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IntroductionThe Omicron BA.1/BA.2 wave in South Africa had lower hospitalisation and mortality than previous SARS-CoV-2 variants and was followed by an Omicron BA.4/BA.5 wave. This study compared admission incidence risk across waves, and the risk of mortality in the Omicron BA.4/BA.5 wave, to the Omicron BA.1/BA.2 and Delta waves. MethodsData from South Africas national hospital surveillance system, SARS-CoV-2 case linelist and Electronic Vaccine Data System were linked and analysed. Wave periods were defined when the country passed a weekly incidence of 30 cases/100,000 people. Mortality rates in the Delta, Omicron BA.1/BA.2 and Omicron BA.4/BA.5 wave periods were compared by post-imputation random effect multivariable logistic regression models. ResultsIn-hospital deaths declined 6-fold from 37,537 in the Delta wave to 6,074 in the Omicron BA.1/BA.2 wave and a further 7-fold to 837 in the Omicron BA.4/BA.5 wave. The case fatality ratio (CFR) was 25.9% (N=144,798), 10.9% (N=55,966) and 7.1% (N=11,860) in the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves respectively. After adjusting for age, sex, race, comorbidities, health sector and province, compared to the Omicron BA.4/BA.5 wave, patients had higher risk of mortality in the Omicron BA.1/BA.2 wave (adjusted odds ratio [aOR] 1.43; 95% confidence interval [CI] 1.32-1.56) and Delta (aOR 3.22; 95% CI 2.98-3.49) wave. Being partially vaccinated (aOR 0.89, CI 0.86-0.93), fully vaccinated (aOR 0.63, CI 0.60-0.66) and boosted (aOR 0.31, CI 0.24-0.41); and prior laboratory-confirmed infection (aOR 0.38, CI 0.35-0.42) were associated with reduced risks of mortality. ConclusionOverall, admission incidence risk and in-hospital mortality, which had increased progressively in South Africas first three waves, decreased in the fourth Omicron BA.1/BA.2 wave and declined even further in the fifth Omicron BA.4/BA.5 wave. Mortality risk was lower in those with natural infection and vaccination, declining further as the number of vaccine doses increased.
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BackgroundData on risk factors for COVID-19-associated hospitalisation and mortality in high HIV prevalence settings are limited. MethodsUsing existing syndromic surveillance programs for influenza-like-illness and severe respiratory illness at sentinel sites in South Africa, we identified factors associated with COVID-19 hospitalisation and mortality. ResultsFrom April 2020 through March 2022, SARS-CoV-2 was detected in 24.0% (660/2746) of outpatient and 32.5% (2282/7025) of inpatient cases. Factors associated with COVID-19-associated hospitalisation included: older age (25-44 [adjusted odds ratio (aOR) 1.8, 95% confidence interval (CI) 1.1-2.9], 45-64 [aOR 6.8, 95%CI 4.2-11.0] and [≥]65 years [aOR 26.6, 95%CI 14.4-49.1] vs 15-24 years); black race (aOR 3.3, 95%CI 2.2-5.0); obesity (aOR 2.3, 95%CI 1.4-3.9); asthma (aOR 3.5, 95%CI 1.4-8.9); diabetes mellitus (aOR 5.3, 95%CI 3.1-9.3); HIV with CD4 [≥]200/mm3 (aOR 1.5, 95%CI 1.1-2.2) and CD4<200/mm3 (aOR 10.5, 95%CI 5.1-21.6) or tuberculosis (aOR 12.8, 95%CI 2.8-58.5). Infection with Beta (aOR 0.5, 95%CI 0.3-0.7) vs Delta variant and being fully vaccinated (aOR 0.1, 95%CI 0.1-0.3) were less associated with COVID-19 hospitalisation. In-hospital mortality was increased in older age (45-64 years [aOR 2.2, 95%CI 1.6-3.2] and [≥]65 years [aOR 4.0, 95%CI 2.8-5.8] vs 25-44 years) and male sex (aOR1.3, 95%CI 1.0-1.6) and was lower in Omicron -infected (aOR 0.3, 95%CI 0.2-0.6) vs Delta-infected individuals. ConclusionActive syndromic surveillance encompassing clinical, laboratory and genomic data identified setting-specific risk factors associated with COVID-19 severity that will inform prioritization of COVID-19 vaccine distribution. Elderly, people with tuberculosis or people living with HIV, especially severely immunosuppressed should be prioritised for vaccination. Summary of articles viewpointCompared to the Delta variant, the Omicron variant was associated with reduced risk of mortality and Beta associated with decreased risk of hospitalisation. Active syndromic surveillance combining clinical, laboratory and genomic data can be used to describe the epidemic timing, epidemiological characteristics of cases, early detection of variants of concern and how these impact disease severity and outcomes; and presents a viable surveillance approach in settings where national surveillance is not possible.
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BackgroundIn South Africa 19% of the adult population aged 15-49 years are living with HIV (LWH). Few data on the influence of HIV on SARS-CoV-2 household transmission are available. MethodsWe performed a case-ascertained, prospective household transmission study of symptomatic index SARS-CoV-2 cases LWH and HIV-uninfected adults and their contacts in South Africa. Households were followed up thrice weekly for 6 weeks to collect nasal swabs for SARS-CoV-2 testing. We estimated household cumulative infection risk (HCIR), duration of SARS-CoV-2 positivity (at cycle threshold value<30 as proxy for high viral load), and assessed associated factors. ResultsWe recruited 131 index cases and 457 household contacts. HCIR was 59% (220/373); not differing by index HIV status (60% [50/83] in cases LWH vs 58% [173/293] in HIV-uninfected cases, OR 1.0, 95%CI 0.4-2.3). HCIR increased with index case age (35-59 years: aOR 3.4 95%CI 1.5-7.8 and [≥]60 years: aOR 3.1, 95%CI 1.0-10.1) compared to 18-34 years, and contacts age, 13-17 years (aOR 7.1, 95%CI 1.5-33.9) and 18-34 years (aOR 4.4, 95%CI 1.0-18.4) compared to <5 years. Mean positivity duration at high viral load was 7 days (range 2-28), with longer positivity in cases LWH (aHR 0.3, 95%CI 0.1-0.7). ConclusionsHIV-infection was not associated with higher HCIR, but cases LWH had longer positivity duration at high viral load. Adults aged >35 years were more likely to transmit, and individuals aged 13-34 to acquire SARS-CoV-2 in the household. Health services must maintain HIV testing with initiation of antiretroviral therapy for those HIV-infected. SummaryIn this case-ascertained, prospective household transmission study, household cumulative infection risk was 59% from symptomatic SARS-CoV-2 index cases, not differing based on index HIV status. Index cases living with HIV were positive for SARS-CoV-2 for longer at higher viral loads.
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In response to the COVID-19 pandemic, the South African government employed various nonpharmaceutical interventions (NPIs) in order to reduce the spread of SARS-CoV-2. In addition to mitigating transmission of SARS-CoV-2, these public health measures have also functioned in slowing the spread of other endemic respiratory pathogens. Surveillance data from South Africa indicates low circulation of respiratory syncytial virus (RSV) throughout the 2020-2021 Southern Hemisphere winter seasons. Here we fit age-structured epidemiological models to national surveillance data to predict the 2022 RSV outbreak following two suppressed seasons. We project a 32% increase in the peak number of monthly hospitalizations among infants [≤] 2 years, with older infants (6-23 month olds) experiencing a larger portion of severe disease burden than typical. Our results suggest that hospital system readiness should be prepared for an intense RSV season in early 2022.
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BackgroundThe SARS-CoV-2 Omicron variant of concern (VOC) almost completely replaced other variants in South Africa during November 2021, and was associated with a rapid increase in COVID-19 cases. We aimed to assess clinical severity of individuals infected with Omicron, using S Gene Target Failure (SGTF) on the Thermo Fisher Scientific TaqPath COVID-19 PCR test as a proxy. MethodsWe performed data linkages for (i) SARS-CoV-2 laboratory tests, (ii) COVID-19 case data, (iii) genome data, and (iv) the DATCOV national hospital surveillance system for the whole of South Africa. For cases identified using Thermo Fisher TaqPath COVID-19 PCR, infections were designated as SGTF or non-SGTF. Disease severity was assessed using multivariable logistic regression models comparing SGTF-infected individuals diagnosed between 1 October to 30 November to (i) non-SGTF in the same period, and (ii) Delta infections diagnosed between April and November 2021. ResultsFrom 1 October through 6 December 2021, 161,328 COVID-19 cases were reported nationally; 38,282 were tested using TaqPath PCR and 29,721 SGTF infections were identified. The proportion of SGTF infections increased from 3% in early October (week 39) to 98% in early December (week 48). On multivariable analysis, after controlling for factors associated with hospitalisation, individuals with SGTF infection had lower odds of being admitted to hospital compared to non-SGTF infections (adjusted odds ratio (aOR) 0.2, 95% confidence interval (CI) 0.1-0.3). Among hospitalised individuals, after controlling for factors associated with severe disease, the odds of severe disease did not differ between SGTF-infected individuals compared to non-SGTF individuals diagnosed during the same time period (aOR 0.7, 95% CI 0.3-1.4). Compared to earlier Delta infections, after controlling for factors associated with severe disease, SGTF-infected individuals had a lower odds of severe disease (aOR 0.3, 95% CI 0.2-0.5). ConclusionEarly analyses suggest a reduced risk of hospitalisation among SGTF-infected individuals when compared to non-SGTF infected individuals in the same time period. Once hospitalised, risk of severe disease was similar for SGTF- and non-SGTF infected individuals, while SGTF-infected individuals had a reduced risk of severe disease when compared to earlier Delta-infected individuals. Some of this reducton is likely a result of high population immunity.
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IntroductionSouth Africa experienced its first wave of COVID-19 peaking in mid-July 2020 and a larger second wave peaking in January 2021, in which the SARS-CoV-2 501Y.V2 lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves of COVID-19. MethodsWe analysed data from the DATCOV national active surveillance system for COVID-19 hospitalisations. We defined four wave periods using incidence risk for hospitalisation, pre-wave 1, wave 1, pre-wave 2 and wave 2. We compared the characteristics of hospitalised COVID-19 cases in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using multivariable logistic regression. ResultsPeak rates of COVID-19 cases, admissions and in-hospital deaths in the second wave exceeded the rates in the first wave (138.1 versus 240.1; 16.7 versus 28.9; and 3.3 versus 7.1 respectively per 100,000 persons). The weekly average incidence risk increase in hospitalisation was 22% in wave 1 and 28% in wave 2 [ratio of growth rate in wave two compared to wave one: 1.04, 95% CI 1.04-1.05]. On multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 20% increased risk of in-hospital mortality in the second wave (adjusted OR 1.2, 95% CI 1.2-1.3). In-hospital case fatality-risk (CFR) increased in weeks of peak hospital occupancy, from 17.9% in weeks of low occupancy (<3,500 admissions) to 29.6% in weeks of very high occupancy (>12,500 admissions) (adjusted OR 1.5, 95% CI 1.4-1.5). Compared to the first wave, individuals hospitalised in the second wave, were more likely to be older, 40-64 years [OR 1.1, 95% CI 1.0-1.1] and [≥]65 years [OR 1.1, 95% CI 1.1-1.1] compared to <40 years; and admitted in the public sector [OR 2.2, 95% CI 1.7-2.8]; and less likely to have comorbidities [OR 0.5, 95% CI 0.5-0.5]. ConclusionsIn South Africa, the second wave was associated with higher incidence and more rapid increase in hospitalisations, and increased in-hospital mortality. While some of this is explained by increasing pressure on the health system, a residual increase in mortality of hospitalised patients beyond this, could be related to the new lineage 501Y.V2. RESEARCH IN CONTEXT O_TEXTBOXEvidence before this studyMost countries have reported higher numbers of COVID-19 cases in the second wave but lower case-fatality risk (CFR), in part due to new therapeutic interventions, increased testing and better prepared health systems. South Africa experienced its second wave which peaked in January 2021, in which the variant of concern, SARS-CoV-2 501Y.V2 predominated. New variants have been shown to be more transmissible and in the United Kingdom, to be associated with increased hospitalisation and mortality rates in people infected with variant B.1.1.7 compared to infection with non-B.1.1.7 viruses. There are currently limited data on the severity of lineage 501Y.V2. Added value of this studyWe analysed data from the DATCOV national active surveillance system for COVID-19 hospitalisations, comparing in-hospital mortality and other patient characteristics between the first and second waves of COVID-19. The study revealed that after adjusting for weekly COVID-19 hospital admissions, there was a 20% increased risk of in-hospital mortality in the second wave. Our study also describes the demographic shift from the first to the second wave of COVID-19 in South Africa, and quantifies the impact of overwhelmed hospital capacity on in-hospital mortality. Implications of all the available evidenceOur data suggest that the new lineage (501Y.V2) in South Africa may be associated with increased in-hospital mortality during the second wave. Our data should be interpreted with caution however as our analysis is based on a comparison of mortality in the first and second wave as a proxy for dominant lineage and we did not have individual-level data on lineage. Individual level studies comparing outcomes of people with and without the new lineage based on sequencing data are needed. To prevent high mortality in a potential third wave, we require a combination of strategies to slow the transmission of SARS-CoV-2, to spread out the peak of the epidemic, which would prevent hospital capacity from being breached. C_TEXTBOX
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Continued uncontrolled transmission of the severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) in many parts of the world is creating the conditions for significant virus evolution. Here, we describe a new SARS-CoV-2 lineage (501Y.V2) characterised by eight lineage-defining mutations in the spike protein, including three at important residues in the receptor-binding domain (K417N, E484K and N501Y) that may have functional significance. This lineage emerged in South Africa after the first epidemic wave in a severely affected metropolitan area, Nelson Mandela Bay, located on the coast of the Eastern Cape Province. This lineage spread rapidly, becoming within weeks the dominant lineage in the Eastern Cape and Western Cape Provinces. Whilst the full significance of the mutations is yet to be determined, the genomic data, showing the rapid displacement of other lineages, suggest that this lineage may be associated with increased transmissibility.
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BackgroundThe interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis (TB) are unclear, particularly in low- and middle-income countries in Africa. South Africa has a national adult HIV prevalence of 19% and TB prevalence of 0.7%. Using a nationally representative hospital surveillance system in South Africa, we investigated the factors associated with in-hospital mortality among individuals with COVID-19. MethodsUsing data from national active hospital surveillance, we describe the demographic characteristics, clinical features, and in-hospital mortality among hospitalised individuals testing positive for SARS-CoV-2, during 5 March 2020 to 27 March 2021. Chained equation multiple imputation was used to account for missing data and random effect multivariable logistic regression models were used to assess the role of HIV-status and underlying comorbidities on in-hospital COVID-19 mortality. FindingsAmong the 219,265 individuals admitted with laboratory confirmed SARS-Cov-2, 51,037 (23.3%) died. Most commonly observed comorbidities among individuals with available data were hypertension (61,098/163,350; 37.4%), diabetes (43,885/159,932; 27.4%), and HIV (13,793/151,779; %), while TB was reported in 3.6% (5,282/146,381) of individuals. While age was the most important predictor, other factors associated with in-hospital COVID-19 mortality were HIV infection [aOR 1.34, 95% CI: 1.27-1.43), past TB [aOR 1.26, 95% CI: 1.15-1.38), current TB [aOR 1.42, 95% CI: 1.22-1.64) and both past and current TB [aOR 1.48, 95% CI: 1.32-1.67) compared to never TB, as well as other described risk factors for COVID-19, such as male sex, non-white race, and chronic underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy. After adjusting for other factors, PLWH not on ART [aOR 1.45, 95% CI: 1.22-1.72] were more likely to die in-hospital compared to PLWH on ART. Among PLWH, the prevalence of other comorbidities was 29.2% compared to 30.8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with increased mortality risk in both PLWH and HIV-uninfected individuals. InterpretationIdentified high risk individuals (older individuals and those with chronic comorbidities and PLWH, particularly those not on ART) would benefit from COVID-19 prevention programmes such as vaccine prioritisation, as well as early referral and treatment. FundingSouth African National Government Research in contextO_ST_ABSEvidence before this studyC_ST_ABSSince the emergence of the COVID-19 pandemic, studies have identified older age, male sex and presence of underlying comorbidities including heart disease and diabetes as risk factors for severe disease and death. There are very few studies, however, carried out in low- and middle-income countries (LMIC) in Africa, many of whom have high poverty rates, limited access to healthcare, and high prevalence of chronic communicable diseases, such as HIV and tuberculosis (TB). Data are also limited from settings with limited access to HIV treatment programmes. Early small cohort studies mainly from high income countries were not conclusive on whether HIV or TB are risk factors for disease severity and death in COVID-19 patients. Large population cohort studies from South Africas Western Cape province and the United Kingdom (UK) have found people living with HIV (PLWH) to have a moderately increased risk of COVID-19 associated mortality. Of these, only the Western Cape study presented data on mortality risk associated with presence of high viral load or immunosuppression, and found similar levels of severity irrespective of these factors. Recent meta-analyses have confirmed the association of HIV with COVID-19 mortality. No studies reported on the interaction between HIV-infection and other non-communicable comorbidities on COVID-19 associated mortality. We performed separate literature searches on PubMed using the following terms: "COVID-19" "risk factors" and "mortality"; "HIV" "COVID-19" and "mortality"; "TB" "COVID-19" and "mortality". All searches included publications from December 1, 2019 until May 5, 2021, without language restrictions. Pooled together, we identified 2,786 published papers. Additionally, we performed two literature searches on MedRxiv using the terms "HIV" "COVID-19" and "mortality", and "TB" "COVID-19" and "mortality" from April 25, 2020 until May 5, 2021, without language restrictions. Pooled together, we identified 7,744 pre-prints. Added value of this studyAmong a large national cohort of almost 220,000 individuals hospitalised with COVID-19 in a setting with 19% adult HIV prevalence and 0.7%TB prevalence, we found that along with age, sex and other comorbidities, HIV and TB were associated with a moderately increased risk of in-hospital mortality. We found increasing risk of in-hospital mortality among PLWH not on ART compared to those on ART. Among PLWH, the prevalence of other comorbidities was high (29%) and the effect of increasing numbers of comorbidities on mortality was similar in PLWH and HIV-uninfected individuals. Our study included 13,793 PLWH from all provinces in the country with varying levels of access to HIV treatment programmes. Implications of all the available evidenceThe evidence suggests that PLWH and TB-infected individuals should be prioritised for COVID-19 prevention and treatment programmes, particularly those with additional comorbidities. Increasing age and presence of chronic underlying illness are important additional factors associated with COVID-19 mortality in a middle-income African setting. The completeness of data is a limitation of this national surveillance system, and additional data are needed to confirm these findings.
