Your browser doesn't support javascript.
loading
A herd immunity approach to the COVID-19 pandemic?
Takefuji, Yoshiyasu.
Afiliación
  • Takefuji Y; Faculty of Data Science, Musashino University, 3-3-3 Ariake Koto-ku, Tokyo, 135-8181 Japan.
Health Technol (Berl) ; 12(5): 1037-1041, 2022.
Article en En | MEDLINE | ID: mdl-35818413
Viral contamination is one of the most urgent and important topics of environmental pollution. COVID-19 is primarily transmitted from person to person, but can also be transmitted from person to animal. Herd immunity must meet the requirements in order to fulfill the goal of mitigating and ending COVID-19. This paper shows five reasons or conditions why herd immunity is not achieved in the present policies without proposed effective strategies in this paper. Unless one of the five reasons for the herd immunity model is met, the promise of herd immunity will not be fulfilled. Many COVID-19 policies worldwide with current vaccines do not meet the requirements. Policymakers have been relying on unreliable R. The number of daily deaths instead of the number of cases is a good indicator of the pandemic which will be mainly used in this paper. Currently, even in vaccinated countries, resurgences are being observed with new variants with spike mutations and immune escape. This paper proposes an effective multipronged approach such as a pharmacological approach and a non-pharmacological approach including digital fencing. Two tools such as scorecovid and deathdaily were used for justifying the claims. Digital fencing as well as pharmacological approaches may be able to overcome the pandemic. Two tools such as scorecovid and deathdaily showed that the proposed multipronged approach will be effective for mitigating the pandemic.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Health Technol (Berl) Año: 2022 Tipo del documento: Article Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Health Technol (Berl) Año: 2022 Tipo del documento: Article Pais de publicación: Alemania