Impact of maternal antenatal nutrition and infection treatment interventions on Longitudinal Infant Development and Growth in rural Ethiopia: protocol of the LIDG child follow-up study.

Introduction: Maternal undernutrition and inflammation in utero may significantly impact the neurodevelopmental potential of offspring. However, few studies have investigated the effects of pregnancy interventions on long-term child growth and development. This study will examine the effects of prenatal nutrition and infection management interventions on long-term growth and neurodevelopmental outcomes of offspring.

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

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

Risk Factors of Pelvic Floor Disorders Among Women in Rural Nepal: A Case-Control Study.

Introduction And Hypothesis: Risk factors for pelvic floor disorders (PFDs) are not well understood in lower resource settings. The objective of this study is to determine the risk factors associated with stress urinary incontinence (SUI), urge urinary incontinence (UUI), and pelvic organ prolapse (POP) among women of reproductive age in rural Nepal.

Methods: This is a case-control study nested within a community-based cross-sectional survey of parous women of reproductive age with PFDs in the Sarlahi District of Nepal.

Factors Predicting Completion of Four or More Antenatal Care Visits in Sarlahi District, Nepal.

Background: A significant number of women die from pregnancy and childbirth complications globally, particularly in low- and middle-income countries (LMICs). Receiving at least four antenatal care (ANC) visits may be important in reducing maternal and perinatal deaths. This study investigates factors associated with attending ≥ 4 ANC visits in Sarlahi district of southern Nepal.

Challenges of COVID-19 Case Forecasting in the US, 2020-2021.

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org).

Impact of topical applications of sunflower seed oil on neonatal mortality and morbidity in southern Nepal: a community-based, cluster-randomised trial.

Introduction: Hospital-based studies have demonstrated topical applications of sunflower seed oil (SSO) to skin of preterm infants can reduce nosocomial infections and improve survival. In South Asia, replacing traditional mustard with SSO might have similar benefits.

Methods: 340 communities in Sarlahi, Nepal were randomised to use mustard oil (MO) or SSO for community practice of daily newborn massage.

Neonatal mortality risk of vulnerable newborns by fine stratum of gestational age and birthweight for 230 679 live births in nine low- and middle-income countries, 2000-2017.

Objective: To describe the mortality risks by fine strata of gestational age and birthweight among 230 679 live births in nine low- and middle-income countries (LMICs) from 2000 to 2017.

Design: Descriptive multi-country secondary data analysis.

Setting: Nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America.

The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy.

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts.

Comparison of pregnancy and neonatal outcomes in a retrospective full pregnancy history survey versus population-based prospective records: a validation study in rural Sarlahi District, Nepal.

Introduction: Countries without complete civil registration and vital statistics systems rely on retrospective full pregnancy history surveys (FPH) to estimate incidence of pregnancy and mortality outcomes, including stillbirth and neonatal death. Yet surveys are subject to biases that impact demographic estimates, and few studies have quantified these effects. We compare data from an FPH vs.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty.

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.

Supplementation with fortified balanced energy-protein during pregnancy and lactation and its effects on birth outcomes and infant growth in southern Nepal: protocol of a 2×2 factorial randomised trial.

Introduction: Many women in low and middle-income countries enter pregnancy with low nutritional reserves with increased risk of fetal growth restriction and poor birth outcomes, including small-for-gestational-age (SGA) and preterm birth. Balanced energy-protein (BEP) supplements have shown reductions in risk of stillbirth and SGA, yet variations in intervention format and composition and limited evidence on the impact of BEP during lactation on growth outcomes warrant further study. This paper describes the protocol of the Maternal Infant Nutrition Trial (MINT) Study, which aims to evaluate the impact of a fortified BEP supplement during pregnancy and lactation on birth outcomes and infant growth in rural Nepal.

Risk factors for neonatal mortality: an observational cohort study in Sarlahi district of rural southern Nepal.

Objectives: To assess the association between maternal characteristics, adverse birth outcomes (small-for-gestational-age (SGA) and/or preterm) and neonatal mortality in rural Nepal.

Design: This is a secondary observational analysis to identify risk factors for neonatal mortality, using data from a randomised trial to assess the impact of newborn massage with different oils on neonatal mortality in Sarlahi district, Nepal.

Setting: Rural Sarlahi district, Nepal.

Informing pandemic response in the face of uncertainty. .

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.

Neonatal mortality risk of vulnerable newborns: A descriptive analysis of subnational, population-based birth cohorts for 238 203 live births in low- and middle-income settings from 2000 to 2017.

Objective: We aimed to understand the mortality risks of vulnerable newborns (defined as preterm and/or born weighing smaller or larger compared to a standard population), in low- and middle-income countries (LMICs).

Design: Descriptive multi-country, secondary analysis of individual-level study data of babies born since 2000.

Setting: Sixteen subnational, population-based studies from nine LMICs in sub-Saharan Africa, Southern and Eastern Asia, and Latin America.

Context-dependent representation of within- and between-model uncertainty: aggregating probabilistic predictions in infectious disease epidemiology.

Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible.

Enhancing Nutrition and Antenatal Infection Treatment (ENAT) study: protocol of a pragmatic clinical effectiveness study to improve birth outcomes in Ethiopia.

Introduction: The WHO Nutrition Target aims to reduce the global prevalence of low birth weight by 30% by the year 2025. The Enhancing Nutrition and Antenatal Infection Treatment (ENAT) study will test the impact of packages of pregnancy interventions to enhance maternal nutrition and infection management on birth outcomes in rural Ethiopia.

Methods And Analysis: ENAT is a pragmatic, open-label, 2×2 factorial, randomised clinical effectiveness study implemented in 12 rural health centres in Amhara, Ethiopia.

Demographic, socio-economic, obstetric, and behavioral factors associated with small-and large-for-gestational-age from a prospective, population-based pregnancy cohort in rural Nepal: a secondary data analysis.

Background: In South Asia, a third of babies are born small-for-gestational age (SGA). The risk factors are well described in the literature, but many studies are in high-and-middle income countries or measure SGA on facility births only. There are fewer studies that describe the prevalence of risk factors for large-for-gestational age (LGA) in low-income countries.

Development of an imputation model to recalibrate birth weights measured in the early neonatal period to time at delivery and assessment of its impact on size-for-gestational age and low birthweight prevalence estimates: a secondary analysis of a pregnancy cohort in rural Nepal.

Objectives: In low-income countries, birth weights for home deliveries are often measured at the nadir when babies may lose up of 10% of their birth weight, biasing estimates of small-for-gestational age (SGA) and low birth weight (LBW). We aimed to develop an imputation model that predicts the 'true' birth weight at time of delivery.

Design: We developed and applied a model that recalibrates weights measured in the early neonatal period to time=0 at delivery and uses those recalibrated birth weights to impute missing birth weights.