia and Tete provinces. Increases in ITN coverage can save a substantial number of child lives in Mozambique. Without continued investment, thousands of avoidable child deaths will occur.

Oxygen systems strengthening as an intervention to prevent childhood deaths due to pneumonia in low-resource settings: systematic review, meta-analysis and cost-effectiveness

OBJECTIVES

Increasing access to oxygen services may improve outcomes among children with pneumonia living in low-resource settings. We conducted a systematic review to estimate the impact and cost-effectiveness of strengthening oxygen services in low-income and middle-income countries with the objective of including oxygen as an intervention in the Lives Saved Tool.

DESIGN

We searched EMBASE and PubMed on 31 March 2021 using keywords and MeSH terms related to 'oxygen', 'pneumonia' and 'child' without restrictions on language or date. The risk of bias was assessed for all included studies using the quality assessment tool for quantitative studies, and we assessed the overall certainty of the evidence using Grading of Recommendations, Assessment, Development and Evaluations. Meta-analysis methods using random effects with inverse-variance weights was used to calculate a pooled OR and 95% CIs. Programme cost data were extracted from full study reports and correspondence with study authors, and we estimated cost-effectiveness in US dollar per disability-adjusted life-year (DALY) averted.

RESULTS

Our search identified 665 studies. Four studies were included in the review involving 75 hospitals and 34 485 study participants. We calculated a pooled OR of 0.52 (95% CI 0.39 to 0.70) in favour of oxygen systems reducing childhood pneumonia mortality. The median cost-effectiveness of oxygen systems strengthening was $US62 per DALY averted (range: US$44-US$225). We graded the risk of bias as moderate and the overall certainty of the evidence as low due to the non-randomised design of the studies.

CONCLUSION

Our findings suggest that strengthening oxygen systems is likely to reduce hospital-based pneumonia mortality and may be cost-effective in low-resource settings. Additional implementation trials using more rigorous designs are needed to strengthen the certainty in the effect estimate.

Review of Existing Models to Predict Reductions in Neural Tube Defects Due to Folic Acid Fortification and Model Results Using Data from Cameroon

Several models have been developed to predict the effects of folic acid fortification programs on prevention of neural tube defects (NTDs), but each relies on different assumptions and data inputs. We identified and reviewed 7 models that predict the effects of folic acid intake or status on NTD risk. We applied 4 of these models [the original and a modified version of the Lives Saved Tool (LiST) and models developed by Arth et al. and Wald et al.] to predict the effect of folic acid fortification of wheat flour on reduction of NTDs using national survey data from Cameroon. The estimated percentage of NTDs averted due to fortified wheat flour (5.0 μg folic acid/g flour) varied by predictive model, with a 21-31% reduction in LiST to 83% in Arth's model, and 15% in Wald's model. As the simulated fortification level was increased from 1.0 to 7.0 μg folic acid/g flour, the pattern of change in estimated numbers of NTDs averted differed due to different model assumptions: the number of NTDs averted increased and then reached a plateau in the modified LiST model (as would be expected in real-world conditions), increased sharply in Arth's model, and increased continuously in Wald's model. This wide variation in predicted effects, and implausible results in some cases, undermines the models' utility for users of model outputs. Concurrent collection of dietary and biomarker data, including plasma and RBC folate concentrations, and NTD outcomes, is necessary to validate these models and monitor change in folic acid intake, folate-related biomarkers, and reduced NTD risk due to fortification. In the meantime, models based on erythrocyte folate concentration are recommended, based on biological plausibility and consistency with empirical evidence. Where erythrocyte folate data are unavailable, sensitivity analyses (using several models) could be conducted to examine the range of possible outcomes.