We extend the baseline Susceptible-Exposed-Infectious-Recovered (SEIR) infectious disease epidemiology model to understand the role of testing and case-dependent quarantine. Our model nests the SEIR model. During a period of asymptomatic infection, testing can reveal infection that otherwise would only be revealed later when symptoms develop. Along with those displaying symptoms, such individuals are deemed known positive cases. Quarantine policy is case-dependent in that it can depend on whether a case is unknown, known positive, known negative, or recovered. Testing therefore makes possible the identification and quarantine of infected individuals and release of non-infected individuals. We fix a quarantine technology-a parameter determining the differential rate of transmission in quarantine-and compare simple testing and quarantine policies. We start with a baseline quarantine-only policy that replicates the rate at which individuals are entering quarantine in the US in March, 2020. We show that the total deaths that occur under this policy can occur under looser quarantine measures and a substantial increase in random testing of asymptomatic individuals. Testing at a higher rate in conjunction with targeted quarantine policies can (i) dampen the economic impact of the coronavirus and (ii) reduce peak symptomatic infections-relevant for hospital capacity constraints. Our model can be plugged into richer quantitative extensions of the SEIR model of the kind currently being used to forecast the effects of public health and economic policies.

BACKGROUND Poor medication adherence is a significant problem in hypertensive African Americans. Although motivational interviewing (MINT) is effective for adoption and maintenance of health behaviors in patients with chronic diseases, its effect on medication adherence remains untested in this population. METHODS This randomized controlled trial tested the effect of a practice-based MINT counseling versus usual care (UC) on medication adherence and blood pressure (BP) in 190 hypertensive African Americans (88% women; mean age 54 years). Patients were recruited from two community-based primary care practices in New York City. The primary outcome was adherence measured by electronic pill monitors; the secondary outcome was within-patient change in office BP from baseline to 12 months. RESULTS Baseline adherence was similar in both groups (56.2% and 56.6% for MINT and UC respectively, p = 0.94). Based on intent-to-treat analysis using mixed effects regression, a significant time X group interaction with model-predicted post-treatment adherence rates of 43% and 57% were found in the UC and MINT groups, respectively (p = 0.027), with a between-group difference of 14% (95% CI, −0.2% to −27%). The between-group difference in systolic and diastolic BP was −6.1 mm Hg (p = .065) and −1.4 mm Hg (p = .465), respectively, in favor of the MINT group. CONCLUSIONS A practice-based MINT counseling led to steady maintenance of medication adherence over time, compared to significant decline in adherence for UC patients. This effect was associated with a clinically meaningful net reduction in systolic BP in favor of the MINT group.

Off-label drug use is common in oncology, due in part to significant unmet medical need, the rarity of many cancers, and the difficulty of conducting randomized controlled trials (RCTs) to support labeling of every drug in every disease setting. As new drugs are developed for use in tumors defined by genomic aberrations, it may be scientifically reasonable to expect that a targeted anti-cancer agent with efficacy in a biomarker-defined population within one tumor type may also have activity in another tumor type expressing the same biomarker. Such expectations also fuel off-label prescribing. However, the current approach to prescribing targeted agents off-label does not capture patient outcomes, thus missing an opportunity to gather data that could validate this approach. We explore the potential for collecting such data, highlight two proposals for oncology-specific patient registries, and put forward considerations that should be addressed to move toward better evidence development around off-label use.