FlattenTheCurve

Can a partially effective vaccine flatten the curve?

by George Taniwaki

During this Covid-19 pandemic, we want to know when we can stop sheltering at home and go back into public spaces again. Further, we want to know which actions can speed up the time before that can happen.

One thing we do know is that when dealing with a novel disease (one that no human appears to have immunity for), the entire population cannot go back to pre-epidemic behavior at the same time before it is safe. Doing so will cause a spike in infections and deaths. This will terrorize the population leading to another round of isolation. If the public loses faith that the government knows when it is safe to change behavior, then when it finally is safe, people will still be afraid and time will be lost during the recovery, causing additional economic hardship.

So when can we go back to normal? I think that can happen only after herd immunity is achieved. This can take a very long time as a trickle of individuals become infected and recover with resistance or die, a process called flattening the curve. Or it can happen pretty quickly after the wide-spread inoculation of individuals with a safe and effective vaccine.

An effective vaccine may take 18 to 24 months to develop. Many people, including President Donald Trump, think staying home this long is unrealistic. Is it possible to shorten that time by releasing a partially effective vaccine sooner? Doing so may help flatten the curve without requiring social distancing.

Partially effective vaccines

An intriguing paper by Eduard Talamàs & Rakesh Vohra, entitled “Free and perfectly safe but only partially effective vaccines can harm everyone” pretty much contains the answer in its title.

The idea is that a partially effective vaccine will cause people to change their behavior too much, too soon, causing the spike we want to avoid. The conclusion is similar to the analysis popularized by Sam Peltzman of the Univ. Chicago (a microeconomics professor while I was a student there) who suggested that stricter automobile safety regulations could lead to increased deaths (of pedestrians) as drivers felt safer and became more reckless (J Polit Econ, Aug 1975).

The most important conclusion in Talamàs et al., is that with overlapping social networks, even those who do not increase the size of their networks after the introduction of the vaccine can be harmed by those who do. This conclusion is slightly different than those of most epidemiological models that assume random contact between individuals rather than strategic networks. A good description of the paper is given by one of the authors, Vohra, at The Leisure of the Theory Class (Apr 2020).