{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:01:32Z","timestamp":1772262092000,"version":"3.50.1"},"reference-count":106,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T00:00:00Z","timestamp":1624838400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Eco-epidemiological can be considered as a significant combination of two research fields of computational biology and epidemiology. These problems mainly take ecological systems into account of the impact of epidemiological factors. In this paper, we examine the chaotic nature of a computational system related to the spread of disease into a specific environment involving a novel differential operator called the Atangana\u2013Baleanu fractional derivative. To approximate the solutions of this fractional system, an efficient numerical method is adopted. The numerical method is an implicit approximate method that can provide very suitable numerical approximations for fractional problems due to symmetry. Symmetry is one of the distinguishing features of this technique compared to other methods in the literature. Through considering different choices of parameters in the model, several meaningful numerical simulations are presented. It is clear that hiring a new derivative operator greatly increases the flexibility of the model in describing the different scenarios in the model. The results of this paper can be very useful help for decision-makers to describe the situation related to the problem, in a more efficient way, and control the epidemic.<\/jats:p>","DOI":"10.3390\/sym13071159","type":"journal-article","created":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T13:39:22Z","timestamp":1624887562000},"page":"1159","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Fractional Approach to a Computational Eco-Epidemiological Model with Holling Type-II Functional Response"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2966-7736","authenticated-orcid":false,"given":"B.","family":"G\u00fcnay","sequence":"first","affiliation":[{"name":"Faculty of Engineering and Natural Sciences, Bah\u00e7e\u015fehir University, 34349 Istanbul, Turkey"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7556-8942","authenticated-orcid":false,"given":"Praveen","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Anand International College of Engineering, Near Kanota, Agra Road, Jaipur 303012, India"},{"name":"Nonlinear Dynamics Research Center (NDRC), Ajman University, Ajman AE 346, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2788-809X","authenticated-orcid":false,"given":"Juan L. G.","family":"Guirao","sequence":"additional","affiliation":[{"name":"Departamento de Matematica Aplicada y Estadistica, Universidad Politecnica de Cartagena, Hospital de Marina, 30203 Murcia, Spain"},{"name":"Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6326-8456","authenticated-orcid":false,"given":"Shaher","family":"Momani","sequence":"additional","affiliation":[{"name":"Nonlinear Dynamics Research Center (NDRC), Ajman University, Ajman AE 346, United Arab Emirates"},{"name":"Department of Mathematics, Faculty of Science, The University of Jordan, Amman 11942, Jordan"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,28]]},"reference":[{"key":"ref_1","unstructured":"Murray, J.D. (2007). Mathematical Biology: I. 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