Inaugural Issue Released for Infectious Disease Modelling
Published 14 December, 2016
“Infectious disease prevention and control” has become a public health challenge due to rapidly changing global connectivity and the environments in which disease spreads.
On the other hand, “big data” has emerged as a buzzword in today’s high-tech and information age. Mathematical modelling may provide the shortest path to bridge the long distance between public health data and decision making and practice. “Building this path is the main objective of Infectious Disease Modelling”, said Professor Jianhong Wu at York University in Canada, who is co-editing this new journal published by KeAi, a joint venture between Elsevier and the Chinese Science Press.
Read the issue at: http://www.sciencedirect.com/science/journal/24680427/1/1
The inaugural issue of this peer-reviewed open access journal contains a number of original scientific contributions on the interface between mathematical modelling and public health decision support relevant to the prevention and control of infectious diseases including Zika, HIV-AIDS, Ecoli, Dengue, MRSA, influenza, to name a few. These studies touch on such critical issues as drug resistance, epidemic potential, outbreak speed, and controllability.
This issue also publishes work from the research group led by biostatistician, Dr. Hulin Wu, at the University of Texas Health Science Center, Houston. His work develops a novel clustering algorithm designed to identify temporal gene response modules for influenza infection.
In the study conducted by the University of Guelph research group led by Chris Bauch, a game theory approach is used to understand the dynamic interaction between populations for optimal antiviral treatment strategies given the potential emergence of antiviral drug resistance during an influenza outbreak.
Commenting on the significance of a mechanistic approach to unraveling the dose-response puzzle of L. monocytogenes developed in the paper by Rahman et al., Professor Jeffrey Farber concluded that “As both a researcher and policy maker, I understand the importance of trying to establish improved dose response models for L. monocytogenes in humans.…This work definitely provides the basis for establishing more accurate dose response models and will thus improve and better inform our current risk assessments in this field”.
Looking for the most recent progress on vector-borne disease transmission dynamics, given the concerns of global spread of dengue and Zika? You will not be disappointed to see the work from University of São Paulo and the London School of Hygiene and Tropical Diseases, and you will be happy to read the study arising from the collaboration between Arizona State University and University of British Columbia. If you want to see more, another paper from Professor Fred Brauer will appear in the second issue.
“We want to use this venue to promote research working to interface mathematical modelling, infection disease data retrieval and analysis, and public health decision support”, says Dr. Yiming Shao from China Centre for Disease Prevention and Control. As a co-editor-in-chief, Dr. Shao emphasizes the importance of rapid publication of original research contributing to the enhancement of this interface, and to the development of cutting edge methodologies motivated by, and applicable to, data collection and informatics for public health decision making and policy.
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