本頁只刊出中文翻譯與中文說明；英文原文請見下方原文連結。
原文連結
論文資訊
- 類型：已發表論文
- 日期：2020-04-02
摘要
I employ a simple 數學 model of an 流行病學c process to evaluate how three basic quantities: the reproduction number (R), the number of infectious individuals (I), and total community size (N) affect strategies to control COVID-19. Numerical simulations show that strict suppression measures at the beginning of an 流行病學c can create low infectious numbers, which thereafter can be managed by mitigation measures over longer periods to flatten the 流行病學c curve. The stronger the suppression measure, the faster it achieves the low levels of exposed and infectious numbers that are conducive to subsequent management. Our results point to a two-step control strategy that begins with some level of confinement to reduce R below 1, followed by sufficient mitigation measures that manage the 流行病學c by maintaining
※ 此為已發表論文，全文需透過期刊付費取得