: Among a prospective cohort of children and adults admitted to a national COVID-19 treatment unit in Uganda from March to December 2020, we characterized the epidemiology of and risk factors for severe illness. Across two epidemic phases differentiated by varying levels of community transmission, the proportion of patients admitted with WHO-defined severe COVID-19 ranged from 5% (7/146; 95% CI: 2–10) to 33% (41/124; 95% CI: 25–42); 21% (26/124; 95% CI: 14–29%) of patients admitted during the peak phase received oxygen therapy. Severe COVID-19 was associated with older age, male sex, and longer duration of illness before admission. Coinfection with HIV was not associated with illness severity; malaria or tuberculosis coinfection was rare. No patients died during admission. Despite low mortality, hospital incidence of severe COVID-19 during the first epidemic peak in Uganda was substantial. Improvements in vaccine deployment and acute care capacity, including oxygen delivery, are urgently needed to prevent and manage severe COVID-19 in sub-Saharan Africa.

: The global burden of sepsis is concentrated in sub-Saharan Africa, where extensive pathogen diversity and limited laboratory capacity challenge targeted antimicrobial management of life-threatening infections. In this context, established and emerging rapid pathogen diagnostics may stratify sepsis patients into subgroups with prognostic and therapeutic relevance. In a prospective cohort of adults (age ≥18 years) hospitalized with suspected sepsis in Uganda, we stratified patients using rapid diagnostics for HIV, tuberculosis (TB), malaria, and influenza, and compared clinical characteristics and 30-day outcomes across these pathogen-driven subgroups. From April 2017 to August 2019, 301 adults were enrolled (median age, 32 years [interquartile range, 26–42 years]; female, n = 178 [59%]). A total of 157 patients (53%) were HIV infected. Sixty-one patients (20%) tested positive for malaria, 52 (17%), for TB (including 49 of 157 [31%] HIV-infected patients), and 17 (6%), for influenza. Co-infection was identified in 33 (11%) patients. The frequency of multi-organ failure, including shock and acute respiratory failure, was greatest among patients with HIV-associated TB. Mortality at 30 days was 19% among patients with malaria, 40% among patients with HIV-associated TB, 32% among HIV-infected patients without microbiological evidence of TB, 6% among patients with influenza, and 11% among patients without a pathogen identified. Despite improvements in anti-retroviral delivery, the burden of sepsis in Uganda remains concentrated among young, HIV-infected adults, with a high incidence of severe HIV-associated TB. In parallel with improvements in acute-care capacity, use of rapid pathogen diagnostics may enhance triage and antimicrobial management during emergency care for sepsis in sub-Saharan Africa, and could be used to enrich study populations when trialing pathogen-specific treatment strategies in the region.

The global burden of sepsis is concentrated in sub-Saharan Africa (SSA), where epidemic HIV and unique pathogen diversity challenge the effective management of severe infections. In this context, patient stratification based on biomarkers of a dysregulated host response may identify subgroups more likely to respond to targeted immunomodulatory therapeutics. In a prospective cohort of adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to develop a prediction model for 30-day mortality that integrates physiology-based risk scores with soluble biomarkers reflective of key domains of sepsis immunopathology. After model evaluation and internal validation, whole-blood RNA sequencing data were analyzed to compare biological pathway enrichment and inferred immune cell profiles between patients assigned differential model-based risks of mortality. Of 260 eligible adults (median age, 32 years; interquartile range, 26–43 years; 59.2% female, 53.9% living with HIV), 62 (23.8%) died by 30 days after hospital discharge. Among 14 biomarkers, soluble tumor necrosis factor receptor 1 (sTNFR1) and angiopoietin 2 (Ang-2) demonstrated the greatest importance for mortality prediction in machine learning models. A clinicomolecular model integrating sTNFR1 and Ang-2 with the Universal Vital Assessment (UVA) risk score optimized 30-day mortality prediction across multiple performance metrics. Patients assigned to the high-risk, UVA-based clinicomolecular subgroup exhibited a transcriptional profile defined by proinflammatory innate immune and necroptotic pathway activation, T-cell exhaustion, and expansion of key immune cell subsets including regulatory and gamma-delta T cells. Clinicomolecular stratification of adults with suspected sepsis in Uganda enhanced 30-day mortality prediction and identified a high-risk subgroup with a therapeutically targetable immunological profile. Further studies are needed to advance pathobiologically informed sepsis management in SSA.

: Scoring systems for organ dysfunction (e.g., the quick Sepsis-related Organ Failure Assessment [qSOFA], Modified Early Warning Score [MEWS], and Universal Vital Assessment [UVA]) are proposed as clinical criteria for sepsis. The content validity of these scoring systems is poorly understood in sub-Saharan Africa, where the global sepsis burden is concentrated. In a prospective cohort of 288 adults hospitalized with suspected sepsis in Uganda, we show that qSOFA, MEWS, and UVA scores were significantly associated with soluble mediators of innate and adaptive immune activation, endothelial dysfunction, and fibrinolysis. Results were consistent after adjustment for demographics, illness duration, and HIV or malaria coinfection. In resource-limited settings in sub-Saharan Africa, organ dysfunction scores may stratify patients at highest risk of poor outcomes and those with more dysregulated host responses. Further studies are needed to better define these relationships, including the temporal dynamics of dysregulated host responses and organ dysfunction in sepsis.

IMPORTANCE: Biologically defined sepsis subtypes have been identified in low- and middle-income countries (LMICs), but limited access to molecular diagnostics constrains broader evaluation and implementation in resource-limited settings. OBJECTIVES: To determine whether bedside-accessible variables could approximate molecular sepsis subtype assignments among Ugandan adults with sepsis. DESIGN, SETTING, AND PARTICIPANTS: Secondary analysis of two prospective observational sepsis cohorts conducted at Tororo General Hospital (Research in the Epidemiology of Severe and Emerging Infections in Uganda-2-Tororo [RESERVE-U-2-TOR]) and Entebbe Regional Referral Hospital (Research in the Epidemiology of Severe and Emerging Infections in Uganda-1-Entebbe [RESERVE-U-1-EBB]), Uganda. Participants were adults 18 years old or older hospitalized with sepsis who underwent transcriptomic ( n = 355) and/or proteomic ( n = 495) profiling. MAIN OUTCOMES AND MEASURES: Prespecified clinical and clinico-microbiologic models were evaluated for discrimination and calibration against Uganda-derived transcriptomic and proteomic sepsis subtypes and, secondarily, high-income country (HIC)-derived sepsis subtypes and immune dysregulation frameworks. RESULTS: In RESERVE-U-2-TOR, clinical models incorporating demographic and physiologic variables showed moderate discrimination for transcriptomic and proteomic subtypes (area under the receiver operating characteristic curve [AUROC], 0.75 [95% CI, 0.69–0.81] and 0.73 [95% CI, 0.66–0.80], respectively), with generally acceptable calibration. Adding rapid HIV, malaria, and tuberculosis test results did not meaningfully improve performance. In RESERVE-U-1-EBB, discrimination was more variable (AUROC range, 0.63–0.75), with generally acceptable calibration. Performance was similarly modest for HIC-derived sepsis subtypes and immune dysregulation axes. CONCLUSIONS AND RELEVANCE: Bedside-accessible clinical variables, with or without rapid microbiologic testing, only partially approximated molecular sepsis frameworks in Uganda. Scalable molecular biomarker platforms are needed to advance precision medicine for sepsis in LMICs.

The recommended approach for response to severe acute respiratory syndrome coronavirus 2, was to test to enable timely detection, isolation and contact tracing so as to reduce the rapid spread of the disease. This highlighted that the laboratory as one of the core capacities of the International Health Regulations and key technical area in the International Health Security was critical in curbing the spread of the virus. Zimbabwe embarked on testing for SARS-CoV-2 in February 2020 following the guidance and support from WHO leveraging the existing testing capacity. Testing was guided by a laboratory pillar which constituted members from different organizations partnering with the Ministry of Health and Child Care. SARS-CoV-2 testing expansion was based on a phased approach using a tiered system in which laboratory staff from lower tiers were seconded to test for coronavirus using RT-PCR with National Microbiology Reference Laboratory (NMRL) being the hub for centralized consolidation of all results. As the pandemic grew nationally, there was an increase in testing per day and reduction in turnaround time as five laboratories were fully capacitated to test using RT-PCR open platforms, thirty-three provincial and district laboratories to test using TB GeneXpert and 5 provincial laboratories to use Abbott platforms.