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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

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Projected spread models.

Jung-Chao Ban¹, Jyy-I Hong², Cheng-Yu Tsai¹

¹Department of Mathematical Sciences, National Chengchi University, Taipei, 11605, Taiwan, ROC.

Journal of Mathematical Biology

|June 26, 2025

Summary

This summary is machine-generated.

This study introduces a novel disease transmission model incorporating both explicit and hidden factors for improved infectious disease prediction and control. The projected spread model offers enhanced accuracy in forecasting disease dynamics.

Keywords:

Projected spread model Random spread model Spread rate Topological spread model

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Area of Science:

Mathematical modeling
Epidemiology
Infectious disease dynamics

Background:

Accurate prediction and control of infectious disease spread are critical public health challenges.
Previous models have limitations in capturing all factors influencing disease transmission.

Purpose of the Study:

To extend existing disease spread models to incorporate both explicit and non-explicit (hidden) factors.
To develop a projected spread model for more comprehensive disease transmission analysis.
To provide the spread rate for the projected spread model.

Main Methods:

Development of a novel disease transmission model integrating explicit and hidden factors.
Extension of prior spread models to a projected spread framework.
Analysis of spread rates using topological and random models.

Main Results:

The projected spread model effectively accounts for both explicit and hidden transmission factors.
Spread rates for the projected model were determined for topological and random scenarios.
Numerical examples and results validate the theoretical framework.

Conclusions:

The proposed model offers a more robust approach to understanding and managing infectious disease spread.
Incorporating non-explicit factors enhances the predictive power of disease transmission models.
The findings provide valuable insights for public health strategies and interventions.