Infodemiological study on the impact of the COVID-19 pandemic on increased headache incidences at the world level
Notice bibliographique
Résumé
The analysis of the public interest as reflected by Internet queries has become a highly valuable tool in many fields. The Google Trends platform, providing timely and informative data, has become increasingly popular in health and medical studies. This study explores whether Internet search frequencies for the keyword "headache" have been increasing after the COVID-19 pandemic outbreak, which could signal an increased incidence of the health problem. Weekly search volume data for 5 years spanning February 2017 to February 2022 were sourced from Google Trends. Six statistical and machine-learning methods were implemented on training and testing sets via pre-set automated forecasting algorithms. Holt-Winters has been identified as overperforming in predicting web query trends through several accuracy measures and the DM test for forecasting superiority and has been employed for producing the baseline level in the estimation of excess query level over the first pandemic wave. Findings indicate that the COVID-19 pandemic resulted in an increased global incidence of headache (as proxied by related web queries) in the first 6 months after its outbreak, with an excess occurrence of 4.53% globally. However, the study also concludes that the increasing trend in headache incidence at the world level would have continued in the absence of the pandemic, but it has been accelerated by the pandemic event. Results further show mixed correlations at the country-level between COVID-19 infection rates and population web-search behavior, suggesting that the increased headache incidence is caused by pandemic-related factors (i.e. increased stress and mental health problems), rather than a direct effect of coronavirus infections. Other noteworthy findings entail that in the Philippines, the term "headache" was the most frequently searched term in the period spanning February 2020 to February 2022, indicating that headache occurrences are a significant aspect that defines population health at the country level. High relative interest is also detected in Kenya and South Africa after the pandemic outbreak. Additionally, research findings indicate that the relative interest has decreased in some countries (i.e. US, Canada, and Australia), whereas it has increased in others (i.e. India and Pakistan) after the pandemic outbreak. We conclude that observing Internet search habits can provide timely information for policymakers on collective health trends, as opposed to ex-post statistics, and can furthermore yield valuable information for the pain management drug market key players about aggregate consumer behavior.
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 | 0,011 | 0,007 |
| 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 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».