BackgroundWell-trained and highly motivated community health workers (CHWs) are critical for delivery of many community-based newborn care interventions. High rates of CHW attrition undermine programme effectiveness and potential for implementation at scale. We investigated reasons for high rates of CHW attrition in Sylhet District in north-eastern Bangladesh.MethodsSixty-nine semi-structured questionnaires were administered to CHWs currently working with the project, as well as to those who had left. Process documentation was also carried out to identify project strengths and weaknesses, which included in-depth interviews, focus group discussions, review of project records (i.e. recruitment and resignation), and informal discussion with key project personnel.ResultsMotivation for becoming a CHW appeared to stem primarily from the desire for self-development, to improve community health, and for utilization of free time. The most common factors cited for continuing as a CHW were financial incentive, feeling needed by the community, and the value of the CHW position in securing future career advancement. Factors contributing to attrition included heavy workload, night visits, working outside of one's home area, familial opposition and dissatisfaction with pay.ConclusionsThe framework presented illustrates the decision making process women go through when deciding to become, or continue as, a CHW. Factors such as job satisfaction, community valuation of CHW work, and fulfilment of pre-hire expectations all need to be addressed systematically by programs to reduce rates of CHW attrition.

BackgroundTo evaluate a delivery strategy for newborn interventions in rural Bangladesh.MethodsA cluster-randomized controlled trial was conducted in Mirzapur, Bangladesh. Twelve unions were randomized to intervention or comparison arm. All women of reproductive age were eligible to participate. In the intervention arm, community health workers identified pregnant women; made two antenatal home visits to promote birth and newborn care preparedness; made four postnatal home visits to negotiate preventive care practices and to assess newborns for illness; and referred sick neonates to a hospital and facilitated compliance. Primary outcome measures were antenatal and immediate newborn care behaviours, knowledge of danger signs, care seeking for neonatal complications, and neonatal mortality.FindingsA total of 4616 and 5241 live births were recorded from 9987 and 11153 participants in the intervention and comparison arm, respectively. High coverage of antenatal (91% visited twice) and postnatal (69% visited on days 0 or 1) home visitations was achieved. Indicators of care practices and knowledge of maternal and neonatal danger signs improved. Adjusted mortality hazard ratio in the intervention arm, compared to the comparison arm, was 1.02 (95% CI: 0.80–1.30) at baseline and 0.87 (95% CI: 0.68–1.12) at endline. Primary causes of death were birth asphyxia (49%) and prematurity (26%). No adverse events associated with interventions were reported.ConclusionLack of evidence for mortality impact despite high program coverage and quality assurance of implementation, and improvements in targeted newborn care practices suggests the intervention did not adequately address risk factors for mortality. The level and cause-structure of neonatal mortality in the local population must be considered in developing interventions. Programs must ensure skilled care during childbirth, including management of birth asphyxia and prematurity, and curative postnatal care during the first two days of life, in addition to essential newborn care and infection prevention and management.Trial RegistrationClinicaltrials.gov NCT00198627

Background Sub-Saharan Africa and south Asia contributed 81% of 5•9 million under-5 deaths and 77% of 2•6 million stillbirths worldwide in 2015. Vital registration and verbal autopsy data are mainstays for the estimation of leading causes of death, but both are non-specific and focus on a single underlying cause. We aimed to provide granular data on the contributory causes of death in stillborn fetuses and in deceased neonates and children younger than 5 years, to inform child mortality prevention efforts. Methods The Child Health and Mortality Prevention Surveillance (CHAMPS) Network was established at sites in seven countries (

Despite reductions over the past 2 decades, childhood mortality remains high in low- and middle-income countries in sub-Saharan Africa and South Asia. In these settings, children often die at home, without contact with the health system, and are neither accounted for, nor attributed with a cause of death. In addition, when cause of death determinations occur, they often use nonspecific methods. Consequently, findings from models currently utilized to build national and global estimates of causes of death are associated with substantial uncertainty. Higher-quality data would enable stakeholders to effectively target interventions for the leading causes of childhood mortality, a critical component to achieving the Sustainable Development Goals by eliminating preventable perinatal and childhood deaths. The Child Health and Mortality Prevention Surveillance (CHAMPS) Network tracks the causes of under-5 mortality and stillbirths at sites in sub-Saharan Africa and South Asia through comprehensive mortality surveillance, utilizing minimally invasive tissue sampling (MITS), postmortem laboratory and pathology testing, verbal autopsy, and clinical and demographic data. CHAMPS sites have established facility- and community-based mortality notification systems, which aim to report potentially eligible deaths, defined as under-5 deaths and stillbirths within a defined catchment area, within 24–36 hours so that MITS can be conducted quickly after death. Where MITS has been conducted, a final cause of death is determined by an expert review panel. Data on cause of death will be provided to local, national, and global stakeholders to inform strategies to reduce perinatal and childhood mortality in sub-Saharan Africa and South Asia.

ResearchObjective To estimate the validity (sensitivity, specificity, and positive and negative predictive values) of a clinical algorithm as used by community health workers (CHWs) to detect and classify neonatal illness during routine household visits in rural Bangladesh. Methods CHWs evaluated breastfeeding and symptoms and signs of illness in 395 neonates selected randomly from neonatal illness surveillance during household visits on postnatal days 0, 2, 5 and 8. Neonates classified with very severe disease (VSD) were referred to a community-based hospital. Within 12 hours of CHW assessments, physicians independently evaluated all neonates seen in a given day by one CHW, randomly chosen from among 36 project CHWs. Physicians recorded symptoms and signs of illness, classified the illness, and determined whether the newborn needed referral-level care at the hospital. Physicians' identification and classification were used as the gold standard in determining the validity of CHWs' identification of symptoms and signs of illness and its classification. Findings CHWs' classification of VSD showed a sensitivity of 73%, a specificity of 98%, a positive predictive value of 57% and a negative predictive value of 99%. A maternal report of any feeding problem as ascertained by physician questioning was significantly associated (P < 0.001) with "not sucking at all" and "not attached at all" or "not well attached" as determined clinically by CHWs during feeding assessment. Conclusion CHWs identified with high validity the neonates with severe illness needing referral-level care. Home-based illness recognition and management, including referral of neonates with severe illness by CHWs, is a promising strategy for improving neonatal health and survival in low-resource developing country settings.Une traduction en français de ce résumé figure à la fin de l'article. Al final del artículo se facilita una traducción al español.