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Modeling zoonotic and vector-borne viruses.
Judson, Seth D; Dowdy, David W.
Affiliation
  • Judson SD; Division of Infectious Diseases, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. Electronic address: sjudson4@jh.edu.
  • Dowdy DW; Division of Infectious Disease Epidemiology, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Curr Opin Virol ; 67: 101428, 2024 Aug.
Article in En | MEDLINE | ID: mdl-39047313
ABSTRACT
The 2013-2016 Ebola virus disease epidemic and the coronavirus disease 2019 pandemic galvanized tremendous growth in models for emerging zoonotic and vector-borne viruses. Therefore, we have reviewed the main goals and methods of models to guide scientists and decision-makers. The elements of models for emerging viruses vary across spectrums from understanding the past to forecasting the future, using data across space and time, and using statistical versus mechanistic methods. Hybrid/ensemble models and artificial intelligence offer new opportunities for modeling. Despite this progress, challenges remain in translating models into actionable decisions, particularly in areas at highest risk for viral disease outbreaks. To address this issue, we must identify gaps in models for specific viruses, strengthen validation, and involve policymakers in model development.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Zoonoses Limits: Animals / Humans Language: En Journal: Curr Opin Virol / Current opinion in virology (Online) Year: 2024 Document type: Article Country of publication: Países Bajos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Zoonoses Limits: Animals / Humans Language: En Journal: Curr Opin Virol / Current opinion in virology (Online) Year: 2024 Document type: Article Country of publication: Países Bajos