COVID-19 Vaccines: Computational tools and Development

Autor: Victor Chukwudi Osamor, Excellent Ikeakanam, Janet U. Bishung, Theresa N. Abiodun, Raphael Henshaw Ekpo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Informatics in Medicine Unlocked, Vol 37, Iss , Pp 101164- (2023)
Druh dokumentu: article
ISSN: 2352-9148
DOI: 10.1016/j.imu.2023.101164
Popis: The 2019 coronavirus outbreak, also known as COVID-19, poses a serious threat to global health and has already had widespread, devastating effects around the world. Scientists have been working tirelessly to develop vaccines to stop the virus from spreading as much as possible, as its cure has not yet been found. As of December 2022, 651,918,402 cases and 6,656,601 deaths had been reported. Globally, over 13 billion doses of vaccine have been administered, representing 64.45% of the world's population that has received the vaccine. To expedite the vaccine development process, computational tools have been utilized. This paper aims to analyze some computational tools that aid vaccine development by presenting positive evidence for proving the efficacy of these vaccines to suppress the spread of the virus and for the use of computational tools in the development of vaccines for emerging diseases.
Databáze: Directory of Open Access Journals