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Early detection of emerging infectious diseases - implications for vaccine development.
Raina MacIntyre, C; Lim, Samsung; Gurdasani, Deepti; Miranda, Miguel; Metcalf, David; Quigley, Ashley; Hutchinson, Danielle; Burr, Allan; Heslop, David J.
Afiliación
  • Raina MacIntyre C; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia; College of Health Solutions and Watts College of Public Service and Community Services, Arizona State University, United States.
  • Lim S; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
  • Gurdasani D; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
  • Miranda M; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
  • Metcalf D; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
  • Quigley A; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
  • Hutchinson D; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia. Electronic address: dani.hutchinson@protonmail.com.
  • Burr A; The Biosecurity Program, Kirby Institute, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
  • Heslop DJ; The School of Population Health, Faculty of Medicine and Health Sciences, University of New South Wales, New South Wales, Australia.
Vaccine ; 42(7): 1826-1830, 2024 Mar 07.
Article en En | MEDLINE | ID: mdl-37271702
Vast quantities of open-source data from news reports, social media and other sources can be harnessed using artificial intelligence and machine learning, and utilised to generate valid early warning signals of emerging epidemics. Early warning signals from open-source data are not a replacement for traditional, validated disease surveillance, but provide a trigger for earlier investigation and diagnostics. This may yield earlier pathogen characterisation and genomic data, which can enable earlier vaccine development or deployment of vaccines. Early warning also provides a more feasible prospect of stamping out epidemics before they spread. There are several of such systems currently, but they are not used widely in public health practice, and only some are publicly available. Routine and widespread use of open-source intelligence, as well as training and capacity building in digital surveillance, will improve pandemic preparedness and early response capability.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Enfermedades Transmisibles Emergentes / Epidemias Tipo de estudio: Diagnostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Vaccine Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Enfermedades Transmisibles Emergentes / Epidemias Tipo de estudio: Diagnostic_studies / Screening_studies Límite: Humans Idioma: En Revista: Vaccine Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos