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Can infectious modelling be applicable globally - lessons from COVID 19.
Magana-Arachchi, Dhammika N; Wanigatunge, Rasika P; Vithanage, Meththika S.
  • Magana-Arachchi DN; Molecular Microbiology and Human Diseases Unit, National Institute of Fundamental Studies, Kandy, Sri Lanka.
  • Wanigatunge RP; Department of Plant and Molecular Biology, Faculty of Science, University of Kelaniya, Sri Lanka.
  • Vithanage MS; Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.
Curr Opin Environ Sci Health ; : 100399, 2022 Oct 22.
Article in English | MEDLINE | ID: covidwho-2082634
ABSTRACT
Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modelling to achieve the needed forecasts, the best example being the COVID-19 pandemic. Scientists used various models to determine how diverse sociodemographic factors correlated and influenced COVID-19 Global transmission and demonstrated the utility of computer models as tools in disease management. However, as modelling is done with assumptions with set rules, calculating uncertainty quantification is essential in infectious modelling when reporting the results and trustfully describing the limitations. This article summarizes the infectious disease modelling strategies, challenges, and global applicability by focusing on the COVID-19 pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Curr Opin Environ Sci Health Year: 2022 Document Type: Article Affiliation country: J.coesh.2022.100399

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Curr Opin Environ Sci Health Year: 2022 Document Type: Article Affiliation country: J.coesh.2022.100399