A Fast Nonparametric Sampling Method for Time to Event in Individual-Level Simulation Models.

The nonparametric sampling method is generic and can sample times to an event from any discrete (or discretizable) hazard without requiring any parametric assumption.The method is showcased with 5 commonly used distributions in discrete-event simulation models.The method produced very similar expected times to events, as well as their probability distribution, compared with analytical results.

Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent.

Purpose: Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized.

Quantification of influenza virus mini viral RNAs using Cas13.

Influenza A virus (IAV) RNA synthesis produces full-length and deletion-containing RNA molecules, which include defective viral genomes (DVG) and mini viral RNAs (mvRNA). Sequencing approaches have shown that DVG and mvRNA species may be present during infection, and that they can vary in size, segment origin, and sequence. Moreover, a subset of aberrant RNA molecules can bind and activate host-pathogen receptor retinoic acid-inducible gene I (RIG-I), leading to innate immune signaling and the expression of type I and III interferons.

Oscillating spatiotemporal patterns of COVID-19 in the United States.

COVID-19 case rates in the US wax and wane in wave-like patterns over time, but the spatial patterns of these temporal epidemic waves have not been well characterized. By analyzing state- and county-level COVID-19 case rate data for spatiotemporal decomposition modes and oscillatory patterns, we demonstrate that the transmission dynamics of COVID-19 feature recurrent spatiotemporal patterns. In addition to the well-recognized national-level annual mid-winter surges, we demonstrate a prominent but previously unrecognized six-month north-south oscillation in the eastern US (Eastern US COVID-19 Oscillator-EUCO) that gives rise to regional sub-epidemics and travelling epidemic waves.