In the past week, the state of Ohio unveiled Ohio State University modeling of projected daily cases of COVID-19 through the end of May. This forecast suggests that social distancing measures have pushed the peak of the epidemic back by a month and reduced peak daily infections from 60,000 new infections down to less than 10,000.
Data from the Ohio Department of Health.
Many who have advocated for flattening the curve say that the reduction of the strain on the health care system—the justification for social distancing policies—would save lives even if the long-term infection rate was the same by making sure everyone who needs treatment has access to it. The OSU modeling, though, suggests the total number of Ohioans infected from the beginning of March through the end of May will be nearly halved from 450,000 to 230,000 through adoption of strict social distancing measures.
So how many fatalities should we expect over that time period? The most straightforward way to estimate this number would be to assume the current fatality rate of 2.6% stays constant. This is close to the US fatality rate of 2.4% (derived from Johns Hopkins University Center for Systems Science and Engineering numbers) so this seems like a reasonable assumption. In this scenario, we would expect to see about 6,000 fatalities from COVID-19 over the next three months. If Ohio’s leading causes of death are similar to what they were in 2017, this would make COVID-19 the sixth leading cause of death in the state, between stroke and Alzheimer’s disease.
A more optimistic scenario would be if Ohio’s social distancing could reduce its fatality rate to that of South Korea (1.7%), the country that has had the lowest fatality rates and has been seen as an international leader in COVID-19 response. In this case, Ohio would lose about 4,000 lives, dropping COVID-19 below Alzheimer’s to be the seventh leading cause of death.
Social distancing measures are designed to reduce hospital overuse and thus depress the fatality rate. We can use alternate fatality rates along with the OSU data to estimate how many people would die without social distancing. If the fatality rate did not change, a best-case scenario, 11,000 Ohioans would die, making COVID-19 the third-largest cause of death after heart disease and cancer. If fatality rates hit Italian levels, a worst-case scenario, 53,000 Ohioans would die of COVID-19, almost twice as many as died of cancer in 2017, making it by far the largest killer of Ohioans.
Data from Ohio Department of Health and Johns Hopkins University Center for Systems Science and Engineering
This means that in a conservative scenario where social distancing does nothing to suppress the fatality rate, about five thousand lives would be saved over the next three months just by reducing the infection rate, about the same as died of Alzheimer’s disease in Ohio throughout all of 2017. If hospital capacity constraints would exacerbate the fatality rate even moderately, bringing Ohio’s fatality rate to the global fatality rate of 5%, social distancing could save almost 17,000 lives over the next three months and if social distancing would prevent Italian-level fatality rates, social distancing could save nearly 50,000 lives. In short, Ohio State’s data suggests social distancing will save a lot of lives.