The weekly cycle of SARS-CoV-2 virus infection is real and controlled by the socioeconomic activities
Document Type : Original Article
Authors
- 1 Department of Molecular Biology and Genetics, Life and Natural Sciences Faculty, Abdullah Gul University, Kayseri, Turkey
- 2 Department of Chemistry, Maynooth University, Ireland and Department of Molecular Biology and Genetics, Life and Natural Sciences Faculty, Abdullah Gul University, Kayseri, Turkey
Abstract
Background: In order to make accurate predictions for decision-making bodies, it is crucial to establish an accurate model. The Weekly Cycle (WC) of daily case counts on global data for countries during the COVID-19 pandemic is regarded as an artifact of daily test numbers and is not included in models. WC's persistence throughout time suggests that it might not. As a result, the nature of WC is thoroughly examined in this retrospective study.
Methods: A model Back-Tracing (BTrac) is created utilizing the Rayleigh distribution and features of the SARS-CoV-2 virus to compute daily infection numbers from daily case numbers after examining the relationship between daily case and test numbers. Additionally, BTrac is adjusted to use both constant and variable daily reproduction numbers (R0) in order to simulate and compare the amount of new infections.
Results: WC has a minimum on weekdays according to the daily infection numbers computed with BTrac. The characteristics of the virus and socioeconomic variables, such as national holidays, govern this weekly minimum. It travels toward Monday and Friday, respectively, throughout the pandemic's increasing and decreasing stages, and it recognizes two distinct settings as working and socializing for the virus's spread. Furthermore, simulation using BTrac predicts less infection than the model with constant R0, and the data indicates a variable rather than constant R0.
Conclusions: A model developed here that incorporates the features of the virus demonstrates the existence of WC and effectively reveals the impact of socioeconomic factors on the pandemic's destiny. Therefore, greater pandemic control may result from decision-making bodies adopting BTrac.
Methods: A model Back-Tracing (BTrac) is created utilizing the Rayleigh distribution and features of the SARS-CoV-2 virus to compute daily infection numbers from daily case numbers after examining the relationship between daily case and test numbers. Additionally, BTrac is adjusted to use both constant and variable daily reproduction numbers (R0) in order to simulate and compare the amount of new infections.
Results: WC has a minimum on weekdays according to the daily infection numbers computed with BTrac. The characteristics of the virus and socioeconomic variables, such as national holidays, govern this weekly minimum. It travels toward Monday and Friday, respectively, throughout the pandemic's increasing and decreasing stages, and it recognizes two distinct settings as working and socializing for the virus's spread. Furthermore, simulation using BTrac predicts less infection than the model with constant R0, and the data indicates a variable rather than constant R0.
Conclusions: A model developed here that incorporates the features of the virus demonstrates the existence of WC and effectively reveals the impact of socioeconomic factors on the pandemic's destiny. Therefore, greater pandemic control may result from decision-making bodies adopting BTrac.