The Importance of Incorporating At-Home Testing Into SARS-CoV-2 Point Prevalence Estimates: Findings From a US National Cohort, February 2022
Notice bibliographique
Résumé
BACKGROUND: Passive, case-based surveillance underestimates the true extent of active infections in the population due to undiagnosed and untested cases, the exclusion of probable cases diagnosed point-of-care rapid antigen tests, and the exclusive use of at-home rapid tests which are not reported as part of case-based surveillance. The extent in which COVID-19 surveillance may be underestimating the burden of infection is likely due to time-varying factors such as decreased test-seeking behaviors and increased access to and availability of at-home testing. OBJECTIVE: The objective of this study is to estimate the prevalence of SARS-CoV-2 based on different definitions of a case to ascertain the extent to which cases of SARS-CoV-2 may be underestimated by case-based surveillance. METHODS: A survey on COVID-19 exposure, infection, and testing was administered to calculate point prevalence of SARS-CoV-2 among a diverse sample of cohort adults from February 8, 2022, to February 22, 2022. Three-point prevalence estimates were calculated among the cohort, as follows: (1) proportion positives based on polymerase chain reaction (PCR) and rapid antigen tests; (2) proportion positives based on testing exclusively with rapid at-home tests; and (3) proportion of probable undiagnosed cases. Test positivity and prevalence differences across booster status were also examined. RESULTS: Among a cohort of 4328, there were a total of 644 (14.9%) cases. The point prevalence estimate based on PCR or rapid antigen tests was 5.5% (95% CI 4.8%-6.2%), 3.7% (95% CI 3.1%-4.2%) based on at-home rapid tests, and 5.7% (95% CI 5.0%-6.4%) based on the case definition of a probable case. The total point prevalence across all definitions was 14.9% (95% CI 13.8%-16.0%). The percent positivity among PCR or rapid tests was 50.2%. No statistically significant differences were observed in prevalence between participants with a COVID-19 booster compared to fully vaccinated and nonboosted participants except among exclusive at-home rapid testers. CONCLUSIONS: Our findings suggest a substantial number of cases were missed by case-based surveillance systems during the Omicron B.1.1.529 surge, when at-home testing was common. Point prevalence surveys may be a rapid tool to be used to understand SARS-CoV-2 prevalence and would be especially important during case surges to measure the scope and spread of active infections in the population.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».