Estimating COVID-19 cases in Puerto Rico using an automated surveillance system.

Due to concerns regarding limited testing and accuracy of estimation of COVID-19 cases, we created an automated surveillance system called "Puerto Rico Epidemiological Evaluation and Prevention of COVID-19 and Influenza" (PREPCOVI) to evaluate COVID-19 incidence and time trends across Puerto Rico. Automated text message invitations were sent to random phone numbers with Puerto Rican area codes. In addition to reported COVID-19 test results, we used a published model to classify cases from specific symptoms (loss of smell and taste, severe persistent cough, severe fatigue, and skipped meals).

Conformational changes, diffusion and collective behavior in monomeric kinesin-based motility.

Molecular motors convert chemical energy into mechanical motion and power the transport of material within living cells; the motion of a motor is thought to be influenced by stochastic chemical state transitions of the molecule as well as intramolecular diffusion of one motor head seeking the next binding site. Existing models for the motility of single-headed monomeric motors that map the system to a simplified two-state Brownian ratchet have some predictive power, but in general are unable to elucidate the contributions of different molecular level processes to the overall effective parameters. In this work, we build a detailed molecular level model of monomeric kinesin motility that naturally incorporates conformational changes (power strokes) and biased diffusion.