OBJECTIVE:To describe the mortality risks by fine strata of gestational age and birthweight among 230 679 live births in nine low- and middle-income countries (LMICs) from 2000 to 2017. DESIGN:Descriptive multi-country secondary data analysis. SETTING:Nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. POPULATION:Liveborn infants from 15 population-based cohorts. METHODS:Subnational, population-based studies with high-quality birth outcome data were invited to join the Vulnerable Newborn Measurement Collaboration. All studies included birthweight, gestational age measured by ultrasound or last menstrual period, infant sex and neonatal survival. We defined adequate birthweight as 2500-3999 g (reference category), macrosomia as ≥4000 g, moderate low as 1500-2499 g and very low birthweight as <1500 g. We analysed fine strata classifications of preterm, term and post-term: ≥42+0, 39+0-41+6 (reference category), 37+0-38+6, 34+0-36+6,34+0-36+6,32+0-33+6, 30+0-31+6, 28+0-29+6 and less than 28 weeks. MAIN OUTCOME MEASURES:Median and interquartile ranges by study for neonatal mortality rates (NMR) and relative risks (RR). We also performed meta-analysis for the relative mortality risks with 95% confidence intervals (CIs) by the fine categories, stratified by regional study setting (sub-Saharan Africa and Southern Asia) and study-level NMR (≤25 versus >25 neonatal deaths per 1000 live births). RESULTS:We found a dose-response relationship between lower gestational ages and birthweights with increasing neonatal mortality risks. The highest NMR and RR were among preterm babies born at <28 weeks (median NMR 359.2 per 1000 live births; RR 18.0, 95% CI 8.6-37.6) and very low birthweight (462.8 per 1000 live births; RR 43.4, 95% CI 29.5-63.9). We found no statistically significant neonatal mortality risk for macrosomia (RR 1.1, 95% CI 0.6-3.0) but a statistically significant risk for all preterm babies, post-term babies (RR 1.3, 95% CI 1.1-1.5) and babies born at 370-386 weeks (RR 1.2, 95% CI 1.0-1.4). There were no statistically significant differences by region or underlying neonatal mortality. CONCLUSIONS:In addition to tracking vulnerable newborn types, monitoring finer categories of birthweight and gestational age will allow for better understanding of the predictors, interventions and health outcomes for vulnerable newborns. It is imperative that all newborns from live births and stillbirths have an accurate recorded weight and gestational age to track maternal and neonatal health and optimise prevention and care of vulnerable newborns.

ObjectiveTo describe the mortality risks by fine strata of gestational age and birthweight among 230679 live births in nine low- and middle-income countries (LMICs) from 2000 to 2017. DesignDescriptive multi-country secondary data analysis. SettingNine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. PopulationLiveborn infants from 15 population-based cohorts. MethodsSubnational, population-based studies with high-quality birth outcome data were invited to join the Vulnerable Newborn Measurement Collaboration. All studies included birthweight, gestational age measured by ultrasound or last menstrual period, infant sex and neonatal survival. We defined adequate birthweight as 2500-3999g (reference category), macrosomia as >= 4000g, moderate low as 1500-2499g and very low birthweight as <1500g. We analysed fine strata classifications of preterm, term and post-term: >= 42(+0), 39(+0)-41(+6) (reference category), 37(+0)-38(+6), 34(+0)-36(+6),34(+0)-36(+6),32(+0)-33(+6), 30(+0)-31(+6), 28(+0)-29(+6) and less than 28weeks. Main outcome measuresMedian and interquartile ranges by study for neonatal mortality rates (NMR) and relative risks (RR). We also performed meta-analysis for the relative mortality risks with 95% confidence intervals (CIs) by the fine categories, stratified by regional study setting (sub-Saharan Africa and Southern Asia) and study-level NMR (<= 25 versus >25 neonatal deaths per 1000 live births). ResultsWe found a dose-response relationship between lower gestational ages and birthweights with increasing neonatal mortality risks. The highest NMR and RR were among preterm babies born at <28weeks (median NMR 359.2 per 1000 live births; RR 18.0, 95% CI 8.6-37.6) and very low birthweight (462.8 per 1000 live births; RR 43.4, 95% CI 29.5-63.9). We found no statistically significant neonatal mortality risk for macrosomia (RR 1.1, 95% CI 0.6-3.0) but a statistically significant risk for all preterm babies, post-term babies (RR 1.3, 95% CI 1.1-1.5) and babies born at 37(0)-38(6)weeks (RR 1.2, 95% CI 1.0-1.4). There were no statistically significant differences by region or underlying neonatal mortality. ConclusionsIn addition to tracking vulnerable newborn types, monitoring finer categories of birthweight and gestational age will allow for better understanding of the predictors, interventions and health outcomes for vulnerable newborns. It is imperative that all newborns from live births and stillbirths have an accurate recorded weight and gestational age to track maternal and neonatal health and optimise prevention and care of vulnerable newborns.

The nature of humanitarian response has evolved in response to increasing humanitarian needs, number and scale of emergencies, and the expansion of certified Emergency Medical Teams. This research examines the International Federation of Red Cross and Red Crescent Societies' clinical and public health Emergency Response Units in emergencies from 2015 through 2019 using a mixed methods approach, consisting of a desk review and primary qualitative data, to inform prioritization of response activities and optimization of health surge support in emergencies. Identified opportunities for improvement include needs assessment, increased modularity, context-appropriate support/integration, human resources and capacity building, monitoring and evaluation, and the overall nature of health surge response to various emergency types. Greater focus on public health response; standardizing deployment criteria, standard operating procedures, and monitoring for clinical surge support; and regional and local capacity building could all improve health service quality and sustainability and facilitate more cost-effective emergency response.

OBJECTIVE We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low- and middle-income countries (LMICs). DESIGN Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000. SETTING Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America. POPULATION Live birth neonates. METHODS We categorically defined five vulnerable newborn types based on size (large- or appropriate- or small-for-gestational age [LGA, AGA, SGA]), and term (T) and preterm (PT): T + LGA, T + SGA, PT + LGA, PT + AGA, and PT + SGA, with T + AGA (reference). A 10-type definition included low birthweight (LBW) and non-LBW, and a four-type definition collapsed AGA/LGA into one category. We performed imputation for missing birthweights in 13 of the studies. MAIN OUTCOME MEASURES Median and interquartile ranges by study for the prevalence, mortality rates and relative mortality risks for the four, six and ten type classification. RESULTS There were 238 143 live births with known neonatal status. Four of the six types had higher mortality risk: T + SGA (median relative risk [RR] 2.8, interquartile range [IQR] 2.0-3.2), PT + LGA (median RR 7.3, IQR 2.3-10.4), PT + AGA (median RR 6.0, IQR 4.4-13.2) and PT + SGA (median RR 10.4, IQR 8.6-13.9). T + SGA, PT + LGA and PT + AGA babies who were LBW, had higher risk compared with non-LBW babies. CONCLUSIONS Small and/or preterm babies in LIMCs have a considerably increased mortality risk compared with babies born at term and larger. This classification system may advance the understanding of the social determinants and biomedical risk factors along with improved treatment that is critical for newborn health.

Author summary There are approximately 50 million nomadic pastoralists in Africa for whom there is little data on healthcare access and utilization. This data scarcity presents a challenge to prevent, treat and control neglected tropical diseases and design the health service delivery mechanisms through which these objectives can be met. Examining a range of studies conducted over a 45-year period, we identified supply- and demand-side influences on health services uptake in ten thematic areas. These included physical proximity to, and quality of, health services; monetary and opportunity costs of accessing care; and societal and gender norms governing power dynamics within nomadic pastoralist groups as well as those between them and health care providers. The knowledge, attitudes and practices of health care providers and health seekers also played a role in utilization, as did hegemonic factors including "political will" and varying degrees of social conflict. NTD research topics included guinea worm, lymphatic filariasis, rabies, soil-transmitted helminths, tuberculosis (bovine and human), cholera, and rift valley fever. Studies pertaining to community-directed initiatives and "One Health" approaches offered promising solutions to increase service uptake. We recommend ways to strengthen future research on this subject to improve health service delivery to, and uptake among, nomadic pastoralist populations. The estimated 50 million nomadic pastoralists in Africa are among the most "hard-to-reach" populations for health-service delivery. While data are limited, some studies have identified these communities as potential disease reservoirs relevant to neglected tropical disease programs, particularly those slated for elimination and eradication. Although previous literature has emphasized the role of these populations' mobility, the full range of factors influencing health service utilization has not been examined systematically. We systematically reviewed empirical literature on health services uptake among African nomadic pastoralists from seven online journal databases. Papers meeting inclusion criteria were reviewed using STROBE- and PRISMA-derived guidelines. Study characteristics were summarized quantitatively, and 10 key themes were identified through inductive qualitative coding. One-hundred two papers published between 1974-2019 presenting data from 16 African countries met our inclusion criteria. Among the indicators of study-reporting quality, limitations (37%) and data analysis were most frequently omitted (18%) We identified supply- and demand-side influences on health services uptake that related to geographic access (79%); service quality (90%); disease-specific knowledge and awareness of health services (59%); patient costs (35%); contextual tailoring of interventions (75%); social structure and gender (50%); subjects' beliefs, behaviors, and attitudes (43%); political will (14%); and social, political, and armed conflict (30%) and community agency (10%). A range of context-specific factors beyond distance to facilities or population mobility affects health service uptake. Approaches tailored to the nomadic pastoralist lifeway, e.g., that integrated human and veterinary health service delivery (a.k.a., "One Health") and initiatives that engaged communities in program design to address social structures were especially promising. Better causal theorization, transdisciplinary and participatory research methods, clearer operational definitions and improved measurement of nomadic pastoralism, and key factors influencing uptake, will improve our understanding of how to increase accessibility, acceptability, quality and equity of health services to nomadic pastoralist populations.

Author summary There are approximately 50 million nomadic pastoralists in Africa for whom there is little data on healthcare access and utilization. This data scarcity presents a challenge to prevent, treat and control neglected tropical diseases and design the health service delivery mechanisms through which these objectives can be met. Examining a range of studies conducted over a 45-year period, we identified supply- and demand-side influences on health services uptake in ten thematic areas. These included physical proximity to, and quality of, health services; monetary and opportunity costs of accessing care; and societal and gender norms governing power dynamics within nomadic pastoralist groups as well as those between them and health care providers. The knowledge, attitudes and practices of health care providers and health seekers also played a role in utilization, as did hegemonic factors including "political will" and varying degrees of social conflict. NTD research topics included guinea worm, lymphatic filariasis, rabies, soil-transmitted helminths, tuberculosis (bovine and human), cholera, and rift valley fever. Studies pertaining to community-directed initiatives and "One Health" approaches offered promising solutions to increase service uptake. We recommend ways to strengthen future research on this subject to improve health service delivery to, and uptake among, nomadic pastoralist populations. The estimated 50 million nomadic pastoralists in Africa are among the most "hard-to-reach" populations for health-service delivery. While data are limited, some studies have identified these communities as potential disease reservoirs relevant to neglected tropical disease programs, particularly those slated for elimination and eradication. Although previous literature has emphasized the role of these populations' mobility, the full range of factors influencing health service utilization has not been examined systematically. We systematically reviewed empirical literature on health services uptake among African nomadic pastoralists from seven online journal databases. Papers meeting inclusion criteria were reviewed using STROBE- and PRISMA-derived guidelines. Study characteristics were summarized quantitatively, and 10 key themes were identified through inductive qualitative coding. One-hundred two papers published between 1974-2019 presenting data from 16 African countries met our inclusion criteria. Among the indicators of study-reporting quality, limitations (37%) and data analysis were most frequently omitted (18%) We identified supply- and demand-side influences on health services uptake that related to geographic access (79%); service quality (90%); disease-specific knowledge and awareness of health services (59%); patient costs (35%); contextual tailoring of interventions (75%); social structure and gender (50%); subjects' beliefs, behaviors, and attitudes (43%); political will (14%); and social, political, and armed conflict (30%) and community agency (10%). A range of context-specific factors beyond distance to facilities or population mobility affects health service uptake. Approaches tailored to the nomadic pastoralist lifeway, e.g., that integrated human and veterinary health service delivery (a.k.a., "One Health") and initiatives that engaged communities in program design to address social structures were especially promising. Better causal theorization, transdisciplinary and participatory research methods, clearer operational definitions and improved measurement of nomadic pastoralism, and key factors influencing uptake, will improve our understanding of how to increase accessibility, acceptability, quality and equity of health services to nomadic pastoralist populations.