Planning for Mpox on a College Campus: A Model-Based Decision-Support Tool.

BACKGROUND: In spring and summer 2022, an outbreak of mpox occurred worldwide, largely confined to men who have sex with men (MSM). There was concern that mpox could break swiftly into congregate settings and populations with high levels of regular frequent physical contact, like university campus communities. OBJECTIVE: To estimate the likelihood of an mpox outbreak and the potential effect of mitigation measures in a residential college setting. DESIGN: A stochastic dynamic SEIR (susceptible, exposed but not infectious, infectious, or recovered) model of mpox transmission in a study population was developed, composed of: a high-risk group representative of the population of MSM with a basic reproductive number (R 0) of 2.4 and a low-risk group with an R 0 of 0.8. Base input assumptions included an incubation time of 7.6 days and time to recovery of 21 days. SETTING: U.S. residential college campus. PARTICIPANTS: Hypothetical cohort of 6500 students. INTERVENTION: Isolation, quarantine, and vaccination of close contacts. MEASUREMENTS: Proportion of 1000 simulations producing sustained transmission; mean cases given sustained transmission; maximum students isolated, quarantined, and vaccinated. All projections are estimated over a planning horizon of 100 days. RESULTS: Without mitigation measures, the model estimated an 83% likelihood of sustained transmission, leading to an average of 183 cases. With detection and isolation of 20%, 50%, and 80% of cases, the average infections would fall to 117, 37, and 8, respectively. Reactive vaccination of contacts of detected cases (assuming 50% detection and isolation) reduced mean cases from 37 to 17, assuming 20 vaccinated contacts per detected case. Preemptive vaccination of 50% of the high-risk population before outbreak reduced cases from 37 to 14, assuming 50% detection and isolation. LIMITATION: A model is a stylized portrayal of behavior and transmission on a university campus. CONCLUSION: Based on our current understanding of mpox epidemiology among MSM in the United States, this model-based analysis suggests that future outbreaks of mpox on college campuses may be controlled with timely detection and isolation of symptomatic cases. PRIMARY FUNDING SOURCE: National Institutes of Health National Institute on Drug Abuse and National Institute of Allergy and Infectious Diseases.

Keep It Up! 3.0: Study protocol for a type III hybrid implementation-effectiveness cluster-randomized trial.

BACKGROUND: Despite evidence that eHealth approaches can be effective in reducing HIV risk, their implementation requirements for public health scale up are not well established, and effective strategies to bring these programs into practice are still unknown. Keep It Up! (KIU!) is an online program proven to reduce HIV risk among young men who have sex with men (YMSM) and ideal candidate to develop and evaluate novel strategies for implementing eHealth HIV prevention programs. KIU! 3.0 is a Type III Hybrid Effectiveness-Implementation cluster randomized trial designed to 1) compare two strategies for implementing KIU!: community-based organizations (CBO) versus centralized direct-to-consumer (DTC) recruitment; 2) examine the effect of strategies and determinants on variability in implementation success; and 3) develop materials for sustainment of KIU! after the trial concludes. In this article, we describe the approaches used to achieve these aims. METHODS: Using county-level population estimates of YMSM, 66 counties were selected and randomized 2:1 to the CBO and DTC approaches. The RE-AIM model was used to drive outcome measurements, which were collected from CBO staff, YMSM, and technology providers. Mixed-methods research mapped onto the domains of the Consolidated Framework for Implementation Research will examine determinants and their relationship with implementation outcomes. DISCUSSION: In comparing our implementation recruitment models, we are examining two strategies which have shown effectiveness in delivering health technology interventions in the past, yet little is known about their comparative advantages and disadvantages in implementation. The results of the trial will further the understanding of eHealth prevention intervention implementation.

Population-Level Strategies for Nirmatrelvir/Ritonavir Prescribing-A Cost-effectiveness Analysis.

Background: New coronavirus disease 2019 (COVID-19) medications force decision-makers to weigh limited evidence of efficacy and cost in determining which patient populations to target for treatment. A case in point is nirmatrelvir/ritonavir, a drug that has been recommended for elderly, high-risk individuals, regardless of vaccination status, even though clinical trials have only evaluated it in unvaccinated patients. A simple optimization framework might inform a more reasoned approach to the trade-offs implicit in the treatment allocation decision. Methods: We conducted a cost-effectiveness analysis using a decision-analytic model comparing 5 nirmatrelvir/ritonavir prescription policy strategies, stratified by vaccination status and risk for severe disease. We considered treatment effectiveness at preventing hospitalization ranging from 21% to 89%. Sensitivity analyses were performed on major parameters of interest. A web-based tool was developed to permit decision-makers to tailor the analysis to their settings and priorities. Results: Providing nirmatrelvir/ritonavir to unvaccinated patients at high risk for severe disease was cost-saving when effectiveness against hospitalization exceeded 33% and cost-effective under all other data scenarios we considered. The cost-effectiveness of other allocation strategies, including those for vaccinated adults and those at lower risk for severe disease, depended on willingness-to-pay thresholds, treatment cost and effectiveness, and the likelihood of severe disease. Conclusions: Priority for nirmatrelvir/ritonavir treatment should be given to unvaccinated persons at high risk of severe disease from COVID-19. Further priority may be assigned by weighing treatment effectiveness, disease severity, drug cost, and willingness to pay for deaths averted.

Applications of methods of psychological support developed for astronauts for use in medical settings

Over the past 40 years, psychological support (PS) for cosmonauts and astronauts has remained an important part of the regular biomedical provision of space crews during extended orbital flights. It includes well-developed principles and a set of methods that have proven its effectiveness for the maintenance of behavioral health under extreme conditions of space flight. The main principle of PS in flight is to restore the usual sensory input to compensate for the monotony and lack of external stimuli as a result of a long stay under isolation and confinement. Risk factors for the psychological health and well-being defined for the astronauts, such as sensory and social deprivation, monotony, confinement, and lack of privacy, also remain part and parcel of several civil professions. These include polar wintering, submarines, working on oil platforms, and ocean fishing. Most of these factors also adversely affect the recovery rate of a large contingent of medical institutions, especially bedridden patients with chronic diseases. Finally, due to the negative epidemiological situation associated with the spread of COVID-19, an increasingly wide range of citizens forced to be in self-isolation faces negative manifestations of the deprivation phenomena described previously. Several cases of successful use of PS under isolation, monotony, crowding, and confinement are presented. Thus, we assume that the use of psychological support methods developed for space flights could be extremely relevant in civil medicine and everyday life.

Estimating deaths averted and cost per life saved by scaling up mRNA COVID-19 vaccination in low-income and lower-middle-income countries in the COVID-19 Omicron variant era: a modelling study.

OBJECTIVES: While almost 60% of the world has received at least one dose of COVID-19 vaccine, the global distribution of vaccination has not been equitable. Only 4% of the population of low-income countries (LICs) has received a full primary vaccine series, compared with over 70% of the population of high-income nations. DESIGN: We used economic and epidemiological models, parameterised with public data on global vaccination and COVID-19 deaths, to estimate the potential benefits of scaling up vaccination programmes in LICs and lower-middle-income countries (LMICs) in 2022 in the context of global spread of the Omicron variant of SARS-CoV2. SETTING: Low-income and lower-middle-income nations. MAIN OUTCOME MEASURES: Outcomes were expressed as number of avertable deaths through vaccination, costs of scale-up and cost per death averted. We conducted sensitivity analyses over a wide range of parameter estimates to account for uncertainty around key inputs. FINDINGS: Globally, universal vaccination in LIC/LMIC with three doses of an mRNA vaccine would result in an estimated 1.5 million COVID-19 deaths averted with a total estimated cost of US$61 billion and an estimated cost-per-COVID-19 death averted of US$40 800 (sensitivity analysis range: US$7400-US$81 500). Lower estimated infection fatality ratios, higher cost-per-dose and lower vaccine effectiveness or uptake lead to higher cost-per-death averted estimates in the analysis. CONCLUSIONS: Scaling up COVID-19 global vaccination would avert millions of COVID-19 deaths and represents a reasonable investment in the context of the value of a statistical life. Given the magnitude of expected mortality facing LIC/LMIC without vaccination, this effort should be an urgent priority.

Projected Long-Term Impact of the Coronavirus Disease 2019 (COVID-19) Pandemic on Hepatitis C Outcomes in the United States: A Modeling Study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic disrupted access to and uptake of hepatitis C virus (HCV) care services in the United States. It is unknown how substantially the pandemic will impact long-term HCV-related outcomes. METHODS: We used a microsimulation to estimate the 10-year impact of COVID-19 disruptions in healthcare delivery on HCV outcomes including identified infections, linkage to care, treatment initiation and completion, cirrhosis, and liver-related death. We modeled hypothetical scenarios consisting of an 18-month pandemic-related disruption in HCV care starting in March 2020 followed by varying returns to pre-pandemic rates of screening, linkage, and treatment through March 2030 and compared them to a counterfactual scenario in which there was no COVID-19 pandemic or disruptions in care. We also performed alternate scenario analyses in which the pandemic disruption lasted for 12 and 24 months. RESULTS: Compared to the "no pandemic" scenario, in the scenario in which there is no return to pre-pandemic levels of HCV care delivery, we estimate 1060 fewer identified cases, 21 additional cases of cirrhosis, and 16 additional liver-related deaths per 100 000 people. Only 3% of identified cases initiate treatment and <1% achieve sustained virologic response (SVR). Compared to "no pandemic," the best-case scenario in which an 18-month care disruption is followed by a return to pre-pandemic levels, we estimated a smaller proportion of infections identified and achieving SVR. CONCLUSIONS: A recommitment to the HCV epidemic in the United States that involves additional resources coupled with aggressive efforts to screen, link, and treat people with HCV is needed to overcome the COVID-19-related disruptions.

A clash of epidemics: Impact of the COVID-19 pandemic response on opioid overdose.

Coronavirus disease 2019 (COVID-19) will have a lasting impact on public health. In addition to the direct effects of COVID-19 infection, physical distancing and quarantine interventions have indirect effects on health. While necessary, physical distancing interventions to control the spread of COVID-19 could have multiple impacts on people living with opioid use disorder, including impacts on mental health that lead to greater substance use, the availability of drug supply, the ways that people use drugs, treatment-seeking behaviors, and retention in care. The degree to which COVID-19 will impact the opioid epidemic and through which of the possible mechanisms that we discuss is important to monitor. We employed simulation modeling to demonstrate the potential impact of physical distancing on overdose mortality.