Spatial Analysis of African Swine Fever Outbreak: A Basis for Developing a Web-Based Decision Support System using Business Analytics and Geospatial Technology

The Philippine hog industry, crucial to national food security and rural economies, is facing a major threat from African Swine Fever (ASF), a highly contagious disease that has devastated the domestic pig population since its emergence in 2019. The economic toll has been severe, with over 300,000 pigs culled to control outbreaks. Despite government efforts, including the declaration of a national state of calamity and various biosecurity measures, the response has been hindered by insufficient testing and weak monitoring mechanisms. This study proposes the development of a web-based decision support system (DSS) to enhance ASF management using Business Analytics, Geographic Information Systems (GIS) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The system aims to map ASF outbreaks in real-time, identify disease hotspots, and provide actionable insights to various stakeholders, including veterinarians, farmers, and policymakers. It integrates descriptive, predictive, and prescriptive analytics to support informed decision-making, optimize resources, and guide targeted interventions. The research uses Region 6, Western Visayas, as a case study, known for its high ASF outbreak rate and significant role in the national hog industry. The DSS employs spatial and non-spatial data, including outbreak trends and biosecurity protocols, and is evaluated by ASF professionals, IT experts, and policymakers to ensure its effectiveness in real-world applications. The system’s potential to improve outbreak forecasting and intervention planning is emphasized, with the goal of strengthening the resilience of the Philippine hog industry and contributing to global sustainability efforts. This study highlights the importance of integrating advanced technologies in managing ASF outbreaks, with a focus on data-driven decision-making to protect food security, promote public health, and support economic growth.

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Publication Details

Journal
Journal of innovative technology convergence.
Published
2024-12-30
DOI
https://doi.org/10.69478/jitc2024v6n4a07
Primary Topic
Animal Disease Management and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Spatial Analysis of African Swine Fever Outbreak: A Basis for Developing a Web-Based Decision Support System using Business Analytics and Geospatial Technology

Alexis John Rubio, Roger Mission
Journal of innovative technology convergence.
Animal Disease Management and Epidemiology
article

Spatial Analysis of African Swine Fever Outbreak: A Basis for Developing a Web-Based Decision Support System using Business Analytics and Geospatial Technology

Alexis John Rubio, Roger Mission
article en

Abstract

The Philippine hog industry, crucial to national food security and rural economies, is facing a major threat from African Swine Fever (ASF), a highly contagious disease that has devastated the domestic pig population since its emergence in 2019. The economic toll has been severe, with over 300,000 pigs culled to control outbreaks. Despite government efforts, including the declaration of a national state of calamity and various biosecurity measures, the response has been hindered by insufficient testing and weak monitoring mechanisms. This study proposes the development of a web-based decision support system (DSS) to enhance ASF management using Business Analytics, Geographic Information Systems (GIS) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The system aims to map ASF outbreaks in real-time, identify disease hotspots, and provide actionable insights to various stakeholders, including veterinarians, farmers, and policymakers. It integrates descriptive, predictive, and prescriptive analytics to support informed decision-making, optimize resources, and guide targeted interventions. The research uses Region 6, Western Visayas, as a case study, known for its high ASF outbreak rate and significant role in the national hog industry. The DSS employs spatial and non-spatial data, including outbreak trends and biosecurity protocols, and is evaluated by ASF professionals, IT experts, and policymakers to ensure its effectiveness in real-world applications. The system’s potential to improve outbreak forecasting and intervention planning is emphasized, with the goal of strengthening the resilience of the Philippine hog industry and contributing to global sustainability efforts. This study highlights the importance of integrating advanced technologies in managing ASF outbreaks, with a focus on data-driven decision-making to protect food security, promote public health, and support economic growth.

Journal of innovative technology convergence.Vol. 6(4)
University of the East (PH), University of Antique (PH)
Openalex Percentile: Top 64%
Animal Disease Management and Epidemiology
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