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SIR mathematical model of convalescent plasma transfusion applied to the COVID-19 pandemic data in Indonesia to control the spread of the disease
3rd International Conference on Mathematics, Statistics and Computing Technology 2021, ICMSCT 2021 ; 2084, 2021.
Article in English | Scopus | ID: covidwho-1574583
ABSTRACT
In this paper we develop a mathematical model of disease transmission dynamics. Although some vaccines for some infectious diseases are available, there are some cases where handling new emerging infectious diseases, such as COVID-19 pandemic, is still a difficult problem to handle. Preventive actions, such as wearing masks, distance guarding, frequent hand washing, and others are still the most important interventions in handling the transmission of this disease. Recently, several countries have allowed the use of convalescent plasma transfusion (CPT) in the management of moderate and severe COVID-19 patients. Several early studies of this use have yielded prospective results with reduced mortality rates. A recent work also shows that using a simple discrete mathematical model of CPT could reduce the outbreak of disease transmission, in the sense of reducing the peak number of active cases and the length of the outbreak itself. In this paper, we use a continuous SIR model applied to COVID-19 pandemic data in Indonesia to address an important question whether convalescent plasma transfusion may reduce the transmission of the disease. © Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd International Conference on Mathematics, Statistics and Computing Technology 2021, ICMSCT 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd International Conference on Mathematics, Statistics and Computing Technology 2021, ICMSCT 2021 Year: 2021 Document Type: Article