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Bayes' Theorem imposes inevitable limitations on the accuracy of screening tests by tying the test's predictive value to the disease prevalence. The aforementioned limitation is independent of the adequacy and make-up of the test and thus…

Methodology · Statistics 2021-09-15 Jacques Balayla

Bayes' Theorem confers inherent limitations on the accuracy of screening tests as a function of disease prevalence. We have shown in previous work that a testing system can tolerate significant drops in prevalence, up until a certain…

Methodology · Statistics 2020-09-01 Jacques Balayla

The relationship between a screening tests' positive predictive value, $\rho$, and its target prevalence, $\phi$, is proportional - though not linear in all but a special case. In consequence, there is a point of local extrema of curvature…

Methodology · Statistics 2021-08-03 Jacques Balayla

Using Bayes' Theorem, we derive generalized equations to determine the positive and negative predictive value of screening tests undertaken sequentially. Where a is the sensitivity, b is the specificity, $\phi$ is the pre-test probability,…

Methodology · Statistics 2020-07-28 Jacques Balayla

From the fundamental theorem of screening (FTS) we obtain the following mathematical relationship relaying the pre-test probability of disease $\phi$ to the positive predictive value $\rho(\phi)$ of a screening test:…

Methodology · Statistics 2021-10-12 Jacques Balayla

We consider state and parameter estimation for compartmental models having both time-varying and time-invariant parameters. Though the described Bayesian computational framework is general, we look at a specific application to the…

Computational Engineering, Finance, and Science · Computer Science 2023-11-07 Brandon Robinson , Philippe Bisaillon , Jodi D. Edwards , Tetyana Kendzerska , Mohammad Khalil , Dominique Poirel , Abhijit Sarkar

Two factors that are often ignored but could play a crucial role in the progression of an infectious disease are the distributions of inherent susceptibility ($\sigma_{inh}$) and external infectivity ($\iota_{ext}$), in a given population.…

Populations and Evolution · Quantitative Biology 2021-01-01 Saumyak Mukherjee , Sayantan Mondal , Biman Bagchi

The SIR model is used extensively in the field of epidemiology, in particular, for the analysis of communal diseases. One problem with SIR and other existing models is that they are tailored to random or Erdos type networks since they do…

Social and Information Networks · Computer Science 2014-10-22 M. S. S. Khan

Many disease models focus on characterizing the underlying transmission mechanism but make simple, possibly naive assumptions about how infections are reported. In this note, we use a simple deterministic Susceptible-Infected-Removed (SIR)…

Populations and Evolution · Quantitative Biology 2019-11-28 Sang Woo Park , Benjamin M. Bolker

The infection dynamics of a population under stationary isolation conditions is modeled. It is underlined that the stationary character of the isolation measures can be expected to imply that an effective SIR model with constant parameters…

Populations and Evolution · Quantitative Biology 2021-10-19 Alejandro Cabo Montes de Oca , Nana Geraldine Cabo Bizet

We prove that, for Poisson transmission and recovery processes, the classic Susceptible $\to$ Infected $\to$ Recovered (SIR) epidemic model of Kermack and McKendrick provides, for any given time $t>0$, a strict lower bound on the expected…

Populations and Evolution · Quantitative Biology 2017-02-13 Robert R. Wilkinson , Frank G. Ball , Kieran J. Sharkey

This article is devoted to the analysis of a particle system model for epidemics among a finite population with susceptible, infective and removed individuals (SIR). The infection mechanism depends on the relative distance between…

Probability · Mathematics 2020-03-10 Monia Capanna

Dynamic properties of spreading infection through a heterogeneous population are studied numerically and analytically using a dynamic variant of Watts and Strogatz Small World Network-based stochastic Susceptible-Exposed-Infectious-Removed…

Populations and Evolution · Quantitative Biology 2019-06-28 O. Mosbah , N. Zekri , M. Mokhtari , S. Sahraoui

Bayesian methods have received increasing attention in medical research, where sensitivity analysis of prior distributions is essential. Such analyses typically require the evaluation of the posterior distribution of a parameter under…

Methodology · Statistics 2025-10-14 Tomohiro Ohigashi , Shonosuke Sugasawa

Throughout human history, epidemics have been a constant presence. Understanding their dynamics is essential to predict scenarios and make substantiated decisions. Mathematical models are powerful tools to describe an epidemic behavior.…

Systems and Control · Electrical Eng. & Systems 2024-07-26 Walter HMendes aselein , Diego Eckhard

The SIR model is a three-compartment model of the time development of an epidemic. After normalizing the dependent variables, the model is a system of two non-linear differential equations for the susceptible proportion $S$ and the infected…

Dynamical Systems · Mathematics 2021-04-27 William G. Faris

Fractional-order SIR models have become increasingly popular in the literature in recent years, however unlike the standard SIR model, they often lack a derivation from an underlying stochastic process. Here we derive a fractional-order…

Populations and Evolution · Quantitative Biology 2016-03-31 Christopher N Angstmann , Bruce I Henry , Anna V McGann

HIV pre-exposure Prophylaxis (PrEP) has become essential for global HIV control, but its implementation coincides with rising bacterial STI rates among men who have sex with men (MSM). While risk-compensation behavioral changes like reduced…

We consider the Susceptible-Infected-Recovered (SIR) epidemic model on a Euclidean network in one dimension in which nodes at a distance $l$ are connected with probability $P(l) \propto l^{-\delta}$ in addition to nearest neighbors. The…

Physics and Society · Physics 2014-07-04 Abdul Khaleque , Parongama Sen

The susceptible-infected-recovered (SIR) model and its variants form the foundation of our understanding of the spread of diseases. Here, each agent can be in one of three states (susceptible, infected, or recovered), and transitions…

Disordered Systems and Neural Networks · Physics 2023-12-25 Claudia Merger , Jasper Albers , Carsten Honerkamp , Moritz Helias
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