COVID-19 far deadlier than the flu — University of Washington analysis of 116 counties

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COVID-19 is a lot more deadly than the flu, concludes a study by the University of Washington.

The study’s results also project a grim future if the US doesn’t put up a strong fight against the spread of the virus.

The national rate of death among people infected with the novel coronavirus – SARS-CoV-2 – that causes COVID-19 and who show symptoms is 1.3%, the study found. The comparable rate of death for the seasonal flu is 0.1%.

“COVID-19 infection is deadlier than flu – we can put that debate to rest,” said study author Anirban Basu, professor of health economics and Stergachis Family endowed director of the CHOICE Institute at the UW School of Pharmacy.

The School of Pharmacy and Basu have developed a website that explores the infection and fatality rates by US counties for people with symptoms. For this study, 116 counties in 33 states had COVID-19 data that fit Basu’s robust criteria for inclusion in the analysis. The site’s projections will be updated as new data becomes available, Basu said.

Basu stresses that this website is not a forecasting tool – it does not predict what will happen in the future. Rather, it uses the estimated death rate among symptomatic COVID-19 cases to project what is happening currently in these communities, such as what are the likely numbers for total infections and symptomatic cases. The tool will also detail how the daily incidence of infections changes.

In the state of Washington, for example, the county-specific fatality estimates ranged from 0.5% to 3.6%. King County at 3.6% is the highest among all 116 US counties studied. Among the state’s other counties that could be included in this analysis were Chelan County at 2.3%, Island County at 2.2% and Spokane County at 2%.

The COVID-19 death rate, the study adds, means that if the same number of people in the US are infected by the end of the year as were infected with the influenza virus – roughly 35.5m in 2018-2019 – then nearly 500,000 people will die of COVID-19. However, the novel coronavirus is more infectious than the influenza virus, Basu noted.

So, a conservative estimate of 20% of the US population becoming infected by the end of the year – with the current trends in social distancing and health care supply continuing, while accounting for those infected who will recover asymptomatically – could result in the number of deaths climbing to between 350,000 and 1.2m.

“This is a staggering number, which can only be brought down with sound public health measures,” Basu said.

To build county-by-county models that could more accurately show how deadly the pandemic is, Basu used publicly reported data on the total COVID-19 cases and deaths.

Realising that both of these reported quantities likely are undercounts and change over time, Basu looked at the trends in the ratio of these two numbers, or the reported “case fatality rates,” to more accurately reflect how deadly the virus is among those who fall sick because of it.

“Our hope is that our study results can help inform local and national policies that will save lives in the future,” said Basu. “Ultimately, we want this work to advance the health of people around the world.”

Basu also noted that the model should not be viewed as the “last word” on estimating the COVID-19 fatality rate, but as one of several methods used to measure the impact of the virus.

“The infection fatality ratio estimate is itself dynamic in nature,” Basu said. “The overall estimate can both increase or decrease in the future, depending on the demographics where the infections will be spreading. It is possible, as the infection spreads to more rural counties of the country, the overall infection fatality rate will increase due to the lack of access to necessary health care delivery.”

This research was funded by the UW CHOICE Institute and the School of Pharmacy.

Knowing the infection fatality rate (IFR) of SARS-CoV and SARS-CoV-2 infections is essential for the fight against the COVID-19 pandemic. Using data through April 20, 2020, we fit a statistical model to COVID-19 case fatality rates over time at the US county level to estimate the COVID-19 IFR among symptomatic cases (IFR-S) as time goes to infinity. The IFR-S in the US was estimated to be 1.3% (95% central credible interval: 0.6% to 2.1%). County-specific rates varied from 0.5% to 3.6%. The overall IFR for COVID-19 should be lower when we account for cases that remain and recover without symptoms. When used with other estimating approaches, our model and our estimates can help disease and policy modelers to obtain more accurate predictions for the epidemiology of the disease and the impact of alternative policy levers to contain this pandemic. The model could also be used with future epidemics to get an early sense of the magnitude of symptomatic infection at the population-level before more direct estimates are available. Substantial variation across patient demographics likely exists and should be the focus of future studies.

Anirban Basu


University of Washington material


Health Affairs abstract

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