There are concerns that pneumococcal conjugate vaccines (PCVs) in sub-Saharan Africa sub-optimally interrupt Streptococcus pneumoniae vaccine-serotype (VT) carriage and transmission. Here we assess PCV carriage using rolling, prospective nasopharyngeal carriage surveys between 2015 and 2018, 3.6–7.1 years after Malawi’s 2011 PCV13 introduction. Carriage decay rate is analysed using non-linear regression. Despite evidence of reduction in VT carriage over the study period, there is high persistent residual carriage. This includes among PCV-vaccinated children 3–5-year-old (16.1% relative reduction from 19.9% to 16.7%); PCV-unvaccinated children 6–8-year-old (40.5% reduction from 26.4% to 15.7%); HIV-infected adults 18-40-years-old on antiretroviral therapy (41.4% reduction from 15.2% to 8.9%). VT carriage prevalence half-life is similar among PCV-vaccinated and PCV-unvaccinated children (3.26 and 3.34 years, respectively). Compared with high-income settings, there is high residual VT carriage 3.6–7.1 years after PCV introduction. Rigorous evaluation of strategies to augment vaccine-induced control of carriage, including alternative schedules and catch-up campaigns, is required.

Community virus surveillance: Even highly effective vaccines will not save us from the need to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) activity, perhaps for years to come. Public health institutions will need early warning of any uptick in cases to prepare and deploy interventions as required. Riley et al. developed a community-wide program that was designed to detect resurgence at low prevalence and has been used to track SARS-CoV-2 virus across England. In the four rounds of sampling from May to September 2020, almost 600,000 people representative of all communities were monitored. The results revealed the greatest prevalence among 18- to 24-year-olds, with increasing incidence among older age groups and elevated odds of infection among some communities. This testing approach offers a model for the type of real-time, country-wide population-based surveillance work that needs to be conducted to monitor SARS-CoV-2. Science , abf0874, this issue p. 990

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.

During the coronavirus disease 2019 (COVID-19) pandemic, gun violence (GV) in the United States (U.S.) was postulated to increase strain on already taxed healthcare resources, such as blood products, intensive care beds, personal protective equipment, and even hospital staff. This report aims to estimate the relative risk of GV in the U.S. during the pandemic compared to before the pandemic. Daily police reports corresponding to gun-related injuries and deaths in the 50 states and the District of Columbia from February 1st, 2019, to March 31st, 2021 were obtained from the GV Archive. Generalized linear mixed-effects models in the form of Poisson regression analysis were utilized to estimate the state-specific rates of GV. Nationally, GV rates were 30% higher between March 01, 2020, and March 31, 2021 (during the pandemic), compared to the same period in 2019 (before the pandemic) [intensity ratio (IR) = 1.30; 95% CI 1.29, 1.32; p < 0.0001]. The risk of GV was significantly higher in 28 states and significantly lower in only one state. National and state-specific rates of GV were higher during the COVID-19 pandemic compared to the same timeframe 1 year prior. State-specific steps to mitigate violence, or at a minimum adequately prepare for its toll during the COVID-19 pandemic, should be taken.

Despite the high prevalence of childhood protein-energy malnutrition and vitamin A deficiency in sub-Saharan Africa, their association has not been explored in this region. A better understanding of the epidemiologic link could help define effective preventive strategies. We aimed to explore the association of vitamin A deficiency (VAD) with stunting, wasting, and underweight among preschool children in Uganda. We analyzed a population-based, cross-sectional data of 4,765 children aged 6–59 months who participated in 2016 Demographic and Health Surveys conducted in Uganda. We utilized generalized linear mixed-effects models with logit link function, adjusting for potential confounders to estimate associations between VAD and stunting, wasting, and underweight. The prevalence of VAD was 8.9% (95% CI: 8.1% to 9.6%, n = 424). Twenty-seven percent were stunted (95% CI: 26.1% to 28.6, n = 1302), 4% wasted (95% CI: 3.6% to 4.7%, n = 196), and 17% underweight (95% CI: 16.0% to 18.2%, n = 813). After adjusting for household factors (e.g., wealth index, education and working status of parents, owning land for agriculture, livestock, herds, or farm animals), vitamin A supplementation, and community factors (e.g., population density, crop growing season lengths, place of residence), children with VAD had 43% higher odds of stunted growth than those without VAD (adjusted odds ratio, 1.43 (95% CI: 1.08 to 1.89, p = 0.01). No association was observed between VAD and wasting or underweight. Vitamin A deficiency was associated with higher odds of stunting, and the association was independent of the individual, household, and community-level variables.

As neglected tropical diseases approach elimination status, there is a need to develop efficient sampling strategies for confirmation (or not) that elimination criteria have been met. This is an inherently difficult task because the relative precision of a prevalence estimate deteriorates as prevalence decreases, and classic survey sampling strategies based on random sampling therefore require increasingly large sample sizes. More efficient strategies for survey design and analysis can be obtained by exploiting any spatial correlation in prevalence within a model-based geostatistics framework. This framework can be used for constructing predictive probability maps that can inform in-country decision makers of the likelihood that their elimination target has been met, and where to invest in additional sampling. We evaluated our methodology using a case study of lymphatic filariasis in Ghana, demonstrating that a geostatistical approach outperforms approaches currently used to determine an evaluation unit’s elimination status.