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. MethodsIn 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. FindingsAmong 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...

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.

Researchers aimed to determine the effects of a teenage pregnancy (TP) prevention program for 816 high school students attending 16 KwaZulu-Natal, South African schools through a randomized control trial. Data were collected at baseline and at the 8-month follow-up in 2009. Results were calculated using multivariate analyses of program effects employing Mplus 6, and indicated significantly healthier attitudes, including intentions to abstain from sex whilst at school, plans to communicate with partners about teenage pregnancy, and increased reports of condom use. Researchers thus provide some support for the effectiveness of a TP prevention program that should be further strengthened in a comprehensive approach that includes schools and families.

The cross-sectional study investigated South African rural high school learners' choice of sexual abstinence in order to be able to develop tailored health education messages. All Grade 9 learners from one class at each of 10 randomly selected rural high schools participated. The Integrated Model for Motivational and Behavioural Change was used to elicit attitudes, social influences, self-efficacy and intentions towards sexual abstinence. Chi-square and t-tests were used for bivariate analysis. In total, 454 learners, mean age 16.7 years (standard deviation 1.41) range 14-20 years, participated, of whom 246 (54.2%) were female. When comparing learners reporting abstinence (n=252) with those not abstinent (n=202), abstinent learners were significantly more often females (P<0.005), younger (16.5 years versus 17.1 years, P<0.005) and drank less alcohol (P<0.005). Abstaining girls believed that their friends and parents think that they should abstain from sex, that their friends abstained from sex and that abstinence helped them to mature emotionally. Abstinent boys expressed intentions to abstain from sex until marriage. Targeted intervention research is required to encourage South African rural high school learners to delay their sexual initiation to reduce their risk of human immunodeficiency virus infection. Different abstinent messages are needed for boys and girls to address the different patterns of behaviour observed.

Background: In 2005, the Health Professions Council of South Africa (HPCSA) extended the duration of the internship programme to ensure that all young medical graduates are adequately prepared to work at a district hospital during their year of community service. King Edward VIII hospital (KEH) is an HPCSA accredited training hospital, which has been training interns for many years. The aim of this study was to assess intern perceptions of their training at the hospital. Methods: This cross-sectional, descriptive study was conducted at KEH in November 2016. A questionnaire was used to collect data, which were analysed descriptively. Results: Only 53% of interns completed the questionnaire. Although teaching and supervision were provided in all domains, perceptions of the quality ranged from excellent to poor. The majority of interns worked the 64-80 hours per month commuted overtime as required by the HPCSA. However, less than 10% expressed positive views regarding the condition of the facilities and infrastructure. Discussion and conclusions: The findings of this study were generally positive with regard to teaching, supervision and hours worked, mostly in accordance with the requirements of the HPCSA. However, a response rate of 53% as well as the single location of the study may limit generalisability and a larger study involving interns across the country is recommended.