Strategies for responding to the COVID-19 pandemic in a rural health system in New York state.

Research and media reports about coronavirus disease 2019 (COVID-19) have largely focused on urban areas due to their high caseloads. However, the COVID-19 pandemic presents distinct and under-recognized challenges to rural areas. This report describes the challenges faced by Bassett Healthcare Network (BHN), a health network in rural upstate New York, and the strategies BHN devised in response. The response to COVID-19 at BHN focused on 4 strategies: (1) Expansion of intensive-care capacity. (2) Redeployment and retraining of workforce. (3) Provision of COVID-19 information, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral testing, and appropriate follow-up for a geographically dispersed population. (4) Coordination of the response to the pandemic across a large, diverse organization. Rural health systems and hospitals can take steps to address the specific challenges posed by the COVID-19 pandemic in their communities. We believe that the strategies BHN employed to adapt to COVID-19 may be useful to other rural health systems. More research is needed to determine which strategies have been most effective in responding to the pandemic in other rural settings.

Cost-effectiveness of Frequent HIV Screening Among High-risk Young Men Who Have Sex With Men in the United States.

BACKGROUND: Of new HIV infections in the US, 20% occur among young men who have sex with men (YMSM, ages 13-24), but >50% of YMSM with HIV are unaware of their status. Using Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN) data, we projected the clinical benefit and cost-effectiveness of frequent HIV screening among high-risk YMSM from age 15. METHODS: Using a mathematical simulation, we examined 3 screening strategies: Yearly, 6-monthly, and 3-monthly, each in addition to the Status quo (SQ, 0.7-10.3% screened/year, stratified by age). We used published data (YMSM-specific when available) including: HIV incidences (0.91-6.41/100PY); screen acceptance (80%), linkage-to-care/antiretroviral therapy (ART) initiation (76%), HIV transmission (0.3-86.1/100PY, by HIV RNA), monthly ART costs ($2290-$3780), and HIV per-screen costs ($38). Projected outcomes included CD4 count at diagnosis, primary HIV transmissions from ages 15-30, quality-adjusted life expectancy, costs, and incremental cost-effectiveness ratios (ICERs, $/quality-adjusted life-year saved [QALY]; threshold ≤$100 000/QALY). RESULTS: Compared to SQ, all strategies increased projected CD4 at diagnosis (296 to 477-515 cells/µL) and quality-adjusted life expectancy from age 15 (44.4 to 48.3-48.7 years) among YMSM acquiring HIV. Compared to SQ, all strategies increased discounted lifetime cost for the entire population ($170 800 to $178 100-$185 000/person). Screening 3-monthly was cost-effective (ICER: $4500/QALY) compared to SQ and reduced primary transmissions through age 30 by 40%. Results were most sensitive to transmission rates; excluding the impact of transmissions, screening Yearly was ≤$100 000/QALY (ICER: $70 900/QALY). CONCLUSIONS: For high-risk YMSM in the US, HIV screening 3-monthly compared to less frequent screening will improve clinical outcomes and be cost-effective.

Identifying global research gaps to mitigate antimicrobial resistance: A scoping review.

OBJECTIVE: Identify research gaps relevant to the global effort to combat antimicrobial resistance. METHODS: Web of Science, PubMed, Scopus, and Ovid MEDLINE were searched for reviews on antimicrobial resistance published between January 1, 2015 and December 31, 2019. Recommendations for future research were identified. FINDINGS: Seventy-four reviews met inclusion criteria; 300 research gaps and recommendations were identified. The largest number were from the human health sector (105; 35%) followed by environmental health (72; 23%), animal health (66; 22%), food and feed (14; 5%), and plants and crops (8; 3%); 35 (12%) involved more than one sector. The largest number of gaps concerned surveillance of resistance (68; 23%), followed by study design or methodology (52; 17%), interventions (41; 14%), risk assessment and modeling (35; 12%), ecological (26; 9%) and biochemical (28; 9%) aspects of resistance, interface between reservoirs of resistant pathogens (24; 8%), and economic (15; 5%) and awareness- and behavior-related (11; 4%) aspects of antimicrobial resistance. CONCLUSIONS: Important research gaps remain in our complete understanding of antimicrobial resistance, and more research is needed about its development, transmission, and impact across the interface of human, animal, and environmental reservoirs.

Novel microsimulation model of tobacco use behaviours and outcomes: calibration and validation in a US population.

BACKGROUND AND OBJECTIVE: Simulation models can project effects of tobacco use and cessation and inform tobacco control policies. Most existing tobacco models do not explicitly include relapse, a key component of the natural history of tobacco use. Our objective was to develop, calibrate and validate a novel individual-level microsimulation model that would explicitly include smoking relapse and project cigarette smoking behaviours and associated mortality risks. METHODS: We developed the Simulation of Tobacco and Nicotine Outcomes and Policy (STOP) model, in which individuals transition monthly between tobacco use states (current/former/never) depending on rates of initiation, cessation and relapse. Simulated individuals face tobacco use-stratified mortality risks. For US women and men, we conducted cross-validation with a Cancer Intervention and Surveillance Modeling Network (CISNET) model. We then incorporated smoking relapse and calibrated cessation rates to reflect the difference between a transient quit attempt and sustained abstinence. We performed external validation with the National Health Interview Survey (NHIS) and the linked National Death Index. Comparisons were based on root-mean-square error (RMSE). RESULTS: In cross-validation, STOP-generated projections of current/former/never smoking prevalence fit CISNET-projected data well (coefficient of variation (CV)-RMSE≤15%). After incorporating smoking relapse, multiplying the CISNET-reported cessation rates for women/men by 7.75/7.25, to reflect the ratio of quit attempts to sustained abstinence, resulted in the best approximation to CISNET-reported smoking prevalence (CV-RMSE 2%/3%). In external validation using these new multipliers, STOP-generated cumulative mortality curves for 20-year-old current smokers and never smokers each had CV-RMSE ≤1% compared with NHIS. In simulating those surveyed by NHIS in 1997, the STOP-projected prevalence of current/former/never smokers annually (1998-2009) was similar to that reported by NHIS (CV-RMSE 12%). CONCLUSIONS: The STOP model, with relapse included, performed well when validated to US smoking prevalence and mortality. STOP provides a flexible framework for policy-relevant analysis of tobacco and nicotine product use.

The Optimal Age for Screening Adolescents and Young Adults Without Identified Risk Factors for HIV.

PURPOSE: To assess the optimal age at which a one-time HIV screen should begin for adolescents and young adults (AYA) in the U.S. without identified HIV risk factors, incorporating clinical impact, costs, and cost-effectiveness. METHODS: We simulated HIV-uninfected 12-year-olds in the U.S. without identified risk factors who faced age-specific risks of HIV infection (.6-71.3/100,000PY). We modeled a one-time screen ($36) at age 15, 18, 21, 25, or 30, each in addition to current U.S. screening practices (30% screened by age 24). Outcomes included retention in care, virologic suppression, life expectancy, lifetime costs, and incremental cost-effectiveness ratios in $/year-of-life saved (YLS) from the health-care system perspective. In sensitivity analyses, we varied HIV incidence, screening and linkage rates, and costs. RESULTS: All one-time screens detected a small proportion of lifetime infections (.1%-10.3%). Compared with current U.S. screening practices, a screen at age 25 led to the most favorable care continuum outcomes at age 25: proportion diagnosed (77% vs. 51%), linked to care (71% vs. 51%), retained in care (68% vs. 44%), and virologically suppressed (49% vs. 32%). Compared with the next most effective screen, a screen at age 25 provided the greatest clinical benefit, and was cost-effective ($96,000/YLS) by U.S. standards (<$100,000/YLS). CONCLUSIONS: For U.S. AYA without identified risk factors, a one-time routine HIV screen at age 25, after the peak of incidence, would optimize clinical outcomes and be cost-effective compared with current U.S. screening practices. Focusing screening on AYA ages 18 or younger is a less efficient use of a one-time screen among AYA than screening at a later age.

A Higher Brain Circuit for Immediate Integration of Conflicting Sensory Information in Drosophila.

Animals continuously evaluate sensory information to decide on their next action. Different sensory cues, however, often demand opposing behavioral responses. How does the brain process conflicting sensory information during decision making? Here, we show that flies use neural substrates attributed to odor learning and memory, including the mushroom body (MB), for immediate sensory integration and modulation of innate behavior. Drosophila melanogaster must integrate contradictory sensory information during feeding on fermenting fruit that releases both food odor and the innately aversive odor CO2. Here, using this framework, we examine the neural basis for this integration. We have identified a local circuit consisting of specific glutamatergic output and PAM dopaminergic input neurons with overlapping innervation in the MB-ß'2 lobe region, which integrates food odor and suppresses innate avoidance. Activation of food odor-responsive dopaminergic neurons reduces innate avoidance mediated by CO2-responsive MB output neurons. We hypothesize that the MB, in addition to its long recognized role in learning and memory, serves as the insect's brain center for immediate sensory integration during instantaneous decision making.