{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T05:03:20Z","timestamp":1764047000657},"reference-count":32,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["New Math. and Nat. Computation"],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p> The objective of this paper is to investigate three new methods to regulate and analyze the spreading of coronavirus disease (COVID-19). COVID-19 started in the city of Wuhan, China at the end of 2019 and spread to the whole world in a short time. This infection caused millions of infected cases globally and still poses a disturbing situation for the people. Recently, some mathematical models have been constructed for better understanding of the coronavirus infection. Mostly, these models are based on classical integer-order derivative using real numbers which cannot capture the fading memory. So, at the current position, it is a challenge for the world to control the spreading of COVID-19. Therefore, the aim of this paper is to utilize fuzzy logic to control the transmission and spreading of COVID-19. Here, we develop three new methods such as the generalized interval-valued intuitionistic fuzzy Einstein weighted geometric (GIVIFEWG) operator, the generalized interval-valued intuitionistic fuzzy Einstein ordered weighted geometric (GIVIFEOWG) operator, and the generalized interval-valued intuitionistic fuzzy Einstein hybrid geometric (GIVIFEHG) operator. Intuitionistic fuzzy information for interval-valued is the moral and decent method to precise the fuzzy information for judgment or decision and Einstein operations are the best approximations, and the generalized aggregation operators are a generalization of most aggregation operators so, in these notes, we can spread the Einstein operations to aggregate the interval-valued intuitionistic fuzzy information based on the generalized aggregation operators. At the end of the paper, an illustration of the emergency situation of COVID-19 is given for demonstrating the effectiveness of the suggested approach, showing the feasibility and reliability of the new methods. <\/jats:p>","DOI":"10.1142\/s1793005722500211","type":"journal-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T03:15:59Z","timestamp":1628651759000},"page":"407-447","source":"Crossref","is-referenced-by-count":5,"title":["Mathematical Calculation of the COVID-19 Disease in Pakistan by Emergency Response Modeling Based on Intuitionistic Fuzzy Decision Process"],"prefix":"10.1142","volume":"18","author":[{"given":"Khaista","family":"Rahman","sequence":"first","affiliation":[{"name":"Department of Mathematics, Shaheed Benazir Bhutto University Sheringal, Upper Dir, Khyber Pakhtunkhwa, Pakistan"}]}],"member":"219","published-online":{"date-parts":[[2021,9,22]]},"reference":[{"key":"S1793005722500211BIB001","doi-asserted-by":"publisher","DOI":"10.3934\/mbe.2020148"},{"key":"S1793005722500211BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103805"},{"key":"S1793005722500211BIB003","doi-asserted-by":"publisher","DOI":"10.1503\/cmaj.200476"},{"key":"S1793005722500211BIB004","doi-asserted-by":"publisher","DOI":"10.1140\/epjp\/s13360-020-00383-y"},{"key":"S1793005722500211BIB005","doi-asserted-by":"publisher","DOI":"10.1016\/j.pbiomolbio.2020.04.002"},{"key":"S1793005722500211BIB006","doi-asserted-by":"publisher","DOI":"10.1016\/j.aej.2020.02.033"},{"key":"S1793005722500211BIB007","doi-asserted-by":"publisher","DOI":"10.1016\/S0019-9958(65)90241-X"},{"key":"S1793005722500211BIB008","doi-asserted-by":"publisher","DOI":"10.1016\/S0165-0114(86)80034-3"},{"key":"S1793005722500211BIB009","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0114(89)90215-7"},{"key":"S1793005722500211BIB010","doi-asserted-by":"publisher","DOI":"10.1080\/03081070600574353"},{"key":"S1793005722500211BIB011","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2006.890678"},{"key":"S1793005722500211BIB012","doi-asserted-by":"publisher","DOI":"10.1002\/int.20498"},{"key":"S1793005722500211BIB013","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2012.2189405"},{"key":"S1793005722500211BIB014","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2012.09.006"},{"key":"S1793005722500211BIB015","doi-asserted-by":"publisher","DOI":"10.1007\/s40815-018-0452-0"},{"key":"S1793005722500211BIB016","doi-asserted-by":"publisher","DOI":"10.1080\/03081079.2011.607448"},{"key":"S1793005722500211BIB017","doi-asserted-by":"publisher","DOI":"10.1109\/CIS.2007.84"},{"key":"S1793005722500211BIB018","doi-asserted-by":"publisher","DOI":"10.1016\/0165-0114(89)90205-4"},{"issue":"2","key":"S1793005722500211BIB019","first-page":"215","volume":"22","author":"Xu Z. 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