Modeling zoonotic and vector-borne viruses

被引:0
|
作者
Judson, Seth D. [1 ]
Dowdy, David W. [2 ]
机构
[1] Johns Hopkins Univ, Sch Med, Dept Med, Div Infect Dis, Baltimore, MD 21218 USA
[2] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Div Infect Dis Epidemiol, Baltimore, MD USA
基金
美国国家卫生研究院;
关键词
INFECTIOUS-DISEASE; INFLUENZA-VIRUSES; TOOLS;
D O I
10.1016/j.coviro.2024.101428
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
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.
引用
收藏
页数:6
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