SARS-CoV-2 Infections in a Triad of Primary School Learners (Grades 1-7), Their Parents, and Teachers in KwaZulu-Natal, South Africa: Protocol for a Cross-Sectional and Nested Case-Cohort Study
Bibliographic record
Abstract
BACKGROUND: In low- and middle-income countries (LMICs) such as South Africa, there is paucity of data on SARS-CoV-2 infections among children attending school, including seroprevalence and transmission dynamics. OBJECTIVE: This pilot study aims to assess (1) the prevalence of self-reported or confirmed SARS-CoV-2 prior infections, COVID-19 symptoms (including long COVID), seroprevalence of SARS-CoV-2 antibodies, and general/mental health, (2) longitudinal changes in SARS-CoV-2 seroprevalence, and (3) SARS-CoV-2 acute infections, immune responses, transmission dynamics, and symptomatic versus asymptomatic contacts in a unique cohort of unvaccinated primary school learners, their parents, teachers, and close contacts in semirural primary school settings. METHODS: Learners (grades 1-7) from primary schools in KwaZulu-Natal, South Africa, their parents, and teachers will be invited to enroll into the COVID kids school study (CoKiDSS). CoKiDSS comprises 3 parts: a cross-sectional survey (N=640), a follow-up survey (n=300), and a nested case-cohort substudy. Finger-prick blood and saliva samples will be collected for serological and future testing, respectively, in the cross-sectional (451 learners:147 parents:42 teachers) and follow-up (210 learners:70 parents:20 teachers) surveys. The nested case-cohort substudy will include cases from the cross-sectional survey with confirmed current SARS-CoV-2 infection (n=30) and their close contacts (n=up to 10 per infected participant). Finger-prick blood (from all substudy participants), venous blood (from cases), and nasal swabs (from cases and contacts) will be collected for serological testing, immunological testing, and viral genome sequencing, respectively. Questionnaires covering sociodemographic and general and mental health information, prior and current SARS-CoV-2 symptoms and testing information, vaccination status, preventative behavior, and lifestyle will be administered. Statistical methods will include generalized linear mixed models, intracluster correlation, descriptive analysis, and graphical techniques. RESULTS: A total of 645 participants were enrolled into the cross-sectional survey between May and August 2023. A subset of 300 participants were followed up in the follow-up survey in October 2023. Screening of the participants into the nested case-cohort substudy is planned between November 2023 and September 2024. Data cleanup and analysis for the cross-sectional survey is complete, while those for the follow-up survey and nested case substudy will be completed by the third quarter of 2024. The dissemination and publication of results is anticipated for the fourth quarter of 2024. CONCLUSIONS: This study provides data from an LMIC setting on the impact of SARS-CoV-2 on school-attending learners, their parents, and teachers 3 years after the SARS-CoV-2 pandemic was declared and 21-24 months after resumption of normal school attendance. In particular, this study will provide data on the prevalence of self-reported or confirmed SARS-CoV-2 prior infection, prior and current symptoms, seroprevalence, changes in seroprevalence, SARS-CoV-2 transmission, SARS-CoV-2 adaptive immune responses, and symptoms of long COVID and mental health among a triad of learners, their parents, and teachers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52713.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".