Reply to “Use of Prediction Models for Risk Analysis and Decision-Making in Public Health—The Catch-22 Conundrum”
Author:
Affiliation:
1. Singapore General Hospital, Singapore
2. Emerging Infectious Diseases Programme, Duke-NUS Medical School, Singapore
Publisher
Academy of Medicine, Singapore
Subject
General Medicine
Reference8 articles.
1. Kalimuddin S, Low JG, Ooi EE. Dengue disease modelling and forecasting: utility and limitations. Ann Acad Med Singapore 2016;45:121-2.
2. Reich NG, Lauer SA, Sakrejda K, Iamsirithaworn S, Hinjoy S, Suangtho P, et al. Challenges in real-time prediction of infectious disease: a case study of dengue in Thailand. PLoS Negl Trop Dis 2016;10:e0004761.
3. Ooi EE, Hart TJ, Tan HC, Chan SH. Dengue seroepidemiology in Singapore. Lancet 2001;357:685-6.
4. Ooi EE, Goh KT, Gubler DJ. Dengue prevention and 35 years of vector control in Singapore. Emerg Infect Dis 2006;12:887-93.
5. Egger JR, Ooi EE, Kelly DW, Woolhouse ME, Davies CR, Coleman PG. Reconstructing historical changes in the force of infection of dengue fever in Singapore: implications for surveillance and control. Bull World Health Organ 2008;86:187-96.
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