Mathematical modeling and analysis of social and ecological determinants for the dynamics of infectious diseases and public health policies

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Guest Editors

Dr. Wandi Ding
Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN, 37132, USA
Email: wding@mtsu.edu

Dr. Yun Kang
College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ 85212, USA
Email: yun.kang@asu.edu

Dr. Anuj Mubayi
School of Human Evolution and Social Change, Arizona State University, Tempe, AZ 85287, USA
Email: amubayi@asu.edu

Manuscript Topics

Infectious diseases, including emerging diseases and zoonotic diseases, caused by bacteria, viruses, fungi or parasites, have been important research themes in public health because of fast changing environment and population structure. The great interests in our new era include components concerning climate/environment change and sustainability of resources due to massive movement and increasing patterns in some populations. The prevention and control of complex nature of infectious threats are crucial for improving public health conditions but need better understanding of its dynamics. Mathematical modeling of infectious diseases has been a powerful tool which has been used to study the driving and adaptive mechanisms of how the diseases spread, to predict the future course of an outbreak, and to evaluate the effectiveness of control strategies of an epidemic. Through this special issue, we seek to collect cutting edge articles that optimizes and identifies the cost-effectiveness of public health interventions including vaccination, drug treatment and other control strategies. Interdisciplinarity and data-driven mathematical modeling approaches will be key in these articles which will not only address public health challenges for a wide range of infectious diseases but also help in developing and advancing policies to prevent, detect, and control infectious diseases in resource limited settings.

This special issue will cover a broad range of quantitative modeling studies for a variety of infectious diseases that will refute or accept empirically driven hypothesis and will be used to draw conclusion on uncertainty trends of diseases. Investigations of model features and mechanism, including qualitative or quantitative analysis of model dynamics, parameter sensitivity analysis, intensive data analysis for parameterization and for patterns from model outputs, and numerical schemes for complex model simulations will provide deeper understanding of disease dynamics and reliable prediction for disease transmissions. Different control measures will be explored via systematic control theory methods to develop effective strategies for disease prevention and control. Temporal and spatial components, age and stage structures, different transmission mechanisms within and between humans and vectors, climate change, environmental factors, antimicrobial resistance, the complex ecological and evolutionary dynamics pertaining to the adaptive biological systems will be explored. Significant novel model development and/or mathematical and numerical analysis related to the issue topics are expected.

Paper Submission
All manuscripts will be peer-reviewed before their acceptance for publication.
The deadline for manuscript submission is August 8, 2020.

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