Avian Influenza (H5N1) Warning System using Dempster-Shafer Theory and Web Mapping
Andino Maseleno, Md. Mahmud Hasan

TL;DR
This paper presents an early warning system for avian influenza using Dempster-Shafer theory combined with web mapping to identify and visualize potential outbreaks based on symptoms and geographic data.
Contribution
It introduces a novel integration of Dempster-Shafer theory with web mapping for real-time avian influenza outbreak detection and visualization in high-risk regions.
Findings
Successful identification of avian influenza presence
Effective visualization through web maps
Applicable in high poultry population areas
Abstract
Based on Cumulative Number of Confirmed Human Cases of Avian Influenza (H5N1) Reported to World Health Organization (WHO) in the 2011 from 15 countries, Indonesia has the largest number death because Avian Influenza which 146 deaths. In this research, the researcher built a Web Mapping and Dempster-Shafer theory as early warning system of avian influenza. Early warning is the provision of timely and effective information, through identified institutions, that allows individuals exposed to a hazard to take action to avoid or reduce their risk and prepare for effective response. In this paper as example we use five symptoms as major symptoms which include depression, combs, wattle, bluish face region, swollen face region, narrowness of eyes, and balance disorders. Research location is in the Lampung Province, South Sumatera. The researcher reason to choose Lampung Province in South…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInfluenza Virus Research Studies · Data-Driven Disease Surveillance
