Optimal diagnostic test allocation strategy during the COVID‐19 pandemic and beyond

Abstract

Timely diagnostic testing for active SARS-CoV-2 viral infections is key to controlling the spread of the virus and preventing severe disease. A central public health challenge is defining test allocation strategies with limited resources. In this paper, we provide a mathematical framework for defining an optimal strategy for allocating viral diagnostic tests. The framework accounts for imperfect test results, selective testing in certain high-risk patient populations, practical constraints in terms of budget and/or total number of available tests, and the purpose of testing. Our method is not only useful for detecting infections, but can also be used for long-time surveillance to detect new outbreaks. In our proposed approach, tests can be allocated across population strata defined by symptom severity and other patient characteristics, allowing the test allocation plan to prioritize higher risk patient populations. We illustrate our framework using historical data from the initial wave of the COVID-19 outbreak in New York City.We extend our proposed method to address the challenge of allocating two different types of diagnostic tests with different costs and accuracy, for example, the RT-PCR and the rapid antigen test (RAT), under budget constraints. We show how this latter framework can be useful to reopening of college campuses where university administrators are challenged with finite resources for community surveillance. We provide a R Shiny web application allowing users to explore test allocation strategies across a variety of pandemic scenarios. This work can serve as a useful tool for guiding public health decision-making at a community level and adapting testing plans to different stages of an epidemic.The conceptual framework has broader relevance beyond the current COVID-19 pandemic.

How could a pooled testing policy have performed in managing the early stages of the COVID‐19 pandemic? Results from a simulation study

“…This has been studied by other researchers for their individual testing policies but could be expanded to use pooled testing. 50 Pooled testing tends to work best in circumstances of low and relatively stable prevalence of the virus, as it means that a lot of the pools will come back negative. This reduces the number of individuals that have to be tested individually and so freeing up more tests for pools.…”

“…This means elderly people (and other groups at higher risk) would be more likely to be included in the pooled testing. This has been studied by other researchers for their individual testing policies but could be expanded to use pooled testing 50 …”

Monitoring epidemic processes under political measures

“…Thus, PCR tests are considered the gold standard in comparison to antibody and antigen tests. 55,56 Since the growth of infections occurs over time, it is necessary to observe the general patterns over a period of time and determine if it is progressive or persistent. Below we visualize the run of performed PCR tests and corresponding COVID-19 reported infections (see Figure 2) as well as their normalized variants, that is, infection rates (see Figure 3, which includes COVID-19 waves and VOC curves as well) for CW 11/2020-04/2023.…”

“…In contrast, antigen tests are very specific but not sensitive, so assuming active infection against a negative test result needs to be confirmed in turn with a PCR test. Thus, PCR tests are considered the gold standard in comparison to antibody and antigen tests 55,56 …”

A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19

“…The rapid adoption of commercial wearable devices such as smartwatches and activity trackers brings forth opportunities to apply artificial intelligence methods toward the development of novel tools to support an intelligent disease detection infrastructure. Methods such as reinforcement learning or graph neural networks have already been proposed to aid contact tracing and surveillance testing 18 , 19 . Multiple studies suggest the utility of digital biomarkers, objective and quantifiable digitally collected physiological and behavioral data (e.g., resting heart rate (RHR), step count, sleep duration, and respiratory rate), collected by consumer devices along with patient-reported symptoms to monitor the progression of respiratory and influenza-like illnesses 20 – 27 .…”