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 (

BackgroundThere is a pressing need to ensure that youth in high HIV prevalence settings are prepared for a safer sexual debut. Smartphone ownership is increasing dramatically in low-income and middle-income countries. Smartphone games that are appropriately grounded in behavioral theory and evidence-based practice have the potential to become valuable tools in youth HIV prevention efforts in Sub-Saharan Africa.ObjectiveTo pilot-test a theory-based, empirically grounded smartphone game for young Kenyans designed to increase age and condom use at first sex, aiming to establish directionality of effects on behavior change.MethodsTumaini (“hope for the future” in Swahili) is an interactive, narrative-based game grounded in social cognitive theory. A randomized controlled pilot study was conducted in Kisumu, Western Kenya, from April to June 2017 with 60 participants aged 11-14 (mean 12.7) years. Intervention arm participants (n=30) were provided with an Android smartphone with Tumaini installed on it and were instructed to play the game for at least 1 hour a day for 16 days; control arm participants (n=30) received no intervention. All participants completed a survey on behavioral mediators, delivered via an audio computer-assisted self-interview system at baseline (T1), post intervention (T2), and at 6 weeks postintervention (T3). The postintervention survey for intervention arm participants included questions eliciting feedback on the game. Intervention arm participants and their parents participated in 8 postintervention focus group discussions. Game log files were analyzed to calculate the length of exposure to the game. Behavioral survey data were analyzed using two-sample t tests to compare mean change from T1 to T2 and to T3 for intervention versus control arm participants. Descriptive statistics on game feedback questions were computed. Focus group transcripts were uploaded to MAXQDA software, where they were labeled with deductive and inductive codes. Data were analyzed thematically and compared across demographics.ResultsIntervention arm participants played Tumaini for a mean of approximately 27 hours. The intervention arm showed significant gains in sexual health-related knowledge and self-efficacy (both P<.001), behavioral intention for risk-avoidance strategies and sexual risk communication (P=.006), and overall survey scores (P<.001) compared with the control arm at T3. The postintervention survey revealed high subjective measures of the game’s value, relevance, and appeal. Focus groups identified a wide range of knowledge and skills the participants had gained, including setting goals and planning how to achieve them, which was perceived as a key motivator for avoiding or reducing risk.ConclusionsThe study supports the need for further research to assess the efficacy of the game-based intervention. If proven efficacious, smartphone games have the potential to dramatically increase the reach of culturally adapted behavioral interventions while ensuring fidelity to intervention design.Trial RegistrationC...

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.

IntroductionDespite a growing body of research on the risks of SARS-CoV-2 infection during pregnancy, there is continued controversy given heterogeneity in the quality and design of published studies.MethodsWe screened ongoing studies in our sequential, prospective meta-analysis. We pooled individual participant data to estimate the absolute and relative risk (RR) of adverse outcomes among pregnant women with SARS-CoV-2 infection, compared with confirmed negative pregnancies. We evaluated the risk of bias using a modified Newcastle-Ottawa Scale.ResultsWe screened 137 studies and included 12 studies in 12 countries involving 13 136 pregnant women.Pregnant women with SARS-CoV-2 infection—as compared with uninfected pregnant women—were at significantly increased risk of maternal mortality (10 studies; n=1490; RR 7.68, 95% CI 1.70 to 34.61); admission to intensive care unit (8 studies; n=6660; RR 3.81, 95% CI 2.03 to 7.17); receiving mechanical ventilation (7 studies; n=4887; RR 15.23, 95% CI 4.32 to 53.71); receiving any critical care (7 studies; n=4735; RR 5.48, 95% CI 2.57 to 11.72); and being diagnosed with pneumonia (6 studies; n=4573; RR 23.46, 95% CI 3.03 to 181.39) and thromboembolic disease (8 studies; n=5146; RR 5.50, 95% CI 1.12 to 27.12).Neonates born to women with SARS-CoV-2 infection were more likely to be admitted to a neonatal care unit after birth (7 studies; n=7637; RR 1.86, 95% CI 1.12 to 3.08); be born preterm (7 studies; n=6233; RR 1.71, 95% CI 1.28 to 2.29) or moderately preterm (7 studies; n=6071; RR 2.92, 95% CI 1.88 to 4.54); and to be born low birth weight (12 studies; n=11 930; RR 1.19, 95% CI 1.02 to 1.40). Infection was not linked to stillbirth. Studies were generally at low or moderate risk of bias.ConclusionsThis analysis indicates that SARS-CoV-2 infection at any time during pregnancy increases the risk of maternal death, severe maternal morbidities and neonatal morbidity, but not stillbirth or intrauterine growth restriction. As more data become available, we will update these findings per the published protocol.

Health and demographic surveillance systems (HDSSs) provide a foundation for characterizing and defining priorities and strategies for improving population health. The Child Health and Mortality Prevention Surveillance (CHAMPS) project aims to inform policy to prevent child deaths through generating causes of death from surveillance data combined with innovative diagnostic and laboratory methods. Six of the 7 sites that constitute the CHAMPS network have active HDSSs: Mozambique, Mali, Ethiopia, Kenya, Bangladesh, and South Africa; the seventh, in Sierra Leone, is in the early planning stages. This article describes the network of CHAMPS HDSSs and their role in the CHAMPS project. To generate actionable health and demographic data to prevent child deaths, the network depends on reliable demographic surveillance, and the HDSSs play this crucial role.