TY  - JOUR
AU  - Mavakala, Arnaud Watusadisi 
AU  - Adoni, Wilfried Yves Hamilton 
AU  - Ben Aoun, Najib 
AU  - Nahhal, Tarik 
AU  - Krichen, Moez 
AU  - Alzahrani, Mohammed Y. 
AU  - Kalala, Franck Mutombo 
PY  - 2023
TI  - COV19-Dijkstra: A COVID-19 Propagation Model Based on Dijkstra’s Algorithm
JF  - Journal of Computer Science
VL  - 19
IS  - 1
DO  - 10.3844/jcssp.2023.75.86
UR  - https://thescipub.com/abstract/jcssp.2023.75.86
AB  - The presence of the coronavirus, known as COVID-19, has prompted several researchers to study the mode of spread and the different defense mechanisms of the virus. As a reminder, obtaining a vaccine, for which much research is being conducted around the world, is a long and expensive process and it is unlikely that the pandemic can be treated in time. In this article, we present a new way to assess and limit the spread of the virus while trying to answer the following important questions: How to use the shortest path algorithm in a graph to analyze and better understand the spread of the virus? How to use the predictive power of the graph using the shortest path algorithm to find the relationships of a person who might be most at risk? The designed algorithm simulates how the virus spreads and infects people through the graph. Since the size of the collected COVID-19 data can reach a large volume over time and speaking of the graph concept, the NOSQL database including Neo4j which is a graph oriented NOSQL database is used for data collection, storage and processing. To enable the design and optimization of virus defense systems, this study proposes a feasible approach to quantify and predict the danger of a virus infection within a community.