The study addresses issues related to the current epidemiological models
being used to address the COVID-19 pandemic, and suggests the “curve” is a
nebulous fairy tale. Furthermore, I argue that these models are based on invalid data and flawed
assumptions. For example, epidemiologists are using a number of positive cases, identified in
systematic data collection manners (e.g., primarily testing frontline workers and symptomatic
people), as proxy measures for infection rate: I suggest that random sample testing, proportional
to population density, would provide an exact measure of infection rate. Finally, I argue that we
are not in a position to reopen the world economy until we have these data, we now need a twopronged approach through which we conduct random sample testing for both COVID-19 and
COVID-19 antibodies, and that we are about to live in a new world in which physical
distancing will be the norm.
1-Robert C Sinclair Professor/Consultant, Sinclair & Associates Consulting, 1614 Jane Street, North Bay, Canada. (firstname.lastname@example.org)2-Rajeev Kumar Master of Technology and Computer Science, Dr. Ram Manohar Lohia Avadh University, Faizabad, India.
COVID-19, World Economy, Re-opening, Infection Rates, Random Sample Testing