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IntroductionPreterm birth is the leading cause of child mortality. This study aimed to develop and validate programmatically feasible and accurate approaches to estimate newborn gestational age (GA) in low resource settings.MethodsThe WHO Alliance for Maternal and Newborn Health Improvement (AMANHI) study recruited pregnant women from population-based cohorts in five countries (Bangladesh, Ghana, Pakistan, Tanzania and Zambia). Women Results7428 liveborn infants were included (n=536 preterm, ConclusionThe best machine-learning model (10 neonatal characteristics and LMP) estimated GA within ±15.7 days of early ultrasound dating. Simpler models performed reasonably well with marginal increases in prediction error. These models hold promise for newborn GA estimation when ultrasound dating is unavailable.

Background Globally, 15 million infants are born preterm and another 23.2 million infants are born small for gestational age (SGA). Determining burden of preterm and SGA births, is essential for effective planning, modification of health policies and targeting interventions for reducing these outcomes for which accurate estimation of gestational age (GA) is crucial. Early pregnancy ultrasound measurements, last menstrual period and post-natal neonatal examinations have proven to be not feasible or inaccurate. Proposed algorithms for GA estimation in western populations, based on routine new-born screening, though promising, lack validation in developing country settings. We evaluated the hypothesis that models developed in USA, also predicted GA in cohorts of South Asia (575) and Sub-Saharan Africa (736) with same precision. Methods Dried heel prick blood spots collected 24-72 hours after birth from 1311 new-borns, were analysed for standard metabolic screen. Regression algorithm based, GA estimates were computed from metabolic data and compared to first trimester ultrasound validated, GA estimates (gold standard). Results Overall Algorithm (metabolites + birthweight) estimated GA to within an average deviation of 1.5 weeks. The estimated GA was within the gold standard estimate by 1 and 2 weeks for 70.5% and 90.1% new-borns respectively. Inclusion of birthweight in the metabolites model improved discriminatory ability of this method, and showed promise in identifying preterm births. Receiver operating characteristic (ROC) curve analysis estimated an area under curve of 0.86 (conservative bootstrap 95% confidence interval (CI) = 0.83 to 0.89); P

Background Maternal morbidity occurs several times more frequently than mortality, yet data on morbidity burden and its effect on maternal, foetal, and newborn outcomes are limited in low- and middle-income countries. We aimed to generate prospective, reliable population-based data on the burden of major direct maternal morbidities in the antenatal, intrapartum, and postnatal periods and its association with maternal, foetal, and neonatal death in South Asia and sub-Saharan Africa. Methods and findings This is a prospective cohort study, conducted in 9 research sites in 8 countries of South Asia and sub-Saharan Africa. We conducted population-based surveillance of women of reproductive age (15 to 49 years) to identify pregnancies. Pregnant women who gave consent were include in the study and followed up to birth and 42 days postpartum from 2012 to 2015. We used standard operating procedures, data collection tools, and training to harmonise study implementation across sites. Three home visits during pregnancy and 2 home visits after birth were conducted to collect maternal morbidity information and maternal, foetal, and newborn outcomes. We measured blood pressure and proteinuria to define hypertensive disorders of pregnancy and woman’s self-report to identify obstetric haemorrhage, pregnancy-related infection, and prolonged or obstructed labour. Enrolled women whose pregnancy lasted at least 28 weeks or those who died during pregnancy were included in the analysis. We used meta-analysis to combine site-specific estimates of burden, and regression analysis combining all data from all sites to examine associations between the maternal morbidities and adverse outcomes. Among approximately 735,000 women of reproductive age in the study population, and 133,238 pregnancies during the study period, only 1.6% refused consent. Of these, 114,927 pregnancies had morbidity data collected at least once in both antenatal and in postnatal period, and 114,050 of them were included in the analysis. Overall, 32.7% of included pregnancies had at least one major direct maternal morbidity; South Asia had almost double the burden compared to sub-Saharan Africa (43.9%, 95% CI 27.8% to 60.0% in South Asia; 23.7%, 95% CI 19.8% to 27.6% in sub-Saharan Africa). Antepartum haemorrhage was reported in 2.2% (95% CI 1.5% to 2.9%) pregnancies and severe postpartum in 1.7% (95% CI 1.2% to 2.2%) pregnancies. Preeclampsia or eclampsia was reported in 1.4% (95% CI 0.9% to 2.0%) pregnancies, and gestational hypertension alone was reported in 7.4% (95% CI 4.6% to 10.1%) pregnancies. Prolonged or obstructed labour was reported in about 11.1% (95% CI 5.4% to 16.8%) pregnancies. Clinical features of late third trimester antepartum infection were present in 9.1% (95% CI 5.6% to 12.6%) pregnancies and those of postpartum infection in 8.6% (95% CI 4.4% to 12.8%) pregnancies. There were 187 pregnancy-related deaths per 100,000 births, 27 stillbirths per 1,000 births, and 28 neonatal deaths per 1,000 live births with variation by country and region. Direct maternal morbidities were associated with each of these outcomes. Conclusions Our findings imply that health programmes in sub-Saharan Africa and South Asia must intensify their efforts to identify and treat maternal morbidities, which affected about one-third of all pregnancies and to prevent associated maternal and neonatal deaths and stillbirths. Trial registration The study is not a clinical trial., Author summary Why was this study done? Estimates of severe direct maternal morbidity are largely based on hospital-based studies with inconsistent definitions and varying selection criteria. Limited data are available from South Asia and sub-Saharan Africa, the 2 regions with the highest maternal and newborn morbidity and mortality, where a larger proportion of births occur at home. What did the researchers do and find? We collected data on maternal morbidities from a cohort of women in the community in multiple sites in sub-Saharan Africa and in South Asia. Out of a cohort of >114,000 women, we found that about 1 in 3 women suffer a maternal morbidity, which was notably higher than the previously reported data. We found that the prevalence of preeclampsia and eclampsia was about 1%, which was lower than previously reported. About 11% of women reported having prolonged or obstructed labour, which was somewhat higher than published estimates. The burden of pregnancy-related infection in postpartum period was higher in South Asia than in sub-Saharan Africa. This is the first study, to our knowledge, to describe the burden of antepartum haemorrhage and late antepartum infection and to clearly demonstrate the association of direct maternal morbidity with adverse pregnancy outcomes. What do these findings mean? Higher burden of direct maternal morbidity and its association with adverse outcomes highlights the need for improving health of women and mothers, including promotion of preconception health and nutrition, and high-quality antepartum, intrapartum and postpartum care.

BACKGROUND "Kangaroo mother care," a type of newborn care involving skin-to-skin contact with the mother or other caregiver, reduces mortality in infants with low birth weight (

Introduction Serious bacterial neonatal infections are a major cause of global neonatal mortality. While hospitalized treatment is recommended, families cannot access inpatient treatment in low resource settings. Two parallel randomized control trials were conducted at five sites in three countries (Democratic Republic of Congo, Kenya, and Nigeria) to compare the effectiveness of treatment with experimental regimens requiring fewer injections with a reference regimen A (injection gentamicin plus injection procaine penicillin both once daily for 7 days) on the outpatient basis provided to young infants (0–59 days) with signs of possible serious bacterial infection (PSBI) when the referral was not feasible. Costs were estimated to quantify the financial implications of scaleup, and cost-effectiveness of these regimens. Methods Direct economic costs (including personnel, drugs and consumable costs) were estimated for identification, prenatal and postnatal visits, assessment, classification, treatment and follow-up. Data on time spent by providers on each activity was collected from 83% of providers. Indirect marginal financial costs were estimated for non-consumables/capital, training, transport, communication, administration and supervision by considering only a share of the total research and health system costs considered important for the program. Total economic costs (direct plus indirect) per young infant treated were estimated based on 39% of young infants enrolled in the trial during 2012 and the number of days each treated during one year. The incremental cost-effectiveness ratio was calculated using treatment failure after one week as the outcome indicator. Experimental regimens were compared to the reference regimen and pairwise comparisons were also made. Results The average costs of treating a young infant with clinical severe infection (a sub-category of PSBI) in 2012 was lowest with regimen D (injection gentamicin once daily for 2 days plus oral amoxicillin twice daily for 7 days) at US$ 20.9 (95% CI US$ 16.4–25.3) or US$ 32.5 (2018 prices). While all experimental regimens B (injection gentamicin once daily plus oral amoxicillin twice daily, both for 7 days), regimen C (once daily of injection gentamicin injection plus injection procaine penicillin for 2 days, thereafter oral amoxicillin twice daily for 5 days) and regimen D were found to be more cost-effective as compared with the reference regimen A; pairwise comparison showed regimen D was more cost-effective than B or C. For fast breathing, the average cost of treatment with regimen E (oral amoxicillin twice daily for 7 days) at US$ 18.3 (95% CI US$ 13.4–23.3) or US$ 29.0 (2018 prices) was more cost-effective than regimen A. Indirect costs were 32% of the total treatment costs. Conclusion Scaling up of outpatient treatment for PSBI when the referral is not feasible with fewer injections and oral antibiotics is cost-effective for young infants and can lead to increased access to treatment resulting in potential reductions in neonatal mortality. Clinical trial registration The trial was registered with Australian New Zealand Clinical Trials Registry under ID ACTRN 12610000286044.

This diagnostic/prognostic study describes the use of cell-free transcriptomics, urine metabolomics, and plasma proteomics for identifying the biological measurements associated with preterm birth., Key Points Question What maternal biological modalities are associated with preterm birth (PTB)? Findings In this diagnostic/prognostic study of 81 pregnant women from 5 birth cohorts in low- and middle-income countries, several correlates of preterm birth in urine and blood were found to be associated with PTB. Although cohort-specific signatures were present, a machine learning algorithm was able to generate a model that was capable of predicting PTB across the cohorts. Meaning Results of this study suggest that most PTBs can be predicted using blood and urine samples collected early in the pregnancy, providing opportunities for interventions., Importance Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB.

Background Social, behavioural and community engagement (SBCE) interventions are essential for global maternal, newborn and child health (MNCH) strategies. Past efforts to synthesise research on SBCE interventions identified a need for clear priorities to guide future research. WHO led an exercise to identify global research priorities for SBCE interventions to improve MNCH. Methods We adapted the Child Health and Nutrition Research Initiative method and combined quantitative and qualitative methods to determine MNCH SBCE intervention research priorities applicable across different contexts. Using online surveys and meetings, researchers and programme experts proposed up to three research priorities and scored the compiled priorities against four criteria – health and social impact, equity, feasibility, and overall importance. Priorities were then ranked by score. A group of 29 experts finalised the top 10 research priorities for each of maternal, newborn or child health and a cross-cutting area. Results A total of 310 experts proposed 867 research priorities, which were consolidated into 444 priorities and scored by 280 experts. Top maternal and newborn health priorities focused on research to improve the delivery of SBCE interventions that strengthen self-care/family care practices and care-seeking behaviour. Child health priorities focused on the delivery of SBCE interventions, emphasising determinants of service utilisation and breastfeeding and nutrition practices. Cross-cutting MNCH priorities highlighted the need for better integration of SBCE into facility-based and community-based health services. Conclusions Achieving global targets for MNCH requires increased investment in SBCE interventions that build capacities of individuals, families and communities as agents of their own health. Findings from this exercise provide guidance to prioritise investments and ensure that they are best directed to achieve global objectives. Stakeholders are encouraged to use these priorities to guide future research investments and to adapt them for country programmes by engaging with national level stakeholders.

BackgroundBiannual vitamin A supplementation is a well-established survival tool for preschool children 6 months and older in vitamin A deficient populations but this schedule misses the opportunity to intervene on most young infant deaths. Randomised trials of neonatal vitamin A supplementation (NVAS) in the first few days of life to assess its impact on under 6-month mortality in low/middle-income countries have had varying results.MethodsInvestigators of 11 published randomised placebo-controlled NVAS trials (n=163 567 children) reanalysed their data according to an agreed plan and pooled the primary outcomes of mortality from supplementation through 6 and 12 months of age using random effects models and meta-regression. One investigator withdrew but allowed use of the data.FindingsOverall there was no effect of NVAS on infant survival through 6 (risk ratio (RR) 0.97; 95% CI 0.89 to 1.06) or 12 months of age (RR 1.00; 95% CI 0.93 to 1.08) but results varied by study population characteristics.NVAS significantly reduced 6-month mortality among the trials conducted in Southern Asia (RR 0.87; 95% CI 0.77 to 0.98), in contexts with moderate or severe vitamin A deficiency (defined as 10% or higher proportion of women with serum retinol 32% mothers had no schooling (RR 0.88; 95% CI 0.80 to 0.96). NVAS did not reduce mortality in the first 6 months of life in trials conducted in Africa, in contexts characterised by a low prevalence of vitamin A deficiency, lower rates of infant mortality and where maternal education was more prevalent. There was a suggestion of increased infant mortality in trials conducted in Africa (RR 1.07; 95% CI 1.00 to 1.15).Individual-level characteristics such as sex, birth weight, gestational age and size, age at dosing, parity, time of breast feeding initiation, maternal education and maternal vitamin A supplementation did not modify the impact of NVAS.ConclusionNVAS reduced infant mortality in South Asia, in contexts where the prevalence of maternal vitamin A deficiency is moderate to severe and early infant mortality is high; but it had no beneficial effect on infant survival in Africa, in contexts where the prevalence of maternal vitamin A deficiency is lower, early infant mortality is low.

Malignant mesothelioma (MM) has a poor prognosis and is largely resistant to standard treatments, so it is important to seek novel therapeutic strategies for this disease. Cancer-initiating cells (CICs) were previously identified in MM using stem cell-associated markers in combination with spheroid cultures. However, the mechanisms underlying the induction and maintenance of CICs in MM remain to be fully explored. Here we showed that the CICs, which had high aldehyde dehydrogenase levels (ALDHbright) and stem cell-associated genes, were expanded in MM cells cultured under sphere-forming conditions. The MM spheroids also initiated tumors in immunodeficient mice more efficiently than did conventional adherent MM cells. In the MM spheroids, the expression of hyaluronan (HA) synthases was upregulated. Inhibiting the HA synthesis or CD44 functions by gene knockdown or neutralizing antibody abolished the formation of large-sized spheroids and the expansion of ALDHbright CICs. The expression of activin-A was also increased in the spheroids, and type I activin-A receptor subunit (ALK4) was upregulated in the ALDHbright CICs. The neutralization of activin-A or functional inactivation of ALK4 diminished the ALDHbright CICs without affecting spheroid formation. The knockdown of CD44 or ALK4 strongly suppressed the tumor growth in immunodeficient mice. These results together suggest that the HA–CD44 and activin-A–ALK4 pathways differentially regulate the spheroid formation and maintenance of ALDHbright CICs in MM cells, and that both pathways play critical roles in tumor growth in immunodeficient hosts. Our findings provide a novel therapeutic option for MM that targets signaling pathways that promote the CIC compartment through CD44 and ALK4.

Objectives: The AMANHI study aims to seek for biomarkers as predictors of important pregnancy-related outcomes, and establish a biobank in developing countries for future research as new methods and technologies become available.Methods: AMANHI is using harmonised protocols to enrol 3000 women in early pregnancies (8-19 weeks of gestation) for population-based follow-up in pregnancy up to 42 days postpartum in Bangladesh, Pakistan and Tanzania, with collection taking place between August 2014 and June 2016. Urine pregnancy tests will be used to confirm reported or suspected pregnancies for screening ultrasound by trained sonographers to accurately date the pregnancy. Trained study field workers will collect very detailed phenotypic and epidemiological data from the pregnant woman and her family at scheduled home visits during pregnancy (enrolment, 24-28 weeks, 32-36 weeks & 38+ weeks) and postpartum (days 0-6 or 42-60). Trained phlebotomists will collect maternal and umbilical blood samples, centrifuge and obtain aliquots of serum, plasma and the buffy coat for storage. They will also measure HbA1C and collect a dried spot sample of whole blood. Maternal urine samples will also be collected and stored, alongside placenta, umbilical cord tissue and membrane samples, which will both be frozen and prepared for histology examination. Maternal and newborn stool (for microbiota) as well as paternal and newborn saliva samples (for DNA extraction) will also be collected. All samples will be stored at -80°C in the biobank in each of the three sites. These samples will be linked to numerous epidemiological and phenotypic data with unique study identification numbers.Importance of the study: AMANHI biobank proves that biobanking is feasible to implement in LMICs, but recognises that biobank creation is only the first step in addressing current global challenges.

Background Around 70% neonatal deaths occur in low birth weight (LBW) babies. Globally, 15% of babies are born with LBW. Kangaroo Mother Care (KMC) appears to be an effective way to reduce mortality and morbidity among LBW babies. KMC comprises of early and continuous skin-to-skin contact between mother and baby as well as exclusive breastfeeding. Evidence derived from hospital-based studies shows that KMC results in a 40% relative reduction in mortality, a 58% relative reduction in the risk of nosocomial infections or sepsis, shorter hospital stay, and a lower risk of lower respiratory tract infections in babies with birth weight

BACKGROUND: Several recent reviews of the methods used to set research priorities have identified the CHNRI method (acronym derived from the "Child Health and Nutrition Research Initiative") as an approach that clearly became popular and widely used over the past decade. In this paper we review the first 50 examples of application of the CHNRI method, published between 2007 and 2016, and summarize the most important messages that emerged from those experiences. METHODS: We conducted a literature review to identify the first 50 examples of application of the CHNRI method in chronological order. We searched Google Scholar, PubMed and so-called grey literature. RESULTS: Initially, between 2007 and 2011, the CHNRI method was mainly used for setting research priorities to address global child health issues, although the first cases of application outside this field (eg, mental health, disabilities and zoonoses) were also recorded. Since 2012 the CHNRI method was used more widely, expanding into the topics such as adolescent health, dementia, national health policy and education. The majority of the exercises were focused on issues that were only relevant to low- and middle-income countries, and national-level applications are on the rise. The first CHNRI-based articles adhered to the five recommended priority-setting criteria, but by 2016 more than two-thirds of all conducted exercises departed from recommendations, modifying the CHNRI method to suit each particular exercise. This was done not only by changing the number of criteria used, but also by introducing some entirely new criteria (eg, "low cost", "sustainability", "acceptability", "feasibility", "relevance" and others). CONCLUSIONS: The popularity of the CHNRI method in setting health research priorities can be attributed to several key conceptual advances that have addressed common concerns. The method is systematic in nature, offering an acceptable framework for handling many research questions. It is also transparent and replicable, because it clearly defines the context and priority-setting criteria. It is democratic, as it relies on "crowd-sourcing". It is inclusive, fostering "ownership" of the results by ensuring that various groups invest in the process. It is very flexible and adjustable to many different contexts and needs. Finally, it is simple and relatively inexpensive to conduct, which we believe is one of the main reasons for its uptake by many groups globally, particularly those in low- and middle-income countries.

Objective To assess the efficacy of ready-to-use therapeutic food (RUTF), centrally produced RUTF (RUTF-C) or locally prepared RUTF (RUTF-L) for home-based management of uncomplicated severe acute malnutrition (SAM) compared with micronutrient-enriched (augmented) energy-dense home-prepared foods (A-HPF, the comparison group). Methods In an individually randomised multicentre trial, we enrolled 906 children aged 6–59 months with uncomplicated SAM. The children enrolled were randomised to receive RUTF-C, RUTF-L or A-HPF. We provided foods, counselling and feeding support until recovery or 16 weeks, whichever was earlier and measured outcomes weekly (treatment phase). We subsequently facilitated access to government nutrition services and measured outcomes once 16 weeks later (sustenance phase). The primary outcome was recovery during treatment phase (weight-for-height ≥−2 SD and absence of oedema of feet). Results Recovery rates with RUTF-L, RUTF-C and A-HPF were 56.9%, 47.5% and 42.8%, respectively. The adjusted OR was 1.71 (95% CI 1.20 to 2.43; p=0.003) for RUTF-L and 1.28 (95% CI 0.90 to 1.82; p=0.164) for RUTF-C compared with A-HPF. Weight gain in the RUTF-L group was higher than in the A-HPF group (adjusted difference 0.90 g/kg/day, 95% CI 0.30 to 1.50; p=0.003). Time to recovery was shorter in both RUTF groups. Morbidity was high and similar across groups. At the end of the study, the proportion of children with weight-for-height Z-score (WHZ) >−2 was similar (adjusted OR 1.12, 95% CI 0.74 to 1.95; p=0.464), higher for moderate malnutrition (WHZ

To estimate neonatal mortality, particularly within 24 hours of birth, in six low- and lower-middle-income countries.We analysed epidemiological data on a total of 149 570 live births collected between 2007 and 2013 in six prospective randomized trials and a cohort study from predominantly rural areas of Bangladesh, Ghana, India, Pakistan, the United Republic of Tanzania and Zambia. The neonatal mortality rate and mortality within 24 hours of birth were estimated for all countries and mortality within 6 hours was estimated for four countries with available data. The findings were compared with published model-based estimates of neonatal mortality.Overall, the neonatal mortality rate observed at study sites in the six countries was 30.5 per 1000 live births (range: 13.6 in Zambia to 47.4 in Pakistan). Mortality within 24 hours was 14.1 per 1000 live births overall (range: 5.1 in Zambia to 20.1 in India) and 46.3% of all neonatal deaths occurred within 24 hours (range: 36.2% in Pakistan to 65.5% in the United Republic of Tanzania). Mortality in the first 6 hours was 8.3 per 1000 live births, i.e. 31.9% of neonatal mortality.Neonatal mortality within 24 hours of birth in predominantly rural areas of six low- and lower-middle-income countries was higher than model-based estimates for these countries. A little under half of all neonatal deaths occurred within 24 hours of birth and around one third occurred within 6 hours. Implementation of high-quality, effective obstetric and early newborn care should be a priority in these settings.Estimer la mortalité néonatale, en particulier dans les 24 heures suivant la naissance, dans six pays à revenu faible et intermédiaire - tranche inférieure.Nous avons analysé des données épidémiologiques portant sur un total de 149 570 naissances vivantes qui avaient été recueillies entre 2007 et 2013 lors de six essais prospectifs randomisés et d'une étude de cohorte réalisés dans des zones majoritairement rurales du Bangladesh, du Ghana, d'Inde, du Pakistan, de Tanzanie et de Zambie. Le taux de mortalité néonatale ainsi que la mortalité dans les 24 heures suivant la naissance ont été estimés pour tous ces pays; la mortalité dans les 6 heures suivant la naissance a été estimée pour quatre pays sur lesquels nous avions des données. Les résultats ont été comparés aux estimations de la mortalité néonatale publiées, qui ont été établies d'après des modèles.Globalement, le taux de mortalité néonatale observé sur les sites étudiés dans les six pays était de 30,5 pour 1000 naissances vivantes (de 13,6 en Zambie à 47,4 au Pakistan). La mortalité globale dans les 24 heures suivant la naissance était de 14,1 pour 1000 naissances vivantes (de 5,1 en Zambie à 20,1 en Inde) et 46,3% de l'ensemble des décès néonataux étaient survenus dans les 24 heures (de 36,2% au Pakistan à 65,5% en Tanzanie). Le taux de mortalité dans les 6 heures suivant la naissance était de 8,3 pour 1000 naissances vivantes, soit 31,9% de la mortalité néonatale totale.La mortalité néonatale dans les 24 heures suivant la naissance dans des zones majoritairement rurales de six pays à revenu faible et intermédiaire-tranche inférieure était supérieure aux estimations établies d'après des modèles pour ces pays. Un peu moins de la moitié des décès néonataux étaient survenus dans les 24 heures suivant la naissance et environ un tiers dans les 6 heures. La mise en place de soins obstétriques et néonataux efficaces et de haute qualité devrait être une priorité dans ces pays.Calcular la mortalidad neonatal, especialmente durante las 24 horas posteriores al nacimiento, en países con ingresos bajos y países con ingresos medios más bajos.Se analizaron datos epidemiológicos de un total de 149 570 nacidos vivos recopilados entre 2007 y 2013 en seis ensayos aleatorizados prospectivos y un estudio de cohortes de zonas principalmente rurales de Bangladesh, Ghana, India, Pakistán, la República Unida de Tanzanía y Zambia. Se calculó la tasa de mortalidad neonatal y la mortalidad durante las 24 horas posteriores al nacimiento en todos los países y se estimó la tasa de mortalidad en 6 horas en cuatro países con información disponible. Los resultados se compararon con estimaciones publicadas basadas en modelos de mortalidad neonatal.En general, la tasa de mortalidad neonatal observada en los lugares de estudio de los seis países fue de 30,5 por cada 1 000 nacidos vivos (alcance: 13,6 en Zambia a 47,4 en Pakistán). En conjunto, la mortalidad durante las primeras 24 horas fue de 14,1 por cada 1 000 nacidos vivos (alcance: 5,1 en Zambia a 20,1 en India) y el 46,3% de todas las muertes neonatales se produjo durante las primeras 24 horas (alcance: 36,2% en Pakistán a 65,5% en la República Unida de Tanzanía). La mortalidad en las primeras 6 horas fue de 8,3 por cada 1 000 nacidos vivos, es decir, un 31,9% de mortalidad neonatal.La mortalidad neonatal durante las 24 horas posteriores al nacimiento en zonas principalmente rurales de seis países con ingresos bajos y países con ingresos medios más bajos fue superior a las estimaciones basadas en modelos realizadas para estos países. Algo menos de la mitad de todas las muertes neonatales se produjeron durante las 24 horas posteriores al nacimiento y cerca de un tercio durante las primeras 6 horas de vida. En estos lugares, la implementación de obstetricia eficaz y de alta calidad y la atención a recién nacidos debería ser una prioridad.تقدير معدل وفيات الأطفال حديثي الولادة، وبالأخص في غضون 24قمنا بتحليل البيانات الوبائية لإجمالي 149,570عمومًا، كان معدل وفيات الأطفال حديثي الولادة الذي لوحظ في مواقع الدراسة في ستة بلدان يبلغ 30.5 لكل 1000 من المواليد على قيد الحياة (نطاق القياس: 13.6 في زامبيا إلى 47.4إن معدل الوفيات للأطفال حديثي الولادة في غضون 24旨在评估 6 个中低收入国家的新生儿死亡率、尤其是出生后 24 小时内的死亡率。.我们一共对 149 570 名新出生婴儿的流行病学数据进行了分析，该数据来自于 2007 年至 2013 年对巴基斯坦、印度、加纳、孟加拉国、坦桑尼亚联合共和国及赞比亚主要乡村地区进行的 6 项前瞻性随机试验和一项队列研究。 我们对所有国家的新生儿死亡率以及新生儿出生后 24 小时内的死亡率进行了评估，并对拥有可用数据的 4 个国家的新生儿出生后 6 小时内的死亡率进行了评估。 我们将调查结果与已发布的、基于模型的新生儿死亡率估算结果进行了比较。.总体而言， 6 个国家的研究地的实际新生儿死亡率为每 1000 名新出生婴儿中有 30.5 名死亡（范围： 从赞比亚的 13.6 到巴基斯坦的 47.4）。 新生儿出生后 24 小时内死亡率为每 1000 名新出生婴儿中共有 14.1 名死亡（范围： 从赞比亚的 5.1 到印度的 20.1），且 46.3% 的新生儿死亡案例发生在婴儿出生后 24 小时内（范围： 从巴基斯坦的 36.2% 到坦桑尼亚联合共和国的 65.5%）。 婴儿出生后 6 小时内的死亡率为每 1000 名新出生婴儿中有 8.3 名死亡，即新生儿死亡率为 31.9%。.6 个中低收入国家主要乡村地区的新生儿出生后 24 小时内的死亡率均高于这些国家的基于模型的估算结果。 略低于一半的新生儿死亡案例发生在婴儿出生后 24 小时内，而大约三分之一的案例发生在婴儿出生后 6 小时内。 上述国家应将实施优质、有效的产科护理和早期新生儿护理视为工作重点。.Дать оценку смертности новорожденных, особенно в первые 24 часа жизни, в шести странах с низким уровнем дохода и уровнем дохода ниже среднего.Проведен анализ эпидемиологических данных, полученных в результате рождения 149 570 живых детей в промежутке с 2007 по 2013 год, на основании шести проспективных рандомизированных исследований и одного когортного исследования в преимущественно сельских регионах Бангладеша, Ганы, Замбии, Индии, Объединенной Республики Танзании и Пакистана. Были рассчитаны показатели смертности новорожденных в первые 24 часа для всех стран, а оценка смертности в первые шесть часов была получена для четырех стран с доступными данными. Результаты сравнили с опубликованными показателями смертности новорожденных, рассчитанными на основе моделирования.В целом показатель смертности новорожденных, наблюдаемый в центрах проведения исследования шести стран, составил 30,5 на 1000 рождений живых детей (от 13,6 в Замбии до 47,4 в Пакистане). Смертность в течение первых суток в целом составляла 14,1 на 1000 рождений живых детей (диапазон: от 5,1 в Замбии до 20,1 в Индии) или 46,3% от всех смертей новорожденных (от 36,2% в Пакистане до 65,5% в Объединенной Республике Танзания). Смертность в первые шесть часов составляла 8,3 на 1000 рождений живых детей или 31,9% от всех смертей новорожденных.Смертность новорожденных в первые 24 часа в преимущественно сельских регионах шести стран с низким уровнем дохода и уровнем дохода ниже среднего была выше, чем показатели, рассчитанные на основе моделирования для этих же стран. Чуть менее половины всех смертей новорожденных произошли в течение 24 часов после рождения, и около трети произошли в течение первых шести часов. Поэтому внедрение высококачественной эффективной акушерской помощи и ухода за новорожденными должно стать первостепенной задачей.

INTRODUCTION: The CHNRI method for setting health research priorities has crowdsourcing as the major component. It uses the collective opinion of a group of experts to generate, assess and prioritize between many competing health research ideas. It is difficult to compare the accuracy of human individual and collective opinions in predicting uncertain future outcomes before the outcomes are known. However, this limitation does not apply to existing knowledge, which is an important component underlying opinion. In this paper, we report several experiments to explore the quantitative properties of human collective knowledge and discuss their relevance to the CHNRI method. METHODS: We conducted a series of experiments in groups of about 160 (range: 122-175) undergraduate Year 2 medical students to compare their collective knowledge to their individual knowledge. We asked them to answer 10 questions on each of the following: (i) an area in which they have a degree of expertise (undergraduate Year 1 medical curriculum); (ii) an area in which they likely have some knowledge (general knowledge); and (iii) an area in which they are not expected to have any knowledge (astronomy). We also presented them with 20 pairs of well-known celebrities and asked them to identify the older person of the pair. In all these experiments our goal was to examine how the collective answer compares to the distribution of students' individual answers. RESULTS: When answering the questions in their own area of expertise, the collective answer (the median) was in the top 20.83% of the most accurate individual responses; in general knowledge, it was in the top 11.93%; and in an area with no expertise, the group answer was in the top 7.02%. However, the collective answer based on mean values fared much worse, ranging from top 75.60% to top 95.91%. Also, when confronted with guessing the older of the two celebrities, the collective response was correct in 18/20 cases (90%), while the 8 most successful individuals among the students had 19/20 correct answers (95%). However, when the system in which the students who were not sure of the correct answer were allowed to either choose an award of half of the point in all such instances, or withdraw from responding, in order to improve the score of the collective, the collective was correct in 19/20 cases (95%), while the 3 most successful individuals were correct in 17/20 cases (85%). CONCLUSIONS: Our experiments showed that the collective knowledge of a group with expertise in the subject should always be very close to the true value. In most cases and under most assumption, the collective knowledge will be more accurate than the knowledge of an "average" individual, but there always seems to be a small group of individuals who manage to out-perform the collective. The accuracy of collective prediction may be enhanced by allowing the individuals with low confidence in their answer to withdraw from answering.

In 2007 and 2008, the World Health Organization's Department for Child and Adolescent Health and Development (later renamed as WHO MNCAH – Maternal, Newborn, Child and Adolescent Health) commissioned five large exercises to define research priorities related to the five major causes of child deaths for the period up to the year 2015. The exercises were based on the CHNRI (Child Health and Nutrition Research Initiative) method, which was just being introduced at the time [1,2]. The selected causes were childhood pneumonia, diarrhoea, birth asphyxia, neonatal infections and preterm birth/low birth weight [3–7]. The context for those exercises was clearly defined: to identify research that could help reduce mortality in children under 5 years of age in low and middle income countries by the year 2015. The criteria used in all five exercises were the “standard” CHNRI criteria: (i) answerability of the research question; (ii) likelihood of the effectiveness of the resulting intervention; (iii) deliverability (with affordability and sustainability); (iv) potential to reduce disease burden; and (v) effect on equity [3–7]. The five criteria used by the scorers were intuitive as they followed the path from generating new knowledge to having an impact on the cause of death. They were chosen with a view to identifying research questions that were most likely to contribute to finding effective solutions to the problems. However, after the five exercises – all of which were published in respected international journals [3–7] – the WHO officers were left with an additional question: how “fundable” were the identified priorities, ie, how attractive were they to research funders? More specifically, should another criterion be added to the CHNRI exercises, which would evaluate the likelihood of obtaining funding support for specific research questions? To answer these questions, coordinators of the CHNRI exercises at the WHO agreed that it would be useful to invite a number of representatives from large funding organizations interested in child health research to take part in a consultation process at the WHO. The process aimed to explore funders perspectives in prioritization of health research. The funders would be presented with the leading research priorities identified through the CHNRI exercises and asked to discuss any potential variation in their likelihood of being funded. If all the leading priorities were equally attractive to funders and likely to attract funding support, this would indicate that the “standard” CHNRI criteria were sufficient for the process of prioritization. However, if there were large differences in attractiveness of the identified research priorities to funders, then adding another criterion to the exercise – “likelihood of obtaining funding support”, or simply “fundability” – would be a useful addition to the standard CHNRI framework.

Large groups of researchers who agree to offer their research ideas and then score them against pre–defined criteria are at the heart of each CHNRI priority–setting exercise. Although the roles of funders and other stakeholders are also very important, much of the exercise is focused on selecting and engaging a large group of researchers, obtaining their input and analysing it to derive the initial results of the process. In a sense, a CHNRI exercise serves to “visualise” the collective knowledge and opinions of many leading researchers on the status of their own research field. Through a simple “crowdsourcing” process conducted within the relevant research community, the CHNRI approach is able to collate a wide spectrum of research ideas and options, and come to a judgement on their strengths and weaknesses, based on the collective knowledge and opinions of many members of the research community. In doing so, it provides valuable information to funders, stakeholders and researchers themselves, which is obtained at low cost and with little time necessary to conduct the exercise.

Setting health research priorities is a complex and value–driven process. The introduction of the Child Health and Nutrition Research Initiative (CHNRI) method has made the process of setting research priorities more transparent and inclusive, but much of the process remains in the hands of funders and researchers, as described in the previous two papers in this series [1,2]. However, the value systems of numerous other important stakeholders, particularly those on the receiving end of health research products, are very rarely addressed in any process of priority setting. Inclusion of a larger and more diverse group of stakeholders in the process would result in a better reflection of the system of values of the broader community, resulting in recommendations that are more legitimate and acceptable. The CHNRI method, as originally proposed, took into account the importance of stakeholders and made provisions for their participation in the process. Although the involvement of a large and diverse group of stakeholders is desirable, they were not expected to propose research ideas, or score them against the set of pre–defined criteria. Because of this, the original CHNRI method proposed that stakeholders should be allowed to “weigh” pre–defined criteria and set “thresholds” for a minimum acceptable score against each criterion that would be required for a research idea to be considered a “research priority”. In choosing the stakeholders, the context of each exercise will be very important and the goals of the specific exercise should be defined before choosing an appropriate “stakeholder group”. Among stakeholders, we would expect to see those affected by the disease of interest and their family members, their carers and health workers, members of general public, media representatives interested in the topic, community leaders, representatives of the consumer groups and industry, but also potentially researchers and funders themselves. Although the latter two groups – researchers and funders – already have a different role assigned in the CHNRI process, this does not exclude them from also being stakeholders in the process [1,2]. In this paper, we aim to review and analyse the experiences in stakeholder involvement across the 50 CHNRI exercises published in the 10–year period between 2007 and 2016, the proposed approaches to involving stakeholders and their effects on the outcome of the prioritization process. One paper in the original CHNRI method series focused on involving stakeholders [3]. That paper presented practical experiences from three separate attempts to involve stakeholders that took place in 2006. The three groups approached were: (i) members of the global research priority setting network; (ii) a diverse group of national–level stakeholders from South Africa; and (iii) participants at a conference related to international child health held in Washington, DC, USA. Each group was asked to complete a short questionnaire to assess the relative importance of the five original CHNRI criteria. Different versions of the questionnaire were used with each group [3]. The results of this exercise indicated that groups of stakeholders vary in the weights they assigned to the 5 criteria, reflecting divergence in the “value” placed on each criterion by each stakeholder group. The diverse group of respondents within the priority–setting network placed the greatest weight on the criterion of “maximum potential for disease burden reduction” and the most stringent threshold on “answerability in an ethical way”. Among the attendees at the international conference on child health, the criterion of “deliverability, answerability and sustainability” was identified as the most important. Finally, in South Africa, where inequity has been a national problem historically, the greatest weight was placed on the “predicted impact on equity” criterion. This comparative analysis by Kapiriri et al. [3] effectively demonstrated that involving a wide range of stakeholders is an important goal for any research priority setting exercise. The criteria that may be of importance to funders, scientists and other technical experts involved in the process of planning and conducting the exercise may not be well aligned with the values of those who should eventually benefit from health research, or with the sentiments of wider society as a whole [3]. This is an important observation, because if the CHNRI process is conducted without regard for the broader social value or research, then it is unrealistic to expect it to fulfil its purpose of being accepted as a fair, transparent and legitimate process for setting investment priorities for health research.

Objective Conduct a global situational analysis to identify the current facilitators and barriers to improving quality of care (QoC) for pregnant women, newborns and children. Study design Metareview of published and unpublished systematic reviews and meta-analyses conducted between January 2000 and March 2013 in any language. Assessment of Multiple Systematic Reviews (AMSTAR) is used to assess the methodological quality of systematic reviews. Settings Health systems of all countries. Study outcome: QoC measured using surrogate indicators––effective, efficient, accessible, acceptable/patient centred, equitable and safe. Analysis Conducted in two phases (1) qualitative synthesis of extracted data to identify and group the facilitators and barriers to improving QoC, for each of the three population groups, into the six domains of WHO9s framework and explore new domains and (2) an analysis grid to map the common facilitators and barriers. Results We included 98 systematic reviews with 110 interventions to improve QoC from countries globally. The facilitators and barriers identified fitted the six domains of WHO9s framework––information, patient–population engagement, leadership, regulations and standards, organisational capacity and models of care. Two new domains, ‘communication’ and ‘satisfaction’, were generated. Facilitators included active and regular interpersonal communication between users and providers; respect, confidentiality, comfort and support during care provision; engaging users in decision-making; continuity of care and effective audit and feedback mechanisms. Key barriers identified were language barriers in information and communication; power difference between users and providers; health systems not accounting for user satisfaction; variable standards of implementation of standard guidelines; shortage of resources in health facilities and lack of studies assessing the role of leadership in improving QoC. These were common across the three population groups. Conclusions The barriers to good-quality healthcare are common for pregnant women, newborns and children; thus, interventions targeted to address them will have uniform beneficial effects. Adopting the identified facilitators would help countries strengthen their health systems and ensure high-quality care for all.

SummaryBackgroundAlthough the benefits of exclusive breastfeeding for child health and survival, particularly in the post-neonatal period, are established, the independent beneficial effect of early breastfeeding initiation remains unclear. We studied the association between timing of breastfeeding initiation and post-enrolment neonatal and post-neonatal mortality up to 6 months of age, as well as the associations between breastfeeding pattern and mortality.MethodsWe examined associations between timing of breastfeeding initiation, post-enrolment neonatal mortality (enrolment 28 days), and post-neonatal mortality up to 6 months of age (29–180 days) in a large cohort from three neonatal vitamin A trials in Ghana, India, and Tanzania. Newborn babies were eligible for these trials if their mother reported that they were likely to stay in the study area for the next 6 months, they could feed orally, were aged less than 3 days, and the primary caregiver gave informed consent. We excluded infants who initiated breastfeeding after 96 h, did not initiate, or had missing initiation status. We pooled the data from both randomised groups of the three trials and then categorised time of breastfeeding initiation as: at ≤1 h, 2–23 h, and 24–96 h. We defined breastfeeding patterns as exclusive, predominant, or partial breastfeeding at 4 days, 1 month, and 3 months of age. We estimated relative risks using log binomial regression and Poisson regression with robust variances. Multivariate models controlled for site and potential confounders.FindingsOf 99 938 enrolled infants, 99 632 babies initiated breastfeeding by 96 h of age and were included in our prospective cohort. 56 981 (57·2%) initiated breastfeeding at ≤1 h, 38 043 (38·2%) at 2–23 h, and 4608 (4·6%) at 24–96 h. Compared with infants initiating breastfeeding within the first hour of life, neonatal mortality between enrolment and 28 days was higher in infants initiating at 2–23 h (adjusted relative risk 1·41 [95% CI 1·24–1·62], p

The present paper describes the ongoing efforts to revitalize the accountability of national governments toward preventable maternal deaths. Maternal death reviews are included in the national health policies of the majority of countries contributing 95% of global maternal deaths. However in actual practice, the extent of implementation and follow-up of recommended actions on lessons learnt from maternal death reviews is inadequate. This paper describes and discusses the role of the Maternal Death Surveillance and Response (MDSR) system in strengthening accountability and ending preventable maternal deaths. MDSR provides a surveillance tool for timely information on where, when, and why maternal deaths occur, builds on maternal death reviews, and includes the missing “response” component for improving quality of care and preventing maternal deaths.

Background Vitamin A supplementation of 6-59 month old children is currently recommended by the World Health Organization based on evidence that it reduces mortality. There has been considerable interest in determining the benefits of neonatal vitamin A supplementation, but the results of existing trials are conflicting. A technical consultation convened by WHO pointed to the need for larger scale studies in Asia and Africa to inform global policy on the use of neonatal vitamin A supplementation. Three trials were therefore initiated in Ghana, India and Tanzania to determine if vitamin A supplementation (50,000 IU) given to neonates once orally on the day of birth or within the next two days will reduce mortality in the period from supplementation to 6 months of age compared to placebo. Methods/Design The trials are individually randomized, double masked, and placebo controlled. The required sample size is 40,200 in India and 32,000 each in Ghana and Tanzania. The study participants are neonates who fulfil age eligibility, whose families are likely to stay in the study area for the next 6 months, who are able to feed orally, and whose parent(s) provide informed written consent to participate in the study. Neonates randomized to the intervention group receive 50,000 IU vitamin A and the ones randomized to the control group receive placebo at the time of enrolment. Mortality and morbidity information are collected through periodic home visits by a study worker during infancy. The primary outcome of the study is mortality from supplementation to 6 months of age. The secondary outcome of the study is mortality from supplementation to 12 months of age. The three studies will be analysed independent of each other. Subgroup analysis will be carried out to determine the effect by birth weight, sex, and timing of DTP vaccine, socioeconomic groups and maternal large-dose vitamin A supplementation. Discussion The three ongoing studies are the largest studies evaluating the efficacy of vitamin A supplementation to neonates. Policy formulation will be based on the results of efficacy of the intervention from the ongoing randomized controlled trials combined with results of previous studies. Trial Registration Ghana: Australian New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12610000582055 ; India: CLINICALTRIALS.GOV - NCT01138449 ; Tanzania: Australian New Zealand Clinical Trials Registry (ANZCTR) - ACTRN12610000636055.