Like many fields of learning, biostatistics has its own vocabulary often seen in medical and public health literature. Phrases like statistical significance", "p-value less than 0.05", "95% confident", and "margin of error" can have enormous impact in a world that relies on statistics to make decisions: Should Drug A be recommended over Drug B? Should a national policy on X be implemented? Does Vitamin C truly prevent colds? However, do we really know what these terms and phrases mean? Understanding the theory and methodology behind study design, estimation and hypothesis testing is crucial to ensuring that findings and practices in public health and biomedicine are supported by reliable evidence.
It is widely acknowledged that as a variable, 'race' often explains a significant portion of the variation we observe in patterns of morbidity and mortality. But it isalso understood that race is a socially determined construct that functions as a proxy for a host of other variables associated with, among others, socioeconomic status, culture, place of residence, and position within social networks. The question that we will explore together is how to deconstruct ‘race’ to understand what factor or group of factors create the patterns of health disparities that are so dramatically present among populations of color here in the US. COVID-19 has exploited these factors tocreate a burden of disease in many communities of color that will substantially impact medicine and public health for much of the foreseeable future.One of the issues of particular salience for medical and public health research is how to go beyond describing the correlation between race and health to create effective interventions for eliminating such disparities. How can our exploration of health disparities generate the levers that we can use to promote health and prevent disease? How well do our explanatory models of race and health provide us with the tools to eliminate disparities and create a system dedicated to creating and preserving health equity?