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Harnessing the Power of AI to Improve Detection, Monitoring, and Public Health Interventions for Japanese
Junhua Xiao1, Evie Kendal1, Faith A A Kwa1
1School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Abstract:
Japanese Encephalitis (JE) is the leading cause of viral encephalitis in regions with endemic Japanese Encephalitis Virus (JEV) infections.
Background/Objectives:
The aim of this review is to consider the potential role of artificial intelligence (AI) to improve detection, monitoring and public health interventions for JE.
Discussion:
As climate change continues to impact mosquito population growth patterns, more regions will be affected by mosquito-borne diseases, including JE. Improving diagnosis and surveillance, while continuing preventive measures, such as widespread vaccination campaigns in endemic regions, will be essential to reduce morbidity and mortality associated with JEV.
Conclusions:
With careful integration, AI mathematical and mechanistic models could be useful tools for combating the growing threat of JEV infections globally.
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