Malaria is an uncommon cause of adult sepsis in south-western Uganda

Malaria is often considered a cause of adult sepsis in malaria endemic areas. However, diagnostic limitations can make distinction between malaria and other infections challenging. Therefore, the objective of this study was to determine the relative contribution of malaria to adult sepsis in south-western Uganda

Outcomes of World Health Organization–defined Severe Respiratory Distress without Shock in Adults in Sub-Saharan Africa

Sepsis is the leading cause of global mortality and is most often attributed to lower respiratory tract infections and subsequent acute respiratory distress syndrome (ARDS) (1). The greatest burden of sepsis rests on sub-Saharan Africa, where lower respiratory tract infections account for approximately 390,000 adult deaths each year (2). However, patients from sub-Saharan Africa are underrepresented in sepsis and ARDS research (3). ARDS is difficult to diagnose in low-income countries because it requires often unavailable imaging, mechanical ventilation to set positive end-expiratory pressure and deliver a reliable fraction of inspired oxygen, and arterial blood gases to identify hypoxemia (4). To mitigate this gap, the World Health Organization (WHO) pragmatically defined severe respiratory distress without shock (SRD) in adults as oxygen saturation of less than 90% or a respiratory rate of more than 30 breaths per minute, and a systolic blood pressure over 90 mm Hg in the setting of infection and in the absence of clinical cardiac failure (5). The natural history of SRD has not been fully described; accordingly, we aimed to evaluate the prevalence, characteristics, and outcomes of SRD in hospitalized patients in sub-Saharan Africa

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in sub-Saharan Africa.

Critical illness is a leading cause of morbidity and mortality in sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA. We pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009-2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score. Of 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27-49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)). We identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies

Artemisinin-Resistant Plasmodium falciparum with High Survival Rates, Uganda, 2014–2016

Because ≈90% of malaria cases occur in Africa, emergence of artemisinin-resistant Plasmodium falciparum in Africa poses a serious public health threat. To assess emergence of artemisinin-resistant parasites in Uganda during 2014–2016, we used the recently developed ex vivo ring-stage survival assay, which estimates ring-stage–specific P. falciparum susceptibility to artemisinin. We conducted 4 cross-sectional surveys to assess artemisinin sensitivity in Gulu, Uganda. Among 194 isolates, survival rates (ratio of viable drug-exposed parasites to drug-nonexposed controls) were high (>10%) for 4 isolates. Similar rates have been closely associated with delayed parasite clearance after drug treatment and are considered to be a proxy for the artemisinin-resistant phenotype. Of these, the PfKelch13 mutation was observed in only 1 isolate, A675V. Population genetics analysis suggested that these possibly artemisinin-resistant isolates originated in Africa. Large-scale surveillance of possibly artemisinin-resistant parasites in Africa would provide useful information about treatment outcomes and help regional malaria control

Decline of FoxP3+ Regulatory CD4 T Cells in Peripheral Blood of Children Heavily Exposed to Malaria

<div><p>FoxP3+ regulatory CD4 T cells (T_regs) help to maintain the delicate balance between pathogen-specific immunity and immune-mediated pathology. Prior studies suggest that T_regs are induced by <i>P</i>. <i>falciparum</i> both <i>in vivo</i> and <i>in vitro</i>; however, the factors influencing T_reg homeostasis during acute and chronic infections, and their role in malaria immunopathogenesis, remain unclear. We assessed the frequency and phenotype of T_regs in well-characterized cohorts of children residing in a region of high malaria endemicity in Uganda. We found that both the frequency and absolute numbers of FoxP3+ T_regs in peripheral blood declined markedly with increasing prior malaria incidence. Longitudinal measurements confirmed that this decline occurred only among highly malaria-exposed children. The decline of T_regs from peripheral blood was accompanied by reduced <i>in vitro</i> induction of T_regs by parasite antigen and decreased expression of TNFR2 on T_regs among children who had intense prior exposure to malaria. While T_reg frequencies were not associated with protection from malaria, there was a trend toward reduced risk of symptomatic malaria once infected with <i>P</i>. <i>falciparum</i> among children with lower T_reg frequencies. These data demonstrate that chronic malaria exposure results in altered T_reg homeostasis, which may impact the development of antimalarial immunity in naturally exposed populations.</p></div

Regulatory T cells decrease over time in individuals with high but not low malaria incidence.

<p>T_reg frequencies of CD4+ T cells (FoxP3+CD25+CD127^dim) were measured at 16, 24 and 36 months of age (PROMOTE- SP arm). <b>(A)</b> Children were divided into tertiles based on incidence of malaria between 16 and 36 months; lowest tertile median incidence 4.0 episodes ppy (IQR 3.0–5.5); intermediate tertile median incidence 8.2 episodes ppy (IQR 7.3–9.2); highest tertile median incidence 13.7 episodes ppy (IQR 10.3–14.6). The median duration since last malaria infection in these three tertiles was 8.5, 20, and 100 days, respectively. Wilcoxon matched pairs signed rank test p values indicated. Between 16 and 36 months, T_reg frequencies declined in individuals in the highest but not lowest tertile of malaria incidence. <b>(B)</b> Changes in T_reg frequencies between 16, 24 and 36 months were compared between children in the lowest, intermediate, and highest tertiles of malaria exposure by generalized estimate equations, accounting for repeated measures, age, duration since last malaria episode and parasite status at time of sampling.</p

Relationship between T_reg frequencies and prospective risk of malaria.

<p>¹ –Multivariate is adjusted for prior malaria incidence</p><p>Relationship between T_reg frequencies and prospective risk of malaria.</p