Open Access

ARTICLE

Epidemiologic Evolution Platform Using Integrated Modeling and Geographic Information System

Adrian Brezulianu¹, Oana Geman^2,*, Muhammad Arif³, Iuliana Chiuchisan², Octavian Postolache², Guojun Wang³

1 Faculty of Electronics, Telecommunications and Information Technology, Gheorghe Asachi Technical University from Iasi, Iasi, 700050, Romania
2 Faculty of Electrical Engineering and Computer Sciences, Stefan cel Mare University of Suceava, Suceava, 720229, Romania
3 School of Computer Science, Guangzhou University, Guangzhou, 510006, China

* Corresponding Author: Oana Geman. Email:

(This article belongs to this Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)

Computers, Materials & Continua 2021, 67(2), 1645-1663. https://doi.org/10.32604/cmc.2021.014225

Received 07 September 2020; Accepted 15 November 2020; Issue published 05 February 2021

Abstract

At the international level, a major effort is being made to optimize the flow of data and information for health systems management. The studies show that medical and economic efficiency is strongly influenced by the level of development and complexity of implementing an integrated system of epidemiological monitoring and modeling. The solution proposed and described in this paper is addressed to all public and private institutions involved in the fight against the COVID-19 pandemic, using recognized methods and standards in this field. The Green-Epidemio is a platform adaptable to the specific features of any public institution for disease management, based on open-source software, allowing the adaptation, customization, and further development of “open-source” applications, according to the specificities of the public institution, the changes in the economic and social environment and its legal framework. The platform has a mathematical model for the spread of COVID-19 infection depending on the location of the outbreaks so that the allocation of resources and the geographical limitation of certain areas can be parameterized according to the number and location of the real-time identified outbreaks. The social impact of the proposed solution is due to the planned applications of information flow management, which is a first step in improving significantly the response time and efficiency of people-operated response services. Moreover, institutional interoperability influences strategic societal factors.

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Keywords

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