Covid Catastrophe Part V: Lockdown Fever
Covid Catastrophe is a seven part series examining the history of the COVID-19 pandemic, its impact on Maine and what data policymakers used to lock down society and centrally-plan our economy. Check back Monday, August 10 for Part VI.
The question remains why the U.S. federal government and many state governors, including Governor Mills, based their early understanding of the coronavirus on models developed by the University of Washington Institute for Health Metrics and Evaluation (IHME) and Imperial College of London (ICL).
In March 2020, ICL released a report that estimated overall case fatality to be 1%, lower than the 3% initially estimated by IHME. They reported that due to, “the (unlikely) absence of any control measures or spontaneous changes in individual behaviour,” after three months, 81% of people in the United States and United Kingdom (UK) would become infected, leading to 2.2 million deaths in the US and over a half-million deaths in the UK. The report assumed that 30% of hospitalized cases would require critical care and that half of those patients would perish.
Despite the recognition by the researchers that a scenario in which no avoidance strategies are employed would be unlikely, the staggering fatality estimates were continuously cited by those in the media and government. These estimates would also prove to be much too high. Today, federal CDC data (below) show the hospitalization rate among those aged 65 and older, the age group at highest risk, to be under 400 per 100,000 population, or 0.4%.
A study published at the end of March in the UK medical journal Lancet, and cited by both IHME and ICL in developing their models, showed a distinct difference in estimated fatality rate by age group. For those younger than 60 years old, the case fatality rate was estimated to be 0.63%, yet for those aged 60 or older, it was estimated to be almost 6%. The Lancet study’s graph of case fatality ratio by age distribution is shown below.
Estimates of Case Fatality Ratio by Age
From the beginning of this global pandemic, the data was clear that this new virus affected the elderly most severely, presenting the highest risks of infection if exposed, hospitalization, and death. State officials could have heeded this information in the early response period, understanding that an effort to protect 100% of the population would not be as effective as an effort to protect 10-20% of the population, and enlisted the aid of charities, businesses, and academic institutions to serve the people most at risk. Authorities could have understood that individuals will voluntarily, substantially alter their behavior such that the grossly overestimated models outlined above would be moot.
The early period of the pandemic was one of great uncertainty. Officials in government and public health were forced to constantly adapt to rapidly changing data and knowledge of the virus and its incursion into the state. No one can blame state leaders for changing policy as they learned more. Yet, even at the time the first case of COVID-19 was recorded in Maine, there was not enough evidence to show that full-scale lockdowns would be the most effective strategy. The available evidence suggested that the vast majority of people would not suffer severe illness; this should have led state leaders to focus on the most vulnerable people in society.
Data available in early March, like studies from The Lancet and WHO could have been used by state officials to support a strategy of containment for the populations most at risk, without causing massive disruption in the economy. Instead, politicians and public health experts selected which data and models they would follow, choosing to anchor themselves to those that supported a lockdown strategy. This is not to say that this choice was made out of malice. This decision was likely made because of pride in the ability of the government to plan society, blinding their ability to recognize the shortfalls of massive government intrusion into daily life.
In this way, executive administrations of many states, including Maine, displayed data that they believed would generate the most excitement and fear, thereby leading more citizens to listen to and follow state guidance to lockdown the economy and society. The fact that these representations of the existing case data did not provide an accurate view of infection rate or fatality rate was not a factor in official decision-making. It seems that the most prominent factor in choosing data to present to the public was whether the public would be more or less willing to follow the recommendations—and later orders—of state authorities.