Jurnal Rekayasa Sistem Industri · 2020 · 13 citations · 7 references
Veterinary MedicineInfectious Disease ControlInfectious DiseasesEpidemiologyImmunizationInfectious Disease EpidemiologyDisease ControlDisease EpidemiologyDisease IncidenceInfectious Disease DynamicsInfectious Disease PreventionMarkov ModelingEpidemic ModelsMarkov Disease ModelsModeling Of Outbreak SpreadStochastic Disease ModelsTemporal Epidemic PatternsTemporal Incidence Patterns
COVID-19 is a new disease that is affecting almost all of the world. Until now there has not been a single drug (vaccine) that can be used to cure it. Many attempts were made to prevent the spread of this disease but COVID-19 patients are increasing every day, although at the same time some are recovering. This study will calculate the probability of additional patients occurring over a long period of time, referred as a steady state state condition, using the Markov chain method. Nine states have been formed to represent the daily increase ranges of COVID-19 patients number. The calculation results show that the possibility of additional patient number between 1 to 91, 92 to 182, 182 to 272, 273 to 363, 364 to 454, 455 to 545, 546 to 636, 637 to 727, or greater than 728 people a day are 0.21197, 0.05644, 0.08408, 0.16337, 0.13999, 0.14512, 0.07189, 0.07695, and 0.05014, respectively.
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Operations Research: Applications and Algorithms
Eric R. Ziegel, Wayne L. Winston · Technometrics · 1988 · 1.7K citations
Stefano Merler, Marco Ajelli, Laura Fumanelli et al. · The Lancet Infectious Diseases · 2015 · 296 citations · Full text
Veterinary Medicine, Infectious Disease Control, Infectious Diseases +17