Correction: Inferring school district learning modalities during the COVID-19 pandemic with a hidden Markov model.

[This corrects the article DOI: 10.1371/journal.pone.0292354.].

Inferring school district learning modalities during the COVID-19 pandemic with a hidden Markov model.

During the COVID-19 pandemic, many public schools across the United States shifted from fully in-person learning to alternative learning modalities such as hybrid and fully remote learning. In this study, data from 14,688 unique school districts from August 2020 to June 2021 were collected to track changes in the proportion of schools offering fully in-person, hybrid and fully remote learning over time. These data were provided by Burbio, MCH Strategic Data, the American Enterprise Institute's Return to Learn Tracker and individual state dashboards. Because the modalities reported by these sources were incomplete and occasionally misaligned, a model was needed to combine and deconflict these data to provide a more comprehensive description of modalities nationwide. A hidden Markov model (HMM) was used to infer the most likely learning modality for each district on a weekly basis. This method yielded higher spatiotemporal coverage than any individual data source and higher agreement with three of the four data sources than any other single source. The model output revealed that the percentage of districts offering fully in-person learning rose from 40.3% in September 2020 to 54.7% in June of 2021 with increases across 45 states and in both urban and rural districts. This type of probabilistic model can serve as a tool for fusion of incomplete and contradictory data sources in order to obtain more reliable data in support of public health surveillance and research efforts.

Gecko: A time-series model for COVID-19 hospital admission forecasting.

During the COVID-19 pandemic, concerns about hospital capacity in the United States led to a demand for models that forecast COVID-19 hospital admissions. These short-term forecasts were needed to support planning efforts by providing decision-makers with insight about future demands for health care capacity and resources. We present a SARIMA time-series model called Gecko developed for this purpose. We evaluate its historical performance using metrics such as mean absolute error, predictive interval coverage, and weighted interval scores, and compare to alternative hospital admission forecasting models. We find that Gecko outperformed baseline approaches and was among the most accurate models for forecasting hospital admissions at the state and national levels from January-May 2021. This work suggests that simple statistical methods can provide a viable alternative to traditional epidemic models for short-term forecasting.

Promotion of Myogenic Maturation by Timely Application of Electric Field Along the Topographical Alignment.

Engineered muscular substitutes can restore the impaired muscle functions when integrated properly into the host tissue. To generate functional muscles with sufficient contractility at the site of transplant, the in vitro construction of fully differentiated muscle fibers would be desired. Many previous reports have identified either topographical alignment or electrical stimulation as an effective tool to promote myogenic differentiation. However, optimization of spatial and temporal arrangement of these two physical cues for better differentiation and maturation of skeletal muscles has not been investigated. In this article, we introduce a novel cell culture system that allows simultaneous application of these two independent directional cues at both orthogonal and parallel arrangements. We then show that the parallel arrangement of the aligned topography and the electric field synergistically facilitates better differentiation and maturation of C2C12, generating myotubes with more fused nuclei. Addition of the electric stimulation at the late stage of myogenic differentiation is found to further improve cell fusion to form multinucleate myotubes through a phosphatidylinositol-3-OH-kinase-dependent pathway. As such, we successfully demonstrated that the combined stimulation of topographical and electrical cues could effectively enhance both myogenic differentiation and maturation in a temporal and orientation-dependent manner, providing the basis for therapeutic strategies for regenerative tissue engineering.