Using Surveillance Data to Estimate Infectious Disease Burden: Opportunities and Challenges.
The article discusses the estimation of infectious disease outbreaks via surveillance data as of 2025. Topics covered include the mechanics of an approach that generated a Bayesian hierarchical model with adjusted estimates from available data, and its applications, limitations and further developme...
| Publicado en: | American Journal of Public Health Vol. 115; no. 4; pp. 454 - 457 |
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| Autores principales: | , |
| Formato: | Artículo |
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American Public Health Association
Apr2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=183628276&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 183628276 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00900036 APH jtl: American Journal of Public Health issn: 00900036 maglogo: N pubinfo: dt: Apr2025 vid: 115 iid: 4 pid: 44 pub: American Public Health Association artinfo: ui: 183628276 10.2105/AJPH.2025.308023 ppf: 454 ppct: 3 formats: tig: atl: Using Surveillance Data to Estimate Infectious Disease Burden: Opportunities and Challenges. aug: au: Hochheiser, Harry Kumar, Praveen affil: Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA. Department of Health Policy and Management, School of Public Health, University of Pittsburgh, Pittsburgh, PA. su: United States Centers for Disease Control & Prevention (U.S.) Communicable diseases Public health surveillance Interprofessional relations Hospital care Influenza Epidemics Public health Global burden of disease sug: subj: Communicable diseases Public health surveillance Interprofessional relations Hospital care Influenza Epidemics Public health United States Centers for Disease Control & Prevention (U.S.) Administration of Public Health Programs Health and Welfare Funds Global burden of disease ab: The article discusses the estimation of infectious disease outbreaks via surveillance data as of 2025. Topics covered include the mechanics of an approach that generated a Bayesian hierarchical model with adjusted estimates from available data, and its applications, limitations and further development. Also noted is the need for open science practices with greater transparency and collaboration to help modelers inform responses to infectious disease outbreaks. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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