The value of infectious disease modeling and trend assessment: a public health perspective

Author(s):  
Cheng Ding ◽  
Xiaoxiao Liu ◽  
Shigui Yang
2017 ◽  
Vol 23 (5) ◽  
Author(s):  
David J. Muscatello ◽  
Abrar A. Chughtai ◽  
Anita Heywood ◽  
Lauren M. Gardner ◽  
David J. Heslop ◽  
...  

2022 ◽  
Vol 43 (1) ◽  
Author(s):  
Anna Bershteyn ◽  
Hae-Young Kim ◽  
R. Scott Braithwaite

Infectious disease transmission is a nonlinear process with complex, sometimes unintuitive dynamics. Modeling can transform information about a disease process and its parameters into quantitative projections that help decision makers compare public health response options. However, modelers face methodologic challenges, data challenges, and communication challenges, which are exacerbated under the time constraints of a public health emergency. We review methods, applications, challenges and opportunities for real-time infectious disease modeling during public health emergencies, with examples drawn from the two deadliest pandemics in recent history: HIV/AIDS and coronavirus disease 2019 (COVID-19). Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.


2005 ◽  
Vol 161 (11) ◽  
pp. 997-998 ◽  
Author(s):  
M. Elizabeth Halloran ◽  
Marc Lipsitch

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