Research Topic · Peer-Reviewed

Population Modeling

Population modeling is the use of mathematical and statistical methods to describe, analyze, and project how the size, structure, and composition of a population change over time under the influence of processes such as birth, death, growth, and movement between states. Models are built to represent the dynamics of …

Curated from this journal's research 📚 9 peer-reviewed articles cited Cited 17× across the literature 🔖 ISSN 2643-2811 🗓 Reviewed July 2026

Overview

Population modeling is the use of mathematical and statistical methods to describe, analyze, and project how the size, structure, and composition of a population change over time under the influence of processes such as birth, death, growth, and movement between states. Models are built to represent the dynamics of a system and to predict its future behavior, and they are commonly classified by structure: deterministic models, often expressed as difference or differential equations, describe expected trajectories, while stochastic models incorporate random variation and uncertainty. A major application is in epidemiology, where compartmental frameworks divide a population into states such as susceptible, infected, and recovered to study the transmission of disease, estimate key parameters, and evaluate the impact of interventions, as in the modeling of typhoid and other infectious-disease outbreaks. Related approaches couple population dynamics with genetics to study mutational processes and the interaction of populations. Building a useful model involves specifying governing relationships, estimating parameters from data, and analyzing equilibria, stability, and sensitivity to assumptions. Because such models inform public health decisions and the assessment of competing scenarios, validation against observed data and clear treatment of uncertainty are essential. As a quantitative tool for understanding change in populations, population modeling is central to model-based research across the biological, health, and social sciences.

Research published in this journal

9 peer-reviewed articles, ranked by relevance. Each links to its DOI.

How this research is being cited

The 9 articles above have been cited 17 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.

A sample of recent works citing this journal's research on Population Modeling, linking to each citing work.

Editorial oversight

Curated from peer-reviewed research published in Model Based Research (ISSN 2643-2811).

Journal editorial board
Yoshiaki Kikuchi · Japan Yung-Yao Chen · Taiwan Yang Chen · United States

This page summarises published research for orientation; it is not medical or professional advice.