This paper is in the following e-collection/theme issue:

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Infodemiology and Infoveillance (1369) Information Retrieval (296) Information Seeking, Information Needs (481) Innovative Methods in Public Health and Surveillance (336)

Published on in Vol 7, No 5 (2021): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18593, first published .
Estimation of Asthma Symptom Onset Using Internet Search Queries: Lag-Time Series Analysis

Estimation of Asthma Symptom Onset Using Internet Search Queries: Lag-Time Series Analysis

Estimation of Asthma Symptom Onset Using Internet Search Queries: Lag-Time Series Analysis

Authors of this article:

Yulin Hswen1, 2 Author Orcid Image ;   Amanda Zhang3 Author Orcid Image ;   Bruno Ventelou2 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Sylvestre E, Cécilia-Joseph E, Bouzillé G, Najioullah F, Etienne M, Malouines F, Rosine J, Julié S, Cabié A, Cuggia M. The Role of Heterogenous Real-world Data for Dengue Surveillance in Martinique: Observational Retrospective Study. JMIR Public Health and Surveillance 2022;8(12):e37122 View
  2. Chai L, Wang Q, Si C, Gao W, Zhang L. Potential Association Between Changes in Microbiota Level and Lung Diseases: A Meta-Analysis. Frontiers in Medicine 2022;8 View
  3. Gabaldi C, Cypriano A, Pedrotti C, Malheiro D, Laselva C, Cendoroglo M, Teich V. Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?. einstein (São Paulo) 2024;22 View