Forecasting the impact of coronavirus disease during delivery hospitalization: an aid for resource utilization.

Background: The ongoing coronavirus disease 2019 pandemic has severely affected the United States. During infectious disease outbreaks, forecasting models are often developed to inform resource utilization. Pregnancy and delivery pose unique challenges, given the altered maternal immune system and the fact that most American women choose to deliver in the hospital setting. Objective: This study aimed to forecast the first pandemic wave of coronavirus disease 2019 in the general population and the incidence of severe, critical, and fatal coronavirus disease 2019 cases during delivery hospitalization in the United States. Study Design: We used a phenomenological model to forecast the incidence of the first wave of coronavirus disease 2019 in the United States. Incidence data from March 1, 2020, to April 14, 2020, were used to calibrate the generalized logistic growth model. Subsequently, Monte Carlo simulation was performed for each week from March 1, 2020, to estimate the incidence of coronavirus disease 2019 for delivery hospitalizations during the first pandemic wave using the available data estimate. Results: From March 1, 2020, our model forecasted a total of 860,475 cases of coronavirus disease 2019 in the general population across the United States for the first pandemic wave. The cumulative incidence of coronavirus disease 2019 during delivery hospitalization is anticipated to be 16,601 (95% confidence interval, 9711-23,491) cases, 3308 (95% confidence interval, 1755-4861) cases of which are expected to be severe, 681 (95% confidence interval, 1324-1038) critical, and 52 (95% confidence interval, 23-81) fatal. Assuming similar baseline maternal mortality rate as the year 2018, we projected an increase in maternal mortality rate in the United States to at least 18.7 (95% confidence interval, 18.0-19.5) deaths per 100,000 live births as a direct result of coronavirus disease 2019. Conclusion: Coronavirus disease 2019 in pregnant women is expected to severely affect obstetrical care. From March 1, 2020, we forecast 3308 severe and 681 critical cases with about 52 coronavirus disease 2019-related maternal mortalities during delivery hospitalization for the first pandemic wave in the United States. These results are significant for informing counseling and resource allocation.

How cockroaches exploit tactile boundaries to find new shelters.

Animals such as cockroaches depend on exploration of unknown environments, and their strategies may inspire robotic approaches. We have previously shown that cockroach behavior, with respect to shelters and the walls of an otherwise empty arena, can be captured with a stochastic state-based algorithm. We call this algorithm RAMBLER, randomized algorithm mimicking biased lone exploration in roaches. In this work, we verified and extended this model by adding a barrier in the previously used arena and conducted more cockroach experiments. In two arena configurations, our simulated model's path length distribution was similar to the experimental distribution (mean experimental path length 3.4 and 3.2 m, mean simulated path length 3.9 and 3.3 m). By analyzing cockroach behavior before, along, and at the end of the barrier, we have generalized RAMBLER to address arbitrarily complex 2D mazes. For biology, this is an abstract behavioral model of a decision-making process in the cockroach brain. For robotics, this is a strategy that may improve exploration for goals, especially in unpredictable environments with non-convex obstacles. Generally, cockroach behavior seems to recommend variability in the absence of planning, and following paths defined by walls.

Encoding wide-field motion and direction in the central complex of the cockroach Blaberus discoidalis.

In the arthropod brain, the central complex (CX) receives various forms of sensory signals and is associated with motor functions, but its precise role in behavior is controversial. The optomotor response is a highly conserved turning behavior directed by visual motion. In tethered cockroaches, 20% procaine injected into the CX reversibly blocked this behavior. We then used multichannel extracellular recording to sample unit activity in the CX in response to wide-field visual motion stimuli, moving either horizontally or vertically at various temporal frequencies. For the 401 units we sampled, we identified five stereotyped response patterns: tonically inhibited or excited responses during motion, phasically inhibited or excited responses at the initiation of motion, and phasically excited responses at the termination of motion. Sixty-seven percent of the units responded to horizontal motion, while only 19% responded to vertical motion. Thirty-eight percent of responding units were directionally selective to horizontal motion. Response type and directional selectivity were sometimes conditional with other stimulus parameters, such as temporal frequency. For instance, 16% of the units that responded tonically to low temporal frequencies responded phasically to high temporal frequencies. In addition, we found that 26% of wide-field motion responding units showed a periodic response that was entrained to the temporal frequency of the stimulus. Our results show a diverse population of neurons within the CX that are variably tuned to wide-field motion parameters. Our behavioral data further suggest that such CX activity is required for effective optomotor responses.