The COVID-19 pandemic has brought into sharp focus the need to harness and leverage our digital infrastructure for remote patient monitoring. As current viral tests and vaccines are slow to emerge, we see a need for more robust disease detection and monitoring of individual and population health, which could be aided by wearable sensors. While the utility of this technology has been used to correlate physiological metrics to daily living and human performance, the translation of such technology toward predicting the incidence of COVID-19 remains a necessity. When used in conjunction with predictive platforms, users of wearable devices could be alerted when changes in their metrics match those associated with COVID-19. Anonymous data localized to regions such as neighborhoods or zip codes could provide public health officials and researchers a valuable tool to track and mitigate the spread of the virus, particularly during a second wave. Identifiable data, for example remote monitoring of cohorts (family, businesses, and facilities) associated with individuals diagnosed with COVID-19, can provide valuable data such as acceleration of transmission and symptom onset. This manuscript describes clinically relevant physiological metrics which can be measured from commercial devices today and highlights their role in tracking the health, stability, and recovery of COVID-19+ individuals and front-line workers. Our goal disseminating from this paper is to initiate a call to action among front-line workers and engineers toward developing digital health platforms for monitoring and managing this pandemic.

Current estimates of terrestrial bird losses across Europe from ingestion of lead ammunition are based on uncertain or generic assumptions. A method is needed to develop defensible European-specific estimates compatible with available data that does not require long-term field studies. We propose a 2-step method using carcass data and population models. The method estimates percentage of deaths diagnosed as directly caused by lead poisoning as a lower bound and, as an upper bound, the percentage of possible deaths from sublethal lead poisoning that weakens birds, making them susceptible to death by other causes. We use these estimates to modify known population-level annual mortality. Our method also allows for potential reductions in reproduction from lead shot ingestion because reductions in survival and reproduction are entered into population models of species with life histories representative of the most groups of susceptible species. The models estimate the sustainability and potential population decreases from lead poisoning in Europe. Using the best available data, we demonstrate the method on two taxonomic groups of birds: gallinaceous birds and diurnal raptors. The direction of the population trends affects the estimate, and we incorporated such trends into the method. Our midpoint estimates of the reduction in population size of the European gallinaceous bird (< 2%) group and raptor group (2.9–7.7%) depend on the species life history, maximum growth rate, population trend, and if reproduction is assumed to be reduced. Our estimates can be refined as more information becomes available in countries with data gaps. We advocate use of this method to improve upon or supplement approaches currently being used. As we demonstrate, the method also can be applied to individual species of concern if enough data across countries are available.

TESTING CAMERA TRAP DENSITY ESTIMATES FROM THE SPATIAL CAPTURE MODEL AND CALIBRATED CAPTURE RATE INDICES AGAINST KANGAROO RAT (DIPODOMYS SPP.) LIVE TRAPPING DATA by Timothy A. Walker Camera trapping studies often focus on estimating population density, which is critical for managing wild populations. Density estimators typically require unique markers such as stripe patterns to identify individuals but most animals do not have such markings. The spatial capture model (SC model; Chandler & Royle, 2013) estimates density without individual identification but lacks sufficient field testing. Here, both the SC model and calibrated capture rate indices were compared against ten sessions of live trapping data on kangaroo rats (Dipodomys spp). These camera and live trapping data were combined in a joint-likelihood model to further compare the two methods. From these comparisons, the factors governing the SC model's success were scrutinized. Additionally, a method for estimating missed captures was developed and tested here. Regressions comparing live trapping density to the SC model density and capture rate were significant only for the capture rate comparison. Missed image rate had a significant relationship with ambient nighttime temperatures but only marginally improved the capture rate index calibration. Results showed the SC model was highly sensitive to deviations from its movement model, producing potentially misleading results. The model may be effective only when movement assumptions hold. Several factors such as camera coverage area, microhabitat, and burrow locations could be incorporated into the SC model density estimation process to improve precision and inference. Table 5. List of summary statistics for each of the CT sessions including information on the number of triggered captures, the number of interval captures, miss rates, average temperatures, camera effort, and amount of camera outages.

We review the documentary All Things Must Pass: The Rise and Fall of Tower Records as a teaching tool for Entrepreneurship and Strategic Management. Through celebrity and former employee interviews, the film covers the founding, expansion, and eventual failure of the Tower Records music retailer. This review highlights many of the film’s key concepts: entrepreneurial opportunity recognition, organizational growth, and industry decline from disruptive technologies. All Things Must Pass is a useful teaching tool that engages in ways that elude most written cases.