Abstract
Control of the 2002-2003 severe acute respiratory syndrome (SARS) outbreak was based on rapid diagnosis coupled with effective patient isolation. We used uncertainty and sensitivity analysis of the basic reproductive number R0 to assess the role that model parameters play in outbreak control. The transmission rate and isolation effectiveness have the largest fractional effect on R0. We estimated the distribution of the reproductive number R0 under perfect isolation conditions. The distribution lies in the interquartile range 0.19-1.08, with a median of 0.49. Even though the median of R0 is <1, we found that 25% of our R0 distribution lies at R0 > 1, even with perfect isolation. This implies the need to simultaneously apply more than one method of control.
Highlights
Control of the 2002–2003 severe acute respiratory syndrome (SARS) outbreak was based on rapid diagnosis coupled with effective patient isolation
94% of SARS cases occurred through transmission in hospital wards [6], and similar effects occurred in Hong Kong and Singapore [7]
Uncertainty Analysis for R0 The resulting R0 distribution lies in the interquartile range 0.43–2.41, with a median of 1.10
Summary
Control of the 2002–2003 severe acute respiratory syndrome (SARS) outbreak was based on rapid diagnosis coupled with effective patient isolation. Symptomatic persons in that study were hospitalized at a mean rate of 1/4.85 days–1. Those who recovered were discharged a mean of 23.5 days after diagnosis, while the mean period to death was 35.9 days after diagnosis. Because no specific treatment for SARS exists, control of the epidemic relied on rapid diagnosis and isolation of patients [1], an approach that is reported to be effective [4]. Control of an outbreak relies partly on identifying what disease parameters are likely to lead to a reduction in the reproduction number R0. We calculate the dependence of R0 on model parameters
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