Acceptability, feasibility and impact of routine screening to detect undiagnosed HIV infection in 17 - 24-month-old children in the western sub-district of Cape Town

OBJECTIVES: To explore the acceptability and feasibility of routine HIV screening in children at primary healthcare clinics and ascertain the prevalence of previously undiagnosed HIV infection in 17 - 24 month old children accessing curative and routine services. METHODS: A survey was conducted in 4 primary health clinics in the western sub-district of Cape Town. Rapid HIV screening of 17 - 24 month old children was performed for consenting caregiver-child pairs. Data on demographics, child health and antenatal history were collected using questionnaires. RESULTS: During recruitment, 358 children (72%) were tested for HIV infection. Most of the children (95.8%) were accompanied by a parent. The prevalence of reported HIV exposure among children was 21% (107/499). Of these, 3 had previously confirmed HIV infection; 1 was reportedly confirmed by a 6-week HIV test, and the other 2 probably contracted the virus via late post-partum transmission. The overall transmission rate was 3.5% (3/86) and the confirmed proportion of HIV-infected children was 0.8% (3/361). No previously unknown HIV infection was detected. CONCLUSIONS: Programmes to prevent mother-to-child transmission are effective, but at-risk infants who test negative at 6 weeks should be monitored for subsequent seroconversion. Parents of HIV-exposed infants are more likely to permit (re)testing of their infants than those whose offspring are not at risk. Routine HIV testing of children is feasible and acceptable at primary level, but may require additional resources to achieve universal coverage. Routine screening at an earlier age may detect previously undiagnosed HIV infection

Acceptability, feasibility and impact of routine screening to detect undiagnosed HIV infection in 17 - 24-month-old children in the western sub-district of Cape Town

Objectives. To explore the acceptability and feasibility of routine HIV screening in children at primary healthcare clinics and ascertain the prevalence of previously undiagnosed HIV infection in 17 - 24 month old children accessing curative and routine services. Methods. A survey was conducted in 4 primary health clinics in the western sub-district of Cape Town. Rapid HIV screening of 17 - 24 month old children was performed for consenting caregiver-child pairs. Data on demographics, child health and antenatal history were collected using questionnaires. Results. During recruitment, 358 children (72%) were tested for HIV infection. Most of the children (95.8%) were accompanied by a parent. The prevalence of reported HIV exposure among children was 21% (107/499). Of these, 3 had previously confirmed HIV infection; 1 was reportedly confirmed by a 6-week HIV test, and the other 2 probably contracted the virus via late post-partum transmission. The overall transmission rate was 3.5% (3/86) and the confirmed proportion of HIV-infected children was 0.8% (3/361). No previously unknown HIV infection was detected. Conclusions. Programmes to prevent mother-to-child transmission are effective, but at-risk infants who test negative at 6 weeks should be monitored for subsequent seroconversion. Parents of HIV-exposed infants are more likely to permit (re)testing of their infants than those whose offspring are not at risk. Routine HIV testing of children is feasible and acceptable at primary level, but may require additional resources to achieve universal coverage. Routine screening at an earlier age may detect previously undiagnosed HIV infection

Individual and community-level risk factors for HIV stigma in 21 Zambian and South African communities: analysis of data from the HPTN071 (PopART) study.

OBJECTIVE: To describe the prevalence and determinants of HIV stigma in 21 communities in Zambia and South Africa. DESIGN: Analysis of baseline data from the HPTN 071 (PopART) cluster-randomized trial. HIV stigma data came from a random sample of 3859 people living with HIV. Community-level exposures reflecting HIV fears and judgements and perceptions of HIV stigma came from a random sample of community members not living with HIV (n = 5088), and from health workers (HW) (n = 851). METHODS: We calculated the prevalence of internalized stigma, and stigma experienced in the community or in a healthcare setting in the past year. We conducted risk-factor analyses using logistic regression, adjusting for clustering. RESULTS: Internalized stigma (868/3859, prevalence 22.5%) was not associated with sociodemographic characteristics but was less common among those with a longer period since diagnosis (P = 0.043). Stigma experienced in the community (853/3859, 22.1%) was more common among women (P = 0.016), older (P = 0.011) and unmarried (P = 0.009) individuals, those who had disclosed to others (P < 0.001), and those with more lifetime sexual partners (P < 0.001). Stigma experienced in a healthcare setting (280/3859, 7.3%) was more common among women (P = 0.019) and those reporting more lifetime sexual partners (P = 0.001) and higher wealth (P = 0.003). Experienced stigma was more common in clusters wherever community members perceived higher levels of stigma, but was not associated with the beliefs of community members or HW. CONCLUSION: HIV stigma remains unacceptably high in South Africa and Zambia and may act as barrier to HIV prevention and treatment. Further research is needed to understand its determinants

Development of parallel measures to assess HIV stigma and discrimination among people living with HIV, community members and health workers in the HPTN 071 (PopART) trial in Zambia and South Africa.

INTRODUCTION: Integrating standardized measures of HIV stigma and discrimination into research studies of emerging HIV prevention approaches could enhance uptake and retention of these approaches, and care and treatment for people living with HIV (PLHIV), by informing stigma mitigation strategies. We sought to develop a succinct set of measures to capture key domains of stigma for use in research on HIV prevention technologies. METHODS: From 2013 to 2015, we collected baseline data on HIV stigma from three populations (PLHIV (N = 4053), community members (N = 5782) and health workers (N = 1560)) in 21 study communities in South Africa and Zambia participating in the HPTN 071 (PopART) cluster-randomized trial. Forty questions were adapted from a harmonized set of measures developed in a consultative, global process. Informed by theory and factor analysis, we developed seven scales, with values ranging from 0 to 3, based on a 4-point agreement Likert, and calculated means to assess different aspects of stigma. Higher means reflected more stigma. We developed two measures capturing percentages of PLHIV who reported experiencing any stigma in communities or healthcare settings in the past 12 months. We validated our measures by examining reliability using Cronbach's alpha and comparing the distribution of responses across characteristics previously associated with HIV stigma. RESULTS: Thirty-five questions ultimately contributed to seven scales and two experience measures. All scales demonstrated acceptable to very good internal consistency. Among PLHIV, a scale captured internalized stigma, and experience measures demonstrated that 22.0% of PLHIV experienced stigma in the community and 7.1% in healthcare settings. Three scales for community members assessed fear and judgement, perceived stigma in the community and perceived stigma in healthcare settings. Similarly, health worker scales assessed fear and judgement, perceived stigma in the community and perceived co-worker stigma in healthcare settings. A higher proportion of community members and health workers reported perceived stigma than the proportion of PLHIV who reported experiences of stigma. CONCLUSIONS: We developed novel, valid measures that allowed for triangulation of HIV stigma across three populations in a large-scale study. Such comparisons will illuminate how stigma influences and is influenced by programmatic changes to HIV service delivery over time

Epidemiology of SARS-CoV-2 infection and SARS-CoV-2 positive hospital admissions among children in South Africa

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.SUPPORTING INFORMATION : TABLE S1: Description of SARS-CoV-2 rRT-PCR positive children <18 years in South Africa, 1 March 2020–19 September 2020 (N = 45 609). TABLE S2: Description of SARS-CoV-2 rRT-PCR positive hospital admissions among children <18 years in South Africa by province, 1 March 2020–19 September 2020 (N = 2007). TABLE S3: Distribution of non-missing variables among children with complete follow up and included in multivariable model (N = 1817). TABLE S4: Factors associated with in-hospital death among SARS-CoV-2 rRT-PCR positive admissions in children <18 years, South Africa, 1 March 2020–19 September 2020. FIGURE S1: Number of SARS-CoV-2 rRT-PCR tests*, percent positive tests and associated- hospital admissions among children <18 years by province and epidemiology week, South Africa, 1 March 2020–19 September 2020.National Department of Health, Republic of South Africahttp://wileyonlinelibrary.com/journal/irvhj2022School of Health Systems and Public Health (SHSPH

Risk factors for COVID-19-related in-hospital mortality in a high HIV and tuberculosis prevalence setting in South Africa : a cohort study

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.DATCOV, as a national surveillance system, is funded by the South African National Institute for Communicable Diseases (NICD) and the South African National Government.http://www.thelancet.com/hivam2022School of Health Systems and Public Health (SHSPH

Risk factors for Coronavirus Disease 2019 (COVID-19) death in a population cohort study from the Western Cape Province, South Africa

BACKGROUND. Risk factors for coronavirus disease 2019 (COVID-19) death in sub-Saharan Africa and the effects of human immunodeficiency virus (HIV) and tuberculosis on COVID-19 outcomes are unknown. METHODS. We conducted a population cohort study using linked data from adults attending public-sector health facilities in the Western Cape, South Africa. We used Cox proportional hazards models, adjusted for age, sex, location, and comorbidities, to examine the associations between HIV, tuberculosis, and COVID-19 death from 1 March to 9 June 2020 among (1) public-sector “active patients” (≥1 visit in the 3 years before March 2020); (2) laboratory-diagnosed COVID-19 cases; and (3) hospitalized COVID-19 cases. We calculated the standardized mortality ratio (SMR) for COVID-19, comparing adults living with and without HIV using modeled population estimates. RESULTS. Among 3 460 932 patients (16% living with HIV), 22 308 were diagnosed with COVID-19, of whom 625 died. COVID- 19 death was associated with male sex, increasing age, diabetes, hypertension, and chronic kidney disease. HIV was associated with COVID-19 mortality (adjusted hazard ratio [aHR], 2.14; 95% confidence interval [CI], 1.70–2.70), with similar risks across strata of viral loads and immunosuppression. Current and previous diagnoses of tuberculosis were associated with COVID-19 death (aHR, 2.70 [95% CI, 1.81–4.04] and 1.51 [95% CI, 1.18–1.93], respectively). The SMR for COVID-19 death associated with HIV was 2.39 (95% CI, 1.96–2.86); population attributable fraction 8.5% (95% CI, 6.1–11.1). CONCLUSIONS. While our findings may overestimate HIV- and tuberculosis-associated COVID-19 mortality risks due to residual confounding, both living with HIV and having current tuberculosis were independently associated with increased COVID-19 mortality. The associations between age, sex, and other comorbidities and COVID-19 mortality were similar to those in other settings.The Western Cape Provincial Health Data Centre from the Western Cape Department of Health, the US National Institutes for Health (grant numbers R01 HD0804, the Bill and Melinda Gates Foundation, the United States Agency for International Development and the Wellcome Trust.https://academic.oup.com/cid/am2023Veterinary Tropical Disease

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

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

Effects of HIV exposure on child growth in the Free State & Western Cape Provinces, South Africa

Includes abstract.Includes bibliographical references.The aim of this analysis was to determine the effects of HIV exposure on child growth and nutritional status in children less than two years of age in the Free State (FS) and Western Cape (WC) Provinces, South Africa