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BackgroundIn March 2020 the South African COVID-19 Modelling Consortium was formed to support government planning for COVID-19 cases and related healthcare. Models were developed jointly by local disease modelling groups to estimate cases, resource needs and deaths due to COVID-19.MethodsThe National COVID-19 Epi Model (NCEM) while initially developed as a deterministic compartmental model of SARS-Cov-2 transmission in the nine provinces of South Africa, was adapted several times over the course of the first wave of infection in response to emerging local data and changing needs of government. By the end of the first wave, the NCEM had developed into a stochastic, spatially-explicit compartmental transmission model to estimate the total and reported incidence of COVID-19 across the 52 districts of South Africa. The model adopted a generalised Susceptible-Exposed-Infectious-Removed structure that accounted for the clinical profile of SARS-COV-2 (asymptomatic, mild, severe and critical cases) and avenues of treatment access (outpatient, and hospitalisation in non-ICU and ICU wards).ResultsBetween end-March and early September 2020, the model was updated several times to generate new sets of projections and scenario analyses to be shared with planners in the national and provincial Departments of Health, the National Treasury and other partners in a variety of formats such as presentations, reports and dashboards. Updates to model structure included finer spatial granularity, limited access to treatment, and the inclusion of behavioural heterogeneity in relation to the adoption of Public Health and Social Measures. These updates were made in response to local data and knowledge and the changing needs of the planners.ConclusionsThe NCEM attempted to incorporate a high level of local data to contextualise the model appropriately to address South Africa’s population and health system characteristics. Origin and contextualisation of data and understanding of the population’s interaction with the health system played a vital role in producing and updating estimates of resource needs, demonstrating the importance of harnessing and developing local modelling capacity.

Children with malnutrition compared with those without are at higher risk of infection, with more severe outcomes. How clinicians assess nutritional risk factors in febrile children in primary care varies. We conducted a post hoc subgroup analysis of febrile children with severe malnutrition enrolled in a randomized, controlled trial in primary care centers in Tanzania. The clinical outcome of children with severe malnutrition defined by anthropometric measures and clinical signs was compared between two electronic clinical diagnostic algorithms: ePOCT, which uses weight-for-age and mid-upper arm circumference to identify and manage severe malnutrition, and ALMANACH, which uses the clinical signs of edema of both feet and visible severe wasting. Those identified as having severe malnutrition by the algorithms in each arm were prescribed antibiotics and referred to the hospital. From December 2014 to February 2016, 106 febrile children were enrolled and randomized in the parent study, and met the criteria to be included in the present analysis. ePOCT identified 56/57 children with severe malnutrition using anthropometric measures, whereas ALMANACH identified 2/49 children with severe malnutrition using clinical signs. The proportion of clinical failure, defined as the development of severe symptoms by day 7 or persisting symptoms at day 7 (per-protocol), was 1.8% (1/56) in the ePOCT arm versus 16.7% (8/48) in the Algorithm for the MANagement of Childhood illnesses arm (risk difference −14.9%, 95% CI −26.0%, −3.8%; risk ratio 0.11, 95% CI 0.01, 0.83). Using anthropometric measures to identify and manage febrile children with severe malnutrition may have resulted in better clinical outcomes than by using clinical signs alone.

Viral infections are the leading cause of childhood acute febrile illnesses motivating consultation in sub-Saharan Africa. The majority of causal viruses are never identified in low-resource clinical settings as such testing is either not part of routine screening or available diagnostic tools have limited ability to detect new/unexpected viral variants. An in-depth exploration of the blood virome is therefore necessary to clarify the potential viral origin of fever in children. Metagenomic next-generation sequencing is a powerful tool for such broad investigations, allowing the detection of RNA and DNA viral genomes. Here, we describe the blood virome of 816 febrile children (

Background The management of childhood infections remains inadequate in resource-limited countries, resulting in high mortality and irrational use of antimicrobials. Current disease management tools, such as the Integrated Management of Childhood Illness (IMCI) algorithm, rely solely on clinical signs and have not made use of available point-of-care tests (POCTs) that can help to identify children with severe infections and children in need of antibiotic treatment. e-POCT is a novel electronic algorithm based on current evidence; it guides clinicians through the entire consultation and recommends treatment based on a few clinical signs and POCT results, some performed in all patients (malaria rapid diagnostic test, hemoglobin, oximeter) and others in selected subgroups only (C-reactive protein, procalcitonin, glucometer). The objective of this trial was to determine whether the clinical outcome of febrile children managed by the e-POCT tool was non-inferior to that of febrile children managed by a validated electronic algorithm derived from IMCI (ALMANACH), while reducing the proportion with antibiotic prescription. Methods and findings We performed a randomized (at patient level, blocks of 4), controlled non-inferiority study among children aged 2–59 months presenting with acute febrile illness to 9 outpatient clinics in Dar es Salaam, Tanzania. In parallel, routine care was documented in 2 health centers. The primary outcome was the proportion of clinical failures (development of severe symptoms, clinical pneumonia on/after day 3, or persistent symptoms at day 7) by day 7 of follow-up. Non-inferiority would be declared if the proportion of clinical failures with e-POCT was no worse than the proportion of clinical failures with ALMANACH, within statistical variability, by a margin of 3%. The secondary outcomes included the proportion with antibiotics prescribed on day 0, primary referrals, and severe adverse events by day 30 (secondary hospitalizations and deaths). We enrolled 3,192 patients between December 2014 and February 2016 into the randomized study; 3,169 patients (e-POCT: 1,586; control [ALMANACH]: 1,583) completed the intervention and day 7 follow-up. Using e-POCT, in the per-protocol population, the absolute proportion of clinical failures was 2.3% (37/1,586), as compared with 4.1% (65/1,583) in the ALMANACH arm (risk difference of clinical failure −1.7, 95% CI −3.0, −0.5), meeting the prespecified criterion for non-inferiority. In a non-prespecified superiority analysis, we observed a 43% reduction in the relative risk of clinical failure when using e-POCT compared to ALMANACH (risk ratio [RR] 0.57, 95% CI 0.38, 0.85, p = 0.005). The proportion of severe adverse events was 0.6% in the e-POCT arm compared with 1.5% in the ALMANACH arm (RR 0.42, 95% CI 0.20, 0.87, p = 0.02). The proportion of antibiotic prescriptions was substantially lower, 11.5% compared to 29.7% (RR 0.39, 95% CI 0.33, 0.45, p < 0.001). Using e-POCT, the most common indication for antibiotic prescription was severe disease (57%, 103/182 prescriptions), while it was non-severe respiratory infections using the control algorithm (ALMANACH) (70%, 330/470 prescriptions). The proportion of clinical failures among the 544 children in the routine care cohort was 4.6% (25/544); 94.9% (516/544) of patients received antibiotics on day 0, and 1.1% (6/544) experienced severe adverse events. e-POCT achieved a 49% reduction in the relative risk of clinical failure compared to routine care (RR 0.51, 95% CI 0.31, 0.84, p = 0.007) and lowered antibiotic prescriptions to 11.5% from 94.9% (p < 0.001). Though this safety study was an important first step to evaluate e-POCT, its true utility should be evaluated through future implementation studies since adherence to the algorithm will be an important factor in making use of e-POCT’s advantages in terms of clinical outcome and antibiotic prescription. Conclusions e-POCT, an innovative electronic algorithm using host biomarker POCTs, including C-reactive protein and procalcitonin, has the potential to improve the clinical outcome of children with febrile illnesses while reducing antibiotic use through improved identification of children with severe infections, and better targeting of children in need of antibiotic prescription. Trial registration ClinicalTrials.gov NCT02225769, In a randomized controlled non-inferiority trial, Kristina Keitel and colleagues compare the use of an electronic algorithm using host biomarker point-of-care-tests to routine care for the management of febrile illnesses in Tanzanian children., Author summary Why was this study done? Case management of children with infections remains inadequate, and antibiotic overprescription is a major challenge. To improve case management of children with acute infections, we developed an innovative tool: e-POCT, a smartphone-based algorithm that uses tests performed at the patient care site (point-of-care tests: oximetry, hemoglobin, C-reactive protein, and procalcitonin). Given the innovative nature of this algorithm, we assessed the safety of e-POCT in treating children with acute infections. What did the researchers do and find? In a randomized trial in Dar es Salaam, Tanzania, we compared the clinical outcomes of 1,586 children under 5 years with acute infections treated using e-POCT with that of 1,583 children treated using the current reference smartphone algorithm (ALMANACH). We observed that e-POCT improved clinical outcomes while reducing antibiotic prescription from 30% to 11%. e-POCT better targeted those children truly in need of antibiotic treatment through enhanced identification of children with severe diseases. What do these findings mean? e-POCT, an innovative smartphone algorithm using point-of-care tests, has the potential to improve clinical outcomes for children with acute infections and to increase the rational use of antibiotics. Future studies should assess e-POCT’s performance in routine care settings.

Background: Viral infections are the leading cause of childhood acute febrile illnesses motivating consultation in sub-Saharan Africa. The majority of causal viruses are never identified in low-resource clinical settings as such testing is either not part of routine screening or available diagnostic tools have limited ability to detect new/unexpected viral variants. An in-depth exploration of the blood virome is therefore necessary to clarify the potential viral origin of fever in children. Untargeted metagenomic next-generation sequencing is a powerful tool for such broad investigations, allowing the detection of RNA and DNA viral genomes. Results: Here, we describe the blood virome of 816 febrile children (Conclusions: This study highlighted several DNA and RNA viral sequences on a population of young children with fever of unknown origin and/or severe outcomes living in Tanzania, and provides a large list of novel viruses that should be considered as a potential cause of human infections.

Background A novel ultrasensitive malaria rapid diagnostic test (us-RDT) has been developed for improved active Plasmodium falciparum infection detection. The usefulness of this us-RDT in clinical diagnosis and fever management has not been evaluated. Methods Diagnostic performance of us-RDT was compared retrospectively to that of conventional RDT (co-RDT) in 3000 children and 515 adults presenting with fever to Tanzanian outpatient clinics. The parasite density was measured by an ultrasensitive qPCR (us-qPCR), and the HRP2 concentration was measured by an enzyme-linked immunosorbent assay. Results us-RDT identified few additional P. falciparum–positive patients as compared to co-RDT (276 vs 265 parasite-positive patients detected), with only a marginally greater sensitivity (75% vs 73%), using us-qPCR as the gold standard (357 parasite-positive patients detected). The specificity of both RDTs was >99%. Five of 11 additional patients testing positive by us-RDT had negative results by us-qPCR. The HRP2 concentration was above the limit of detection for co-RDT (>3653 pg of HRP2 per mL of blood) in almost all infections (99% [236 of 239]) with a parasite density >100 parasites per µL of blood. At parasite densities 793 pg/mL) and co-RDT in 29 (25%) and 24 (20%) of 118 patients, respectively. Conclusion There is neither an advantage nor a risk of using us-RDT, rather than co-RDT, for clinical malaria diagnosis. In febrile patients, only a small proportion of infections are characterized by a parasite density or an HRP2 concentration in the range where use of us-RDT would confer a meaningful advantage over co-RDT., Ultrasensitive rapid diagnostic tests (RDTs) for malaria, designed for Plasmodium falciparum elimination campaigns, may be used off label in clinical practice. The diagnostic performances of ultrasensitive and conventional RDTs were similar in febrile Tanzanian outpatients, which is explained by the underlying HRP2 concentration and parasite density distributions.

Fever is the leading cause of paediatric outpatient consultations in Sub-Saharan Africa. Although most are suspected to be of viral origin, a putative causative pathogen is not identified in over a quarter of these febrile episodes. Using a de novo assembly sequencing approach, we report the detection (15.4%) of dicistroviruses (DicV) RNA in sera collected from 692 febrile Tanzanian children. In contrast, DicV RNA was only detected in 1/77 (1.3%) plasma samples from febrile Tanzanian adults, suggesting that children could represent the primary susceptible population. Estimated viral load by specific quantitative real-time RT–PCR assay ranged from < 1.32E3 to 1.44E7 viral RNA copies/mL serum. Three DicV full-length genomes were obtained, and a phylogenetic analyse on the capsid region showed the presence of two clusters representing tentative novel genus. Although DicV-positive cases were detected throughout the year, a significantly higher positivity rate was observed during the rainy season. This study reveals that novel DicV RNA is frequently detected in the blood of Tanzanian children, paving the way for further investigations to determine if DicV possibly represent a new agent in humans.

BackgroundThe safety and efficacy of using C-reactive protein (CRP) to decide on antibiotic prescription among febrile children at risk of pneumonia has not been tested.MethodsThis was a randomized (1:1) controlled noninferiority trial in 9 primary care centers in Tanzania (substudy of the ePOCT trial evaluating a novel electronic decision algorithm). Children aged 2–59 months with fever and cough and without life-threatening conditions received an antibiotic based on a CRP-informed strategy (combination of CRP ≥80 mg/L plus age/temperature-corrected tachypnea and/or chest indrawing) or current World Health Organization standard (respiratory rate ≥50 breaths/minute). The primary outcome was clinical failure by day (D) 7; the secondary outcomes were antibiotic prescription at D0, secondary hospitalization, or death by D30.ResultsA total of 1726 children were included (intervention: 868, control: 858; 0.7% lost to follow-up). The proportion of clinical failure by D7 was 2.9% (25/865) in the intervention arm vs 4.8% (41/854) in the control arm (risk difference, –1.9% [95% confidence interval {CI}, –3.7% to –.1%]; risk ratio [RR], 0.60 [95% CI, .37–.98]). Twenty of 865 (2.3%) children in the intervention arm vs 345 of 854 (40.4%) in the control arm received antibiotics at D0 (RR, 0.06 [95% CI, .04–.09]). There were fewer secondary hospitalizations and deaths in the CRP arm: 0.5% (4/865) vs 1.5% (13/854) (RR, 0.30 [95% CI, .10–.93]).ConclusionsCRP testing using a cutoff of ≥80 mg/L, integrated into an electronic decision algorithm, was able to improve clinical outcome in children with respiratory infections while substantially reducing antibiotic prescription.Clinical Trials RegistrationNCT02225769.