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Background: South Africa's first SARS-CoV-2 case was identified 5th March 2020 and national lockdown followed March 26th. Households are an important location for secondary SARS-CoV-2 infection. Physical distancing and sanitation - infection mitigation recommended by the World Health Organization (WHO) at the time - are difficult to implement in limited-resource settings because of overcrowded living conditions., Methods: This study (ClinicalTrials.gov NCT05119348) was conducted from August 2020 to September 2021 in two densely populated, low socioeconomic Cape Town community sub-districts. New COVID-19 index cases (ICs) identified at public clinics were randomised to an infection mitigation intervention (STOPCOV) delivered by lay community health workers (CHWs) or standard of care group. STOPCOV mitigation measures included one initial household assessment conducted by a CHW in which face masks, sanitiser, bleach and written information on managing and preventing spread were provided. This was followed by regular telephonic follow-up from CHWs. SARS-CoV-2 PCR and IgM/IgG serology was performed at baseline, weeks 1, 2, 3 and 4 of follow-up., Results: The study randomised 81 ICs with 245 HHCs. At baseline, no HHCs in the control and 7 (5%) in the intervention group had prevalent SARS-CoV-2. The secondary infection rate (SIR) based on SARS-CoV-2 PCR testing was 1.9% (n = 2) in control and 2.9% (n = 4) in intervention HHCs (p = 0.598). At baseline, SARS-CoV-2 antibodies were present in 15% (16/108) of control and 38% (52/137) of intervention participants. At study end incidence was 8.3% (9/108) and 8.03% (11/137) in the intervention and control groups respectively. Antibodies were present in 23% (25/108) of control HHCs over the course of the study vs. 46% (63/137) in the intervention arm. CHWs made twelve clinic and 47 food parcel referrals for individuals in intervention households in need., Discussion: Participants had significant exposure to SARS-CoV-2 infections prior to the study. In this setting, household transmission mitigation was ineffective. However, CHWs may have facilitated other important healthcare and social referrals., (© 2024. The Author(s).)

Background: COVID-19 experiences on noncommunicable diseases (NCDs) from district-level hospital settings during waves I and II are scarcely documented. The aim of this study is to investigate the NCDs associated with COVID-19 severity and mortality in a district-level hospital with a high HIV/TB burden., Methods: This was a retrospective observational study that compared COVID-19 waves I and II at Khayelitsha District Hospital in Cape Town, South Africa. COVID-19 adult patients with a confirmed SARS-CoV-2 polymerase chain reaction (PCR) or positive antigen test were included. In order to compare the inter wave period, clinical and laboratory parameters on hospital admission of noncommunicable diseases, the Student t-test or Mann-Whitney U for continuous data and the X2 test or Fishers' Exact test for categorical data were used. The role of the NCD subpopulation on COVID-19 mortality was determined using latent class analysis (LCA)., Findings: Among 560 patients admitted with COVID-19, patients admitted during wave II were significantly older than those admitted during wave I. The most prevalent comorbidity patterns were hypertension (87%), diabetes mellitus (65%), HIV/AIDS (30%), obesity (19%), Chronic Kidney Disease (CKD) (13%), Congestive Cardiac Failure (CCF) (8.8%), Chronic Obstructive Pulmonary Disease (COPD) (3%), cerebrovascular accidents (CVA)/stroke (3%), with similar prevalence in both waves except HIV status [(23% vs 34% waves II and I, respectively), p = 0.022], obesity [(52% vs 2.5%, waves II and I, respectively), p <0.001], previous stroke [(1% vs 4.1%, waves II and I, respectively), p = 0.046]. In terms of clinical and laboratory findings, our study found that wave I patients had higher haemoglobin and HIV viral loads. Wave II, on the other hand, had statistically significant higher chest radiography abnormalities, fraction of inspired oxygen (FiO2), and uraemia. The adjusted odds ratio for death vs discharge between waves I and II was similar (0.94, 95%CI: 0.84-1.05). Wave I had a longer average survival time (8.0 vs 6.1 days) and a shorter average length of stay among patients discharged alive (9.2 vs 10.7 days). LCA revealed that the cardiovascular phenotype had the highest mortality, followed by diabetes and CKD phenotypes. Only Diabetes and hypertension phenotypes had the lowest mortality., Conclusion: Even though clinical and laboratory characteristics differed significantly between the two waves, mortality remained constant. According to LCA, the cardiovascular, diabetes, and CKD phenotypes had the highest death probability., Competing Interests: The authors received no specific funding for this work., (Copyright: © 2023 Mnguni et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: While a large proportion of people with HIV (PWH) have experienced SARS-CoV-2 infections, there is uncertainty about the role of HIV disease severity on COVID-19 outcomes, especially in lower-income settings. We studied the association of mortality with characteristics of HIV severity and management, and vaccination, among adult PWH., Methods: We analysed observational cohort data on all PWH aged ≥15 years experiencing a diagnosed SARS-CoV-2 infection (until March 2022), who accessed public sector healthcare in the Western Cape province of South Africa. Logistic regression was used to study the association of mortality with evidence of antiretroviral therapy (ART) collection, time since first HIV evidence, CD4 cell count, viral load (among those with evidence of ART collection) and COVID-19 vaccination, adjusting for demographic characteristics, comorbidities, admission pressure, location and time period., Results: Mortality occurred in 5.7% (95% CI: 5.3,6.0) of 17,831 first-diagnosed infections. Higher mortality was associated with lower recent CD4, no evidence of ART collection, high or unknown recent viral load and recent first HIV evidence, differentially by age. Vaccination was protective. The burden of comorbidities was high, and tuberculosis (especially more recent episodes of tuberculosis), chronic kidney disease, diabetes and hypertension were associated with higher mortality, more strongly in younger adults., Conclusions: Mortality was strongly associated with suboptimal HIV control, and the prevalence of these risk factors increased in later COVID-19 waves. It remains a public health priority to ensure PWH are on suppressive ART and vaccinated, and manage any disruptions in care that occurred during the pandemic. The diagnosis and management of comorbidities, including for tuberculosis, should be optimized., (© 2023 The Authors. Journal of the International AIDS Society published by John Wiley & Sons Ltd on behalf of the International AIDS Society.)

Background: The coronavirus disease 2019 (COVID-19) pandemic continues to evolve. Globally, COVID-19 continues to strain even the most resilient healthcare systems, with Omicron being the latest variant. We made a thorough search for literature describing the effects of the COVID-19 in a high human immunodeficiency virus (HIV)/tuberculosis (TB) burden district-level hospital setting. We found scanty literature., Methods: A retrospective observational study was conducted at Khayelitsha District Hospital in Cape Town, South Africa (SA) over the period March 2020-December 2021. We included confirmed COVID-19 cases with HIV infection aged from 18 years and above. Analysis was performed to identify predictors of mortality or hospital discharge among people living with HIV (PLWH). Predictors investigated include CD4 count, antiretroviral therapy (ART), TB, non-communicable diseases, haematological, and biochemical parameters., Findings: This cohort of PLWH with SARS-CoV-2 infection had a median (IQR) age of 46 (37-54) years, male sex distribution of 29.1%, and a median (IQR) CD4 count of 267 (141-457) cells/mm3. Of 255 patients, 195 (76%) patients were discharged, 60 (24%) patients died. One hundred and sixty-nine patients (88%) were on ART with 73(28%) patients having acquired immunodeficiency syndrome (AIDS). After multivariable analysis, smoking (risk ratio [RR]: 2.86 (1.75-4.69)), neutrophilia [RR]: 1.024 (1.01-1.03), and glycated haemoglobin A1 (HbA1c) [RR]: 1.01 (1.007-1.01) were associated with mortality., Conclusion: The district hospital had a high COVID-19 mortality rate among PLWH. Easy-to-access biomarkers such as CRP, neutrophilia, and HbA1c may play a significant role in informing clinical management to prevent high mortality due to COVID-19 in PLWH at the district-level hospitals., (© 2023. The Author(s).)

Objectives: We aimed to compare the 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 May 01-May 21, 2022 (BA.4/BA.5 wave) and equivalent previous 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 previous infection., Results: Among 3793 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 a lower risk of severe outcomes than previous waves. Previous infection (aHR 0.29, 95% CI 0.24; 0.36) and vaccination (aHR 0.17; 95% CI 0.07; 0.40 for at least three doses vs no vaccine) were protective., Conclusion: Disease severity was similar among 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 previous infection and vaccination, both of which were strongly protective., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Public health dashboards have been used in the past to communicate and guide local responses to outbreaks, epidemics, and a host of various health conditions. During the first year of the COVID-19 pandemic, dashboards proliferated but the availability and quality differed across the world. This study aimed to evaluate the quality, access, and end-user experience of one such dashboard in the Western Cape province, South Africa., Methods: We analysed retrospective aggregate data on viewership over time for the first year since launch of the dashboard (30 April 2020 - 29 April 2021) and conducted a cross-sectional survey targeting adult users of the dashboard at one year post the initial launch. The self-administered, anonymous questionnaire with a total of 13 questions was made available via an online digital survey tool for a 2-week period (6 May 2021 - 21 May 2021)., Results: After significant communication by senior provincial political leaders, adequate media coverage and two waves of COVID-19 the Western Cape public COVID-19 dashboard attracted a total of 2,248,456 views during its first year. The majority of these views came from Africa/South Africa with higher median daily views during COVID-19 wave periods. A total of 794 participants responded to the survey questionnaire. Reported devices used to access the dashboard differed statistically between occupational status groups with students tending toward using mobile devices whilst employed and retired participants tending toward using desktop computers/laptops. Frequency of use increases with increasing age with 65.1% of those > 70 years old viewing it daily. Overall, 76.4% of respondents reported that the dashboard influenced their personal planning and behaviour. High Likert score ratings were given for clarity, ease of use and overall end-user experience, with no differences seen across the various age groups surveyed., Conclusion: The study demonstrated that both the availability of data and an understanding of end-user need is critical when developing and delivering public health tools that may ultimately garner public trust and influence individual behaviour., (© 2022. The Author(s).)

Omicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. Here, we use the presence/absence of the S-gene target as a proxy for SARS-CoV-2 variant/lineage for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We link national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assess severity using multivariable logistic regression comparing the risk of hospitalisation and risk of severe disease, once hospitalised, for Delta, BA.1, BA.2 and BA.4/BA.5 infections. After controlling for factors associated with hospitalisation and severe outcome respectively, BA.4/BA.5-infected individuals had a similar odds of hospitalisation (aOR 1.24, 95% CI 0.98-1.55) and severe outcome (aOR 0.72, 95% CI 0.41-1.26) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 showed similar severity to the BA.1 lineage and continued to show reduced clinical severity compared to the Delta variant., (© 2022. The Author(s).)

Aims: The coronavirus disease 2019 (COVID-19) pandemic and ensuing restrictions have negatively affected the mental health and well-being of the general population, and there is increasing evidence suggesting that lockdowns have led to a disruption of health services. In March 2020, South Africa introduced a lockdown in response to the COVID-19 pandemic, entailing the suspension of all non-essential activities and a complete ban of tobacco and alcohol sales. We studied the effect of the lockdown on mental health care utilisation rates in private-sector care in South Africa., Methods: We conducted an interrupted time-series analysis using insurance claims from 1 January 2017 to 1 June 2020 of beneficiaries 18 years or older from a large private sector medical insurance scheme. We calculated weekly outpatient consultation and hospital admission rates for organic mental disorders, substance use disorders, serious mental disorders, depression, anxiety, other mental disorders, any mental disorder and alcohol withdrawal syndrome. We calculated adjusted odds ratios (OR) for the effect of the lockdown on weekly outpatient consultation and hospital admission rates and the weekly change in rates during the lockdown until 1 June 2020., Results: 710 367 persons were followed up for a median of 153 weeks. Hospital admission rates (OR 0.38; 95% confidence interval (CI) 0.33-0.44) and outpatient consultation rates (OR 0.74; 95% CI 0.63-0.87) for any mental disorder decreased substantially after the introduction of the lockdown and did not recover to pre-lockdown levels by 1 June 2020. Health care utilisation rates for alcohol withdrawal syndrome doubled after the introduction of the lockdown, but the statistical uncertainty around the estimates was large (OR 2.24; 95% CI 0.69-7.24)., Conclusions: Mental health care utilisation rates for inpatient and outpatient services decreased substantially after the introduction of the lockdown. Hospital admissions and outpatient consultations for alcohol withdrawal syndrome increased after the introduction of the lockdown, but statistical uncertainty precludes strong conclusions about a potential unintended effect of the alcohol sales ban. Governments should integrate strategies for ensuring access and continuity of essential mental health services during lockdowns in pandemic preparedness planning.

Vaccine effectiveness is lower and wanes faster against infection and symptomatic disease caused by the omicron variant of SARS-CoV-2 than was observed with previous variants. Vaccine effectiveness against severe omicron disease, on average, is higher, but has shown variability, including rapid apparent waning, in some studies. Assessing vaccine effectiveness against omicron severe disease using hospital admission as a measure of severe disease has become more challenging because of omicron's attenuated intrinsic severity and its high prevalence of infection. Many hospital admissions likely occur among people with incidental omicron infection or among those with infection-induced exacerbation of chronic medical conditions. To address this challenge, the World Health Organization held a virtual meeting on March 15, 2022, to review evidence from several studies that assessed Covid-19 vaccine effectiveness against severe omicron disease using several outcome definitions. Data was shown from studies in South Africa, the United States, the United Kingdom and Qatar. Several approaches were proposed that better characterize vaccine protection against severe Covid-19 disease caused by the omicron variant than using hospitalization of omicron-infected persons to define severe disease. Using more specific definitions for severe respiratory Covid-19 disease, such as indicators of respiratory distress (e.g. oxygen requirement, mechanical ventilation, and ICU admission), showed higher vaccine effectiveness than against hospital admission. Second, vaccine effectiveness against progression from omicron infection to hospitalization, or severe disease, also showed higher vaccine protection. These approaches might better characterize vaccine performance against severe Covid-19 disease caused by omicron, as well as future variants that evade humoral immunity, than using hospitalization with omicron infection as an indicator of severe disease., Competing Interests: Declaration of Competing Interest Dr. Walter Orenstein is an uncompensated member of the Scientific Advisory Board for Moderna., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Objectives: The objective was to compare COVID-19 outcomes in the Omicron-driven fourth wave with prior waves in the Western Cape, assess the contribution of undiagnosed prior infection to differences in outcomes in a context of high seroprevalence due to prior infection and determine whether protection against severe disease conferred by prior infection and/or vaccination was maintained., Methods: In this cohort study, we included public sector patients aged ≥20 years with a laboratory-confirmed COVID-19 diagnosis between 14 November and 11 December 2021 (wave four) and equivalent prior wave periods. We compared the risk between waves of the following outcomes using Cox regression: death, severe hospitalisation or death and any hospitalisation or death (all ≤14 days after diagnosis) adjusted for age, sex, comorbidities, geography, vaccination and prior infection., Results: We included 5144 patients from wave four and 11,609 from prior waves. The risk of all outcomes was lower in wave four compared to the Delta-driven wave three (adjusted hazard ratio (aHR) [95% confidence interval (CI)] for death 0.27 [0.19; 0.38]. Risk reduction was lower when adjusting for vaccination and prior diagnosed infection (aHR: 0.41, 95% CI: 0.29; 0.59) and reduced further when accounting for unascertained prior infections (aHR: 0.72). Vaccine protection was maintained in wave four (aHR for outcome of death: 0.24; 95% CI: 0.10; 0.58)., Conclusions: In the Omicron-driven wave, severe COVID-19 outcomes were reduced mostly due to protection conferred by prior infection and/or vaccination, but intrinsically reduced virulence may account for a modest reduction in risk of severe hospitalisation or death compared to the Delta-driven wave., (© 2022 The Authors Tropical Medicine & International Health Published by John Wiley & Sons Ltd.)

Background: At present, it is unclear whether the extent of reduced risk of severe disease seen with SARS-Cov-2 Omicron variant infection is caused by a decrease in variant virulence or by higher levels of population immunity., Methods: RdRp target delay (RTD) in the Seegene Allplex TM 2019-nCoV PCR assay is a proxy marker for the Delta variant. The absence of this proxy marker in the transition period was used to identify suspected Omicron infections. Cox regression was performed for the outcome of hospital admission in those who tested positive for SARS-CoV-2 on the Seegene Allplex TM assay from November 1 to December 14, 2021 in the Western Cape Province, South Africa, in the public sector. Adjustments were made for vaccination status and prior diagnosis of infection., Results: A total of 150 cases with RTD and 1486 cases without RTD were included. Cases without RTD had a lower hazard of admission (adjusted hazard ratio [aHR], 0.56; 95% confidence interval [CI], 0.34-0.91). Complete vaccination was protective against admission, with an aHR of 0.45 (95% CI, 0.26-0.77)., Conclusion: Omicron has resulted in a lower risk of hospital admission compared with contemporaneous Delta infection, when using the proxy marker of RTD. Under-ascertainment of reinfections with an immune escape variant remains a challenge to accurately assessing variant virulence., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Routine SARS-CoV-2 surveillance in the Western Cape region of South Africa (January-August 2021) found a reduced RT-PCR amplification efficiency of the RdRp-gene target of the Seegene, Allplex 2019-nCoV diagnostic assay from June 2021 when detecting the Delta variant. We investigated whether the reduced amplification efficiency denoted by an increased RT-PCR cycle threshold value (RΔE) can be used as an indirect measure of SARS-CoV-2 Delta variant prevalence. We found a significant increase in the median RΔE for patient samples tested from June 2021, which coincided with the emergence of the SARS-CoV-2 Delta variant within our sample set. Whole genome sequencing on a subset of patient samples identified a highly conserved G15451A, non-synonymous mutation exclusively within the RdRp gene of Delta variants, which may cause reduced RT-PCR amplification efficiency. While whole genome sequencing plays an important in identifying novel SARS-CoV-2 variants, monitoring RΔE value can serve as a useful surrogate for rapid tracking of Delta variant prevalence., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: We aimed to assess the effectiveness of a single dose of the Ad26.COV2.S vaccine (Johnson & Johnson) in health-care workers in South Africa during two waves of the South African COVID-19 epidemic., Methods: In the single-arm, open-label, phase 3B implementation Sisonke study, health-care workers aged 18 years and older were invited for vaccination at one of 122 vaccination sites nationally. Participants received a single dose of 5 × 10 10 viral particles of the Ad26.COV2.S vaccine. Vaccinated participants were linked with their person-level data from one of two national medical insurance schemes (scheme A and scheme B) and matched for COVID-19 risk with an unvaccinated member of the general population. The primary outcome was vaccine effectiveness against severe COVID-19, defined as COVID-19-related admission to hospital, hospitalisation requiring critical or intensive care, or death, in health-care workers compared with the general population, ascertained 28 days or more after vaccination or matching, up to data cutoff. This study is registered with the South African National Clinical Trial Registry, DOH-27-022021-6844, ClinicalTrials.gov, NCT04838795, and the Pan African Clinical Trials Registry, PACTR202102855526180, and is closed to accrual., Findings: Between Feb 17 and May 17, 2021, 477 102 health-care workers were enrolled and vaccinated, of whom 357 401 (74·9%) were female and 119 701 (25·1%) were male, with a median age of 42·0 years (33·0-51·0). 215 813 vaccinated individuals were matched with 215 813 unvaccinated individuals. As of data cutoff (July 17, 2021), vaccine effectiveness derived from the total matched cohort was 83% (95% CI 75-89) to prevent COVID-19-related deaths, 75% (69-82) to prevent COVID-19-related hospital admissions requiring critical or intensive care, and 67% (62-71) to prevent COVID-19-related hospitalisations. The vaccine effectiveness for all three outcomes were consistent across scheme A and scheme B. The vaccine effectiveness was maintained in older health-care workers and those with comorbidities including HIV infection. During the course of the study, the beta (B.1.351) and then the delta (B.1.617.2) SARS-CoV-2 variants of concerns were dominant, and vaccine effectiveness remained consistent (for scheme A plus B vaccine effectiveness against COVID-19-related hospital admission during beta wave was 62% [95% CI 42-76] and during delta wave was 67% [62-71], and vaccine effectiveness against COVID-19-related death during beta wave was 86% [57-100] and during delta wave was 82% [74-89])., Interpretation: The single-dose Ad26.COV2.S vaccine shows effectiveness against severe COVID-19 disease and COVID-19-related death after vaccination, and against both beta and delta variants, providing real-world evidence for its use globally., Funding: National Treasury of South Africa, the National Department of Health, Solidarity Response Fund NPC, The Michael & Susan Dell Foundation, The Elma Vaccines and Immunization Foundation, and the Bill & Melinda Gates Foundation., Competing Interests: Declaration of interests L-GB declares honoraria for advisory roles from MSD, ViiV Health Care, and Gilead. RJL declares Department of Science and Innovation and South African Medical Research Council (SAMRC) funding to the KwaZulu-Natal Research Innovation and Sequencing Platform at the University of KwaZulu-Natal for the Network for Genomic Surveillance South Africa, which supported the genomic sequencing for this study; and committee membership of the Ministerial Advisory Committee on COVID-19 Vaccines (a committee that makes recommendations to the Minister of South Africa on the national COVID-19 vaccine programme. CC declares grants or contracts from CDC, PATH, the Bill & Melinda Gates Foundation, SAMRC, Wellcome Trust, and Sanofi Pasteur in the past 36 months. MG reports grants from SAMRC during the conduct of the study, and grants from the Bill & Melinda Gates Foundation outside of the submitted work. DBa reports grants from US National Institutes of Health (NIH) and Janssen during the conduct of the study; grants from Defense Advanced Research projects Agency, Massachusetts Consortium on Pathogen Readiness, Ragon Institute, the Bill & Melinda Gates Foundation, SAMRC, Henry Jackson Foundation, Musk Foundation, Gilead, Legend Bio, CureVac, Sanofi, Intima Bio, Alkermes, and Zentalis; and personal fees from SZQ Bio, Pfizer, Celsion, Avidea, Laronde, Meissa, and Vector Sciences outside of the submitted work DBr has three patents (63/121,482; 63/133,969; 63/135,182) licensed to Janssen. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: The SARS-CoV-2 omicron variant of concern was identified in South Africa in November, 2021, and was associated with an increase in COVID-19 cases. We aimed to assess the clinical severity of infections with the omicron variant using S gene target failure (SGTF) on the Thermo Fisher Scientific TaqPath COVID-19 PCR test as a proxy., Methods: We did data linkages for national, South African COVID-19 case data, SARS-CoV-2 laboratory test data, SARS-CoV-2 genome data, and COVID-19 hospital admissions data. For individuals diagnosed with COVID-19 via TaqPath PCR tests, infections were designated as either SGTF or non-SGTF. The delta variant was identified by genome sequencing. Using multivariable logistic regression models, we assessed disease severity and hospitalisations by comparing individuals with SGTF versus non-SGTF infections diagnosed between Oct 1 and Nov 30, 2021, and we further assessed disease severity by comparing SGTF-infected individuals diagnosed between Oct 1 and Nov 30, 2021, with delta variant-infected individuals diagnosed between April 1 and Nov 9, 2021., Findings: From Oct 1 (week 39), 2021, to Dec 6 (week 49), 2021, 161 328 cases of COVID-19 were reported in South Africa. 38 282 people were diagnosed via TaqPath PCR tests and 29 721 SGTF infections and 1412 non-SGTF infections were identified. The proportion of SGTF infections increased from two (3·2%) of 63 in week 39 to 21 978 (97·9%) of 22 455 in week 48. After controlling for factors associated with hospitalisation, individuals with SGTF infections had significantly lower odds of admission than did those with non-SGTF infections (256 [2·4%] of 10 547 vs 121 [12·8%] of 948; adjusted odds ratio [aOR] 0·2, 95% CI 0·1-0·3). After controlling for factors associated with disease severity, the odds of severe disease were similar between hospitalised individuals with SGTF versus non-SGTF infections (42 [21%] of 204 vs 45 [40%] of 113; aOR 0·7, 95% CI 0·3-1·4). Compared with individuals with earlier delta variant infections, SGTF-infected individuals had a significantly lower odds of severe disease (496 [62·5%] of 793 vs 57 [23·4%] of 244; aOR 0·3, 95% CI 0·2-0·5), after controlling for factors associated with disease severity., Interpretation: Our early analyses suggest a significantly reduced odds of hospitalisation among individuals with SGTF versus non-SGTF infections diagnosed during the same time period. SGTF-infected individuals had a significantly reduced odds of severe disease compared with individuals infected earlier with the delta variant. Some of this reduced severity is probably a result of previous immunity., Funding: The South African Medical Research Council, the South African National Department of Health, US Centers for Disease Control and Prevention, the African Society of Laboratory Medicine, Africa Centers for Disease Control and Prevention, the Bill & Melinda Gates Foundation, the Wellcome Trust, and the Fleming Fund., Competing Interests: Declaration of interests CC has received grant support from the South African Medical Research Council, the UK Foreign, Commonwealth and Development Office, the Wellcome Trust, the US Centers for Disease Control and Prevention, and Sanofi Pasteur. NW and MdP have received grant support from Sanofi Pasteur and the Bill & Melinda Gates Foundation. AvG has received grant support from Sanofi Pasteur, the US Centers for Disease Control and Prevention, the South African Medical Research Council, the Bill & Melinda Gates Foundation, WHO, the Fleming Fund, and the Wellcome Trust. RW declares personal shareholding in Adcock Ingram Holdings, Dischem Pharmacies, Discovery, Netcare, and Aspen Pharmacare Holdings. WS has received grant support from the South African Medical Research Council, with funds received from the Department of Science and Innovation, and the Bill & Melinda Gates Foundation. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Competing Interests: Competing interests: The authors completed the ICMJE Declaration of Interest Form (available upon request from the corresponding author), and declare no conflicts of interest.

Background: The first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves., Methods: In this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression., Findings: Peak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240·4 cases per 100 000 people vs 136·0 cases per 100 000 people; admissions, 27·9 admissions per 100 000 people vs 16·1 admissions per 100 000 people; deaths, 8·3 deaths per 100 000 people vs 3·6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1·19, 95% CI 1·18-1·20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40-64 years (adjusted odds ratio [aOR] 1·22, 95% CI 1·14-1·31), and older than 65 years (aOR 1·38, 1·25-1·52), compared with younger than 40 years; of Mixed race (aOR 1·21, 1·06-1·38) compared with White race; and admitted in the public sector (aOR 1·65, 1·41-1·92); and less likely to be Black (aOR 0·53, 0·47-0·60) and Indian (aOR 0·77, 0·66-0·91), compared with White; and have a comorbid condition (aOR 0·60, 0·55-0·67). For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1·31, 95% CI 1·28-1·35). In-hospital case-fatality risk increased from 17·7% in weeks of low admission (<3500 admissions) to 26·9% in weeks of very high admission (>8000 admissions; aOR 1·24, 1·17-1·32)., Interpretation: In South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage., Funding: DATCOV as a national surveillance system is funded by the National Institute for Communicable Diseases and the South African National Government., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: The interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis is unclear, particularly in low-income and middle-income countries in Africa. South Africa has a national HIV prevalence of 19% among people aged 15-49 years and a tuberculosis prevalence of 0·7% in people of all ages. Using a nationally representative hospital surveillance system in South Africa, we aimed to investigate the factors associated with in-hospital mortality among patients with COVID-19., Methods: In this cohort study, we used data submitted to DATCOV, a national active hospital surveillance system for COVID-19 hospital admissions, for patients admitted to hospital with laboratory-confirmed SARS-CoV-2 infection between March 5, 2020, and March 27, 2021. Age, sex, race or ethnicity, and comorbidities (hypertension, diabetes, chronic cardiac disease, chronic pulmonary disease and asthma, chronic renal disease, malignancy in the past 5 years, HIV, and past and current tuberculosis) were considered as risk factors for COVID-19-related in-hospital mortality. COVID-19 in-hospital mortality, the main outcome, was defined as a death related to COVID-19 that occurred during the hospital stay and excluded deaths that occurred because of other causes or after discharge from hospital; therefore, only patients with a known in-hospital outcome (died or discharged alive) were included. Chained equation multiple imputation was used to account for missing data and random-effects multivariable logistic regression models were used to assess the role of HIV status and underlying comorbidities on COVID-19 in-hospital mortality., Findings: Among the 219 265 individuals admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and known in-hospital outcome data, 51 037 (23·3%) died. Most commonly observed comorbidities among individuals with available data were hypertension in 61 098 (37·4%) of 163 350, diabetes in 43 885 (27·4%) of 159 932, and HIV in 13 793 (9·1%) of 151 779. Tuberculosis was reported in 5282 (3·6%) of 146 381 individuals. Increasing age was the strongest predictor of COVID-19 in-hospital mortality. Other factors associated were HIV infection (adjusted odds ratio 1·34, 95% CI 1·27-1·43), past tuberculosis (1·26, 1·15-1·38), current tuberculosis (1·42, 1·22-1·64), and both past and current tuberculosis (1·48, 1·32-1·67) compared with never tuberculosis, as well as other described risk factors for COVID-19, such as male sex; non-White race; underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy in the past 5 years; and treatment in the public health sector. After adjusting for other factors, people with HIV not on antiretroviral therapy (ART; adjusted odds ratio 1·45, 95% CI 1·22-1·72) were more likely to die in hospital than were people with HIV on ART. Among people with HIV, the prevalence of other comorbidities was 29·2% compared with 30·8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with increased COVID-19 in-hospital mortality risk in both people with HIV and HIV-uninfected individuals., Interpretation: Individuals identified as being at high risk of COVID-19 in-hospital mortality (older individuals and those with chronic comorbidities and people with HIV, particularly those not on ART) would benefit from COVID-19 prevention programmes such as vaccine prioritisation as well as early referral and treatment., Funding: South African National Government., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: COVID-19 outcomes and risk factors, including comorbidities and medication regimens, in people living with diabetes (PLWD) are poorly defined for low- and middle-income countries., Methods: The Provincial Health Data Centre (Western Cape, South Africa) is a health information exchange collating patient-level routine health data for approximately 4 million public sector health care seekers. Data from COVID-19 patients diagnosed between March and July 2020, including PLWD, were analysed to describe risk factors, including dispensed diabetes medications and comorbidities, and their association with COVID-19 outcomes in this population., Findings: There were 64,476 COVID-19 patients diagnosed. Of 9305 PLWD, 44.9% were hospitalised, 4.0% admitted to ICU, 0.6% received ventilation and 15.4% died. In contrast, proportions of COVID-19 patients without diabetes were: 12.2% hospitalised, 1.0% admitted, 0.1% ventilated and 4.6% died. PLWD were significantly more likely to be admitted (OR:3.73, 95 %CI: 3.53, 3.94) and to die (OR:3.01, 95 %CI: 2.76,3.28). Significant hospitalised risk factors included HIV infection, chronic kidney disease, current TB, male sex and increasing age. Significant risk factors for mortality were CKD, male sex, HIV infection, previous TB and increasing age. Pre-infection use of insulin was associated with a significant increased risk for hospitalisation (OR:1·39, 95 %CI:1·24,1·57) and mortality (OR1·49, 95 %CI:1·27; 1·74) and metformin was associated with a reduced risk for hospitalisation (OR:0·62,95 %CI:0·55, 0·71) and mortality (OR 0·77, 95 %CI:0·64; 0·92)., Interpretation: Using routine health data from this large virtual cohort, we have described the association of infectious and noncommunicable comorbidities as well as pre-infection diabetes medications with COVID-19 outcomes in PLWD in the Western Cape, South Africa., Funding: This research was funded in part, by the Wellcome Trust 203135/Z/16/Z, through support of NT. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. The Wellcome Centre for Infectious Diseases Research in Africa is supported by core funding from the Wellcome Trust [203135/Z/16/Z]. NT receives funding from the CIDRI-Africa Wellcome Trust grant (203135/Z/16/Z), and NT and TT receive funding from the NIH H3ABioNET award (U24HG006941). NT receives funding from the UKRI/MRC (MC&#95;PC&#95;MR/T037733/1)., Competing Interests: Declaration of Competing Interest JAD has been a speaker and on advisory board for Novartis, Novo Nordisk, Sanofi, Lilly, Servier, MSD, Aspen, Abbott, AstraZeneca, MSD and Boehringer Ingelheim; ILR, WT, and PJR have been a speaker for Sanofi and Aspen. AC has been a speaker for Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Medtronic, Merck, Novo Nordisk, Sanofi and on an advisory board for Abbott, AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Merck, Novartis, Novo Nordisk, Sanofi. All other authors declare no competing interests., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Around 2·5 million deaths and more than 110 million COVID-19 cases have been reported globally. Although it initially appeared that HIV infection was not a risk factor for COVID-19 or more severe disease, more recent large studies suggest that people living with HIV (particularly with low CD4 cell counts or untreated HIV infection) might have a more severe clinical course than those who are HIV-negative. Moreover, the COVID-19 pandemic has disrupted HIV prevention and treatment services worldwide, creating huge challenges to the continuity of essential activities. We have reviewed the most relevant features of COVID-19 in people living with HIV and highlighted topics where further research is required., Competing Interests: Declaration of interests JA has participated in advisory boards and received consulting honoraria or research grants, or both, from Gilead Sciences, Janssen Pharmaceuticals, and ViiV Healthcare, outside the submitted work. EM reports grants and personal fees from Merck Sharp & Dohme and ViiV Healthcare, and personal fees from Gilead Sciences and Janssen Pharmaceuticals, outside the submitted work. JMM reports grants and personal fees from AbbVie, Angelini, ContraFect, Cubist, Genentech, Gilead Sciences, Jansen Pharmaceuticals, Lysovant, Medtronic, Merck Sharp & Dohme, Novartis, Pfizer, and ViiV Healthcare, outside the submitted work. All other authors declare no competing interests. The views and opinions expressed in this Review are those of the authors and do not necessarily reflect the official policy or position of the WHO., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Continued uncontrolled transmission of SARS-CoV-2 in many parts of the world is creating conditions for substantial evolutionary changes to the virus 1,2 . Here we describe a newly arisen lineage of SARS-CoV-2 (designated 501Y.V2; also known as B.1.351 or 20H) that is defined by eight mutations in the spike protein, including three substitutions (K417N, E484K and N501Y) at residues in its receptor-binding domain that may have functional importance 3-5 . This lineage was identified in South Africa after the first wave of the epidemic in a severely affected metropolitan area (Nelson Mandela Bay) that is located on the coast of the Eastern Cape province. This lineage spread rapidly, and became dominant in Eastern Cape, Western Cape and KwaZulu-Natal provinces within weeks. Although the full import of the mutations is yet to be determined, the genomic data-which show rapid expansion and displacement of other lineages in several regions-suggest that this lineage is associated with a selection advantage that most plausibly results from increased transmissibility or immune escape 6-8 .

Humanity is currently facing the challenge of two devastating pandemics caused by two very different RNA viruses: HIV-1, which has been with us for decades, and SARS-CoV-2, which has swept the world in the course of a single year. The same evolutionary strategies that drive HIV-1 evolution are at play in SARS-CoV-2. Single nucleotide mutations, multi-base insertions and deletions, recombination, and variation in surface glycans all generate the variability that, guided by natural selection, enables both HIV-1's extraordinary diversity and SARS-CoV-2's slower pace of mutation accumulation. Even though SARS-CoV-2 diversity is more limited, recently emergent SARS-CoV-2 variants carry Spike mutations that have important phenotypic consequences in terms of both antibody resistance and enhanced infectivity. We review and compare how these mutational patterns manifest in these two distinct viruses to provide the variability that fuels their evolution by natural selection.

There are few data on the real-world effectiveness of COVID-19 vaccines and boosting in Africa, which experienced widespread SARS-CoV-2 infection before vaccine availability. We assessed the association between vaccination and severe COVID-19 in the Western Cape, South Africa, in an observational cohort study of >2 million adults during 2020–2022. We described SARS-CoV-2 testing, COVID-19 outcomes, and vaccine uptake over time. We used multivariable cox models to estimate the association of BNT162b2 and Ad26.COV2.S vaccination with COVID-19-related hospitalization and death, adjusting for demographic characteristics, underlying health conditions, socioeconomic status proxies, and healthcare utilization. We found that by the end of 2022, 41% of surviving adults had completed vaccination and 8% had received a booster dose. Recent vaccination was associated with notable reductions in severe COVID-19 during periods dominated by Delta, and Omicron BA.1/2 and BA.4/5 (sub)lineages. During the latest Omicron BA.4/5 wave, within 3 months of vaccination or boosting, BNT162b2 and Ad26.COV2.S were each 84% effective against death (95% CIs: 57–94 and 49–95, respectively). However, distinct reductions of effectiveness occurred at longer times post completing or boosting vaccination. Results highlight the importance of continued emphasis on COVID-19 vaccination and boosting for those at high risk of severe COVID-19, even in settings with widespread infection-induced immunity. [ABSTRACT FROM AUTHOR]

Background: The emergence of genetic variants of SARS-CoV-2 was associated with changing epidemiological characteristics throughout coronavirus disease 2019 (COVID-19) pandemic in population-based studies. Individual-level data on the clinical characteristics of infection with different SARS-CoV-2 variants in African countries is less well documented. Objectives: To describe the evolving clinical differences observed with the various SARS-CoV-2 variants of concern and compare the Omicron-driven wave in infections to the previous Delta-driven wave. Method: We performed a retrospective observational cohort study among patients admitted to a South African referral hospital with COVID-19 pneumonia. Patients were stratified by epidemiological wave period, and in a subset, the variants associated with each wave were confirmed by genomic sequencing. Outcomes were analysed by Cox proportional hazard models. Results: We included 1689 patients were included, representing infection waves driven predominantly by ancestral, Beta, Delta and Omicron BA1/BA2 & BA4/BA5 variants. Crude 28-day mortality was 25.8% (34/133) in the Omicron wave period versus 37.1% (138/374) in the Delta wave period (hazard ratio [HR] 0.68 [95% CI 0.47–1.00] p = 0.049); this effect persisted after adjustment for age, gender, HIV status and presence of cardiovascular disease (adjusted HR [aHR] 0.43 [95% CI 0.28–0.67] p < 0.001). Hospital-wide SARS-CoV-2 admissions and deaths were highest during the Delta wave period, with a decoupling of SARS-CoV-2 deaths and overall deaths thereafter. Conclusion: There was lower in-hospital mortality during Omicron-driven waves compared with the prior Delta wave, despite patients admitted during the Omicron wave being at higher risk. Contribution: This study summarises clinical characteristics associated with SARS-CoV-2 variants during the COVID-19 pandemic at a South African tertiary hospital, demonstrating a waning impact of COVID-19 on healthcare services over time despite epidemic waves driven by new variants. Findings suggest the absence of increasing virulence from later variants and protection from population and individual-level immunity. [ABSTRACT FROM AUTHOR]