Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020
Abstract
1. Introduction
2. Methods
2.1. Model
2.2. Sensitivity of the Basic Reproduction Number
2.3. Estimation of the Infection Rate
3. Results
3.1. Peak Prediction
3.2. Possible Effect of Intervention
4. Discussion
- The essential epidemic size, which is characterized by , would not be affected by the identification rate p in a realistic parameter range –, in particular, .
- The intervention exactly has a positive effect on the delay of the epidemic peak, which would contribute to improve the medical environment utilizing the extra time period.
- Intervention over a relatively long period is needed to effectively reduce the final epidemic size.
Funding
Acknowledgments
Conflicts of Interest
References
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Week | Number of Newly Reported Cases | Number of Accumulated Cases |
---|---|---|
12 January–18 January | 1 | 1 |
19 January–25 January | 2 | 3 |
26 January–1 February | 14 | 17 |
2 February–8 February | 8 | 25 |
9 February–16 February | 28 | 53 |
17 February–23 February | 79 | 132 |
24 February–1 March | 107 | 239 |
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Kuniya, T. Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020. J. Clin. Med. 2020, 9, 789. https://doi.org/10.3390/jcm9030789
Kuniya T. Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020. Journal of Clinical Medicine. 2020; 9(3):789. https://doi.org/10.3390/jcm9030789
Chicago/Turabian StyleKuniya, Toshikazu. 2020. "Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020" Journal of Clinical Medicine 9, no. 3: 789. https://doi.org/10.3390/jcm9030789
APA StyleKuniya, T. (2020). Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020. Journal of Clinical Medicine, 9(3), 789. https://doi.org/10.3390/jcm9030789