Epidemiology: Open Access
Open Access

The COVID-19 pandemic has resulted in a concomitant deluge of medical, biological, and epidemiologic research. Clinicians are rightly interested in incorporating the best new evidence-based practices when treating COVID-19 patients and instituting SARS-CoV-2 transmission prevention protocols. However, without sufficient background knowledge, evaluating epidemiologic studies can be challenging, and a failure to identify sources of bias could lead to poor treatment decisions. Here, we provide a brief primer on key concepts and terms related to COVID-19 epidemiology in the hopes that this information will help provide clinicians with a starting point for evaluating the emerging COVID-19 literature.

The SARS-CoV-2 virus has infected millions of people globally; there are over 2 million thousand reported deaths and almost 95 million confirmed cases of COVID-19 worldwide from January 2020 to 2021. The pandemic has also spurred a huge scientific effort to understand the biology, epidemiology, and clinical treatment of the virus. Epidemiology is the study of distribution and determinants of disease states in human populations and many epidemiological studies of SARS-CoV-2 have emerged which have contributed to a better understanding of the disease. Moreover, these epidemiological findings can inform clinical practice to improve patient outcomes. Yet, many clinicians may be unfamiliar with the basic epidemiology concepts needed to read, evaluate, and incorporate evidence-based medicine into their clinical practice, particularly as they apply to emerging infectious diseases. In this review, we aim to elucidate common epidemiological concepts essential to understanding the COVID-19 literature, with a particular focus for clinicians. Essential epidemiological concepts will be discussed, such as the terms to define morbidity and mortality, disease progression in infected individuals, and disease transmission between individuals. We will also explore basic infectious disease modeling terms.

Infectious disease modeling

Since irresistible illness can be communicated, numerical models need to consider the spread of sickness between people. There is a plenitude of Coronavirus writing dependent on numerical demonstrating, and clinicians may not be comfortable with the phrasing needed to comprehend these models. We momentarily depict the significant boundaries in irresistible sickness demonstrating. All things considered, by a contaminated person where all contacts are conceivably powerless. This action is generally utilized in the beginning phases of the scourge, preceding the populace acquiring insusceptibility or non-drug mediations being executed in the populace.

R0 depicts the infectiousness and contagiousness of microbes and is a component of contact rates among people, transmission likelihood, and number of infective people. In this way, R0 gauges are not resolved solely by the microorganism, and fluctuation in R0 relies upon nearby socio behavioral and natural settings. R0 for Coronavirus is as of now assessed to be 2.63 and goes from 0.4-4.6, yet different investigations have assessed R0 to run as high as 5 or 6.

Another significant measure is the time-changing viable propagation number (R, Re, or Rt). This action is the quantity of individuals in a populace who can be contaminated by a person at a particular time; it mirrors the changing degrees of invulnerability in the populace and the impact of control estimates restricting transmission.