Abstract
Background
In this study, we compared admission incidence risk and the risk of mortality in the Omicron BA.4/BA.5 wave to previous waves.
Methods
Data from South Africa's SARS-CoV-2 case ...linelist, national COVID-19 hospital surveillance system, and Electronic Vaccine Data System were linked and analyzed. Wave periods were defined when the country passed a weekly incidence of 30 cases/100 000 population. In-hospital case fatality ratios (CFRs) during the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves were compared using post-imputation random effect multivariable logistic regression models.
Results
The CFR was 25.9% (N = 37 538 of 144 778), 10.9% (N = 6123 of 56 384), and 8.2% (N = 1212 of 14 879) 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 with 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, 1.3; 95% confidence interval CI: 1.2–1.4) and Delta wave (aOR, 3.0; 95% CI: 2.8–3.2). Being partially vaccinated (aOR, 0.9; 95% CI: .9–.9), fully vaccinated (aOR, 0.6; 95% CI: .6–.7), and boosted (aOR, 0.4; 95% CI: .4–.5) and having prior laboratory-confirmed infection (aOR, 0.4; 95% CI: .3–.4) were associated with reduced risks of mortality.
Conclusions
Overall, admission incidence risk and in-hospital mortality, which had increased progressively in South Africa's first 3 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.
Admission incidence risk and in-hospital mortality decreased in the Omicron BA.1/BA.2 wave, reducing even further in the 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.
Globally, long-term care facilities (LTCFs) experienced a large burden of deaths during the COVID-19 pandemic. The study aimed to describe the temporal trends as well as the characteristics and risk ...factors for mortality among residents and staff who tested positive for SARS-CoV-2 in selected LTCFs across South Africa.
We analysed data reported to the DATCOV sentinel surveillance system by 45 LTCFs. Outbreaks in LTCFs were defined as large if more than one-third of residents and staff had been infected or there were more than 20 epidemiologically linked cases. Multivariable logistic regression was used to assess risk factors for mortality amongst LTCF residents.
A total of 2324 SARS-CoV-2 cases were reported from 5 March 2020 through 31 July 2021; 1504 (65%) were residents and 820 (35%) staff. Among LTCFs, 6 reported sporadic cases and 39 experienced outbreaks. Of those reporting outbreaks, 10 (26%) reported one and 29 (74%) reported more than one outbreak. There were 48 (66.7%) small outbreaks and 24 (33.3%) large outbreaks reported. There were 30 outbreaks reported in the first wave, 21 in the second wave and 15 in the third wave, with 6 outbreaks reporting between waves. There were 1259 cases during the first COVID-19 wave, 362 during the second wave, and 299 during the current third wave. The case fatality ratio was 9% (138/1504) among residents and 0.5% (4/820) among staff. On multivariable analysis, factors associated with SARS-CoV-2 mortality among LTCF residents were age 40-59 years, 60-79 years and ≥ 80 years compared to < 40 years and being a resident in a LTCF in Free State or Northern Cape compared to Western Cape. Compared to pre-wave 1, there was a decreased risk of mortality in wave 1, post-wave 1, wave 2, post-wave 2 and wave 3.
The analysis of SARS-CoV-2 cases in sentinel LTCFs in South Africa points to an encouraging trend of decreasing numbers of outbreaks, cases and risk for mortality since the first wave. LTCFs are likely to have learnt from international experience and adopted national protocols, which include improved measures to limit transmission and administer early and appropriate clinical care.
Older age, male sex, and non-white race have been repor ted to be risk factors for COVID-19 mor tality. Few studies have explored how these intersecting factors contribute to COVID-19 outcomes. This ...study aimed to compare demographic characteristics and trends in SARS-CoV-2 admissions and the health care they received. Hospital admission data were collected through DATCOV, an active national COVID-19 surveillance programme. Descriptive analysis was used to compare admissions and deaths by age, sex, race, and health sector as a proxy for socio-economic status. COVID-19 mor tality and healthcare utilisation were compared by race using random effect multivariable logistic regression models. On multivariable analysis, black African patients (adjusted OR aOR 1.3, 95% confidence interval CI 1.2, 1.3), coloured patients (aOR 1.2, 95% CI 1.1, 1.3), and patients of Indian descent (aOR 1.2, 95% CI 1.2, 1.3) had increased risk of in-hospital COVID-19 mor tality compared to white patients; and admission in the public health sector (aOR 1.5, 95% CI 1.5, 1.6) was associated with increased risk of mor tality compared to those in the private sector. There were higher percentages of COVID-19 hospitalised individuals treated in ICU, ventilated, and treated with supplemental oxygen in the private compared to the public sector. There were increased odds of non-white patients being treated in ICU or ventilated in the private sector, but decreased odds of black African patients being treated in ICU (aOR 0.5; 95% CI 0.4, 0.5) or ventilated (aOR 0.5; 95% CI 0.4, 0.6) compared to white patients in the public sector. These ifndings demonstrate the impor tance of collecting and analysing data on race and socio-economic status to ensure that disease control measures address the most vulnerable populations affected by COVID-19.Significance: • These findings demonstrate the importance of collecting data on socio-economic status and race alongside age and sex, to identify the populations most vulnerable to COVID-19. • This study allows a better understanding of the pre-existing inequalities that predispose some groups to poor disease outcomes and yet more limited access to health interventions. • Interventions adapted for the most vulnerable populations are likely to be more effective. • The national government must provide efficient and inclusive non-discriminatory health services, and urgently improve access to ICU, ventilation and oxygen in the public sector. • Transformation of the healthcare system is long overdue, including narrowing the gap in resources between the private and public sectors.
The following terminology was erroneously reported: “non-white race” should be “people of colour”, or “black African, coloured and people of Indian descent”.
South Africa reported a notable increase in COVID-19 cases from mid-November, 2021, onwards, starting in Tshwane District, which coincided with the rapid community spread of the SARS-CoV-2 omicron ...(B.1.1.529) variant. This increased infection rate coincided with a rapid increase in paediatric COVID-19-associated admissions to hospital (hereafter referred to as hospitalisations).
The Tshwane Maternal-Child COVID-19 study is a multicentre observational study in which we investigated the clinical manifestations and outcomes of paediatric patients (aged ≤19 years) who had tested positive for SARS-CoV-2 and were admitted to hospital for any reason in Tshwane District during a 6-week period at the beginning of the fourth wave of the COVID-19 epidemic in South Africa. We used five data sources, which were: (1) COVID-19 line lists; (2) collated SARS-CoV-2 testing data; (3) SARS-CoV-2 genomic sequencing data; (4) COVID-19 hospitalisation surveillance; and (5) clinical data of public sector COVID-19-associated hospitalisations among children aged 13 years and younger.
Between Oct 31 and Dec 11, 2021, 6287 children and adolescents in Tshwane District were recorded as having COVID-19. During this period, 2550 people with COVID-19 were hospitalised, of whom 462 (18%) were aged 19 years or younger. The number of paediatric cases was higher than in the three previous SARS-CoV-2 waves, uncharacteristically increasing ahead of adult hospitalisations. 75 viral samples from adults and children in the district were sequenced, of which 74 (99%) were of the omicron variant. Detailed clinical notes were available for 138 (75%) of 183 children aged ≤13 years with COVID-19 who were hospitalised. 87 (63%) of 138 children were aged 0-4 years. In 61 (44%) of 138 cases COVID-19 was the primary diagnosis, among whom symptoms included fever (37 61% of 61), cough (35 57%), shortness of breath (19 31%), seizures (19 31%), vomiting (16 26%), and diarrhoea (15 25%). Median length of hospital stay was 2 days IQR 1-3). 122 (88%) of 138 children with available data needed standard ward care and 27 (20%) needed oxygen therapy. Seven (5%) of 138 children were ventilated and four (3%) died during the study period, all related to complex underlying copathologies. All children and 77 (92%) of 84 parents or guardians with available data were unvaccinated to COVID-19.
Rapid increases in paediatric COVID-19 cases and hospitalisations mirror high community transmission of the SARS-CoV-2 omicron variant in Tshwane District, South Africa. Continued monitoring is needed to understand the long-term effect of the omicron variant on children and adolescents.
South African Medical Research Council, South African Department of Science & Innovation, G7 Global Health Fund.
This study describes characteristics of admitted HCWs reported to the DATCOV surveillance system and factors associated with in-hospital mortality in South African HCW.
Data from 5 March 2020 to 30 ...April 2021 were obtained from DATCOV, a national hospital surveillance monitoring COVID-19 admissions in South Africa. Characteristics of HCWs were compared to non-HCWs. Furthermore, a logistic regression model was used to assess factors associated with in-hospital mortality among HCWs.
There were a total of 169,678 confirmed COVID-19 admissions, of which 6,364 (3.8%) were HCWs. HCW admissions were high in wave 1 (48.6%; n=3,095) than in wave 2 (32.0%; n=2,036). Admitted HCWs were less likely to be male (28.2%; n=1,791) (aOR 0.3; 95% CI (0.3-0.4), in the age group 50-59 (33.1%; n=2,103) (aOR 1.4; 95%CI (1.1-1.8), accessing private health sectors (63.3%; n=4,030) (aOR 1.3; 95%CI (1.1-1.5). Age, comorbidities, race, wave, province and sector were significant risk factors for COVID-19 related mortality.
The trends in cases show a decline in HCW admissions in wave 2 compared to wave 1. Acquired SARS-COV-2 immunity from prior infection may be a reason for reduced admissions and mortality of HCWs despite the more transmissible and more severe Beta variant in wave 2.
•HCW admissions increased in wave 1 (48.6%) than in wave 2 (32.0%) period.•HCWs were less likely to have mortality (aOR 0.6; 95%CI (0.5-0.7) as an outcome.•Age, race, wave, sector, province were risk factors for in-hospital mortality.•Weekly hospital admissions increased the risk of COVID-19 mortality for HCWs.
Older age, male sex, and non-white race have been reported to be risk factors for COVID-19 mortality. Few studies have explored how these intersecting factors contribute to COVID-19 outcomes. This ...study aimed to compare demographic characteristics and trends in SARS-CoV-2 admissions and the health care they received. Hospital admission data were collected through DATCOV an active national COVID-19 surveillance programme. Descriptive analysis was used to compare admissions and deaths by age, sex, race, and health sector as a proxy for socio-economic status. COVID-19 mortality and healthcare utilisation were compared by race using random effect multivariable logistic regression models. On multivariable analysis, black African patients (adjusted OR aOR 1.3, 95% confidence interval CI 1.2, 1.3), coloured patients (aOR 1.2, 95% CI 1.1, 1.3), and patients of Indian descent (aOR 1.2, 95% CI 1.2, 1.3) had increased risk of in-hospital COVID-19 mortality compared to white patients; and admission in the public health sector (aOR 1.5, 95% CI 1.5, 1.6) was associated with increased risk of mortality compared to those in the private sector. There were higher percentages of COVID-19 hospitalised individuals treated in ICU, ventilated, and treated with supplemental oxygen in the private compared to the public sector. There were increased odds of non-white patients being treated in ICU or ventilated in the private sector, but decreased odds of black African patients being treated in ICU (aOR 0.5; 95% CI 0.4, 0.5) or ventilated (aOR 0.5; 95% CI 0.4, 0.6) compared to white patients in the public sector. These findings demonstrate the importance of collecting and analysing data on race and socio-economic status to ensure that disease control measures address the most vulnerable populations affected by COVID-19.
In 2021, the HIV prevalence among South African adults was 18% and more than 2 million people had uncontrolled HIV and, therefore, had increased risk of poor outcomes with SARS-CoV-2 infection. We ...investigated trends in COVID-19 admissions and factors associated with in-hospital COVID-19 mortality among people living with HIV and people without HIV.
In this analysis of national surveillance data, we linked and analysed data collected between March 5, 2020, and May 28, 2022, from the DATCOV South African national COVID-19 hospital surveillance system, the SARS-CoV-2 case line list, and the Electronic Vaccination Data System. All analyses included patients hospitalised with SARS-CoV-2 with known in-hospital outcomes (ie, who were discharged alive or had died) at the time of data extraction. We used descriptive statistics for admissions and mortality trends. Using post-imputation random-effect multivariable logistic regression models, we compared characteristics and the case fatality ratio of people with HIV and people without HIV. Using modified Poisson regression models, we compared factors associated with mortality among all people with COVID-19 admitted to hospital and factors associated with mortality among people with HIV.
Among 397 082 people with COVID-19 admitted to hospital, 301 407 (75·9%) were discharged alive, 89 565 (22·6%) died, and 6110 (1·5%) had no recorded outcome. 270 737 (68·2%) people with COVID-19 had documented HIV status (22 858 with HIV and 247 879 without). Comparing characteristics of people without HIV and people with HIV in each COVID-19 wave, people with HIV had increased odds of mortality in the D614G (adjusted odds ratio 1·19, 95% CI 1·09-1·29), beta (1·08, 1·01-1·16), delta (1·10, 1·03-1·18), omicron BA.1 and BA.2 (1·71, 1·54-1·90), and omicron BA.4 and BA.5 (1·81, 1·41-2·33) waves. Among all COVID-19 admissions, mortality was lower among people with previous SARS-CoV-2 infection (adjusted incident rate ratio 0·32, 95% CI 0·29-0·34) and with partial (0·93, 0·90-0·96), full (0·70, 0·67-0·73), or boosted (0·50, 0·41-0·62) COVID-19 vaccination. Compared with people without HIV who were unvaccinated, people without HIV who were vaccinated had lower risk of mortality (0·68, 0·65-0·71) but people with HIV who were vaccinated did not have any difference in mortality risk (1·08, 0·96-1·23). In-hospital mortality was higher for people with HIV with CD4 counts less than 200 cells per μL, irrespective of viral load and vaccination status.
HIV and immunosuppression might be important risk factors for mortality as COVID-19 becomes endemic.
South African National Institute for Communicable Diseases, the South African National Government, and the United States Agency for International Development.
Introduction
We describe epidemiology and outcomes of confirmed SARS‐CoV‐2 infection and positive admissions among children <18 years in South Africa, an upper‐middle income setting with high ...inequality.
Methods
Laboratory and hospital COVID‐19 surveillance data, 28 January ‐ 19 September 2020 was used. Testing rates were calculated as number of tested for SARS‐CoV‐2 divided by population at risk; test positivity rates were calculated as positive tests divided by total number of tests. In‐hospital case fatality ratio (CFR) was calculated based on hospitalized positive admissions with outcome data who died in‐hospital and whose death was judged SARS‐CoV‐2 related by attending physician.
Findings
315 570 children aged <18 years were tested for SARS‐CoV‐2; representing 8.9% of all 3 548 738 tests and 1.6% of all children in the country. Of children tested, 46 137 (14.6%) were positive. Children made up 2.9% (n = 2007) of all SARS‐CoV‐2 positive admissions to sentinel hospitals. Among children, 47 died (2.6% case‐fatality). In‐hospital deaths were associated with male sex adjusted odds ratio (aOR) 2.18 (95% confidence intervals CI 1.08–4.40) vs female; age <1 year aOR 4.11 (95% CI 1.08–15.54), age 10–14 years aOR 4.20 (95% CI1.07–16.44), age 15–17 years aOR 4.86 (95% 1.28–18.51) vs age 1–4 years; admission to a public hospital aOR 5.07(95% 2.01–12.76) vs private hospital and ≥1 underlying conditions aOR 12.09 (95% CI 4.19–34.89) vs none.
Conclusions
Children with underlying conditions were at greater risk of severe SARS‐CoV‐2 outcomes. Children > 10 years, those in certain provinces and those with underlying conditions should be considered for increased testing and vaccination.
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![Corrigendum: ]The intersect...](http://api.summon.serialssolutions.com/2.0.0/image/issn/XR4PS5YY4K/1996-7489/small "Corrigendum: ]The intersection of age, sex, race and socioeconomic status in COVID-19 hospital admissions and deaths in South Africa")