The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
SARS outbreaks in Ontario, Hong Kong and Singapore: the role of diagnosis and isolation as a control mechanism
Open accessAbstract
In this article we use global and regional data from the SARS epidemic in conjunction with a model of susceptible, exposed, infective, diagnosed, and recovered classes of people (“SEIJR”) to extract average properties and rate constants for those populations. The model is fitted to data from the Ontario (Toronto) in Canada, Hong Kong in China and Singapore outbreaks and predictions are made based on various assumptions and observations, including the current effect of isolating individuals diagnosed with SARS. The epidemic dynamics for Hong Kong and Singapore appear to be different from the dynamics in Toronto, Ontario. Toronto shows a very rapid increase in the number of cases between March 31st and April 6th, followed by a significant slowing in the number of new cases. We explain this as the result of an increase in the diagnostic rate and in the effectiveness of patient isolation after March 26th. Our best estimates are consistent with SARS eventually being contained in Toronto, although the time of containment is sensitive to the parameters in our model. It is shown that despite the empirically modeled heterogeneity in transmission, SARS’ average reproductive number is 1.2, a value quite similar to that computed for some strains of influenza (J. Math. Biol. 27 (1989) 233). Although it would not be surprising to see levels of SARS infection higher than 10% in some regions of the world (if unchecked), lack of data and the observed heterogeneity and sensitivity of parameters prevent us from predicting the long-term impact of SARS. The possibility that 10 or more percent of the world population at risk could eventually be infected with the virus in conjunction with a mortality rate of 3–7% or more, and indications of significant improvement in Toronto support the stringent measures that have been taken to isolate diagnosed cases.
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Cites
Identification of a novel coronavirus in patients with severe acute respiratory syndrome
Drosten, C., Günther, S., Preiser, W., van der Werf, S., Brodt, H.-R., Becker, S., Rabenau, H., Panning, M., Kolesnikova, L., Fouchier, R. A. M., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa030747 · Cited by 4,574
Cited by
Network theory and SARS: predicting outbreak diversity
Meyers, L. A., Pourbohloul, B., Newman, M. E. J., Skowronski, D. M., & Brunham, R. C. (2005) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2004.07.026 · Cited by 705
A Simulation of a COVID-19 Epidemic Based on a Deterministic SEIR Model
Carcione, J. M., Santos, J. E., Bagaini, C., & Ba, J. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2020.00230 · Cited by 365
Media/Psychological Impact on Multiple Outbreaks of Emerging Infectious Diseases
Liu, R., Wu, J., & Zhu, H. (2007) · Computational and Mathematical Methods in Medicine · doi:10.1080/17486700701425870 · Cited by 304
Morgenstern, C., Rawson, T., Routledge, I., Kont, M., Imai-Eaton, N., Skarp, J., Doohan, P., McCain, K., Johnson, R., Unwin, H. J. T., et al. (2025) · The Lancet Microbe · doi:10.1016/j.lanmic.2025.101144 · Cited by 6
Metadata
- Authors
- Chowell, G., Fenimore, P. W., Castillo-Garsow, M. A., & Castillo-Chavez, C.
- Venue
- Journal of Theoretical Biology
- Publisher
- Elsevier BV
- Published
- 2003-09
- Volume
- 224
- Issue
- 1
- Pages
- 1-8
- ISSN
- 0022-5193 (ISSN-L)
- OpenAlex
- W2037677991
- Cited by
- 292
- References
- 1
- FWCI
- 19.78
- Type
- journal article
- Language
- en
- Open access
- green
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- Chowell, G., Fenimore, P. W., Castillo-Garsow, M. A., & Castillo-Chavez, C. (2003). SARS outbreaks in Ontario, Hong Kong and Singapore: the role of diagnosis and isolation as a control mechanism. Journal of Theoretical Biology. https://doi.org/10.1016/s0022-5193(03)00228-5
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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