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Population-based seroepidemiological surveys provide accurate estimates of disease burden. We compare the COVID-19 prevalence estimates from two serial serological surveys and the associated risk factors among women and children in a peri-urban area of Karachi, Pakistan.The AMANHI-COVID-19 study enrolled women and children between November 2020 and March 2021. Blood samples were collected from March to June 2021 (baseline) and September to December 2021 (follow-up) to test for anti-SARS-CoV-2 antibodies using ROCHE Elecsys®. Participants were visited or called weekly during the study for recording symptoms of COVID-19. We report the proportion of participants with anti-SARS-CoV-2 antibodies and symptoms in each survey and describe infection risk factors using step-wise binomial regression analysis.The adjusted seroprevalence among women was 45.3% (95% confidence interval (CI) = 42.6-47.9) and 82.3% (95% CI = 79.9-84.4) at baseline and follow-up survey, respectively. Among children, it was 18.4% (95% CI = 16.1-20.7) and 57.4% (95% CI = 54.3-60.3) at baseline and follow-up, respectively. Of the women who were previously seronegative, 404 (74.4%) tested positive at the follow-up survey, as did 365 (50.4%) previously seronegative children. There was a high proportion of asymptomatic infection. At baseline, being poorest and lacking access to safe drinking water lowered the risk of infection for both women (risk ratio (RR) = 0.8, 95% CI = 0.7-0.9 and RR = 1.2, 95% CI = 1.1-1.4, respectively) and children (RR = 0.7, 95% CI = 0.5-1.0 and RR = 1.4, 95% CI = 1.0-1.8, respectively). At the follow-up survey, the risk of infection was lower for underweight women and children (RR = 0.4, 95% CI = 0.3-0.7 and RR = 0.7, 95% CI = 0.5-0.8, respectively) and for women in the 30-39 years age group and children who were 24-36 months of age (RR = 0.6, 95% CI = 0.4-0.9 and RR = 0.7, 95% CI = 0.5-0.9, respectively). In both surveys, paternal employment was an important predictor of seropositivity among children (RR = 0.7, 95% CI = 0.6-0.9 and RR = 0.8, 95% CI = 0.7-1.0, respectively).There was a high rate of seroconversion among women and children. Infection was generally mild. Parental education plays an important role in protection of children from COVID-19.

Bangladesh reported its first COVID-19 case on March 8, 2020. Despite lockdowns and promoting behavioural interventions, as of December 31, 2021, Bangladesh reported 1.5 million confirmed cases and 27 904 COVID-19-related deaths. To understand the course of the pandemic and identify risk factors for SARs-Cov-2 infection, we conducted a cohort study from November 2020 to December 2021 in rural Bangladesh.After obtaining informed consent and collecting baseline data on COVID-19 knowledge, comorbidities, socioeconomic status, and lifestyle, we collected data on COVID-like illness and care-seeking weekly for 54 weeks for women (n = 2683) and their children (n = 2433). Between March and July 2021, we tested all participants for SARS-CoV-2 antibodies using ROCHE's Elecsys® test kit. We calculated seropositivity rates and 95% confidence intervals (95% CI) separately for women and children. In addition, we calculated unadjusted and adjusted relative risk (RR) and 95% CI of seropositivity for different age and risk groups using log-binomial regression models.Overall, about one-third of women (35.8%, 95% CI = 33.7-37.9) and one-fifth of children (21.3%, 95% CI = 19.2-23.6) were seropositive for SARS-CoV-2 antibodies. The seroprevalence rate doubled for women and tripled for children between March 2021 and July 2021. Compared to women and children with the highest household wealth (HHW) tertile, both women and children from poorer households had a lower risk of infection (RR, 95% CI for lowest HHW tertile women (0.83 (0.71-0.97)) and children (0.75 (0.57-0.98)). Most infections were asymptomatic or mild. In addition, the risk of infection among women was higher if she reported chewing tobacco (RR = 1.19,95% CI = 1.03-1.38) and if her husband had an occupation requiring him to work indoors (RR = 1.16, 95% CI = 1.02-1.32). The risk of infection was higher among children if paternal education was5 years (RR = 1.37, 95% CI = 1.10-1.71) than in children with a paternal education of ≤5 years.We provided prospectively collected population-based data, which could contribute to designing feasible strategies against COVID-19 tailored to high-risk groups. The most feasible strategy may be promoting preventive care practices; however, collecting data on reported practices is inadequate. More in-depth understanding of the factors related to adoption and adherence to the practices is essential.

Knowledge of gestational age is critical for guiding preterm neonatal care. In the last decade, metabolic gestational dating approaches emerged in response to a global health need; because in most of the developing world, accurate antenatal gestational age estimates are not feasible. These methods initially developed in North America have now been externally validated in two studies in developing countries, however, require shipment of samples at sub-zero temperature.A subset of 330 pairs of heel prick dried blood spot samples were shipped on dry ice and in ambient temperature from field sites in Tanzania, Bangladesh and Pakistan to laboratory in Iowa (USA). We evaluated impact on recovery of analytes of shipment temperature, developed and evaluated models for predicting gestational age using a limited set of metabolic screening analytes after excluding 17 analytes that were impacted by shipment conditions of a total of 44 analytes.With the machine learning model using all the analytes, samples shipped in dry ice yielded a Root Mean Square Error (RMSE) of 1.19 weeks compared to 1.58 weeks for samples shipped in ambient temperature. Out of the 44 screening analytes, recovery of 17 analytes was significantly different between the two shipment methods and these were excluded from further machine learning model development. The final model, restricted to stable analytes provided a RMSE of 1.24 (95% confidence interval (CI) = 1.10-1.37) weeks for samples shipped on dry ice and RMSE of 1.28 (95% CI = 1.15-1.39) for samples shipped at ambient temperature. Analysis for discriminating preterm births (gestational age37 weeks), yielded an area under curve (AUC) of 0.76 (95% CI = 0.71-0.81) for samples shipped on dry ice and AUC of 0.73 (95% CI = 0.67-0.78) for samples shipped in ambient temperature.In this study, we demonstrate that machine learning algorithms developed using a sub-set of newborn screening analytes which are not sensitive to shipment at ambient temperature, can accurately provide estimates of gestational age comparable to those from published regression models from North America using all analytes. If validated in larger samples especially with more newborns34 weeks, this technology could substantially facilitate implementation in LMICs.

To address the disproportionate burden of preterm birth (PTB) in low- and middle-income countries, this study aimed to (1) verify the performance of the United States-validated spontaneous PTB (sPTB) predictor, comprised of the IBP4/SHBG protein ratio, in subjects from Bangladesh, Pakistan and Tanzania enrolled in the Alliance for Maternal and Newborn Health Improvement (AMANHI) biorepository study, and (2) discover biomarkers that improve performance of IBP4/SHBG in the AMANHI cohort. The performance of the IBP4/SHBG biomarker was first evaluated in a nested case control validation study, then utilized in a follow-on discovery study performed on the same samples. Levels of serum proteins were measured by targeted mass spectrometry. Differences between the AMANHI and U.S. cohorts were adjusted using body mass index (BMI) and gestational age (GA) at blood draw as covariates. Prediction of sPTB < 37 weeks and < 34 weeks was assessed by area under the receiver operator curve (AUC). In the discovery phase, an artificial intelligence method selected additional protein biomarkers complementary to IBP4/SHBG in the AMANHI cohort. The IBP4/SHBG biomarker significantly predicted sPTB < 37 weeks (n = 88 vs. 171 terms ≥ 37 weeks) after adjusting for BMI and GA at blood draw (AUC= 0.64, 95% CI: 0.57–0.71, p < .001). Performance was similar for sPTB < 34 weeks (n = 17 vs. 184 ≥ 34 weeks): AUC = 0.66, 95% CI: 0.51–0.82, p = .012. The discovery phase of the study showed that the addition of endoglin, prolactin, and tetranectin to the above model resulted in the prediction of sPTB < 37 with an AUC= 0.72 (95% CI: 0.66–0.79, p-value < .001) and prediction of sPTB < 34 with an AUC of 0.78 (95% CI: 0.67–0.90, p < .001). A protein biomarker pair developed in the U.S. may have broader application in diverse non-U.S. populations.

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 (

Background Babies born early and/or small for gestational age in Low and Middle-income countries (LMICs) contribute substantially to global neonatal and infant mortality. Tracking this metric is critical at a population level for informed policy, advocacy, resources allocation and program evaluation and at an individual level for targeted care. Early prenatal ultrasound examination is not available in these settings, gestational age (GA) is estimated using new-born assessment, last menstrual period (LMP) recalls and birth weight, which are unreliable. Algorithms in developed settings, using metabolic screen data, provided GA estimates within 1–2 weeks of ultrasonography-based GA. We sought to leverage machine learning algorithms to improve accuracy and applicability of this approach to LMICs settings. Methods This study uses data from AMANHI-ACT, a prospective pregnancy cohorts in Asia and Africa where early pregnancy ultrasonography estimated GA and birth weight are available and metabolite screening data in a subset of 1318 new-borns were also available. We utilized this opportunity to develop machine learning (ML) algorithms. Random Forest Regressor was used where data was randomly split into model-building and model-testing dataset. Mean absolute error (MAE) and root mean square error (RMSE) were used to evaluate performance. Bootstrap procedures were used to estimate confidence intervals (CI) for RMSE and MAE. For pre-term birth identification ROC analysis with bootstrap and exact estimation of CI for area under curve (AUC) were performed. Results Overall model estimated GA had MAE of 5.2 days (95% CI 4.6–6.8), which was similar to performance in SGA, MAE 5.3 days (95% CI 4.6–6.2). GA was correctly estimated to within 1 week for 85.21% (95% CI 72.31–94.65). For preterm birth classification, AUC in ROC analysis was 98.1% (95% CI 96.0–99.0; p p = 0.002). Conclusions Machine learning algorithms and models applied to metabolomic gestational age dating offer a ladder of opportunity for providing accurate population-level gestational age estimates in LMICs settings. These findings also point to an opportunity for investigation of region-specific models, more focused feasible analyte models, and broad untargeted metabolome investigation.

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.

The AMANHI Biobank cohort is a large cohort of pregnant women and their babies in sub-Saharan Africa and South Asia aimed at studying the interactions between genes and a wide range of varying environmental exposures on key pregnancy and birth outcomes. The cohort is well characterized for clinical, epidemiological and socio-economic information with harmonized data collection across all sites. The samples were collected and stored following standard operating procedures and provide an excellent opportunity for biological characterization. The cohort includes a total of 10 001 women enrolled between May 2014 and June 2018 across Sylhet-Bangladesh, Karachi-Pakistan and Pemba Island-Tanzania, who have given birth to 9938 babies. Follow-up included three to four visits during pregnancy: at baseline, at 24–28 weeks, at 32–36 weeks and after 37 completed weeks of gestational age to collect routine epidemiological data and biological samples, and two additional visits after birth: between 1 and 6 days after birth and the second one between 42 and 60 days of age, in which the newborn’s samples were taken. The data set comprises a wide range of phenotypical data and environmental measures, biological samples, as well as a multiplicity of outcomes from the mother, the fetus and the neonate. The AMANHI biobank data is available at the Department for Maternal, Newborn, Child and Adolescent Health, and Ageing at the World Health Organization, which is the coordination centre of the study. Queries regarding the data and potential collaborations can be sent to Dr Rajiv Bahl (bahlr@who.int).

Background COVID-19 is disrupting health services for mothers and newborns, particularly in low- and middle-income countries (LMIC). Preterm newborns are particularly vulnerable. We undertook analyses of the benefits of kangaroo mother care (KMC) on survival among neonates weighing ≤2000 g compared with the risk of SARS-CoV-2 acquired from infected mothers/caregivers. Methods We modelled two scenarios over 12 months. Scenario 1 compared the survival benefits of KMC with universal coverage (99%) and mortality risk due to COVID-19. Scenario 2 estimated incremental deaths from reduced coverage and complete disruption of KMC. Projections were based on the most recent data for 127 LMICs (~90% of global births), with results aggregated into five regions. Findings Our worst-case scenario (100% transmission) could result in 1,950 neonatal deaths from COVID-19. Conversely, 125,680 neonatal lives could be saved with universal KMC coverage. Hence, the benefit of KMC is 65-fold higher than the mortality risk of COVID-19. If recent evidence of 10% transmission was applied, the ratio would be 630-fold. We estimated a 50% reduction in KMC coverage could result in 12,570 incremental deaths and full disruption could result in 25,140 incremental deaths, representing a 2·3–4·6% increase in neonatal mortality across the 127 countries. Interpretation The survival benefit of KMC far outweighs the small risk of death due to COVID-19. Preterm newborns are at risk, especially in LMICs where the consequences of disruptions are substantial. Policymakers and healthcare professionals need to protect services and ensure clearer messaging to keep mothers and newborns together, even if the mother is SARS-CoV-2-positive. Funding Eunice Kennedy Shriver National Institute of Child Health & Human Development; Bill & Melinda Gates Foundation; Elma Philanthropies; Wellcome Trust; and Joint Global Health Trials scheme of Department of Health and Social Care, Department for International Development, Medical Research Council, and Wellcome Trust.

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.

Few studies have examined HRQOL in pediatric Tx recipients' parents. This study investigated HRQOL in these parents and relationships between HRQOL and perceived burden of nurturing, family functioning, and social support. Self-report anonymous questionnaires and a survey of medical records were completed between September and December 2013. The SF-36v2, which evaluates physical, psychological, and social health, was used to measure HRQOL. While values for physical and psychological health were higher than standard values (Cohen's d = 0.34 and 0.17, respectively), social health scores were lower (d = 0.21). "Parental consultation unrelated to donation" (standardized partial regression coefficient: β = -0.52) was associated with physical health. "Family functioning" and "Commuting time between home and primary follow-up hospital" (β = 0.57 and -0.31) were related to psychological health. "Total score for perceived burden of nurturing" (β = -0.31) was related to social health. Regarding parental HRQOL, while physical and psychological health was favorable, social health was impaired. In clinical practice, interventions targeting parents' physical conditions and facilitation of community and family understanding and support to share recipients' nurturing are important in improving parental HRQOL.

OBJECTIVE: The objective of the Alliance for Maternal and Newborn Health Improvement (AMANHI) gestational age study is to develop and validate a programmatically feasible and simple approach to accurately assess gestational age of babies after they are born. The study will provide accurate, population-based rates of preterm birth in different settings and quantify the risks of neonatal mortality and morbidity by gestational age and birth weight in five South Asian and sub-Saharan African sites. METHODS: This study used on-going population-based cohort studies to recruit pregnant women early in pregnancy (

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

this trial was designed to examine the safety and efficacy of oral amoxicillin for young infants with fast breathing compared with that of an injectable penicillin–gentamicin combination. the study is currently being conducted in the Democratic Republic of Congo, Kenya and nigeria. Methods/Design: this is a randomized, open-label equivalence trial. All births in the community are visited at home by trained community health workers to identify sick infants who are then referred to a trial study nurse for assessment. the primary outcome is treatment failure by day 8 after enrollment, defined as clinical deterioration, development of a serious adverse event including death, persistence of fast breathing by day 4 or recurrence up to day 8. Secondary outcomes include adherence to study therapy, relapse, death between days 9 and 15 and adverse effects associated with the study drugs. Study outcomes are assessed on days 4, 8, 11 and 15 after randomization by an independent outcome assessor who is blinded to the treatment being given. Discussion: the results of this study will help inform the development of policies for the treatment of fast breathing among neonates and young infants in resource-limited settings.

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.