第447行: |
第447行: |
| | | |
| ====Pandemic analysis==== | | ====Pandemic analysis==== |
| + | 流行病分析 |
| + | |
| The [[SIR model]] is one of the most well known algorithms on predicting the spread of global pandemics within an infectious population. | | The [[SIR model]] is one of the most well known algorithms on predicting the spread of global pandemics within an infectious population. |
| + | |
| + | The SIR model is one of the most well known algorithms on predicting the spread of global pandemics within an infectious population. |
| + | |
| + | SIR模型是预测全球传染病在感染人群中传播的最著名的算法之一。 |
| | | |
| =====Susceptible to infected===== | | =====Susceptible to infected===== |
| + | |
| + | 易感人群 |
| + | |
| : <math>S = \beta\left(\frac 1 N \right)</math> | | : <math>S = \beta\left(\frac 1 N \right)</math> |
| | | |
| The formula above describes the "force" of infection for each susceptible unit in an infectious population, where {{math|β}} is equivalent to the transmission rate of said disease. | | The formula above describes the "force" of infection for each susceptible unit in an infectious population, where {{math|β}} is equivalent to the transmission rate of said disease. |
| + | |
| + | 这个公式描述的是人群中每个易感单元的感染“力”,其中 {{math|β}} 代表的是疾病的传播概率。 |
| | | |
| To track the change of those susceptible in an infectious population: | | To track the change of those susceptible in an infectious population: |
| + | 跟踪人群中易感人数随时间的变化: |
| | | |
| : <math>\Delta S = \beta \times S {1\over N} \, \Delta t</math> | | : <math>\Delta S = \beta \times S {1\over N} \, \Delta t</math> |
| | | |
| =====Infected to recovered===== | | =====Infected to recovered===== |
− | | + | 感染到康复 |
| : <math>\Delta I = \mu I \, \Delta t</math> | | : <math>\Delta I = \mu I \, \Delta t</math> |
| | | |
| Over time, the number of those infected fluctuates by: the specified rate of recovery, represented by <math>\mu</math> but deducted to one over the average infectious period <math>{1\over \tau}</math>, the numbered of infectious individuals, <math>I</math>, and the change in time, <math>\Delta t</math>. | | Over time, the number of those infected fluctuates by: the specified rate of recovery, represented by <math>\mu</math> but deducted to one over the average infectious period <math>{1\over \tau}</math>, the numbered of infectious individuals, <math>I</math>, and the change in time, <math>\Delta t</math>. |
| + | |
| + | 随着时间的推移,感染人数的波动幅度为: 以<math>\mu</math>来表示特定的恢复率,移除的平均感染期记为<math>{1\over \tau}</math>,感染个体的数量 <math>I</math>,以及时间的变化<math>\Delta t</math>。 |
| + | |
| | | |
| =====Infectious period===== | | =====Infectious period===== |
| + | 感染时期 |
| + | |
| Whether a population will be overcome by a pandemic, with regards to the SIR model, is dependent on the value of <math>R_0</math> or the "average people infected by an infected individual." | | Whether a population will be overcome by a pandemic, with regards to the SIR model, is dependent on the value of <math>R_0</math> or the "average people infected by an infected individual." |
| + | 就 SIR 模型而言,被流行病感染的人口数量,取决于数学<math>R_0</math>基本传染数的数值,是指被感染个体能感染普通人群的人数。比如<math>R_0 = 3</math>,意味着一个感染者平均感染3个未感染者。 |
| | | |
| : <math>R_0 = \beta\tau = {\beta\over\mu}</math> | | : <math>R_0 = \beta\tau = {\beta\over\mu}</math> |