Changing Epidemiology of COVID-19 in Children and Adolescents Over Four Successive Epidemic Waves in South Africa, 2020-2022.

BACKGROUND: South Africa experienced four waves of SARS-CoV-2 infection, dominated by Wuhan-Hu, Beta, Delta, and Omicron (BA.1/BA.2). We describe the trends in SARS-CoV-2 testing, cases, admissions, and deaths among children and adolescents in South Africa over successive waves. METHODS: We analyzed national SARS-CoV-2 testing, case, and admissions data from March 2020 to February 2022 and estimated cumulative rates by age group for each endpoint. The severity in the third versus the fourth wave was assessed using multivariable logistic regression. RESULTS: Individuals ≤18 years comprised 35% (21,008,060/60,142,978) of the population but only 12% (424,394/3,593,644) of cases and 6% (26,176/451,753) of admissions. Among individuals ≤18 years, infants had the highest admission (505/100,000) rates. Testing, case, and admission rates generally increased successively in the second (Beta) and third (Delta) waves among all age groups. In the fourth (Omicron BA.1/BA.2) wave, the case rate dropped among individuals ≥1 year but increased among those <1 year. Weekly admission rates for children <1 year (169/100,000) exceeded rates in adults (124/100,000) in the fourth wave. The odds of severe COVID-19 in all admitted cases were lower in the fourth wave versus the third wave in each age group, but they were twice as high in admitted cases with at least one comorbidity than those without. CONCLUSIONS: The admission rate for children <5 years was higher in the fourth wave than in previous waves, but the overall outcomes were less severe. However, children with at least one comorbidity had increased odds of severe disease, warranting consideration of prioritizing this group for vaccination.

Etiological Surveillance of Genital Ulcer Syndrome in South Africa: 2019 to 2020.

BACKGROUND: Herpes simplex virus (HSV) has been the leading cause of genital ulcer syndrome (GUS) in South Africa for more than a decade, and acyclovir therapy is incorporated into syndromic management guidelines. We conducted surveillance at 3 sentinel sites to define the common sexually transmitted etiologies of GUS and to determine whether current syndromic management is appropriate. Secondary objectives of surveillance were to determine the seroprevalence of coinfections (HIV, syphilis, HSV-2) in persons presenting with GUS. METHODS: Consecutive, consenting adult men and women presenting with visible genital ulceration were enrolled between January 1, 2019, and December 31, 2020. Genital ulcer swab and blood specimens were collected and transported to a central sexually transmitted infection reference laboratory in Johannesburg. RESULTS: Among 190 participants with GUS, HSV-2 was the most frequently detected ulcer pathogen (49.0%; 95% confidence interval [CI], 41.9%-56.1%). The relative prevalence of the second most common ulcer-derived pathogen, Treponema pallidum, was 26.3% (95% CI, 20.5%-33.1%), with 90% of primary syphilis cases having a positive rapid plasma reagin (RPR) titer. Male sex was independently associated with primary syphilis compared with herpetic ulcers, after adjusting for the effect of casual sex partners and other exposures (adjusted odds ratio, 3.53; 95% CI, 1.35-9.21; P = 0.010). The overall HIV prevalence among participants was 41.3% (78 of 189; 95% CI, 34.2%-48.6%). CONCLUSIONS: Herpes simplex virus 2 remains the predominant cause of GUS, justifying the continued use of acyclovir in syndromic guidelines. Adequate supplies of benzathine penicillin G for syphilis treatment are essential at primary health care level, in addition to the provision of syphilis and HIV risk reduction services.

Tuberculosis screening among ambulatory people living with HIV: a systematic review and individual participant data meta-analysis.

BACKGROUND: The WHO-recommended tuberculosis screening and diagnostic algorithm in ambulatory people living with HIV is a four-symptom screen (known as the WHO-recommended four symptom screen [W4SS]) followed by a WHO-recommended molecular rapid diagnostic test (eg Xpert MTB/RIF [hereafter referred to as Xpert]) if W4SS is positive. To inform updated WHO guidelines, we aimed to assess the diagnostic accuracy of alternative screening tests and strategies for tuberculosis in this population. METHODS: In this systematic review and individual participant data meta-analysis, we updated a search of PubMed (MEDLINE), Embase, the Cochrane Library, and conference abstracts for publications from Jan 1, 2011, to March 12, 2018, done in a previous systematic review to include the period up to Aug 2, 2019. We screened the reference lists of identified pieces and contacted experts in the field. We included prospective cross-sectional, observational studies and randomised trials among adult and adolescent (age ≥10 years) ambulatory people living with HIV, irrespective of signs and symptoms of tuberculosis. We extracted study-level data using a standardised data extraction form, and we requested individual participant data from study authors. We aimed to compare the W4SS with alternative screening tests and strategies and the WHO-recommended algorithm (ie, W4SS followed by Xpert) with Xpert for all in terms of diagnostic accuracy (sensitivity and specificity), overall and in key subgroups (eg, by antiretroviral therapy [ART] status). The reference standard was culture. This study is registered with PROSPERO, CRD42020155895. FINDINGS: We identified 25 studies, and obtained data from 22 studies (including 15 666 participants; 4347 [27·7%] of 15 663 participants with data were on ART). W4SS sensitivity was 82% (95% CI 72-89) and specificity was 42% (29-57). C-reactive protein (≥10 mg/L) had similar sensitivity to (77% [61-88]), but higher specificity (74% [61-83]; n=3571) than, W4SS. Cough (lasting ≥2 weeks), haemoglobin (<10 g/dL), body-mass index (<18·5 kg/m2), and lymphadenopathy had high specificities (80-90%) but low sensitivities (29-43%). The WHO-recommended algorithm had a sensitivity of 58% (50-66) and a specificity of 99% (98-100); Xpert for all had a sensitivity of 68% (57-76) and a specificity of 99% (98-99). In the one study that assessed both, the sensitivity of sputum Xpert Ultra was higher than sputum Xpert (73% [62-81] vs 57% [47-67]) and specificities were similar (98% [96-98] vs 99% [98-100]). Among outpatients on ART (4309 [99·1%] of 4347 people on ART), W4SS sensitivity was 53% (35-71) and specificity was 71% (51-85). In this population, a parallel strategy (two tests done at the same time) of W4SS with any chest x-ray abnormality had higher sensitivity (89% [70-97]) and lower specificity (33% [17-54]; n=2670) than W4SS alone; at a tuberculosis prevalence of 5%, this strategy would require 379 more rapid diagnostic tests per 1000 people living with HIV than W4SS but detect 18 more tuberculosis cases. Among outpatients not on ART (11 160 [71·8%] of 15 541 outpatients), W4SS sensitivity was 85% (76-91) and specificity was 37% (25-51). C-reactive protein (≥10 mg/L) alone had a similar sensitivity to (83% [79-86]), but higher specificity (67% [60-73]; n=3187) than, W4SS and a sequential strategy (both test positive) of W4SS then C-reactive protein (≥5 mg/L) had a similar sensitivity to (84% [75-90]), but higher specificity than (64% [57-71]; n=3187), W4SS alone; at 10% tuberculosis prevalence, these strategies would require 272 and 244 fewer rapid diagnostic tests per 1000 people living with HIV than W4SS but miss two and one more tuberculosis cases, respectively. INTERPRETATION: C-reactive protein reduces the need for further rapid diagnostic tests without compromising sensitivity and has been included in the updated WHO tuberculosis screening guidelines. However, C-reactive protein data were scarce for outpatients on ART, necessitating future research regarding the utility of C-reactive protein in this group. Chest x-ray can be useful in outpatients on ART when combined with W4SS. The WHO-recommended algorithm has suboptimal sensitivity; Xpert for all offers slight sensitivity gains and would have major resource implications. FUNDING: World Health Organization.

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.

The importation and establishment of community transmission of SARS-CoV-2 during the first eight weeks of the South African COVID-19 epidemic.

BACKGROUND: We describe the epidemiology of COVID-19 in South Africa following importation and during implementation of stringent lockdown measures. METHODS: Using national surveillance data including demographics, laboratory test data, clinical presentation, risk exposures (travel history, contacts and occupation) and outcomes of persons undergoing COVID-19 testing or hospitalised with COVID-19 at sentinel surveillance sites, we generated and interpreted descriptive statistics, epidemic curves, and initial reproductive numbers (Rt). FINDINGS: From 4 March to 30 April 2020, 271,670 SARS-CoV-2 PCR tests were performed (462 tests/100,000 persons). Of these, 7,892 (2.9%) persons tested positive (median age 37 years (interquartile range 28-49 years), 4,568 (58%) male, cumulative incidence of 13.4 cases/100,000 persons). Hospitalization records were found for 1,271 patients (692 females (54%)) of whom 186 (14.6%) died. Amongst 2,819 cases with data, 489/2819 (17.3%) travelled internationally within 14 days prior to diagnosis, mostly during March 2020 (466 (95%)). Cases diagnosed in April compared with March were younger (median age, 37 vs. 40 years), less likely female (38% vs. 53%) and resident in a more populous province (98% vs. 91%). The national initial Rt was 2.08 (95% confidence interval (CI): 1.71-2.51). INTERPRETATION: The first eight weeks following COVID-19 importation were characterised by early predominance of imported cases and relatively low mortality and transmission rates. Despite stringent lockdown measures, the second month following importation was characterised by community transmission and increasing disease burden in more populous provinces.

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. FUNDING: South African National Government.