Department Environmental Science, Policy and Management, University of California, Berkeley, 94720, CA, USA.
School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, Durban, 4000, South Africa.
BMC Med Educ. 2022 Aug 20;22(1):632. doi: 10.1186/s12909-022-03674-3.
An understanding of epidemiological dynamics, once confined to mathematical epidemiologists and applied mathematicians, can be disseminated to a non-mathematical community of health care professionals and applied biologists through simple-to-use simulation applications. We used Numerus Model Builder RAMP (Runtime Alterable Model Platform) technology, to construct deterministic and stochastic versions of compartmental SIR (Susceptible, Infectious, Recovered with immunity) models as simple-to-use, freely available, epidemic simulation application programs.
We take the reader through simulations used to demonstrate the following concepts: 1) disease prevalence curves of unmitigated outbreaks have a single peak and result in epidemics that 'burn' through the population to become extinguished when the proportion of the susceptible population drops below a critical level; 2) if immunity in recovered individuals wanes sufficiently fast then the disease persists indefinitely as an endemic state, with possible dampening oscillations following the initial outbreak phase; 3) the steepness and initial peak of the prevalence curve are influenced by the basic reproductive value R, which must exceed 1 for an epidemic to occur; 4) the probability that a single infectious individual in a closed population (i.e. no migration) gives rise to an epidemic increases with the value of R>1; 5) behavior that adaptively decreases the contact rate among individuals with increasing prevalence has major effects on the prevalence curve including dramatic flattening of the prevalence curve along with the generation of multiple prevalence peaks; 6) the impacts of treatment are complicated to model because they effect multiple processes including transmission, recovery and mortality; 7) the impacts of vaccination policies, constrained by a fixed number of vaccination regimens and by the rate and timing of delivery, are crucially important to maximizing the ability of vaccination programs to reduce mortality.
Our presentation makes transparent the key assumptions underlying SIR epidemic models. Our RAMP simulators are meant to augment rather than replace classroom material when teaching epidemiological dynamics. They are sufficiently versatile to be used by students to address a range of research questions for term papers and even dissertations.
对流行病学动态的理解,曾经局限于数学流行病学家和应用数学家,现在可以通过易于使用的模拟应用程序传播到非数学的医疗保健专业人员和应用生物学家群体中。我们使用 Numerus Model Builder RAMP(运行时可更改的模型平台)技术,构建了确定性和随机性的 SIR(易感者、感染者、具有免疫力的恢复者) compartment 模型,作为简单易用、免费提供的流行模拟应用程序。
我们引导读者进行模拟,以演示以下概念:1)未减轻的暴发的疾病流行曲线有一个单一的高峰,导致流行在易感人群比例降至临界水平以下时就会熄灭;2)如果恢复期个体的免疫力迅速下降,那么疾病将无限期地持续存在,成为地方性状态,可能会在初始暴发阶段后出现衰减波动;3)陡峭程度和初始流行曲线高峰受基本繁殖值 R 的影响,R 必须大于 1 才能发生流行;4)在封闭种群(即无迁移)中,单个传染性个体引发流行的概率随着 R>1 而增加;5)随着流行率的增加而自适应地降低个体之间接触率的行为对流行曲线有重大影响,包括流行曲线的显著变平以及多个流行高峰的产生;6)治疗的影响难以建模,因为它们会影响包括传播、恢复和死亡率在内的多个过程;7)疫苗接种政策的影响受到固定数量的疫苗接种方案以及交付速度和时间的限制,对于最大限度地提高疫苗接种计划降低死亡率的能力至关重要。
我们的介绍使 SIR 流行模型的关键假设变得透明。我们的 RAMP 模拟器旨在补充而不是替代课堂材料,以教授流行病学动态。它们足够灵活,可供学生用于解决一系列研究问题,甚至是学期论文和论文。