Patterns of disease on admission to children’s wards and changes during a COVID-19 outbreak in KwaZulu-Natal Province, South Africa

Background. Major causes of under-5 child deaths in South Africa (SA) are well recognised, and child mortality rates are falling. The focus of child health is therefore shifting from survival to disease prevention and thriving, but local data on the non-fatal disease burden are limited. Furthermore, COVID-19 has affected children’s health and wellbeing, both directly and indirectly.Objectives. To describe the pattern of disease on admission of children at different levels of care, and assess whether this has been affected by COVID-19.Methods. Retrospective reviews of children’s admission and discharge registers were conducted for all general hospitals in iLembe and uMgungundlovu districts in KwaZulu-Natal Province, SA, from January 2018 to September 2020. The Global Burden of Disease framework was adapted to create a data capture sheet with four broad diagnostic categories and 37 specific cause categories. Monthly admission numbers were recorded per cause category, and basic descriptive analysis was completed in Microsoft Excel.Results. Overall, 36 288 admissions were recorded across 18 hospital wards, 32.0% at district, 49.8% at regional and 18.2% at tertiary level. Communicable diseases, perinatal conditions and nutritional deficiencies (CPNs) accounted for 37.4% of admissions, non-communicable diseases (NCDs) for 43.5% and injuries for 17.1%. The distribution of broad diagnostic categories varied across levels of care, with CPNs being more common at district level and NCDs more common at regional and tertiary levels. Unintentional injuries represented the most common cause category (16.6%), ahead of lower respiratory tract infections (16.1%), neurological conditions (13.6%) and diarrhoeal disease (8.4%). The start of the local COVID-19 outbreak coincided with a 43.1% decline in the mean number of monthly admissions. Admissions due to neonatal conditions and intentional injuries remained constant during the COVID-19 outbreak, while those due to other disease groups (particularly respiratory infections) declined.Conclusions. Our study confirms previous concerns around a high burden of childhood injuries in our context. Continued efforts are needed to prevent and treat traditional neonatal and childhood illnesses. Concurrently, the management of NCDs should be prioritised, and evidence-based strategies are sorely needed to address the high injury burden in SA

Outcomes of laboratory-confirmed SARS-CoV-2 infection during resurgence driven by Omicron lineages BA.4 and BA.5 compared with previous waves in the Western Cape Province, South Africa

OBJECTIVE: We aimed to compare clinical severity of Omicron BA.4/BA.5 infection with BA.1 and earlier variant infections among laboratory-confirmed SARS-CoV-2 cases in the Western Cape, South Africa, using timing of infection to infer the lineage/variant causing infection. METHODS: We included public sector patients aged ≥20 years with laboratory-confirmed COVID-19 between 1-21 May 2022 (BA.4/BA.5 wave) and equivalent prior wave periods. We compared the risk between waves of (i) death and (ii) severe hospitalization/death (all within 21 days of diagnosis) using Cox regression adjusted for demographics, comorbidities, admission pressure, vaccination and prior infection. RESULTS: Among 3,793 patients from the BA.4/BA.5 wave and 190,836 patients from previous waves the risk of severe hospitalization/death was similar in the BA.4/BA.5 and BA.1 waves (adjusted hazard ratio (aHR) 1.12; 95% confidence interval (CI) 0.93; 1.34). Both Omicron waves had lower risk of severe outcomes than previous waves. Prior infection (aHR 0.29, 95% CI 0.24; 0.36) and vaccination (aHR 0.17; 95% CI 0.07; 0.40 for at least 3 doses vs. no vaccine) were protective. CONCLUSION: Disease severity was similar amongst diagnosed COVID-19 cases in the BA.4/BA.5 and BA.1 periods in the context of growing immunity against SARS-CoV-2 due to prior infection and vaccination, both of which were strongly protective

Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants, respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity

Clinical features and outcomes of COVID-19 admissions in a population with a high prevalence of HIV and tuberculosis: a multicentre cohort study

Background There is still a paucity of evidence on the outcomes of coronavirus disease 2019 (COVID-19) among people living with human immunodeficiency virus (PWH) and those co-infected with tuberculosis (TB), particularly in areas where these conditions are common. We describe the clinical features, laboratory findings and outcome of hospitalised PWH and human immunodeficiency virus (HIV)-uninfected COVID-19 patients as well as those co-infected with tuberculosis (TB). Methods We conducted a multicentre cohort study across three hospitals in Cape Town, South Africa. All adults requiring hospitalisation with confirmed COVID-19 pneumonia from March to July 2020 were analysed. Results PWH comprised 270 (19%) of 1434 admissions. There were 47 patients with active tuberculosis (3.3%), of whom 29 (62%) were PWH. Three-hundred and seventy-three patients (26%) died. The mortality in PWH (n = 71, 26%) and HIV-uninfected patients (n = 296, 25%) was comparable. In patients with TB, PWH had a higher mortality than HIV-uninfected patients (n = 11, 38% vs n = 3, 20%; p = 0.001). In multivariable survival analysis a higher risk of death was associated with older age (Adjusted Hazard Ratio (AHR) 1.03 95%CI 1.02–1.03, p < 0.001), male sex (AHR1.38 (95%CI 1.12–1.72, p = 0.003) and being “overweight or obese” (AHR 1.30 95%CI 1.03–1.61 p = 0.024). HIV (AHR 1.28 95%CI 0.95–1.72, p 0.11) and active TB (AHR 1.50 95%CI 0.84–2.67, p = 0.17) were not independently associated with increased risk of COVID-19 death. Risk factors for inpatient mortality in PWH included CD4 cell count < 200 cells/mm3, higher admission oxygen requirements, absolute white cell counts, neutrophil/lymphocyte ratios, C-reactive protein, and creatinine levels. Conclusion In a population with high prevalence of HIV and TB, being overweight/obese was associated with increased risk of mortality in COVID-19 hospital admissions, emphasising the need for public health interventions in this patient population

Development and validation of quantitative PCR assays for HIV-associated cryptococcal meningitis in sub-Saharan Africa: a diagnostic accuracy study

Background: HIV-associated cryptococcal meningitis is the second leading cause of AIDS-related deaths, with a 10-week mortality rate of 25–30%. Fungal load assessed by colony-forming unit (CFU) counts is used as a prognostic marker and to monitor response to treatment in research studies. PCR-based assessment of fungal load could be quicker and less labour-intensive. We sought to design, optimise, and validate quantitative PCR (qPCR) assays for the detection, identification, and quantification of Cryptococcus infections in patients with cryptococcal meningitis in sub-Saharan Africa. Methods: We developed and validated species-specific qPCR assays based on DNA amplification of QSP1 (QSP1A specific to Cryptococcus neoformans, QSP1B/C specific to Cryptococcus deneoformans, and QSP1D specific to Cryptococcus gattii species) and a pan-Cryptococcus assay based on a multicopy 28S rRNA gene. This was a longitudinal study that validated the designed assays on cerebrospinal fluid (CSF) of 209 patients with cryptococcal meningitis at baseline (day 0) and during anti-fungal therapy (day 7 and day 14), from the AMBITION-cm trial in Botswana and Malawi (2018–21). Eligible patients were aged 18 years or older and presenting with a first case of cryptococcal meningitis. Findings: When compared with quantitative cryptococcal culture as the reference, the sensitivity of the 28S rRNA was 98·2% (95% CI 95·1–99·5) and of the QSP1 assay was 90·4% (85·2–94·0) in CSF at day 0. Quantification of the fungal load with QSP1 and 28S rRNA qPCR correlated with quantitative cryptococcal culture (R2=0·73 and R2=0·78, respectively). Both Botswana and Malawi had a predominant C neoformans prevalence of 67% (95% CI 55–75) and 68% (57–73), respectively, and lower C gattii rates of 21% (14–31) and 8% (4–14), respectively. We identified ten patients that, after 14 days of treatment, harboured viable but non-culturable yeasts based on QSP1 RNA detection (without any positive CFU in CSF culture). Interpretation: QSP1 and 28S rRNA assays are useful in identifying Cryptococcus species. qPCR results correlate well with baseline quantitative cryptococcal culture and show a similar decline in fungal load during induction therapy. These assays could be a faster alternative to quantitative cryptococcal culture to determine fungal load clearance. The clinical implications of the possible detection of viable but non-culturable cells in CSF during induction therapy remain unclear. Funding: European and Developing Countries Clinical Trials Partnership; Swedish International Development Cooperation Agency; Wellcome Trust/UK Medical Research Council/UKAID Joint Global Health Trials; and UK National Institute for Health Research

Development and validation of quantitative PCR assays for HIV-associated cryptococcal meningitis in sub-Saharan Africa: a diagnostic accuracy study

Background: HIV-associated cryptococcal meningitis is the second leading cause of AIDS-related deaths, with a 10-week mortality rate of 25–30%. Fungal load assessed by colony-forming unit (CFU) counts is used as a prognostic marker and to monitor response to treatment in research studies. PCR-based assessment of fungal load could be quicker and less labour-intensive. We sought to design, optimise, and validate quantitative PCR (qPCR) assays for the detection, identification, and quantification of Cryptococcus infections in patients with cryptococcal meningitis in sub-Saharan Africa. Methods: We developed and validated species-specific qPCR assays based on DNA amplification of QSP1 (QSP1A specific to Cryptococcus neoformans, QSP1B/C specific to Cryptococcus deneoformans, and QSP1D specific to Cryptococcus gattii species) and a pan-Cryptococcus assay based on a multicopy 28S rRNA gene. This was a longitudinal study that validated the designed assays on cerebrospinal fluid (CSF) of 209 patients with cryptococcal meningitis at baseline (day 0) and during anti-fungal therapy (day 7 and day 14), from the AMBITION-cm trial in Botswana and Malawi (2018–21). Eligible patients were aged 18 years or older and presenting with a first case of cryptococcal meningitis. Findings: When compared with quantitative cryptococcal culture as the reference, the sensitivity of the 28S rRNA was 98·2% (95% CI 95·1–99·5) and of the QSP1 assay was 90·4% (85·2–94·0) in CSF at day 0. Quantification of the fungal load with QSP1 and 28S rRNA qPCR correlated with quantitative cryptococcal culture (R2=0·73 and R2=0·78, respectively). Both Botswana and Malawi had a predominant C neoformans prevalence of 67% (95% CI 55–75) and 68% (57–73), respectively, and lower C gattii rates of 21% (14–31) and 8% (4–14), respectively. We identified ten patients that, after 14 days of treatment, harboured viable but non-culturable yeasts based on QSP1 RNA detection (without any positive CFU in CSF culture). Interpretation: QSP1 and 28S rRNA assays are useful in identifying Cryptococcus species. qPCR results correlate well with baseline quantitative cryptococcal culture and show a similar decline in fungal load during induction therapy. These assays could be a faster alternative to quantitative cryptococcal culture to determine fungal load clearance. The clinical implications of the possible detection of viable but non-culturable cells in CSF during induction therapy remain unclear

Risk factors for Coronavirus disease 2019 (Covid-19) death in a population cohort study from the Western Cape province, South Africa

Risk factors for coronavirus disease 2019 (COVID-19) death in sub-Saharan Africa and the effects of human immunodeficiency virus (HIV) and tuberculosis on COVID-19 outcomes are unknown. We conducted a population cohort study using linked data from adults attending public-sector health facilities in the Western Cape, South Africa. We used Cox proportional hazards models, adjusted for age, sex, location, and comorbidities, to examine the associations between HIV, tuberculosis, and COVID-19 death from 1 March to 9 June 2020 among (1) public-sector “active patients” (≥1 visit in the 3 years before March 2020); (2) laboratory-diagnosed COVID-19 cases; and (3) hospitalized COVID-19 cases. We calculated the standardized mortality ratio (SMR) for COVID-19, comparing adults living with and without HIV using modeled population estimates.Among 3 460 932 patients (16% living with HIV), 22 308 were diagnosed with COVID-19, of whom 625 died. COVID19 death was associated with male sex, increasing age, diabetes, hypertension, and chronic kidney disease. HIV was associated with COVID-19 mortality (adjusted hazard ratio [aHR], 2.14; 95% confidence interval [CI], 1.70–2.70), with similar risks across strata of viral loads and immunosuppression. Current and previous diagnoses of tuberculosis were associated with COVID-19 death (aHR, 2.70 [95% CI, 1.81–4.04] and 1.51 [95% CI, 1.18–1.93], respectively). The SMR for COVID-19 death associated with HIV was 2.39 (95% CI, 1.96–2.86); population attributable fraction 8.5% (95% CI, 6.1–11.1)

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century