SECURE INTERNET OF THINGS-BASED CLOUD FRAMEWORK TO CONTROL ZIKA VIRUS OUTBREAK.

Area of Science:

• Public Health
• Infectious Disease Epidemiology
• Digital Health

Background:

• Zika virus (ZikaV) poses a significant global health threat, causing outbreaks and severe congenital malformations.
• Existing methods for ZikaV detection and control are insufficient to manage widespread epidemics.
• The integration of mobile technology and the Internet of Things (IoT) offers novel solutions for disease surveillance.

Purpose of the Study:

• To propose a novel cloud-based system for the prevention and control of Zika virus disease.
• To leverage mobile phones and IoT for enhanced ZikaV outbreak management.
• To develop an integrated system for early diagnosis and geographic risk assessment.

Main Methods:

• A Naive Bayesian Network (NBN) was employed for the initial diagnosis of potentially infected individuals.
• Google Maps Web service was utilized for Geographic Positioning System (GPS)-based risk assessment.
• The system maps infected users, mosquito-dense areas, and breeding sites to aid public health authorities.

Main Results:

• The proposed system demonstrated high accuracy in the initial diagnosis of users based on their symptoms.
• Accurate GPS-based risk assessments were achieved, identifying high-risk zones effectively.
• System performance was validated using a dataset comprising 2 million users.

Conclusions:

• The developed cloud-based system provides accurate classification of infected users via NBN.
• The system effectively identifies risk-prone areas using Google Maps integration.
• This approach enhances the capability of healthcare authorities in controlling ZikaV outbreaks.