Daily Oral HIV Pre-exposure Prophylaxis Among Young Men Who Have Sex With Men in the United States: Cost-saving at Generic Drug Price.

BACKGROUND: Adherence and retention concerns raise questions about the effectiveness and cost-effectiveness of oral HIV pre-exposure prophylaxis (PrEP) in young men who have sex with men (YMSM). METHODS: Using an adolescent-focused simulation model, we compared annual HIV screening alone with tenofovir disoproxil fumarate/emtricitabine-based oral PrEP with every 3-month HIV screening in YMSM (aged 15-24) at increased risk of HIV. Data derived from published sources included: age-stratified HIV incidence/100 person-years (PY) on- or off-PrEP (0.6-10.1 or 0.4-6.4), PrEP retention at 6 years (28%), transmissions by HIV RNA level (0.0-78.4/100PY) and annual costs of antiretroviral therapy ($32 000-69 000), HIV care ($3100-34 600), and PrEP program/generic drug ($900/360). Outcomes included transmissions (percent of cohort infected), quality-adjusted life-years (QALYs), costs ($), and incremental cost-effectiveness ratios ($/QALY). We explored the sensitivity of findings to variation in HIV incidence and drug prices. RESULTS: Compared with annual screening alone, PrEP would increase QALYs (9.58 to 9.67), reduce new infections (37% to 30%), and decrease costs (by $5000) over 10 years. PrEP would remain cost-saving for HIV incidence off-PrEP ≥5.1/100PY or annual PrEP price ≤$1200. Over a lifetime horizon, PrEP would be cost-saving for HIV incidence off-PrEP ≥1.0/100PY, across all retention assumptions examined. PrEP would not be cost-effective at HIV incidence ≤0.1/100PY, regardless of drug price, due to programmatic costs. CONCLUSIONS: In US YMSM at increased risk of HIV, generic oral PrEP and every-3-month screening would be cost-saving compared with annual screening alone, even with high discontinuation and low adherence, over a range of HIV incidences.

Impact of pre-exposure prophylaxis uptake among gay, bisexual, and other men who have sex with men in urban centers in Brazil: a modeling study.

BACKGROUND: Men who have sex with men (MSM) in Brazil remain disproportionately affected by HIV. We estimated the potential incidence reduction by five years with increased uptake of publicly-funded, daily, oral tenofovir/emtricitabine (TDF/FTC) for HIV pre-exposure prophylaxis (PrEP) among MSM using the Cost Effectiveness of Preventing AIDS Complications microsimulation model. We used national data, local studies, and literature to inform model parameters for three cities: Rio de Janeiro, Salvador, and Manaus. RESULTS: In Rio de Janero, a PrEP intervention achieving 10% uptake within 60 months would decrease incidence by 2.3% whereas achieving 60% uptake within 24 months would decrease incidence by 29.7%; results were similar for Salvador and Manaus. In sensitivity analyses, decreasing mean age at PrEP initiation from 33 to 21 years increased incidence reduction by 34%; a discontinuation rate of 25% per year decreased it by 12%. CONCLUSION: Targeting PrEP to young MSM and minimizing discontinuation could substantially increase PrEP's impact.

College Campuses and COVID-19 Mitigation: Clinical and Economic Value.

BACKGROUND: Colleges in the United States are determining how to operate safely amid the coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVE: To examine the clinical outcomes, cost, and cost-effectiveness of COVID-19 mitigation strategies on college campuses. DESIGN: The Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation model, was used to examine alternative mitigation strategies. The CEACOV model tracks infections accrued by students and faculty, accounting for community transmissions. DATA SOURCES: Data from published literature were used to obtain parameters related to COVID-19 and contact-hours. TARGET POPULATION: Undergraduate students and faculty at U.S. colleges. TIME HORIZON: One semester (105 days). PERSPECTIVE: Modified societal. INTERVENTION: COVID-19 mitigation strategies, including social distancing, masks, and routine laboratory screening. OUTCOME MEASURES: Infections among students and faculty per 5000 students and per 1000 faculty, isolation days, tests, costs, cost per infection prevented, and cost per quality-adjusted life-year (QALY). RESULTS OF BASE-CASE ANALYSIS: Among students, mitigation strategies reduced COVID-19 cases from 3746 with no mitigation to 493 with extensive social distancing and masks, and further to 151 when laboratory testing was added among asymptomatic persons every 3 days. Among faculty, these values were 164, 28, and 25 cases, respectively. Costs ranged from about $0.4 million for minimal social distancing to about $0.9 million to $2.1 million for strategies involving laboratory testing ($10 per test), depending on testing frequency. Extensive social distancing with masks cost $170 per infection prevented ($49 200 per QALY) compared with masks alone. Adding routine laboratory testing increased cost per infection prevented to between $2010 and $17 210 (cost per QALY gained, $811 400 to $2 804 600). RESULTS OF SENSITIVITY ANALYSIS: Results were most sensitive to test costs. LIMITATION: Data are from multiple sources. CONCLUSION: Extensive social distancing with a mandatory mask-wearing policy can prevent most COVID-19 cases on college campuses and is very cost-effective. Routine laboratory testing would prevent 96% of infections and require low-cost tests to be economically attractive. PRIMARY FUNDING SOURCE: National Institutes of Health.

Clinical Impact, Costs, and Cost-effectiveness of Expanded Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Massachusetts.

BACKGROUND: We projected the clinical and economic impact of alternative testing strategies on coronavirus disease 2019 (COVID-19) incidence and mortality in Massachusetts using a microsimulation model. METHODS: We compared 4 testing strategies: (1) hospitalized: polymerase chain reaction (PCR) testing only for patients with severe/critical symptoms warranting hospitalization; (2) symptomatic: PCR for any COVID-19-consistent symptoms, with self-isolation if positive; (3) symptomatic + asymptomatic once: symptomatic and 1-time PCR for the entire population; and (4) symptomatic + asymptomatic monthly: symptomatic with monthly retesting for the entire population. We examined effective reproduction numbers (Re = 0.9-2.0) at which policy conclusions would change. We assumed homogeneous mixing among the Massachusetts population (excluding those residing in long-term care facilities). We used published data on disease progression and mortality, transmission, PCR sensitivity/specificity (70%/100%), and costs. Model-projected outcomes included infections, deaths, tests performed, hospital-days, and costs over 180 days, as well as incremental cost-effectiveness ratios (ICERs, $/quality-adjusted life-year [QALY]). RESULTS: At Re = 0.9, symptomatic + asymptomatic monthly vs hospitalized resulted in a 64% reduction in infections and a 46% reduction in deaths, but required >66-fold more tests/day with 5-fold higher costs. Symptomatic + asymptomatic monthly had an ICER <$100 000/QALY only when Re ≥1.6; when test cost was ≤$3, every 14-day testing was cost-effective at all Re examined. CONCLUSIONS: Testing people with any COVID-19-consistent symptoms would be cost-saving compared to testing only those whose symptoms warrant hospital care. Expanding PCR testing to asymptomatic people would decrease infections, deaths, and hospitalizations. Despite modest sensitivity, low-cost, repeat screening of the entire population could be cost-effective in all epidemic 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.

The Cost-effectiveness of Human Immunodeficiency Virus (HIV) Preexposure Prophylaxis and HIV Testing Strategies in High-risk Groups in India.

BACKGROUND: The human immunodeficiency virus (HIV) epidemic in India is concentrated among 3.1 million men who have sex with men (MSM) and 1.1 million people who inject drugs (PWID), with a mean incidence of 0.9-1.4 per 100 person-years. We examined the cost-effectiveness of both preexposure prophylaxis (PrEP) and HIV testing strategies for MSM and PWID in India. METHODS: We populated an HIV microsimulation model with India-specific data and projected clinical and economic outcomes of 7 strategies for MSM/PWID, including status quo; a 1-time HIV test; routine HIV testing every 3, 6, or 12 months; and PrEP with HIV testing every 3 or 6 months. We used a willingness-to-pay threshold of US$1950, the 2017 Indian per capita gross domestic product, to define cost-effectiveness. RESULTS: HIV testing alone increased life expectancy by 0.07-0.30 years in MSM; PrEP added approximately 0.90 life-years to status quo. Results were similar in PWID. PrEP with 6-month testing was cost-effective for both MSM (incremental cost-effectiveness ratio [ICER], $1000/year of life saved [YLS]) and PWID (ICER, $500/YLS). Results were most sensitive to HIV incidence. PrEP with 6-month testing would increase HIV-related expenditures by US$708 million (MSM) and US$218 million (PWID) over 5 years compared to status quo. CONCLUSIONS: While the World Health Organization recommends PrEP with quarterly HIV testing, our analysis identifies PrEP with semiannual testing as the cost-effective HIV prevention strategy for Indian MSM and PWID. Since nationwide scale-up would require a substantial fiscal investment, areas of highest HIV incidence may be the appropriate initial targets for PrEP scale-up.

A novel method to estimate the indirect community benefit of HIV interventions using a microsimulation model of HIV disease.

BACKGROUND: Microsimulation models of human immunodeficiency virus (HIV) disease that simulate individual patients one at a time and assess clinical and economic outcomes of HIV interventions often provide key details regarding direct individual clinical benefits ("individual benefit"), but they may lack detail on transmissions, and thus may underestimate an intervention's indirect benefits ("community benefit"). Dynamic transmission models can be used to simulate HIV transmissions, but they may do so at the expense of the clinical detail of microsimulations. We sought to develop, validate, and demonstrate a practical, novel method that can be integrated into existing HIV microsimulation models to capture this community benefit, integrating the effects of reduced transmission while keeping the clinical detail of microsimulations. METHODS: We developed a new method to capture the community benefit of HIV interventions by estimating HIV transmissions from the primary cohort of interest. The method captures the benefit of averting infections within the cohort of interest by estimating a corresponding gradual decline in incidence within the cohort. For infections averted outside the cohort of interest, our method estimates transmissions averted based on reductions in HIV viral load within the cohort, and the benefit (life-years gained and cost savings) of averting those infections based on the time they were averted. To assess the validity of our method, we paired it with the Cost-effectiveness of Preventing AIDS Complications (CEPAC) Model - a validated and widely-published microsimulation model of HIV disease. We then compared the consistency of model-estimated outcomes against outcomes of a widely-validated dynamic compartmental transmission model of HIV disease, the HIV Optimization and Prevention Economics (HOPE) model, using the intraclass correlation coefficient (ICC) with a two-way mixed effects model. Replicating an analysis done with HOPE, validation endpoints were number of HIV transmissions averted by offering pre-exposure prophylaxis (PrEP) to men who have sex with men (MSM) and people who inject drugs (PWID) in the US at various uptake and efficacy levels. Finally, we demonstrated an application of our method in a different setting by evaluating the clinical and economic outcomes of a PrEP program for MSM in India, a country currently considering PrEP rollout for this high-risk group. RESULTS: The new method paired with CEPAC demonstrated excellent consistency with the HOPE model (ICC = 0.98 for MSM and 0.99 for PWID). With only the individual benefit of the intervention incorporated, a PrEP program for MSM in India averted 43,000 transmissions over a 5-year period and resulted in a lifetime incremental cost-effectiveness ratio (ICER) of US$2,300/year-of-life saved (YLS) compared to the status quo. After applying both the direct (individual) and indirect (community) benefits, PrEP averted 86,000 transmissions over the same period and resulted in an ICER of US$600/YLS. CONCLUSIONS: Our method enables HIV microsimulation models that evaluate clinical and economic outcomes of HIV interventions to estimate the community benefit of these interventions (in terms of survival gains and cost savings) efficiently and without sacrificing clinical detail. This method addresses an important methodological gap in health economics microsimulation modeling and allows decision scientists to make more accurate policy recommendations.

Personalized Prediction of Glaucoma Progression Under Different Target Intraocular Pressure Levels Using Filtered Forecasting Methods.

PURPOSE: To generate personalized forecasts of how patients with open-angle glaucoma (OAG) experience disease progression at different intraocular pressure (IOP) levels to aid clinicians with setting personalized target IOPs. DESIGN: Secondary analyses using longitudinal data from 2 randomized controlled trials. PARTICIPANTS: Participants with moderate or advanced OAG from the Collaborative Initial Glaucoma Treatment Study (CIGTS) or the Advanced Glaucoma Intervention Study (AGIS). METHODS: By using perimetric and tonometric data from trial participants, we developed and validated Kalman Filter (KF) models for fast-, slow-, and nonprogressing patients with OAG. The KF can generate personalized and dynamically updated forecasts of OAG progression under different target IOP levels. For each participant, we determined how mean deviation (MD) would change if the patient maintains his/her IOP at 1 of 7 levels (6, 9, 12, 15, 18, 21, or 24 mmHg) over the next 5 years. We also model and predict changes to MD over the same time horizon if IOP is increased or decreased by 3, 6, and 9 mmHg from the level attained in the trials. MAIN OUTCOME MEASURES: Personalized estimates of the change in MD under different target IOP levels. RESULTS: A total of 571 participants (mean age, 64.2 years; standard deviation, 10.9) were followed for a mean of 6.5 years (standard deviation, 2.8). Our models predicted that, on average, fast progressors would lose 2.1, 6.7, and 11.2 decibels (dB) MD under target IOPs of 6, 15, and 24 mmHg, respectively, over 5 years. In contrast, on average, slow progressors would lose 0.8, 2.1, and 4.1 dB MD under the same target IOPs and time frame. When using our tool to quantify the OAG progression dynamics for all 571 patients, we found no statistically significant differences over 5 years between progression for black versus white, male versus female, and CIGTS versus AGIS participants under different target IOPs (P > 0.05 for all). CONCLUSIONS: To our knowledge, this is the first clinical decision-making tool that generates personalized forecasts of the trajectory of OAG progression at different target IOP levels. This approach can help clinicians determine appropriate, personalized target IOPs for patients with OAG.

Coordinating clinic and surgery appointments to meet access service levels for elective surgery.

Providing timely access to surgery is crucial for patients with high acuity diseases like cancer. We present a methodological framework to make efficient use of scarce resources including surgeons, operating rooms, and clinic appointment slots with a goal of coordinating clinic and surgery appointments so that patients with different acuity levels can see a surgeon in the clinic and schedule their surgery within a maximum wait time target that is clinically safe for them. We propose six heuristic scheduling policies with two underlying ideas behind them: (1) proactively book a tentative surgery day along with the clinic appointment at the time an appointment request is received, and (2) intelligently space out clinic and surgery appointments such that if the patient does not need his/her surgery appointment there is sufficient time to offer it to another patient. A 2-stage stochastic discrete-event simulation approach is employed to evaluate the six scheduling policies. In the first stage of the simulation, the heuristic policies are compared in terms of the average operating room (OR) overtime per day. The second stage involves fine-tuning the most-effective policy. A case study of the division of colorectal surgery (CRS) at the Mayo Clinic confirms that all six policies outperform the current scheduling protocol by a large margin. Numerical results demonstrate that the final policy, which we refer to as Coordinated Appointment Scheduling Policy considering Indication and Resources (CASPIR), performs 52% better than the current scheduling policy in terms of the average OR overtime per day under the same access service level. In conclusion, surgical divisions desiring stratified patient urgency classes should consider using scheduling policies that take the surgical availability of surgeons, patients' demographics and indication of disease into consideration when scheduling a clinic consultation appointment.

Mitigating the COVID-19 Pandemic through Data-Driven Resource Sharing.

COVID-19 outbreaks in local communities can result in a drastic surge in demand for scarce resources such as mechanical ventilators. To deal with such demand surges, many hospitals (1) purchased large quantities of mechanical ventilators, and (2) canceled/postponed elective procedures to preserve care capacity for COVID-19 patients. These measures resulted in a substantial financial burden to the hospitals and poor outcomes for non-COVID-19 patients. Given that COVID-19 transmits at different rates across various regions, there is an opportunity to share portable healthcare resources to mitigate capacity shortages triggered by local outbreaks with fewer total resources. This paper develops a novel data-driven adaptive robust simulation-based optimization (DARSO) methodology for optimal allocation and relocation of mechanical ventilators over different states and regions. Our main methodological contributions lie in a new policy-guided approach and an efficient algorithmic framework that mitigates critical limitations of current robust and stochastic models and make resource-sharing decisions implementable in real-time. In collaboration with epidemiologists and infectious disease doctors, we give proof of concept for the DARSO methodology through a case study of sharing ventilators among regions in Ohio and Michigan. The results suggest that our optimal policy could satisfy ventilator demand during the first pandemic's peak in Ohio and Michigan with 14% (limited sharing) to 63% (full sharing) fewer ventilators compared to a no sharing strategy (status quo), thereby allowing hospitals to preserve more elective procedures. Furthermore, we demonstrate that sharing unused ventilators (rather than purchasing new machines) can result in 5% (limited sharing) to 44% (full sharing) lower expenditure, compared to no sharing, considering the transshipment and new ventilator costs.

Using simulation modeling to inform intervention and implementation selection in a rapid stakeholder-engaged hybrid effectiveness-implementation randomized trial.

BACKGROUND: Implementation research generally assumes established evidence-based practices and prior piloting of implementation strategies, which may not be feasible during a public health emergency. We describe the use of a simulation model of the effectiveness of COVID-19 mitigation strategies to inform a stakeholder-engaged process of rapidly designing a tailored intervention and implementation strategy for individuals with serious mental illness (SMI) and intellectual/developmental disabilities (ID/DD) in group homes in a hybrid effectiveness-implementation randomized trial. METHODS: We used a validated dynamic microsimulation model of COVID-19 transmission and disease in late 2020/early 2021 to determine the most effective strategies to mitigate infections among Massachusetts group home staff and residents. Model inputs were informed by data from stakeholders, public records, and published literature. We assessed different prevention strategies, iterated over time with input from multidisciplinary stakeholders and pandemic evolution, including varying symptom screening, testing frequency, isolation, contact-time, use of personal protective equipment, and vaccination. Model outcomes included new infections in group home residents, new infections in group home staff, and resident hospital days. Sensitivity analyses were performed to account for parameter uncertainty. Results of the simulations informed a stakeholder-engaged process to select components of a tailored best practice intervention and implementation strategy. RESULTS: The largest projected decrease in infections was with initial vaccination, with minimal benefit for additional routine testing. The initial level of actual vaccination in the group homes was estimated to reduce resident infections by 72.4% and staff infections by 55.9% over the 90-day time horizon. Increasing resident and staff vaccination uptake to a target goal of 90% further decreased resident infections by 45.2% and staff infections by 51.3%. Subsequent simulated removal of masking led to a 6.5% increase in infections among residents and 3.2% among staff. The simulation model results were presented to multidisciplinary stakeholders and policymakers to inform the "Tailored Best Practice" package for the hybrid effectiveness-implementation trial. CONCLUSIONS: Vaccination and decreasing vaccine hesitancy among staff were predicted to have the greatest impact in mitigating COVID-19 risk in vulnerable populations of group home residents and staff. Simulation modeling was effective in rapidly informing the selection of the prevention and implementation strategy in a hybrid effectiveness-implementation trial. Future implementation may benefit from this approach when rapid deployment is necessary in the absence of data on tailored interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04726371.

The cost-effectiveness of a resilience-based psychosocial intervention for HIV prevention among MSM in India.

OBJECTIVE: MSM in India are at a high risk for HIV infection given psychosocial challenges, sexual orientation stress, and stigma. We examined the cost-effectiveness of a novel resilience-based psychosocial intervention for MSM in India. DESIGN: We parameterized a validated microsimulation model (CEPAC) with India-specific data and results from a randomized trial and examined two strategies for MSM: status quo HIV care ( SQ ), and a trial-based psychosocial intervention ( INT ) focused on building resilience to stress, improving mental health, and reducing condomless anal sex (CAS). METHODS: We projected lifetime clinical and economic outcomes for MSM without HIV initially. Intervention effectiveness, defined as reduction in self-reported CAS, was estimated at 38%; cost was $49.37/participant. We used a willingness-to-pay threshold of US$2100 (2019 Indian per capita GDP) per year of life saved (YLS) to define cost-effectiveness. We also assessed the 5-year budget impact of offering this intervention to 20% of Indian MSM. RESULTS: Model projections showed the intervention would avert 2940 HIV infections among MSM over 10 years. Over a lifetime horizon, the intervention was cost-effective (ICER = $900/YLS). Results were most sensitive to intervention effectiveness and cost; the intervention remained cost-effective under plausible ranges of these parameters. Offering this intervention in the public sector would require an additional US$28 M over 5 years compared with SQ . CONCLUSION: A resilience-based psychosocial intervention integrated with HIV risk reduction counseling among MSM in India would reduce HIV infections and be cost-effective. Programs using this approach should be expanded as a part of comprehensive HIV prevention in India.

Correlates of analog vs human basal insulin use among individuals with type 2 diabetes: A cross-sectional study.

BACKGROUND: Given the shift from use of less expensive human to costlier analog insulins for treatment of type 2 diabetes (T2D), we examine characteristics and glycemic control associated with type of basal insulin use. METHODS: We analyzed respondents with T2D in six consecutive National Health and Nutrition Examination Survey (NHANES) cycles (2005-2016). Logistic regression models examined associations between demographics, socioeconomic factors, and NHANES cycle with (1) type of basal insulin use and (2) hemoglobin A1c <8.0% and <7.0% according to basal insulin type. FINDINGS: Basal insulin use increased from 9.6% to 17.2% of respondents with T2D between 2005 and 2016. Among 723 respondents meeting inclusion criteria, the proportion using analog basal insulin rose from 58% to 88%. African American (aOR 0.42, 95% CI 0.24-0.74) and Hispanic (aOR 0.54, 95% CI 0.30-0.96) respondents had lower odds of analog basal insulin use than non-Hispanic White respondents in adjusted and unadjusted models. Older age and having health insurance, but not type of basal insulin use, associated with meeting HbA1c targets. INTERPRETATION: Non-White NHANES respondents were less likely to use analog basal insulin than White respondents. Increased analog basal insulin use between 2005 and 2016 was not associated with improved glycemic control.

Comparing Perimetric Loss at Different Target Intraocular Pressures for Patients with High-Tension and Normal-Tension Glaucoma.

PURPOSE: To compare forecasted changes in mean deviation (MD) for patients with normal-tension glaucoma (NTG) and high-tension open-angle glaucoma (HTG) at different target intraocular pressures (IOPs) using Kalman filtering, a machine learning technique. DESIGN: Retrospective cohort study. PARTICIPANTS: From the Collaborative Initial Glaucoma Treatment Study or Advanced Glaucoma Intervention Study, 496 patients with HTG; from Japan, 262 patients with NTG. METHODS: Using the first 5 sets of tonometry and perimetry measurements, each patient was classified as a fast progressor, slow progressor, or nonprogressor. Using Kalman filtering, personalized forecasts of MD changes over 2.5 years' follow-up were generated for fast and slow progressors with HTG and NTG with IOPs maintained at hypothetical IOP targets of 9 to 21 mmHg. Future MD loss with different percentage IOP reductions from baseline (0%-50%) were also assessed for the groups. MAIN OUTCOME MEASURES: Mean forecasted MD change at different target IOPs. RESULTS: The mean (± standard deviation) patient age was 63.5 ± 10.5 years for NTG and 66.5 ± 10.9 years for HTG. Over the 2.5-year follow-up, at target IOPs of 9, 15, and 21 mmHg, respectively, the mean forecasted MD losses for fast progressors with NTG were 2.3 ± 0.2, 4.0 ± 0.2, and 5.7 ± 0.2 dB; for slow progressors with NTG, losses were 0.63 ± 0.02, 1.02 ± 0.03, and 1.49 ± 0.07 dB; for fast progressors with HTG, losses were 1.8 ± 0.1, 3.4 ± 0.1, and 5.1 ± 0.1 dB; and for slow progressors with HTG, losses were 0.55 ± 0.06, 1.04 ± 0.08, and 1.59 ± 0.10 dB. Fast progressors with NTG had greater MD decline than fast progressors with HTG at each target IOP (P ≤ 0.007 for all). The MD decline for slow progressors with HTG and NTG were similar (P ≥ 0.24 for all target IOPs). Fast progressors with HTG had greater MD loss than those with NTG with 0%-10% IOP reduction since baseline (P ≤ 0.01 for all), but not 25% (P = 0.07) or 50% (P = 0.76) reduction since baseline. CONCLUSIONS: Machine learning algorithms using Kalman filtering techniques demonstrate promise at forecasting future MD values at different target IOPs for patients with NTG and HTG.

Cost-effectiveness of public health strategies for COVID-19 epidemic control in South Africa: a microsimulation modelling study.

BACKGROUND: Health-care resource constraints in low-income and middle-income countries necessitate the identification of cost-effective public health interventions to address COVID-19. We aimed to develop a dynamic COVID-19 microsimulation model to assess clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal province, South Africa. METHODS: We compared different combinations of five public health interventions: health-care testing alone, where diagnostic testing is done only for individuals presenting to health-care centres; contact tracing in households of cases; isolation centres, for cases not requiring hospital admission; mass symptom screening and molecular testing for symptomatic individuals by community health-care workers; and quarantine centres, for household contacts who test negative. We calibrated infection transmission rates to match effective reproduction number (Re) estimates reported in South Africa. We assessed two main epidemic scenarios for a period of 360 days, with an Re of 1·5 and 1·2. Strategies with incremental cost-effectiveness ratio (ICER) of less than US$3250 per year of life saved were considered cost-effective. We also did sensitivity analyses by varying key parameters (Re values, molecular testing sensitivity, and efficacies and costs of interventions) to determine the effect on clinical and cost projections. FINDINGS: When Re was 1·5, health-care testing alone resulted in the highest number of COVID-19 deaths during the 360-day period. Compared with health-care testing alone, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres reduced mortality by 94%, increased health-care costs by 33%, and was cost-effective (ICER $340 per year of life saved). In settings where quarantine centres were not feasible, a combination of health-care testing, contact tracing, use of isolation centres, and mass symptom screening was cost-effective compared with health-care testing alone (ICER $590 per year of life saved). When Re was 1·2, health-care testing, contact tracing, use of isolation centres, and use of quarantine centres was the least costly strategy, and no other strategies were cost-effective. In sensitivity analyses, a combination of health-care testing, contact tracing, use of isolation centres, mass symptom screening, and use of quarantine centres was generally cost-effective, with the exception of scenarios in which Re was 2·6 and when efficacies of isolation centres and quarantine centres for transmission reduction were reduced. INTERPRETATION: In South Africa, strategies involving household contact tracing, isolation, mass symptom screening, and quarantining household contacts who test negative would substantially reduce COVID-19 mortality and would be cost-effective. The optimal combination of interventions depends on epidemic growth characteristics and practical implementation considerations. FUNDING: US National Institutes of Health, Royal Society, Wellcome Trust.

College campuses and COVID-19 mitigation: clinical and economic value.

BACKGROUND: Decisions around US college and university operations will affect millions of students and faculty amidst the COVID-19 pandemic. We examined the clinical and economic value of different COVID-19 mitigation strategies on college campuses. METHODS: We used the Clinical and Economic Analysis of COVID-19 interventions (CEACOV) model, a dynamic microsimulation that tracks infections accrued by students and faculty, accounting for community transmissions. Outcomes include infections, $/infection-prevented, and $/quality-adjusted-life-year ($/QALY). Strategies included extensive social distancing (ESD), masks, and routine laboratory tests (RLT). We report results per 5,000 students (1,000 faculty) over one semester (105 days). RESULTS: Mitigation strategies reduced COVID-19 cases among students (faculty) from 3,746 (164) with no mitigation to 493 (28) with ESD and masks, and further to 151 (25) adding RLTq3 among asymptomatic students and faculty. ESD with masks cost $168/infection-prevented ($49,200/QALY) compared to masks alone. Adding RLTq3 ($10/test) cost $8,300/infection-prevented ($2,804,600/QALY). If tests cost $1, RLTq3 led to a favorable cost of $275/infection-prevented ($52,200/QALY). No strategies without masks were cost-effective. CONCLUSION: Extensive social distancing with mandatory mask-wearing could prevent 87% of COVID-19 cases on college campuses and be very cost-effective. Routine laboratory testing would prevent 96% of infections and require low cost tests to be economically attractive.

Clinical Outcomes, Costs, and Cost-effectiveness of Strategies for Adults Experiencing Sheltered Homelessness During the COVID-19 Pandemic.

Importance: Approximately 356 000 people stay in homeless shelters nightly in the United States. They have high risk of contracting coronavirus disease 2019 (COVID-19). Objective: To assess the estimated clinical outcomes, costs, and cost-effectiveness associated with strategies for COVID-19 management among adults experiencing sheltered homelessness. Design, Setting, and Participants: This decision analytic model used a simulated cohort of 2258 adults residing in homeless shelters in Boston, Massachusetts. Cohort characteristics and costs were adapted from Boston Health Care for the Homeless Program. Disease progression, transmission, and outcomes data were taken from published literature and national databases. Surging, growing, and slowing epidemics (effective reproduction numbers [Re], 2.6, 1.3, and 0.9, respectively) were examined. Costs were from a health care sector perspective, and the time horizon was 4 months, from April to August 2020. Exposures: Daily symptom screening with polymerase chain reaction (PCR) testing of individuals with positive symptom screening results, universal PCR testing every 2 weeks, hospital-based COVID-19 care, alternative care sites (ACSs) for mild or moderate COVID-19, and temporary housing were each compared with no intervention. Main Outcomes and Measures: Cumulative infections and hospital-days, costs to the health care sector (US dollars), and cost-effectiveness, as incremental cost per case of COVID-19 prevented. Results: The simulated population of 2258 sheltered homeless adults had a mean (SD) age of 42.6 (9.04) years. Compared with no intervention, daily symptom screening with ACSs for pending tests or confirmed COVID-19 and mild or moderate disease was associated with 37% fewer infections (1954 vs 1239) and 46% lower costs ($6.10 million vs $3.27 million) at an Re of 2.6, 75% fewer infections (538 vs 137) and 72% lower costs ($1.46 million vs $0.41 million) at an Re of 1.3, and 51% fewer infections (174 vs 85) and 51% lower costs ($0.54 million vs $0.26 million) at an Re of 0.9. Adding PCR testing every 2 weeks was associated with a further decrease in infections; incremental cost per case prevented was $1000 at an Re of 2.6, $27 000 at an Re of 1.3, and $71 000 at an Re of 0.9. Temporary housing with PCR every 2 weeks was most effective but substantially more expensive than other options. Compared with no intervention, temporary housing with PCR every 2 weeks was associated with 81% fewer infections (376) and 542% higher costs ($39.12 million) at an Re of 2.6, 82% fewer infections (95) and 2568% higher costs ($38.97 million) at an Re of 1.3, and 59% fewer infections (71) and 7114% higher costs ($38.94 million) at an Re of 0.9. Results were sensitive to cost and sensitivity of PCR and ACS efficacy in preventing transmission. Conclusions and Relevance: In this modeling study of simulated adults living in homeless shelters, daily symptom screening and ACSs were associated with fewer severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and decreased costs compared with no intervention. In a modeled surging epidemic, adding universal PCR testing every 2 weeks was associated with further decrease in SARS-CoV-2 infections at modest incremental cost and should be considered during future surges.

Clinical Impact, Costs, and Cost-Effectiveness of Expanded SARS-CoV-2 Testing in Massachusetts.

Background We projected the clinical and economic impact of alternative testing strategies on COVID-19 incidence and mortality in Massachusetts using a microsimulation model. Methods We compared five testing strategies: 1) PCR-severe-only: PCR testing only patients with severe/critical symptoms; 2) Self-screen: PCR-severe-only plus self-assessment of COVID-19-consistent symptoms with self-isolation if positive; 3) PCR-any-symptom: PCR for any COVID-19-consistent symptoms with self-isolation if positive; 4) PCR-all: PCR-any-symptom and one-time PCR for the entire population; and, 5) PCR-all-repeat: PCR-all with monthly re-testing. We examined effective reproduction numbers (R e , 0.9-2.0) at which policy conclusions would change. We used published data on disease progression and mortality, transmission, PCR sensitivity/specificity (70/100%) and costs. Model-projected outcomes included infections, deaths, tests performed, hospital-days, and costs over 180-days, as well as incremental cost-effectiveness ratios (ICERs, $/quality-adjusted life-year [QALY]). Results In all scenarios, PCR-all-repeat would lead to the best clinical outcomes and PCR-severe-only would lead to the worst; at R e 0.9, PCR-all-repeat vs. PCR-severe-only resulted in a 63% reduction in infections and a 44% reduction in deaths, but required >65-fold more tests/day with 4-fold higher costs. PCR-all-repeat had an ICER <$100,000/QALY only when R e ≥1.8. At all R e values, PCR-any-symptom was cost-saving compared to other strategies. Conclusions Testing people with any COVID-19-consistent symptoms would be cost-saving compared to restricting testing to only those with symptoms severe enough to warrant hospital care. Expanding PCR testing to asymptomatic people would decrease infections, deaths, and hospitalizations. Universal screening would be cost-effective when paired with monthly retesting in settings where the COVID-19 pandemic is surging.

Clinical Outcomes, Costs, and Cost-effectiveness of Strategies for People Experiencing Sheltered Homelessness During the COVID-19 Pandemic.

IMPORTANCE: Approximately 356,000 people stay in homeless shelters nightly in the US. They are at high risk for COVID-19. OBJECTIVE: To assess clinical outcomes, costs, and cost-effectiveness of strategies for COVID-19 management among sheltered homeless adults. DESIGN: We developed a dynamic microsimulation model of COVID-19 in sheltered homeless adults in Boston, Massachusetts. We used cohort characteristics and costs from Boston Health Care for the Homeless Program. Disease progression, transmission, and outcomes data were from published literature and national databases. We examined surging, growing, and slowing epidemics (effective reproduction numbers [Re] 2.6, 1.3, and 0.9). Costs were from a health care sector perspective; time horizon was 4 months, from April to August 2020. SETTING & PARTICIPANTS: Simulated cohort of 2,258 adults residing in homeless shelters in Boston. INTERVENTIONS: We assessed daily symptom screening with polymerase chain reaction (PCR) testing of screen-positives, universal PCR testing every 2 weeks, hospital-based COVID-19 care, alternate care sites [ACSs] for mild/moderate COVID-19, and temporary housing, each compared to no intervention. MAIN OUTCOMES AND MEASURES: Cumulative infections and hospital-days, costs to the health care sector (US dollars), and cost-effectiveness, as incremental cost per case prevented of COVID-19. RESULTS: We simulated a population of 2,258 sheltered homeless adults with mean age of 42.6 years. Compared to no intervention, daily symptom screening with ACSs for pending tests or confirmed COVID-19 and mild/moderate disease led to 37% fewer infections and 46% lower costs (Re=2.6), 75% fewer infections and 72% lower costs (Re=1.3), and 51% fewer infections and 51% lower costs (Re=0.9). Adding PCR testing every 2 weeks further decreased infections; incremental cost per case prevented was $1,000 (Re=2.6), $27,000 (Re=1.3), and $71,000 (Re=0.9). Temporary housing with PCR every 2 weeks was most effective but substantially more costly than other options. Results were sensitive to cost and sensitivity of PCR and ACS efficacy in preventing transmission. CONCLUSIONS & RELEVANCE: In this modeling study of simulated adults living in homeless shelters, daily symptom screening and ACSs were associated with fewer COVID-19 infections and decreased costs compared with no intervention. In a modeled surging epidemic, adding universal PCR testing every 2 weeks was associated with further decrease in COVID-19 infections at modest incremental cost and should be considered during future surges.

Cost-effectiveness of public health strategies for COVID-19 epidemic control in South Africa: a microsimulation modelling study.

BACKGROUND: Healthcare resource constraints in low and middle-income countries necessitate selection of cost-effective public health interventions to address COVID-19. METHODS: We developed a dynamic COVID-19 microsimulation model to evaluate clinical and economic outcomes and cost-effectiveness of epidemic control strategies in KwaZulu-Natal, South Africa. Interventions assessed were Healthcare Testing (HT), where diagnostic testing is performed only for those presenting to healthcare centres; Contact Tracing (CT) in households of cases; Isolation Centres (IC), for cases not requiring hospitalisation; community health worker-led Mass Symptom Screening and molecular testing for symptomatic individuals (MS); and Quarantine Centres (QC), for household contacts who test negative. Given uncertainties about epidemic dynamics in South Africa, we evaluated two main epidemic scenarios over 360 days, with effective reproduction numbers (Re) of 1·5 and 1·2. We compared HT, HT+CT, HT+CT+IC, HT+CT+IC+MS, HT+CT+IC+QC, and HT+CT+IC+MS+QC, considering strategies with incremental cost-effectiveness ratio (ICER)