Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 13, 30 November 2023
Open
Access | Article
The application of biostatistics in COVID-19 epidemic
* Author to whom correspondence should be addressed.
Abstract
Between the years 2020 and 2022, the COVID-19 pandemic is anticipated to emerge as the most severe global epidemic. The objective of this study is to examine the utilization of biostatistics in the domains of medication development, analysis of epidemic trends, and survival model analysis within the context of the COVID-19 pandemic. Through the utilization of a literature review method, this research delved into the examination of prospective therapeutic interventions employed in the realm of drug development studies. Specifically, the paper explored the efficacy and potential of camostat mesylate and remdesivir, alongside the exploration of immunotherapeutic strategies. Furthermore, the study examines the use of mathematical modeling in forecasting the trajectory of epidemic dissemination, and the significance of survival model analysis in comprehending patient longevity. The study revealed that medication development and immunotherapy play a crucial role in effectively combating novel coronavirus pneumonia. Furthermore, the utilization of mathematical modeling can provide valuable insights into forecasting the propagation of the epidemic. Additionally, survival model analysis can offer guidance in the allocation of medical resources and aid in decision-making processes. The findings of this research will contribute to a deeper comprehension and more effective mitigation of worldwide public health issues, such as the ongoing COVID-19 pandemic.
Keywords
COVID-19, Biostatistics, Models, Survival Analysis
References
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2. Santarpia, J. L. et al. Transmission Potential of SARS-CoV-2 in Viral Shedding Observed at the University of Nebraska Medical Center. (2020) doi:https://doi.org/10.1101/2020. 03.23.20039446.
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4. Tang, X. et al. On the origin and continuing evolution of SARS-CoV-2. National Science Review 7, (2020).
5. Xiao, Y. et al. Update on treatment and preventive interventions against COVID-19: an overview of potential pharmacological agents and vaccines. Molecular Biomedicine 1, 5 (2020).
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7. Hu, Y. et al. Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis. Journal of Clinical Virology 127, (2020).
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-189-6
- ISBN (Online)
- 978-1-83558-190-2
- Published Date
- 30 November 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/13/20240758
- Copyright
- 30 November 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited