The COVID-19 curve may be emblematic of the global pandemic, but the ubiquitous graphic doesn’t accurately represent the dynamics of the spread of the disease—or the full benefits of slowing its spread.
That’s according to Assistant Professor of Biology Chris Moore, an ecologist who studies the distribution and abundance of organisms—and disease, disease ecology, and disease modeling.
Moore acknowledges that it’s of the utmost importance that we flatten the COVID-19 curve so that the number of people sickened by the virus at any one time is kept below the treatment capacity of our healthcare system. But the national discussion around that issue, he says, has missed other benefits of slowing the spread of the disease, including not only stretching the curve over a longer period of time, but also reducing the total number of infections and gives the healthcare industry time to produce much-needed supplies like PPE and ventilators.
“There are aspects of the dynamics of the disease that are sometimes misrepresented,” Moore said, pointing out that some COVID-19 curve graphics are accurate but others are not, and aren’t derived from the reality of epidemiological processes, including transmission rates and recovery rates. In fact, the curve associated with COVID-19 should be more of an asymmetrical hump derived from epidemiological models. The bell-shape implies that a disease will dissipate at the same rate as it has spread. The reality, he said, is that the spread slows as the number of people who have been infected and survived increases.
“You have this balance of growth and then retardation,” he said, when describing how many infected people there are at any given time. Growth, in this case, is the rate at which people are transmitting the disease to one another; retardation means there are fewer people susceptible to the disease, whether that’s through distancing, immunity, vaccination, or death.
A COVID-19 curve that more accurately reflected the typical spread of disease would have a steep increase on the left side, as the infection spread in a susceptible population, and then an increasingly gradual and longer downward slope representing the slowing infection rate, Moore said. It’s analogous to fire, he said. “It’s going to come in and burn really, really quickly, but then it will smolder for a long time.”
Moore says this points to the importance of ongoing mitigation efforts. “When that epidemic peak is delayed, the total number that are infected is fewer,” he said, because the number of susceptible people is reduced as the disease in effect inoculates those who have been infected and are recovering. From a practical point of view, the delay would also allow more time for manufacturing of protective equipment and ventilators, meaning that fewer people would die because of a lack of hospital care.
“If we delay when we get this epidemic peak by even weeks or months, we would save thousands and thousands of lives,” Moore said.
He was planning a course on the ecology of disease this semester, focusing on Lyme disease. Then, in January, he began to see reports on social media from epidemiologists and public health professionals who were seeing a potential pandemic—the novel coronavirus. “I emailed my students (during Jan Plan, before the start of the semester) and said, ‘We should pay attention to this.’”
They did, with two weeks of the course devoted to COVID-19 as it spread in China and then Europe. Before classes were canceled and students left campus, Moore was focusing on risk and the effects of flattening the curve of the spread of a disease. “We actually built models to show what happens when you flatten the curve in terms of individuals,” he said. “It’s standard epidemiology where you have two groups—one that engages in high-risk activities and one that engages in low-risk activities.”
That model is based on one used for study of the spread of sexually transmitted diseases, but it transferred easily to COVID-19. “We could interpret that as those who are self-isolating and those who aren’t,” Moore said. “The students could get a mechanistic understanding of what happens when only thirty percent or fully seventy percent are self-quarantining. … They could change those values and see what effects that actually has on the epidemic size.”
The effect was dramatic.
“The propensity for populations to proliferate is just mind-blowing,” Moore said. “When you put an organism into an environment where it can thrive and reproduce, when two becomes four, four becomes eight—that kind of growth is so powerful, and it can be overwhelming in an instant. That’s exactly what happens with disease.”
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