Coronavirüs Hastalığının Halk Sağlığı Etkisinin Ölçülmesi 2019: Pandemi Zamanlarında Sağlık Hizmetlerinde Yeni Bir Perspektif

Abstract

Since the spark of the recent Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), public
 health concerns have motivated the accumulation of a vast amount of data about the Coronavirus
 Disease 2019 (COVID-19). The most important metrics for the pandemic progression are the recorded
 cases and reported deaths datasets which were comprehensively collected pertaining to the outbreak.
 The reliance on the census of morbidity and mortality lists solely appeared to be inadequate to assess
 or forecast the disease. It is proposed that a significant extension of this data should be amended to be
 much more useful for public health authorities and official organizations. It would be plausible to adopt
 a practical use of quantitative metrics that could be easily understandable and applied for measuring
 such a catastrophic pandemic. Three parameters that might be observed primarily involve assessing
 the outbreak magnitude, rate of change with time and the degree of stability of the difference in the rate
 of morbidities and mortalities at different intervals. In addition, empirical modeling implementation using
 the curve-fitting approach could be conducted to describe the pattern of the epidemic according to the
 cumulative daily datasets