Faculty in the department of Statistics at the University of Washington are actively engaged in research related to COVID-19. Here we focus on a few of these efforts.
Boeing International Professor Adrian Raftery has been appointed as a founding member of the Executive Committee of the National Academy of Sciences Societal Experts Action Network (SEAN) set up in collaboration with NSF to coordinate the NAS response to COVID-19 questions in the area.
Professor of Statistics and Computer Science Sham Kakade is leading the CovidSafe app project. This app, which will be available on both the Android and IOS platforms, will help contact tracers slow the spread of the virus. You can listen to a recent interview that Sham gave with KUOW’s Bill Radke here.
Associate Professor of Statistics and Sociology Tyler McCormick is involved in a multidisciplinary proposal for a community and healthcare facility based testing strategy, aimed at helping policymakers who are forced to make decisions in the face of uncertainties about the coronavirus. The strategy uses a combination of risk-stratified testing and sequential decision-making to quickly identify changes in COVID-19 cases within small geographic areas.
Together with Associate Professor Rachel Heath of the Department of Economics, McCormick has also begun to develop and implement a sampling strategy for workers in manufacturing settings. The project focuses on manufacturing workers in low-resource settings and uses a mobile-phone based network sampling approach to quickly obtain representative samples of workers when traditional in-person data collection is not possible, with the goal of obtaining insights about the scope and scale of COVID-19 responses in the workplace. This work is funded by a UW Population Health Initiative rapid response grant.
Assistant Professor Alex Luedtke is collaborating with researchers at Johns Hopkins University, Emory, and Weill-Cornell to identify statistical methods for the analysis of COVID-19 therapeutic trials that require smaller sample sizes compared to standard statistical approaches. They have shown that their proposed approaches can achieve the same power as competing approaches using 10-20% fewer samples. Their initial results have been posted on medRxiv.
In addition, Luedtke is developing statistical methods to be used in the primary analyses of several upcoming NIH-sponsored COVID-19 vaccine efficacy trials. Luedtke will also be part of a small group of independent biostatisticians working on an effort to use harmonized statistical analyses to analyze data from these trials. Furthermore, he is involved in writing the statistical analysis plan for the WHO Solidarity trail for COVID-19 vaccines.
Associate Professor of Statistics & Computer Science and Engineering Emily Fox has used Apple Maps mobility data to develop an epidemiological model to infer the impact of human mobility on SARS-CoV-2 transmission in the United States. This framework enables real-time tracking of the effective reproductive number and forecasting of transmission under different mobility policies, informing both intervention evaluations and surge planning for healthcare systems. A pre-print of Fox’s work can be found on MedRxiv.
Professor Jon Wakefield is working with Department of Statistics alum Zehang Richard Li and epidemiology graduate student Julianne Meisner on estimating the excess mortality that may be attributable to COVID-19. They are using space-time smoothing with a delayed reporting model and are looking at county level data in the US.
We are grateful to these and other members of the Statistics faculty who have rapidly reprioritized their research to serve our broad community as we cope with the COVID-19 pandemic.