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

1 BACKGROUND

Since its emergence in Wuhan, China, in December 2019, the novel SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19) has culminated in a global pandemic with global cases and deaths continuing to climb.1 By September 19, 2020, the cut-off date for this report, 30.6 million cases of COVID-19 and 95, 000-related deaths had been reported to the World Health Organization (WHO),1 and children aged <18 years were estimated to have contributed to 8.5% of COVID-19 cases globally.2-4 However, the proportion of cases in children varied by country and was as high as 11% in the United States, 23% in Paraguay, and 15% in Brazil.5

Several factors might contribute to the lower reported incidence of COVID-19 among children: SARS-CoV-2 infection is more likely to be asymptomatic or cause milder symptoms in children (80%) than in adults (40–60%), and children may be less likely to receive medical care or be tested.2, 6-10 Furthermore, some data suggest children under 10 years of age might be 48% less susceptible to infection following exposure compared to adults.10 Therefore, the testing rates could be lower in that population.11, 12

Published data from the United States suggest rates of admission to hospital and intensive care units (ICUs) have been lower among children with COVID-19 (cumulative hospitalization rates eight cases per 100,000 children <18 years) than adults (164.5 cases per 100,000 adults).13, 14 Systematic reviews of studies published up to May 2020 reported pediatric case fatality ratio (CFR) ranging between 0% (in two studies) and 0.2% across their respective included studies.15-19 In a study of 114,000 SARS-CoV-2 positive deaths in the United States, children aged <18 years made up <0.3% of all deaths.20 Subsequent studies of children hospitalized with COVID-19 have described greater risk of severe disease especially among children with obesity and other underlying medical conditions compared to those without these conditions.13, 21, 22

There is a paucity of studies describing the epidemiology and clinical features of COVID-19 among children in Africa. Of published studies, a relatively small number of children were studied, ranging from 34–1,439.23-25 Findings from China,7 Europe,15 and North America,19 where the majority of studies of COVID-19 in children were conducted, may not be generalizable to countries such as South Africa where conditions such as malnutrition, childhood obesity, tuberculosis, HIV infection, or HIV exposure among children are more prevalent and background child mortality rates from other bacterial and viral infections are higher than other countries.26, 27 Additionally, sub-optimal sanitation, overcrowding, and limited access to health care likely reduce the efficacy of non-pharmacological interventions against COVID-19. We describe the epidemiology of SARS-CoV-2 infection and hospitalization among children aged <18 years in South Africa. Specifically, we describe age-specific population level testing rates, incidence of laboratory-confirmed SARS-CoV-2 infection, and the clinical characteristics and outcomes of children admitted with COVID-19 at sentinel hospitals. We also identify modifiable factors associated with in-hospital deaths to guide interventions for this population.

2 METHODS 2.1 Setting

South Africa is an upper middle-income country with high income inequality—GINI coefficient of 0.65 at national level.28 The country had an estimated 2020 mid-year population of 59.6 million, of which 33.5% (an estimated 20 million) were children <18 years old.29 In 2019, the country's under five mortality rate was 34 per 1,000 live births compared to 2 per 1,000 in the Nordic countries, 6 per 1,000 in the United States, and 117 per 1000 in Nigeria and Somalia.29, 30 The country is divided administratively into nine provinces in which there are wide variations in income and healthcare access and quality. The majority of the population lives in low-income settings characterized by high levels of unemployment and limited access to medical insurance and medical care. South Africa started real time reverse transcription polymerase chain reaction (rRT-PCR) testing for SARS-CoV-2 infection on January 28, 2020, and the first case of SARS-CoV-2 infection was reported on March 5, 2020. As part of non-pharmaceutical interventions to curb the spread of the epidemic, schools were closed on March 18, 2020, and measures restricting non-essential travel and trade were introduced on March 27, 2020. Restrictions were gradually eased starting May 1, 2020, paradoxically as the epidemic started to surge, with phased reopening of schools from June 8, 2020, with all children returning to school by September 1, 2020.

2.2 Data sources and collection procedures

SARS-CoV-2 rRT-PCR results were reported by both public and private laboratories to a surveillance system coordinated by the National Institute for Communicable Diseases (NICD). Limited demographic and epidemiological data such as age, sex, and contact information were obtained at the time of specimen collection. People meeting the South African National Department of Health (NDOH) case definition for persons under investigation (PUI) were tested. In March 2020, a PUI was defined as a person, regardless of age, with acute onset of fever >38.5°C with one or more of the following: cough, fever, or sore throat and contact with a known case of COVID-19.31 This definition was revised several times over the reporting period. For example on June 1, 2020, the guidance around which individuals could be tested by SARS-CoV-2 rRT-PCR was changed to restrict testing to those with symptoms, those who needed admission, and those with underlying conditions.31 For hospitalized people, data were collected at admission, during hospitalization, and at discharge using the DATCOV system, a prospective surveillance program for sentinel hospitals. The DATCOV system was introduced in phases starting April 2020.32 Healthcare workers treating COVID-19 patients of all ages reported demographic characteristics, clinical signs and symptoms, treatment provided, presence of underlying medical conditions, and outcomes among patients who had positive SARS-CoV-2 rRT-PCR tests and were admitted to participating sentinel hospitals (including public [government owned and operated] and private [individual or non-government entity owned and operated] facilities), using a structured electronic form. In addition to direct data captured by hospital staff, some sentinel hospitals exported data from COVID-19 admissions into the DATCOV system. The number of reporting, sentinel hospitals expanded during the study period. By September 19, 2020, there were 513 hospitals (269 public and 244 private hospitals) reporting COVID-19 admissions on the DATCOV platform. This represented 100% of private sector hospitals and 88% of all public sector hospitals in the country.33 Because not all hospitals started reporting admissions at the same time, hospitals which started reporting later in the surveillance period could submit their data retrospectively to include all admissions regardless of age.32

2.3 Laboratory procedures

Testing for SARS-CoV-2 using rRT-PCR began on January 28, 2020, at the reference laboratory at NICD and was expanded to a national network of private and public laboratories at the beginning of March 2020. The SARS-CoV-2 rRT-PCR testing from public sector facilities was free to the user while testing at private sector facilities required user fees in cash or through health insurance. By September 19, 2020, public sector laboratories accounted for 45.8% of all cumulative tests conducted and 41.4% of all positive tests, despite serving an estimated 80% of the population.34 Respiratory specimens, including nasopharyngeal swabs, nasal swabs, oropharyngeal swabs, and occasionally lower respiratory tract specimens (sputum, tracheal aspirate, and broncho-alveolar lavage) were collected at the discretion of the attending healthcare worker and submitted to testing laboratories. Laboratories used any one of several in-house and commercial rRT-PCR assays including the TIB Molbiol LightMix® Modular SARS-CoV (COVID19) assay (Roche Diagnostics, Basel, Switzerland) and Allplex™ 2019-nCoV assay (Seegene, Seoul, Republic of Korea) to test for the presence of SARS-CoV-2 RNA. Test results were automatically fed into the NICD data warehouse after result confirmation. Patients received their results through a short-text messaging system (SMS) directly from the laboratory or through the ordering physician.

2.4 Data management

Data on SARS-CoV-2 rRT-PCR tests conducted and case notifications were extracted from laboratory information systems, while data on hospitalizations were extracted from the DATCOV platform. Once extracted, duplicate entries by name and date of birth were identified and removed. The hospital dataset was compared with the line list of all laboratory-confirmed cases in order to exclude admissions that were not laboratory-confirmed. Data captured in SARS-CoV-2 testing database, case line list, and DATCOV database as of September 19, 2020, were extracted on the September 22, 2020, and exported into STATA® 14.2 (Stata Corporation, College Station, Texas, United States) for analysis.

2.5 Data analysis

Descriptive statistics were used to determine the age-specific testing, percent positive and incidence rates, and case fatality ratios (CFRs) comparing children (age <18 years) to adults (age ≥18 years) overall. Among children, descriptive statistics were used to describe testing rate, percent positive proportion, incidence rate, and case fatality ratios by age categories, sex, epidemiology week, and location (province). The main outcomes analyzed were (1) the SARS-CoV-2 rRT-PCR testing rate and percent positive, (2) incidence of laboratory-confirmed SARS-CoV-2 infection, and (3) in-hospital CFR among SARS-CoV-2-positive admissions. The testing rate (per 100,000 persons) was determined as the number of unique SARS-CoV-2 rRT-PCR tests—excluding repeat tests—divided by the population size based on the 2020 mid-year population estimates,29 stratified by age and sex and epidemiology week. The incidence of laboratory-confirmed SARS-CoV-2 infection was also presented as number of new infections per 100,000 persons. A SARS-CoV-2 positive admission was a person admitted to hospital with a confirmed SARS-CoV-2 rRT-PCR positive result regardless of the reason for admission. The CFR among hospitalized patients was determined as the percentage of SARS-CoV-2 positive admissions with a documented outcome who died during their stay at a sentinel hospital and whose death was possibly SARS-CoV-2 infection-related as determined by the attending physicians. Having an underlying condition was determined as report of at least one of the following chronic, pre-existing conditions at admission: asthma or any other chronic respiratory disease, any diabetes, hypertension, chronic kidney disease, a chronic heart disease, any history of malignancy, active or previous tuberculosis, HIV infection, or another chronic illness the children had at admission and coded as “other.” Information on underlying conditions was obtained from medical record review or self-reported by patient or caregiver.

Univariate and multivariable random effects logistic regression with and without multiple imputation were developed to determine factors independently associated with in-hospital death. Covariates assessed a priori in the model were age, sex, province, admission at public versus private hospitals, and presence of an underlying medical condition. A random effects model taking into account admission facility was used to account for potential differences in the service population and the quality of care of each facility, whereas chained equation multiple imputation over 10 imputation runs was used to account for missing data on the selected covariates. Incomplete variables included in the imputation chain were ethnicity, hospital admission month, and comorbidities such as HIV infection, tuberculosis (TB) infection, hypertension, diabetes, malignancy, reported obesity, asthma, chronic pulmonary disease, cardiac disease, and renal disease. Complete variables included in the imputation model were sex, province, whether a child was admitted to a private or public hospitals, and the in-hospital outcome. Analysis of admissions was limited to the first admission for COVID-19. Because of low burden of most underlying conditions, reported underlying conditions were grouped together as absence or presence of any non-communicable comorbid condition(s). For the multivariable model, we assessed all variables that were statistically significant at p < 0.2 on univariate analysis and dropped non-significant factors (p ≥ 0.05) using manual backward elimination.

2.6 Ethical considerations

The NICD has ethical clearance for essential communicable diseases surveillance and outbreak response investigation activities from the University of the Witwatersrand's Human Research Ethics Committee (Medical) (M160667). This activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy.* All personal and identifying information were removed, and case records were uniquely assigned to a system-generated record identifier.

3 RESULTS 3.1 Testing rate and SARS-CoV-2 rRT-PCR percentage test positive

From January 28 to September 19, 2020, 3,548,738 unique SARS-CoV-2 rRT-PCR tests were performed across all age groups (5,952 tests per 100,000 persons). Of these, 315,570 (8.9%) were performed on children aged <18 years, a rate of 1581 tests per 100,000 persons, which was fivefold lower than among adults who had a rate of 8,153 tests per 100,000 persons. The number of tests conducted varied by province (Table 1). A SARS-CoV-2 rRT-PCR test was positive in 46,137/313,584 valid tests (14.6%) among children compared to 587,460/3,186,450 tests (18.4%) among adults. Among children, the percentage of positive SARS-CoV-2 rRT-PCR tests increased with age from 7.8% (2,120/27,253) among those aged <1 year to 19.1% (6,155/32,147) in those aged 17 years (Figure 1A). The weekly testing rate among children increased from <1 per 100,000 persons in epidemiology week March 1–7, 2020, peaking at 128 per 100,000 persons in week July 5–12, 2020, then declining steadily to <74 per 100,000 persons during weeks August 2 to September 19, 2020. The percentage of SARS-CoV-2 rRT-PCR test positivity among children varied with age categories <18 years, but overall increased from a low of 1.1% in weeks March 29 to April 4, 2020, peaking at 22.3% in week July 19–25, 2020, before declining to 8.3% in week August 16–22, 2020 (Figure 2).

TABLE 1. Distribution of total population, SARS-CoV-2 rRT- PCR tests, positive cases, and SARS-CoV-2 positive hospital admissions among children <18 years by province, South Africa, March 1, 2020, to September 19, 2020 Province Total populationa Population aged <18 years in the province b Population of children in province as % of total populationc Population of children in province as % of all children in countryd SARS-CoV-2 rRT-PCR tests done on children n (%)e SARS-CoV-2 rRT-PCR testing rate per 100,000f SARS-CoV-2 rRT-PCR percent positive (%)g SARS-CoV-2 rRT-PCR positive cases reported n (%)h Incidence per 100,000i SARS-CoV-2 admissions n (%)j Eastern Cape 6,734,001 2,598,744 38.6 13.0 37,651 (11.9) 1,448.8 18.8 7,422 (16.3) 285.6 225 (11.2) Free State 2 ,928,903 987,049 33.7 4.9 24,534 (7.8) 2,485.6 16.9 4,026 (8.8) 407.9 137 (6.8) Gauteng 15,488,137 4,268,374 27.6 21.4 90,697 (28.7) 2,124.9 14.6 12,709 (27.9) 297.7 413 (20.6) KwaZulu Natal 11,531,628 4,321,495 37.5 21.6 75,630 (24.0) 1,750.1 13.5 10,023 (22.0) 231.9 360 (17.9) Limpopo 5,852,553 2,310,964 39.5 11.6 11,315 (3.6) 489.6 9.9 1,264 (2.8) 54.7 58 (2.9) Mpumalanga 4,679,786 1,621,363 34.6 8.1 13,991 (4.4) 862.9 15.2 1,986 (4.4) 122.5 60 (3.0) North West 4,108,816 1,404,681 34.2 7.0 8,199 (2.6) 583.7 16.5 1,734 (3.8) 123.4 81 (4.0) Northern Cape 1,292,786 440,893 34.1 2.2 7,642 (2.4) 1,733.3 17.2 1,601 (3.5) 363.1 44 (2.2) Western Cape 7,005,741 2,012,667 28.7 10.1 43,058 (13.6) 2,139.4 11.8 4,844 (10.6) 240.7 629 (31.3) Total 59,622,350 19,966,230 33.5 100.0 315,570k (100.0) 1,580.5 14.6 45,609 (100.0) 228.4

2007

(100.0)

Abbreviation: rRT- PCR, real-time reverse transcriptase polymerase chain reaction. a Total population of South Africa according to 2020 Statistics South Africa mid-year population (available from http://www.statssa.gov.za/?p=13453). b Population of children <18 years according to 2020 Statistics South Africa mid-year population (available from http://www.statssa.gov.za/?p=13453). c Proportion of population represented by children <18 years (calculated as 2 as a fraction of 1). d Proportion of the national population of children found in each province according to 2020 Statistics South Africa mid-year population (available from http://www.statssa.gov.za/?p=13453). e Number of SARS-CoV-2 tests conducted among children in each province and as proportion of total number of tests conducted among children nationally. f Testing rate among children, determined as number of tests5 divided by population aged <18 years2. g Proportion of valid childhood tests which were positive. h SARS-Co-V-2 cases among children <18 years reported from each province during the surveillance period and as percentage total number of cases reported in the surveillance period. i Number of cases per 100,000 population. Determined as number of SARS-CoV-2 cases reported7 divided by population aged <18 years.2 j SARS-Co-V-2-associated admissions among children <18 years reported from each province during the surveillance period and as percentage total number of associated admissions among children <18 years. k Included 2,583 (0.9%) for whom province was unknown. image

SARS-CoV2 rRT-PCR: (A) number of tests and percent positive, (B) number of new positive cases, and (C) number of associated- hospital admissions among children <18 years, by age and sex, South Africa, March 1, 2020, to September 19, 2020. rRT-PCR, real-time reverse transcriptase polymerase chain reaction

image

Weekly number of SARS-CoV-2 rRT-PCR8* tests and percent positive among children <18 years by age, South Africa, March 1, 2020 to September 19, 2020. rRT-PCR, real-time reverse transcriptase polymerase chain reaction

3.2 Incidence of laboratory confirmed SARS-CoV-2 infection

Overall, 662,343 (18.7%) people had tested positive on SARS-CoV-2 rRT-PCR and were reported to the NICD by September 19, 2020. Of the 640,449 (96.7%) who had age data available, 45,609 (7.1%) were children (0–17 years old). Among children testing positive, the median age was 12.4 years (interquartile range [IQR] 7.4–15.7 years), and 20,412 (44.8%) were male (Table S1). Most SARS-CoV-2 positive children (85.6%) resided in the country's five most populous provinces—Eastern Cape, Free State, Gauteng, KwaZulu-Natal, and Western Cape Provinces (Table 1). The overall cumulative incidence risk among children was 228.4 per 100,000 persons, which was sevenfold lower than in adults (incidence 1,615 per 100,000 persons). The cumulative incidence among children aged <2 years old (160.9 per 100,000 persons) was higher in males (173.7 per 100,000 persons) than females (141.5 per 100,000 persons), but lower than in children aged ≥2 years (237.3 per 100,000 persons) (Figure 1B). Nationally, the weekly incidence increased from <1 per 100,000 children during week March 1–7 peaking at 27.5 per 100,000 children in week July 5–11 (Figure S1B).

3.3 Characteristics of SARS-CoV-2 positive hospital admissions

There were 70,622 new SARS-CoV-2 rRT-PCR positive admissions captured on DATCOV during the surveillance period. Of these, 185 (0.3%) were excluded for missing age data, false positive results or because patients were from long-term care facilities. Of those with age data available (N = 70,437), only 2,007 (2.9%) were children. The number of SARS-CoV-2 rRT-PCR positive admissions varied by age and province (Tables 1 and S2). The median age of hospitalized children was 6.8 years (IQR 1.1–14.4 years) of whom 1,004 (50.0%) were male. SARS-CoV-2 rRT-PCR admissions among children were highest in infants (age <1 year) and children 13–17 years but lowest among those aged 3 to 12 years (Figure 1C). Admissions increased from one in week March 1–7, 2020, to a peak of 172 in week July 12–18, 2020 (Figure S1C).

Tables 2 and S2 describe the clinical characteristics of hospitalized children overall, categorized by specified age categories and by province. Of the 1,426 children with data on underlying medical conditions, 231 (16.1%) had ≥1 documented conditions reported. The most common comorbidities were chronic respiratory (106/231, 46.7%), HIV infection (37/231, 16.3%), and diabetes mellitus (36/231, 15.9%), although the frequency of underlying conditions varied with age category (Figure 3). Data on underlying medical conditions was available for 915/1,119 (81.9%) of children admitted to private sector hospitals versus 511/890 (57.8%) among those admitted to public sector hospitals. However, underlying conditions were more frequently reported among children admitted at public versus private hospitals (152/511 [29.8%] vs. 79/915 [8.6%], respectively, p < 0.001).

TABLE 2. Characteristics of COVID-19 associated hospital admissions to sentinel hospitals by children <18 years by age, South Africa, March 1, 2020, to September 19, 2020 (N = 2,007) Variable <1 year 1–4 years 5–9 years 10–14 years 15–17 years All children (N = 469) (N = 449) (N = 267) (N = 366) (N = 456) (N = 2,007) Age Age (median, IQR) 2.7 (0.8–6.5) months 2.2 (1.5–3.3) years 7.6 (6.4–8.8) years 12.9 (11.4–14.0) years 17.0 (16.1–17.6) years 6.8 (1.1–14.4) years Sex Male, n (%) 260 (55.4) 255 (56.8) 156 (58.4) 177 (48.4) 156 (34.3) 1,004 (50.0) Province Eastern Cape 28 (6.0) 32 (7.1) 24 (9.0) 44 (12.0) 97 (21.3) 225 (11.2) Free State 14 (3.0) 32 (7.1) 15 (5.6) 31 (8.5) 45 (9.9) 137 (6.8) Gauteng 94 (20.0) 94 (20.9) 63 (23.6) 82 (22.3) 80 (17.5) 413 (20.6) Kwa-Zulu Natal 82 (17.5) 70 (15.6) 50 (18.7) 83 (22.7) 75 (16.5) 360 (17.9) Limpopo 14 (3.0) 5 (1.1) 12 (4.5) 11 (3.0) 16 (3.5) 58 (2.9) Mpumalanga 13 (2.8) 16 (3.6) 6 (2.3) 8 (2.2) 17 (3.7) 60 (3.0) North-West 9 (1.9) 15 (3.3) 8 (3.0) 15 (4.1) 34 (7.5) 81 (4.0) Northern Cape 5 (1.1) 10 (2.2) 8 (3.0) 14 (3.8) 7 (1.5) 44 (2.2) Western Cape 210 (45.8) 175 (39.0) 81 (30.3) 78 (21.2) 85 (18.6) 629 (31.3) Hospital Public hospital, n (%) 238 (50.8) 171 (38.1) 108 (40.5) 162 (44.3) 211 (46.3) 890 (44.3) Data available on underlying conditions (yes, n [%]) 256 (54.6) 307 (68.4) 200 (74.9) 281 (76.8) 382 (83.8) 1,426 (71.1) ≥1 underlying conditions reported, n (%)a 27 (10.6) 52 (16.9) 39 (19.5) 55 (19.6) 58 (15.2) 231 (16.2) LOS, days (median, IQR) 4 (2–9) 3 (1–5) 2 (1–6) 3 (1.5–8) 4 (2–7.5) 3 (2–7) Ever admitted to high care, n (%) 28 (6.0) 15 (3.3) 7 (2.6) 20 (5.5) 14 (3.1) 84 (4.2) Ever admitted ICU, n (%) 64 (13.7) 24 (5.4) 18 (6.7) 27 (7.4) 21 (4.6) 154 (7.7) Ever ventilated, n (%) 25 (5.3) 5 (1.1) 10 (3.8) 12 (3.3)

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