How the United States Flunked the COVID-19 Test: Some Observations and Several Lessons

Abstract

The unprecedented COVID-19 pandemic has already caused enormous economic and human life losses in the United States and it is still ravaging the country. In this article, the authors argue that the pandemic has exposed key issues of concern in several areas of the American government system ranging from federalist intergovernmental relations to public health system and to health care policy. These issues of concern include the strained federal-state relations in emergency management, inadequate data collection and data reporting for disease surveillance and control, politicization and diminished role of science and evidence in administrative decision making, and underinvestment in public health programs especially in minority health. Based on their analysis, the authors admonish that it is critically important for the U.S. government to learn from the failed response to the pandemic and offer several recommendations for improving its response to future public health emergencies and research in public administration.

Modeling COVID-19 outbreaks in United States with distinct testing, lockdown speed and fatigue rates

“…And even in locales with successful outbreak responses such as Finland [11], or Hawaii in our own model, we note that the proportion of cases undetected in the early states of the outbreak is very high. For our United States fit we estimated an IFR of 0.009 (95% confidence interval .007 to .011), which is in line with the observed IFR for countries with very high levels of testing such as South Korea [16] and Finland [11].…”

“…To obtain parameter estimates for our model in each state and territory, we utilized cumulative death and case totals [10] as well as daily testing data, inferred from [3]. The data used for the whole US fit was obtained by combining data from all subsidiary states and territories due to concerns about data reliability at the federal level [16]. Even at the state level the raw testing data contained a number of reporting irregularities, as evidenced by several days with negative daily testing instance.…”

Modelling COVID-19 outbreaks in USA with distinct testing, lockdown speed and fatigue rates

“…To obtain parameter estimates for our model in each state and territory, we used cumulative death and case totals [24] as well as daily testing data, inferred from [21]. The data used for the whole US fit was obtained by combining data from all subsidiary states and territories due to concerns about data reliability at the federal level [25]. Even at the state level, the raw testing data contained a number of reporting irregularities, as evidenced by several days with negative daily testing instance.…”

Why Should Businesses Support Public Health?

“…In addition, decisions made by government officials are often driven by prospects of short-term “pay-offs” and political expediency, whereas the business community and community at large could make a difference by mobilizing constituent pressure and championing of new norms. 22…”