Community health worker (CHW) presence, number and timing of visits, behavior change messaging strategies, and focus on specific household members for different behaviors associates with maternal and newborn care practices. n Local sociocultural factors such as the decision dynamics of households and common false beliefs about neonatal care should inform how the CHW communicates.

Introduction: Neisseria meningitidis serogroup B is the most common form of meningococcal infection in young adults in the U.S. Vaccines have recently become available, but it is not clear that the benefits outweigh the costs. The purpose of this study was to assess cost effectiveness and determine potentially favorable conditions for universal vaccination. Methods: Costs and benefits of universal vaccination at college entry versus no universal vaccination with an outbreak response were estimated in 2018 in the context of a mid-sized U.S.based 4-year college from both a health sector and a societal perspective. Probability, cost, and utility data were obtained from the published literature. Costs (2015 U.S.$) and benefits were discounted at 3%. One-way and multivariable probabilistic sensitivity analyses were performed including variations in the specific vaccine used. Further testing of the model's parameters at extremes was used to identify favorable conditions for universal vaccination.

The contribution of district prioritization on maternal and newborn health interventions coverage in rural India Background In 2001, India prioritized eight most socioeconomically disadvantaged states known as Empowered Action Group (EAG) states and in 2013, it prioritized 190 of the 718 as high priority districts (HPDs) to accelerate the decline in maternal and newborn mortality. This paper assesses whether the HPDs achieved a greater coverage of maternal and newborn health interventions than the non-HPDs and HPDs in EAG states achieved greater coverage than those in non-EAG states. Methods We used data from the Sample Registration System to assess rural neonatal mortality trends in EAG states and all India. We computed a co-coverage index based on seven maternal and newborn health interventions from the 2015/16 National Family Health Survey. Difference in differences (DID) analyses were used to examine the contribution of district prioritization, considering the HPDs and the illiterate as treatment groups and 2013 as the time cutoff for the pre-and post-treatment. Results Neonatal mortality declined in rural India from 36 to 27 per 1000 live births during 2010-2016 at 4.5% per year. Four EAG states experienced faster rates of decline than the national rate. From 2013, the co-coverage index increased significantly more in the HPDs compared to non-HPDs (DID = 0.11, P ≤ 0.005). The district prioritization effect on co-coverage was statistically significant in only EAG states (DID = 0.13, P ≤ 0.05). The coverage gains for illiterate mothers were greater than for literate mothers, especially in the HPDs. Conclusions The district prioritization in India is associated with greater improvements in the coverage of maternal and newborn health services in EAG states and the HPDs, including reductions in inequalities within those states and districts. There are however still large gaps between states and districts and within districts by the mother' s literacy status that need further prioritization to make progress towards the SDG targets by 2030. Electronic supplementary material: The online version of this article contains supplementary material.

IntroductionImproving the quality of care during childbirth is essential for reducing neonatal and maternal mortality. One barrier to improving quality of care is understanding the appropriate level to target interventions. We examine quality of care data during labour and delivery from multiple countries to assess whether quality varies primarily from nurse to nurse within the same facility, or primarily between facilities.MethodsTo assess the relative contributions of nurses and facilities to variance in quality of care, we performed a variance decomposition analysis using a linear mixed effect model on two data sources: (1) the number of vital signs assessed for women in labour from a study of nurse practices in Uttar Pradesh, India; 2) broad-scale indices of respectful and competent care generated from Service Provision Assessments in Kenya and Malawi. We used unsupervised clustering, a data mining technique that groups objects together based on similar characteristics, to identify groups of facilities that displayed distinct patterns of vital signs assessment behaviour.ResultsWe found 3–10 times more variance in quality of care was explained by the facility where a patient received care than by the nurse who provided it. The unsupervised clustering analysis revealed groups of facilities with highly distinct patterns of vital signs assessment, even when overall rates of vital signs assessments were similar (eg, some facilities consistently test fetal heart rate, but not other vitals, others only blood pressure).ConclusionFacilities within a region can vary substantially in the quality of care they provide to women in labour, but within a facility, nurses tend to provide similar care. This holds true both for care that can be influenced by equipment availability and technical training (eg, vital signs assessment), as well as cultural aspects (eg, respectful care).