Medical Student Experience and Outcomes, as Well as Preceptor Experience, with Rapid Conversion of a Preclinical Medical School Course to a Remote-Based Learning Format in the Setting of the COVID-19 Pandemic

Objectives To assess student outcomes and experiences, as well as preceptor experiences, after emergently converting a preclinical medical school renal course to a remote setting during the COVID-19 pandemic. Methods First-year medical student examination scores and responses to Likert-scale questions on end-of-course evaluations from the 2018–2019 (traditional) and 2019–2020 (remote) academic years were compared. Free-text responses from students and preceptors were analyzed using a qualitative summative approach to extract major themes in perceptions of remote learning. Results Mean student scores on course examinations did not significantly differ between the traditional and remote settings (p = 0.23 and 0.84 respectively). Quantitative analysis of student evaluations revealed no significant difference across all items in mean Likert-scale responses. Student and preceptor free-text responses identified course leader engagement and responsiveness as essential to the success of remote-based learning. Optimal group size and online etiquette are areas that require attention. Conclusions Despite rapid conversion of a preclinical medical school renal course to a remote-based format in the setting of the COVID-19 pandemic, student scores and evaluations remain positive and largely unchanged.

Pooling Strategy Optimization for Accelerating Asymptomatic COVID-19 Screening

Testing has been a major factor that limits our response to the COVID-19 pandemic. The method of sample pooling and group test has recently been introduced. However, it is still not clearly known how to determine the appropriate group size. In this paper, we develop an analytical method and a numerical algorithm to determine the optimal group size, which minimizes the total number of tests, maximizes the speedup of the pooling strategy, and minimizes both time and cost of testing. The optimal group size is determined by the fraction of infected people and independent of the size of the population. Furthermore, both the optimal pooling size and the achieved speedup grow exponentially with the reciprocal of the fraction of infected people, a quite impressive and nontrivial result. Our method is effective in supporting faster and cheaper asymptomatic COVID-19 screening. Our research has important social implications and financial impacts. For example, if the percentage of infected people is 0.001, we can achieve speedup of almost 16, which means that months of testing time can be reduced to days, and over 93% of the testing cost can be saved. Such a result has not been available in the known literature, and is a significant progress and great advance in pooling strategy optimization for accelerating asymptomatic COVID-19 screening.

Changes in group size during resource shifts reveal drivers of sociality across the tree of life

ABSTRACTFrom biofilms to whale pods, organisms have repeatedly converged on sociality as a strategy to improve individual fitness. Yet, it remains challenging to identify the most important drivers—and by extension, the evolutionary mechanisms—of sociality for particular species. Here, we present a conceptual framework, literature review, and model demonstrating that the direction and magnitude of the response of group size to sudden resource shifts provides a strong indication of the underlying drivers of sociality. We catalog six functionally distinct mechanisms related to the acquisition of resources, and we model these mechanisms’ effects on the survival of individuals foraging in groups. We find that whether, and to what degree, optimal group size increases, decreases, or remains constant when resource abundance declines depends strongly on the dominant mechanism. Existing empirical data support our model predictions, and we demonstrate how our framework can be used to predict the dominant social benefit for particular species. Together, our framework and results show that a single easily measurable characteristic, namely, group size under different resource abundances, can illuminate the potential drivers of sociality across the tree of life.