在各种简单的疾病模型中,感染人数的变化率可以写成
在哪里
I 是感染人数,S 是易感人群数量,
¹ 是人口总数,b 是疾病的传播率,m 是个体离开受感染群体的速度。
这里 IQ 表示 I 对时间的导数,我们将在整篇论文中使用此惯例。
方程 (1) 适用于多种单组模型。根据 Castillo-Chavez 等人 [3] 的观点,我们允许 b 成为 ¹ 的函数,从而允许对混合做出各种假设。根据模型的类型,人均移除率 m 可能包括“背景”死亡率或疾病引起的死亡率,或向免疫、易感或隔离区转变的速率。][1]
答案1
排版这个有什么问题?请澄清你的问题!你在哪里遇到问题?请使用如下的 MWE:
% arara: pdflatex
% arara: pdflatex
\documentclass{article}
\usepackage[english]{babel}
\usepackage{csquotes}
\usepackage{mathtools}
\begin{document}
In a wide variety of simple disease models, the rate of change in the number of
infected people can be written as
\begin{equation}\label{eq:1}
\dot{I}=\beta\frac{SI}{T}-mI=\biggl(\beta\frac{S}{T}-m\biggr)I,
\end{equation}
where $I$ is the number of infected people, $S$ is the number of susceptible people,
$T$ is the total number of people in the population, $\beta$ is the transmission rate
of the disease, and $m$ is the rate at which individuals leave the infected group.
Here $\dot{I}$ means the derivative of $I$ with respect to time, a convention we will
use throughout the paper. Equation \eqref{eq:1} is applicable to a wide variety of
one-group models. Following Ca\-stillo-Chavez et al.\ [3], we allow $b$ to be a
function of $T$, allowing a variety of assumptions about mixing. Depending on the type
of model, the per-capi\-ta removal rate, $m$, may include the rate of
\enquote{background} mortality or disease-induced mortality, or transitions to immune,
susceptible or quarantined compartments.
\end{document}