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.

BackgroundDespite recent efforts and successes in reducing the malaria burden globally, this infection still accounts for an estimated 212 million clinical cases, 2 million severe malaria cases, and approximately 429,000 deaths annually. Even with the routine use of effective anti-malarial drugs, the case fatality rate for severe malaria remains unacceptably high, with cerebral malaria being one of the most life-threatening complications. Up to one-third of cerebral malaria survivors are left with long-term cognitive and neurological deficits. From a population point of view, the decrease of malaria transmission may jeopardize the development of naturally acquired immunity against the infection, leading to fewer total cases, but potentially an increase in severe cases. The pathophysiology of severe and cerebral malaria is not completely understood, but both parasite and host determinants contribute to its onset and outcomes. Adjunctive therapy, based on modulating the host response to infection, could help to improve the outcomes achieved with specific anti-malarial therapy.Results and conclusionsIn the last decades, several interventions targeting different pathways have been tested. However, none of these strategies have demonstrated clear beneficial effects, and some have shown deleterious outcomes. This review aims to summarize evidence from clinical trials testing different adjunctive therapy for severe and cerebral malaria in humans. It also highlights some preclinical studies which have evaluated novel strategies and other candidate therapeutics that may be evaluated in future clinical trials.

The impact of delayed treatment of uncomplicated P. falciparum malaria on progression to severe malaria: A systematic review and a pooled multicentre individual-patient meta-analysis. PLoS Med 17(10): e1003359.

BACKGROUND: Although the burden of postdischarge mortality (PDM) in low-income settings appears to be significant, no clear recommendations have been proposed in relation to follow-up care after hospitalization. We aimed to determine the burden of pediatric PDM and develop predictive models to identify children who are at risk for dying after discharge. METHODS:Deaths after hospital discharge among children aged <15 years in the last 17 years were reviewed in an area under demographic and morbidity surveillance in Southern Mozambique. We determined PDM over time (up to 90 days) and derived predictive models of PDM using easily collected variables on admission. RESULTS:Overall PDM was high (3.6%), with half of the deaths occurring in the first 30 days. One primary predictive model for all ages included young age, moderate or severe malnutrition, a history of diarrhea, clinical pneumonia symptoms, prostration, bacteremia, having a positive HIV status, the rainy season, and transfer or absconding, with an area under the curve of 0.79 (0.75-0.82) at day 90 after discharge. Alternative models for all ages including simplified clinical predictors had a similar performance. A model specific to infants <3 months old was used to identify as predictors being a neonate, having a low weight-for-age z score, having breathing difficulties, having hypothermia or fever, having oral candidiasis, and having a history of absconding or transfer to another hospital, with an area under the curve of 0.76 (0.72-0.91) at day 90 of follow-up. CONCLUSIONS: Death after discharge is an important although poorly recognized contributor to child mortality. A simple predictive algorithm based on easily recognizable variables could readily be used to identify most infants and children who are at a high risk of dying after discharge.abstract