Evaluating COVID-19 Exposure Notification Effectiveness With SimAEN: A Simulation Tool Designed for Public Health Decision Making.

OBJECTIVES: Exposure notification (EN) supplements traditional contact tracing by using proximity sensors in smartphones to record close contact between persons. This ledger is used to alert persons of potential SARS-CoV-2 exposure, so they can quarantine until their infection status is determined. We describe a model that estimates the impact of EN implementation on reducing the spread of SARS-CoV-2 and on the workload of public health officials, in combination with other key public health interventions such as traditional contact tracing, face mask wearing, and testing. METHODS: We created an agent-based model, Simulated Automated Exposure Notification (SimAEN), to explore the effectiveness of EN to slow the spread of SARS-CoV-2. We varied selected simulation variables, such as population adoption of EN and EN detector sensitivity configurations, to illustrate the potential effects of EN. We executed 20 simulations with SimAEN for each scenario and derived results for each simulation. RESULTS: When more sensitive versus more specific EN configurations were compared, the effective reproductive number, RE, was minimally affected (a decrease <0.03). For scenarios with increasing levels of EN adoption, an increasing number of additional infected persons were identified through EN, and total infection counts in the simulated population decreased; RE values for this scenario decreased with increasing EN adoption (a decrease of 0.1 to 0.2 depending on the scenario). CONCLUSIONS: Estimates from SimAEN can help public health officials determine which levels of EN adoption in combination with other public health interventions can maximize prevention of COVID-19 while minimizing unnecessary quarantine in their jurisdiction.

Developing strategies for three-dimensional imaging of oxygen tension in the rodent retina.

Insufficient oxygen delivery and retinal hypoxia have been implicated as causal in the development of many devastating diseases of the eye. While the two-dimensional imaging of retinal oxygen tension (PO2) has now been applied in a variety of different animal models, it is fundamentally a luminescence-based system lacking depth discrimination. However, mammalian retinal tissue is nourished by two distinct vascular beds, the retinal and the choroidal vasculatures, and they are exceedingly difficult to separate using traditional two-dimensional imaging strategies. Numerous studies have demonstrated that retinal and choroidal PO2 differ substantially. Therefore, the single PO2 value currently returned through data analysis cannot accurately represent the separate contributions of the choroidal and retinal vasculatures to the state of retinal oxygenation. Such a separation would significantly advance our understanding of oxygen delivery dynamics in these two very distinct vasculatures. In this study, we investigate new strategies for generating separate retinal and choroidal PO2 maps in the rodent retina using our existing phosphorescence-based lifetime imaging system.