Artificial Intelligence for Detection, Control and Monitoring of Monkeypox Outbreaks Using a Mobile Application

Monkeypox is a disease of zoonotic origin that reflects the connection between human, animal, and environmental health. It is transmitted primarily through direct contact with body fluids, skin lesions, or contaminated surfaces. Being of interest after the global outbreak of 2022, which recorded nearly 70,000 cases in more than 100 countries. This study presents a prototype mobile application that incorporates tools such as artificial intelligence (AI) for early detection and monitoring of the disease. The mobile-D methodology was used. The results were validated by experts and users, reaching an average of 85% in user satisfaction and 81% in expert evaluation, indicating a high level of acceptance. This application facilitates real-time data collection, improving communication between health authorities and the population, which is crucial for disease control. With the use of AI and data analysis, the application seeks to optimize case management and support health systems in at-risk areas, representing a significant advance in the response to monkeypox.

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Publication Details

Journal
International Journal of Online and Biomedical Engineering (iJOE)
Published
2024-12-19
DOI
https://doi.org/10.3991/ijoe.v20i16.52867
Primary Topic
Poxvirus research and outbreaks
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence for Detection, Control and Monitoring of Monkeypox Outbreaks Using a Mobile Application

Michael Cabanillas-Carbonell
International Journal of Online and Biomedical Engineering (iJOE)
Poxvirus research and outbreaks
article

Artificial Intelligence for Detection, Control and Monitoring of Monkeypox Outbreaks Using a Mobile Application

Michael Cabanillas-Carbonell
article en

Abstract

Monkeypox is a disease of zoonotic origin that reflects the connection between human, animal, and environmental health. It is transmitted primarily through direct contact with body fluids, skin lesions, or contaminated surfaces. Being of interest after the global outbreak of 2022, which recorded nearly 70,000 cases in more than 100 countries. This study presents a prototype mobile application that incorporates tools such as artificial intelligence (AI) for early detection and monitoring of the disease. The mobile-D methodology was used. The results were validated by experts and users, reaching an average of 85% in user satisfaction and 81% in expert evaluation, indicating a high level of acceptance. This application facilitates real-time data collection, improving communication between health authorities and the population, which is crucial for disease control. With the use of AI and data analysis, the application seeks to optimize case management and support health systems in at-risk areas, representing a significant advance in the response to monkeypox.

International Journal of Online and Biomedical Engineering (iJOE)Vol. 20(16)
Private University of the North (PE)
Openalex Percentile: Top 76%
Poxvirus research and outbreaks
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Artificial Intelligence for Detection, Control and Monitoring of Monkeypox Outbreaks Using a Mobile Application — Michael Cabanillas-Carbonell · International Journal of Online and Biomedical Engineering (iJOE) (2024) | TGRS Research Map | TGRS