というNBER論文をアンドリュー・ローらが書いている。原題は「A Cost/Benefit Analysis of Clinical Trial Designs for COVID-19 Vaccine Candidates」で、著者はDonald A. Berry(ベリー・コンサルタンツLLC*1)、Scott Berry(同)、Peter Hale(ワクチン研究基金*2)、Leah Isakov(セキーラス*3), Andrew W. Lo(MIT)、Kien Wei Siah(同)、Chi Heem Wong(同)。

We compare and contrast the expected duration and number of infections and deaths averted among several designs for clinical trials of COVID-19 vaccine candidates, including traditional randomized clinical trials and adaptive and human challenge trials. Using epidemiological models calibrated to the current pandemic, we simulate the time course of each clinical trial design for 504 unique combinations of parameters, allowing us to determine which trial design is most effective for a given scenario. A human challenge trial provides maximal net benefits—averting an additional 1.1M infections and 8,000 deaths in the U.S. compared to the next best clinical trial design—if its set-up time is short or the pandemic spreads slowly. In most of the other cases, an adaptive trial provides greater net benefits.