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第7行：
第7行： − + 第17行：
第17行： − 这些模型的起源于20世纪早期，其中克马克和麦克德里克1927年的著作意义重大。+ 第25行：
第25行： − 这些模型通常使用常微分方程(确定的) ，但也可以使用随机框架（任意的），这种框架更加现实，但分析起来要复杂得多。+ 第33行：
第33行： − 模型试图预测疾病的传播方式、感染总人数、流行病持续时间等，并估计各种流行病学参数，如生殖数量。这些模型可以显示不同的公共卫生干预措施对疫情结果的影响，例如，在指定人群中发放数量有限的疫苗时，最有效的技术是什么。+ 第45行：
第45行： − SIR 模型是最简单的'''<font color="#ff8000">传染病模型Compartmental models</font>'''之一，许多模型都是这种基本形式的衍生物。该模式由三个部分组成:+ 第51行：
第51行： − S：易感者。当一个易感者和一个感病者产生“传染性接触”时，易感者就会感染这种疾病，并被归入感病者。+ 第57行：
第57行： − I：感病者。这些人已经感染，并且有能力感染易感者。+ 第63行：
第63行： − R：康复者或病死者。这些人已经感染，或者已经从疾病中康复并被归入康复者，或者已经死亡。假定死亡人数与总人口相比微不足道。这种类别也可称为“康复者”或“抵抗者”。+ 第71行：
第71行： − 这个模型可以合理地预测传染病在人与人之间传播的情况，以及康复带来持久抵抗力的情况，如麻疹、腮腺炎和风疹等疾病。+ − + − Spatial SIR model simulation. Each cell can infect its eight immediate neighbors. − − 【图1：Spatial SIR model simulation. Each cell can infect its eight immediate neighbors.空间 SIR 模型仿真。每个细胞都能感染它的八个近邻。】
无编辑摘要
Compartmental models simplify the mathematical modelling of infectious diseases. The population is assigned to compartments with labels - for example, S, I, or R, (Susceptible, Infectious, or Recovered). People may progress between compartments. The order of the labels usually shows the flow patterns between the compartments; for example SEIS means susceptible, exposed, infectious, then susceptible again.
Compartmental models simplify the mathematical modelling of infectious diseases. The population is assigned to compartments with labels - for example, S, I, or R, (Susceptible, Infectious, or Recovered). People may progress between compartments. The order of the labels usually shows the flow patterns between the compartments; for example SEIS means susceptible, exposed, infectious, then susceptible again.
'''<font color="#ff8000">传染病模型Compartmental models</font>'''简化了传染病的数学模型。人口被划分到带有标签的类别，例如，S，I，或 R，(易感者，感病者，或康复者)。不同类别中的人数会发生变化。标签的顺序通常显示类别之间的流动模式，例如 SEIS模型意味着易感染成为暴露者、然后成为感病者，然后再次回到易感者。
'''<font color="#ff8000">房室模型Compartmental models</font>'''简化了传染病传播的数学模型。人群被划分为带有标签的类别，例如，S，I，和 R，(易感者，染病者和康复者)。不同类别人群的标签会发生变化。标签的变化反映了不同类别人群之间的转化模式，例如SEIS模型代表易感者类型可以转变为暴露者类型、暴露者类型可以转变为染病者类型，染病者类型可以再次转变回易感者类型。
==[[用户:Agnes|Agnes]]（[[用户讨论:Agnes|讨论]]）[翻译]译者知识水平限制，通过多方查询资料对传染病模型有了基本了解之后，在“SEIS means susceptible, exposed, infectious, then susceptible again”的翻译中，选择增添了一些成分，但此部分的翻译仍然存疑
==[[用户:Agnes|Agnes]]（[[用户讨论:Agnes|讨论]]）[翻译]译者知识水平限制，通过多方查询资料对传染病模型有了基本了解之后，在“SEIS means susceptible, exposed, infectious, then susceptible again”的翻译中，选择增添了一些成分，但此部分的翻译仍然存疑
The origin of such models is the early 20th century, with an important work being that of Kermack and McKendrick in 1927.
The origin of such models is the early 20th century, with an important work being that of Kermack and McKendrick in 1927.
这类模型起源于20世纪初，克马克和麦克德里克在1927年的一项重要工作。
The models are most often run with ordinary differential equations (which are deterministic), but can also be used with a stochastic (random) framework, which is more realistic but much more complicated to analyze.
The models are most often run with ordinary differential equations (which are deterministic), but can also be used with a stochastic (random) framework, which is more realistic but much more complicated to analyze.
这些模型通常使用确定参数的常微分方程进行分析，但也可以使用具有随机参数的随机框架进行分析，这种随机框架更加贴近现实，但分析起来要复杂得多。
Models try to predict things such as how a disease spreads, or the total number infected, or the duration of an epidemic, and to estimate various epidemiological parameters such as the reproductive number. Such models can show how different public health interventions may affect the outcome of the epidemic, e.g., what the most efficient technique is for issuing a limited number of vaccines in a given population.
Models try to predict things such as how a disease spreads, or the total number infected, or the duration of an epidemic, and to estimate various epidemiological parameters such as the reproductive number. Such models can show how different public health interventions may affect the outcome of the epidemic, e.g., what the most efficient technique is for issuing a limited number of vaccines in a given population.
模型试图预测疾病的传播方式、感染总人数、流行病持续时间等，并估计各种流行病学参数，如再生数。这些模型可以显示不同的公共卫生干预措施如何对疾病传播产生影响，例如，控制疾病传播最有效的方式是在指定人群中发放数量有限的疫苗。
The SIR model is one of the simplest compartmental models, and many models are derivatives of this basic form. The model consists of three compartments:
The SIR model is one of the simplest compartmental models, and many models are derivatives of this basic form. The model consists of three compartments:
'''<font color="#ff8000">SIR 模型</font>'''是最简单的房室模型之一，许多模型都是这种基本模型的衍生物。该模型由三种类型的人群组成:
:'''S''': The number of '''s'''usceptible individuals. When a susceptible and an infectious individual come into "infectious contact", the susceptible individual contracts the disease and transitions to the infectious compartment.
:'''S''': The number of '''s'''usceptible individuals. When a susceptible and an infectious individual come into "infectious contact", the susceptible individual contracts the disease and transitions to the infectious compartment.
S: The number of susceptible individuals. When a susceptible and an infectious individual come into "infectious contact", the susceptible individual contracts the disease and transitions to the infectious compartment.
S: The number of susceptible individuals. When a susceptible and an infectious individual come into "infectious contact", the susceptible individual contracts the disease and transitions to the infectious compartment.
S：易感者。当一个易感者和一个感病者产生“传染性接触”时，易感者就会感染这种疾病，并被归入染病者类别。
:'''I''': The number of '''i'''nfectious individuals. These are individuals who have been infected and are capable of infecting susceptible individuals.
:'''I''': The number of '''i'''nfectious individuals. These are individuals who have been infected and are capable of infecting susceptible individuals.
I: The number of infectious individuals. These are individuals who have been infected and are capable of infecting susceptible individuals.
I: The number of infectious individuals. These are individuals who have been infected and are capable of infecting susceptible individuals.
I：染病者。这类人群已经感染疾病，并且有能力感染易感者。
:'''R''' for the number of '''r'''emoved (and immune) or deceased individuals. These are individuals who have been infected and have either recovered from the disease and entered the removed compartment, or died. It is assumed that the number of deaths is negligible with respect to the total population. This compartment may also be called "'''r'''ecovered" or "'''r'''esistant".
:'''R''' for the number of '''r'''emoved (and immune) or deceased individuals. These are individuals who have been infected and have either recovered from the disease and entered the removed compartment, or died. It is assumed that the number of deaths is negligible with respect to the total population. This compartment may also be called "'''r'''ecovered" or "'''r'''esistant".
R: for the number of removed (and immune) or deceased individuals. These are individuals who have been infected and have either recovered from the disease and entered the removed compartment, or died. It is assumed that the number of deaths is negligible with respect to the total population. This compartment may also be called "recovered" or "resistant".
R: for the number of removed (and immune) or deceased individuals. These are individuals who have been infected and have either recovered from the disease and entered the removed compartment, or died. It is assumed that the number of deaths is negligible with respect to the total population. This compartment may also be called "recovered" or "resistant".
R：康复者或病死者。这些人已经被感染过，并且已经从疾病中康复并被归入康复者类别，或者已经因感染疾病死亡。假如死亡数量与总人口数量相比可以忽略不计，这种类别人群也可称为“康复者”或“抵抗者”。
This model is reasonably predictive for infectious diseases that are transmitted from human to human, and where recovery confers lasting resistance, such as measles, mumps and rubella.
This model is reasonably predictive for infectious diseases that are transmitted from human to human, and where recovery confers lasting resistance, such as measles, mumps and rubella.
这个模型可以合理地预测传染病在人与人之间传播的情况，以及康复后会产生持续性抗体的疾病，如麻疹、腮腺炎和风疹等疾病。
[[File:SIR model simulated using python.gif|thumb|Spatial SIR model simulation. Each cell can infect its eight immediate neighbors.]]
[[File:SIR model simulated using python.gif|thumb|图1：Spatial SIR model simulation. Each cell can infect its eight immediate neighbors.空间 SIR 模型仿真。每个单元都能感染它的八个相邻单元。]]