Paediatric hospitalisations due to COVID-19 during the first SARS-CoV-2 omicron (B.1.1.529) variant wave in South Africa: a multicentre observational study

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Study Justification:
This study aimed to investigate the impact of the SARS-CoV-2 omicron variant on paediatric hospitalisations during the fourth wave of the COVID-19 epidemic in South Africa. The justification for this study is based on the notable increase in COVID-19 cases and paediatric hospitalisations observed in Tshwane District, coinciding with the rapid community spread of the omicron variant. Understanding the clinical manifestations and outcomes of paediatric patients is crucial for effective management and resource allocation.
Study Highlights:
– The study found that paediatric COVID-19 cases and hospitalisations increased rapidly during the omicron variant wave in Tshwane District, South Africa.
– The number of paediatric cases was higher than in previous waves, and hospitalisations in children occurred ahead of adult hospitalisations.
– The majority of hospitalised children were aged 0-4 years, and common symptoms included fever, cough, shortness of breath, seizures, vomiting, and diarrhoea.
– The median length of hospital stay was 2 days, and most children required standard ward care, with a smaller proportion needing oxygen therapy.
– Four children died during the study period, all related to complex underlying copathologies.
– All children and the majority of parents or guardians were unvaccinated against COVID-19.
Recommendations:
– Continued monitoring is necessary to understand the long-term effects of the omicron variant on children and adolescents.
– Public health measures should prioritize vaccination efforts for children and their parents or guardians to reduce the risk of severe illness and hospitalisation.
– Healthcare facilities should be prepared to provide appropriate care for paediatric COVID-19 cases, including adequate ward capacity and oxygen therapy availability.
– Public health messaging should emphasize the importance of early recognition of COVID-19 symptoms in children and prompt healthcare seeking.
Key Role Players:
– Researchers and scientists involved in COVID-19 surveillance and epidemiology
– Healthcare providers, including paediatricians and nurses
– Public health officials and policymakers
– Hospital administrators and managers
– Community leaders and organizations
Cost Items for Planning Recommendations:
– Vaccine procurement and distribution
– Public health education and awareness campaigns
– Healthcare facility capacity expansion, including additional ward beds and oxygen supply
– Training and education for healthcare providers on paediatric COVID-19 management
– Data collection and analysis for ongoing monitoring and surveillance

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it is based on a multicentre observational study that collected data from multiple sources. The study provides detailed information on the number of pediatric COVID-19 cases and hospitalizations during the fourth wave in South Africa, as well as clinical manifestations, outcomes, and vaccination status. However, to improve the evidence, the abstract could include more information on the methodology used, such as the sample size, data collection methods, and statistical analysis. Additionally, providing information on the limitations of the study would further strengthen the evidence.

Background: 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). Methods: 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. Findings: 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. Interpretation: 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. Funding: South African Medical Research Council, South African Department of Science & Innovation, G7 Global Health Fund.

In this multicentre observational study (The Tshwane Maternal-Child COVID-19 study), we collated paediatric COVID-19-related data (ie, for children aged ≤19 years) during the early stages of the fourth COVID-19 wave in South Africa. Our key population of interest was children aged ≤13 years who had been admitted to any of 38 hospitals in Tshwane District during this period. We also collected data for adolescents aged 14 to 19 years, and adults older than 19 years, for comparison. The Tshwane Maternal-Child COVID-19 research study received permission from the ethics committees of both Health Sciences Faculties in Tshwane (University of Pretoria [reference number 822/2020] and Sefako Makgatho Health Sciences University [reference number SMUREC/M/54/2021:IR]), together with the Tshwane District Research Committee. Additionally, three large public sector hospitals (Steve Biko Academic Hospital, Kalafong Academic Hospital, and George Mukhari Academic Hospital) are part of the SA COVID KIDS study and have received ethics approval from the South African Medical Research Council (reference number EC048-11/2020). Ethics approval was also obtained for sequencing of COVID-19 samples (University of Pretoria Ethics Committee, reference number 101/2017). Individual patient consent was not needed for the genome samples at is part of ongoing routine surveilance. We extracted data relevant to the Tshwane District from the following sources: district-based COVID-19 line lists for contact tracing activities (totals, with age breakdowns); SARS-CoV-2 testing data collated by the National Institute for Communicable Diseases (NICD); SARS-CoV-2 genomic sequencing data from samples obtained within the district through the Zoonotic Arbo and Respiratory Virus Research Group (ZARV) at the Department of Medical Virology, National Health Laboratory Services (NHLS), University of Pretoria (Pretoria, South Africa) and from the NGS-SA from the global reference database for SARS-CoV-2 viral genomes, Global Initiative on Sharing Avian Influenza Data (GISAID); COVID-19 hospitalisation data (DATCOV hospital surveillance system, collated by the NICD); and clinical data of public sector paediatric (ie, aged ≤13 years) hospitalisations due to COVID-19, collected for the SA COVID Kids study and for local planning of paediatric clinical services. SARS-CoV-2 testing data were extracted from the NICD for adults, adolescents, and children for the period March 1, 2020, to Dec 5, 2020. A laboratory-confirmed COVID-19 case was defined as any person who tested positive for SARS-CoV-2 on either a real-time RT-PCR (rRT-PCR) or an antigen test using samples obtained from nasopharyngeal or oropharyngeal swabs, with testing done at NHLS laboratories located in four public sector hospitals in the Tshwane District. Access to SARS-CoV-2 testing was not substantially constrained; increased access to rapid antigen testing for enhanced speed of diagnosis was the most important change in COVID-19 testing practices since Oct 5, 2021. For genomic sequencing, we used clinical samples from adults and children from public sector clinics and hospitals in Tshwane District submitted to NHLS for SARS-CoV-2 rRT-PCR testing. Positive cases among adult and paediatric patients from Nov 7 to 29, 2021 (epidemiological weeks 45–48), were collected by ZARV staff for genome sequencing. SARS-CoV-2-positive samples with crossing point threshold values (ct) of 30 or less were sent for next-generation sequencing at the Research Innovation and Sequencing Platform at the University of KwaZulu-Natal (Durban, South Africa), as part of the NGS-SA initiative. Sequences were submitted to GISAID and assigned to lineages. Regarding the DATCOV surveillance system, 38 hospitals in Tshwane District were submitting hospitalisation data during our study period, including all nine public sector hospitals and 25 private sector hospitals (as of Dec 11, 2021). Due to restructuring during the COVID-19 pandemic, one public sector district hospital was closely linked to its adjacent public sector central hospital and subsequently counted as one academic hospital complex for the purposes of this study. The dataset includes information on patient numbers, age groups, sex, level of hospital care, length of stay, and patient outcomes. Although the DATCOV system provides overall disease surveillance, it does not provide detailed clinical data. Therefore, we collated clinical data from treating clinicians and hospital files to supplement and verify the DATCOV data, including clinical presentation, diagnoses, management, and outcomes. Symptoms were analysed in a subgroup of children (aged ≤13 years) with primary SARS-CoV-2 infection. A COVID-19-associated hospitalisation was defined by DATCOV as any person who tested positive for SARS-CoV-2 and was admitted to hospital, regardless of the reason for hospitalisation. Hospitals in the South African public health sector are divided into different levels of care; however, for geographical reasons, care is often first accessed at the closest hospital and not necessarily linked to disease severity. For descriptive purposes, we grouped public sector hospitals into central and academic hospitals (n=3) and regional and district hospitals (n=5) with high care and intensive care services available at central and academic hospitals, and with standard inpatient care (including oxygen therapy, fluid management, and antibiotics) available at all levels. Children who were referred from another hospital were classed as being at the higher level hospital, irrespective of the reason for referral, to avoid being included twice in the dataset. The DATCOV surveillance system reports on children and adolescents aged 19 years and younger. We used descriptive statistics, including mean (SD), ranges, median (IQR), and counts and proportions to describe demographic characteristics for tests, cases, and hospitalisations, and further stratified these data by age group (<1 year; 1–4 years; 5–9 years; 10–14 years; 15–19 years). We calculated the crude admission rate as the number of admissions in different age groups as a proportion of the population (as per Statistics South Africa mid-year population estimates for 2020),19 and present these data as admissions per 1 000 000 people, by age and week of admission. For our in-depth analysis of clinical features, we assessed data for all paediatric patients (aged ≤13 years) admitted to public sector hospitals who had detailed clinical notes from their treated physician. We also did subgroup analyses within this population by primary diagnosis on admission. The funders did not have a role in the study design, data collection, data analysis, data interpretation, or writing of the report.

The provided text appears to be a detailed description of the methods and data sources used in a multicentre observational study on paediatric hospitalizations due to COVID-19 during the omicron variant wave in South Africa. It does not contain any specific innovations or recommendations for improving access to maternal health. If you have any specific questions or need assistance with a different topic, please let me know.
AI Innovations Description
The description provided is a detailed account of the methods and data sources used in a multicentre observational study conducted in Tshwane District, South Africa. The study aimed to investigate the clinical manifestations and outcomes of pediatric patients (aged ≤19 years) who tested positive for SARS-CoV-2 and were admitted to hospitals during the fourth wave of the COVID-19 epidemic.

The study collected data from various sources, including COVID-19 line lists, SARS-CoV-2 testing data, genomic sequencing data, COVID-19 hospitalization surveillance, and clinical data of pediatric hospitalizations. The data sources provided information on the number of COVID-19 cases and hospitalizations, age breakdowns, symptoms, length of hospital stay, required care, and patient outcomes.

The study found a rapid increase in pediatric COVID-19 cases and hospitalizations, particularly among children aged 0-4 years. The majority of children hospitalized with COVID-19 required standard ward care, and a smaller percentage needed oxygen therapy. A small number of children required ventilation, and unfortunately, four deaths were reported during the study period, all related to underlying copathologies. It is worth noting that all children and the majority of parents or guardians were unvaccinated against COVID-19.

The study concludes that the rapid increase in pediatric COVID-19 cases and hospitalizations reflects the high community transmission of the SARS-CoV-2 omicron variant in Tshwane District. Continued monitoring is necessary to understand the long-term effects of the omicron variant on children and adolescents.

The study was funded by the South African Medical Research Council, South African Department of Science & Innovation, and G7 Global Health Fund. The funders did not have a role in the study design, data collection, analysis, interpretation, or report writing.
AI Innovations Methodology
The provided text describes the methodology used in the multicentre observational study called the Tshwane Maternal-Child COVID-19 study. The study aimed to investigate the clinical manifestations and outcomes of pediatric patients (aged ≤19 years) who tested positive for SARS-CoV-2 and were admitted to hospitals in Tshwane District, South Africa during the fourth wave of the COVID-19 epidemic.

The study collected data from various sources, including COVID-19 line lists, SARS-CoV-2 testing data, genomic sequencing data, COVID-19 hospitalization surveillance, and clinical data of pediatric hospitalizations. The data sources provided information on the number of COVID-19 cases, hospitalizations, genomic sequencing results, clinical symptoms, length of hospital stay, required care, and patient outcomes.

To analyze the data, the study used descriptive statistics such as mean, median, ranges, counts, and proportions. The data were stratified by age groups and weeks of admission. The study calculated the crude admission rate as the number of admissions in different age groups as a proportion of the population. In-depth analysis was conducted on pediatric patients with detailed clinical notes, including subgroup analyses based on the primary diagnosis on admission.

To simulate the impact of recommendations on improving access to maternal health, a methodology could include the following steps:

1. Identify the recommendations: Review existing literature, guidelines, and expert opinions to identify potential recommendations for improving access to maternal health. These recommendations could include interventions such as increasing the number of healthcare facilities, improving transportation infrastructure, enhancing healthcare workforce capacity, implementing telemedicine services, and promoting community-based care.

2. Define the simulation parameters: Determine the variables and parameters that will be used to simulate the impact of the recommendations. This could include factors such as the number of healthcare facilities, distance to healthcare facilities, availability of transportation, healthcare workforce capacity, and utilization rates.

3. Collect baseline data: Gather data on the current state of maternal health access, including the number of healthcare facilities, their locations, transportation infrastructure, healthcare workforce capacity, and utilization rates. This data will serve as the baseline for comparison.

4. Develop a simulation model: Create a simulation model that incorporates the identified recommendations and the baseline data. The model should simulate the impact of the recommendations on improving access to maternal health by estimating changes in variables such as the number of healthcare facilities, distance to healthcare facilities, transportation availability, and healthcare workforce capacity.

5. Run the simulation: Execute the simulation model using the defined parameters and recommendations. The simulation should generate outputs that quantify the potential impact of the recommendations on improving access to maternal health, such as changes in the number of women accessing healthcare services, reduction in travel time to healthcare facilities, and increase in healthcare workforce capacity.

6. Analyze the results: Analyze the simulation results to assess the effectiveness of the recommendations in improving access to maternal health. Evaluate the changes in the simulated variables and compare them to the baseline data to determine the potential impact of the recommendations.

7. Refine and iterate: Based on the analysis of the simulation results, refine the recommendations and simulation model if necessary. Repeat the simulation process to further assess the impact of the refined recommendations.

By following this methodology, policymakers and healthcare stakeholders can gain insights into the potential impact of recommendations on improving access to maternal health and make informed decisions on implementing effective interventions.

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