Duration of Behavioral Policy Interventions and Incidence of COVID-19 by Social Vulnerability of US Counties, April-December 2020.

OBJECTIVE: State-issued behavioral policy interventions (BPIs) can limit community spread of COVID-19, but their effects on COVID-19 transmission may vary by level of social vulnerability in the community. We examined the association between the duration of BPIs and the incidence of COVID-19 across levels of social vulnerability in US counties. METHODS: We used COVID-19 case counts from USAFacts and policy data on BPIs (face mask mandates, stay-at-home orders, gathering bans) in place from April through December 2020 and the 2018 Social Vulnerability Index (SVI) from the Centers for Disease Control and Prevention. We conducted multilevel linear regression to estimate the associations between duration of each BPI and monthly incidence of COVID-19 (cases per 100 000 population) by SVI quartiles (grouped as low, moderate low, moderate high, and high social vulnerability) for 3141 US counties. RESULTS: Having a BPI in place for longer durations (ie, ≥2 months) was associated with lower incidence of COVID-19 compared with having a BPI in place for <1 month. Compared with having no BPI in place or a BPI in place for <1 month, differences in marginal mean monthly incidence of COVID-19 per 100 000 population for a BPI in place for ≥2 months ranged from -4 cases in counties with low SVI to -401 cases in counties with high SVI for face mask mandates, from -31 cases in counties with low SVI to -208 cases in counties with high SVI for stay-at-home orders, and from -227 cases in counties with low SVI to -628 cases in counties with high SVI for gathering bans. CONCLUSIONS: Establishing COVID-19 prevention measures for longer durations may help reduce COVID-19 transmission, especially in communities with high levels of social vulnerability.

Evaluation of a Clinical Decision Support System for the most evidence-based approach to managing perioperative anticoagulation.

STUDY OBJECTIVE: We explored the feasibility of a Clinical Decision Support System (CDSS) to guide evidence-based perioperative anticoagulation. DESIGN: Prospective randomised clinical management simulation multicentre study. SETTING: Five University and 11 general hospitals in Germany. PARTICIPANTS: We enrolled physicians (anaesthesiologist (n = 73), trauma surgeons (n = 2), unknown (n = 1)) with different professional experience. INTERVENTIONS: A CDSS based on a multiple-choice test was developed and validated at the University Hospital of Frankfurt (phase-I). The CDSS comprised European guidelines for the management of anticoagulation in cardiology, cardio-thoracic, non-cardio-thoracic surgery and anaesthesiology. Phase-II compared the efficiency of physicians in identifying evidence-based approach of managing perioperative anticoagulation. In total 168 physicians were randomised to CDSS (PERI-KOAG) or CONTROL. MEASUREMENTS: Overall mean score and association of processing time and professional experience were analysed. The multiple-choice test consists of 11 cases and two correct answers per question were required to gain 100% success rate (=22 points). MAIN RESULTS: In total 76 physicians completed the questionnaire (n = 42 PERI-KOAG; n = 34 CONTROL; attrition rate 54%). Overall mean score (max. 100% = 22 points) was significantly higher in PERI-KOAG compared to CONTROL (82 ± 15% vs. 70 ± 10%; 18 ± 3 vs. 15 ± 2 points; P = 0.0003). A longer processing time is associated with significantly increased overall mean scores in PERI-KOAG (≥33 min. 89 ± 10% (20 ± 2 points) vs. <33 min. 73 ± 15% (16 ± 3 points), P = 0.0005) but not in CONTROL (≥33 min. 74 ± 13% (16 ± 3 points) vs. <33 min. 69 ± 9% (15 ± 2 points), P = 0.11). Within PERI-KOAG, there is a tendency towards higher results within the more experienced group (>5 years), but no significant difference to less (≤5 years) experienced colleagues (87 ± 10% (19 ± 2 points) vs. 78 ± 17% (17 ± 4 points), P = 0.08). However, an association between professional experience and success rate in CONTROL has not been shown (71 ± 8% vs. 70 ± 13%, 16 ± 2 vs. 15 ± 3 points; P = 0.66). CONCLUSIONS: CDSS significantly improved the identification of evidence-based treatment approaches. A precise usage of CDSS is mandatory to maximise efficiency.

The Impact of Covid-19 State Closure Orders on Consumer Spending, Employment, and Business Revenue.

CONTEXT: In response to the COVID-19 pandemic, states across the United States implemented various strategies to mitigate transmission of SARS-CoV-2 (the virus that causes COVID-19). OBJECTIVE: To examine the effect of COVID-19-related state closures on consumer spending, business revenue, and employment, while controlling for changes in COVID-19 incidence and death. DESIGN: The analysis estimated a difference-in-difference model, utilizing temporal and geographic variation in state closure orders to analyze their impact on the economy, while controlling for COVID-19 incidence and death. PARTICIPANTS: State-level data on economic outcomes from the Opportunity Insights data tracker and COVID-19 cases and death data from usafacts.org. INTERVENTIONS: The mitigation strategy analyzed within this study was COVID-19-related state closure orders. Data on these orders were obtained from state government Web sites containing executive or administrative orders. MAIN OUTCOME MEASURES: Outcomes include state-level estimates of consumer spending, business revenue, and employment levels. RESULTS: Analyses showed that although state closures led to a decrease in consumer spending, business revenue, and employment, they accounted for only a small portion of the observed decreases in these outcomes over the first wave of COVID-19. CONCLUSIONS: The impact of COVID-19 on economic activity likely reflects a combination of factors, in addition to state closures, such as individuals' perceptions of risk related to COVID-19 incidence, which may play significant roles in impacting economic activity.