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Volume 10, Number 8—August 2004

Letter

Estimating SARS Incubation Period

Suggested citation for this article

Figure 1

Thumbnail of Simulation of frequency distribution of incubation period of severe acute respiratory syndrome. Data used for this simulation were obtained from Canada, Hong Kong, and the United States, for a total sample size of 19. Many of the patients included in the database had multiple possible incubation periods (see Table), resulting in the confidence intervals displayed for each day.

Figure 1. Simulation of frequency distribution of incubation period of severe acute respiratory syndrome. Data used for this simulation were obtained from Canada, Hong Kong, and the United States, for a total sample...

Figure 2

Thumbnail of Simulation of frequency distribution of incubation period of severe acute respiratory syndrome. Data used for this simulation were obtained from Canada, Hong Kong, and the United States, for a total sample size of 19. Many of the patients included in the database had multiple possible incubation periods (see Table), resulting in the confidence intervals displayed for each day.

Figure 2. Cumulative frequency incubation period of severe acute respiratory syndrome. Data are the mean frequencies of each individual incubation period, as shown in Figure 1. Data used for this...

In reply: Drs. Wong and Tam (1) are correct in stating that their method of calculating mean frequencies of possible incubation periods for patients with severe acute respiratory syndrome (SARS) is simpler than the method that I presented (2). However, their method cannot replicate the confidence intervals shown in Figure 1 in my article. These researchers can only replicate Figure 2 in my article, which shows the cumulative distribution of the mean frequencies of individual incubation periods.

The comparative complexity of my method provides data that are essential for making public health decisions. For example, public health officials need to know incubation periods to determine appropriate periods of quarantine and isolation and how long to conduct intensive (and expensive) surveillance after the last clinical case has been reported. To reduce costs and to enhance public support, public health officials may keep quarantine and isolation periods to a minimum. They also need to know the risk for failure of such interventions attributable to patients with relatively long incubation periods. Both Figure 2 in my article and Drs. Wong and Tam’s data show that approximately 95% of the mean incubation period will be <12 days (i.e., 5% will incubate for 13 to 18 days). By summing the 95th percentiles for days 13 through 18 from my Figure 1, it can be seen that <30% of patients will have incubation periods >12 days (the actual probability of any given percentage incubating for >12 days can be easily calculated by using the spreadsheet which is an appendix to my article). Public health officials need to understand the degree of variability associated with any data used to make public health policies. Sole reliance on the mean incubation periods (or mean frequencies) will hide more than is shown, which increases the probability of failed public health interventions.

Martin I. Meltzer*Comments to Author 
Author affiliation: *Centers for Disease Control and Prevention, Atlanta, Georgia, USA

References

  1. Wong TW, Tam W. Estimating SARS incubation period [letter]. Emerg Infect Dis. 2004;10:15034.PubMed
  2. Meltzer MI. Multiple contact dates and SARS incubation periods. Emerg Infect Dis. 2004;10:2079.PubMed

Figures

Suggested citation for this article: Meltzer MI. SARS incubation periods: author response [letter]. Emerg Infect Dis [serial on the Internet]. 2004 Aug [date cited]. Available from: http://wwwnc.cdc.gov/eid/article/10/8/04-0427

DOI: 10.3201/eid1008.040427

Related Links

Table of Contents – Volume 10, Number 8—August 2004

Comments to the Authors

Please use the form below to submit correspondence to the authors or contact them at the following address:

Martin I. Meltzer, Centers for Disease Control and Prevention, 1600 Clifton Road, Mailstop D59, Atlanta, GA 30333, USA; fax: 404-371-5445

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