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The U.S. Ryan White HIV/AIDS Program (RWHAP) funds comprehensive services for people living with HIV to support viral suppression (VS). We analyzed five years of RWHAP data from the Minneapolis-St. Paul region to (1) assess variation and (2) evaluate the causal effect of each RWHAP service on sustained VS by race/ethnicity. Sixteen medical and support services were included. Descriptive analyses assessed service use and trends over time. Causal analyses used generalized estimating equations and propensity scores to adjust for the probability of service use. Receipt of AIDS Drug Assistance Program and financial aid consistently showed higher probabilities of sustained VS, while food aid and transportation aid had positive impacts on VS at higher levels of service encounters; however, the impact of services could vary by race/ethnicity. For example, financial aid increased the probability of sustained VS by at least 3 percentage points for white, Hispanic and Black/African American clients, but only 1.6 points for Black/African-born clients. This study found that services addressing socioeconomic needs typically had positive impacts on viral suppression, yet service use and impact of services often varied by race/ethnicity. This highlights a need to ensure these services are designed and delivered in ways that equitably serve all clients. [ABSTRACT FROM AUTHOR]

Background: Gonorrhea incidence in the United States has risen by nearly 50% in the last decade, while screening rates have increased. Gonorrhea sequelae rates could indicate whether increased gonorrhea incidence is due to better screening. We estimated the association of gonorrhea diagnosis with pelvic inflammatory disease (PID), ectopic pregnancy (EP), and tubal factor infertility (TFI) in women and detected changes in associations over time. Materials and Methods: This retrospective cohort study included 5,553,506 women aged 18–49 tested for gonorrhea in the IBM MarketScan claims administrative database from 2013–2018 in the United States. We estimated incidence rates and hazard ratios (HRs) of gonorrhea diagnosis for each outcome, adjusting for potential confounders using Cox proportional hazards models. We tested the interaction between gonorrhea diagnosis and the initial gonorrhea test year to identify changes in associations over time. Results: We identified 32,729 women with a gonorrhea diagnosis (mean follow-up time in years: PID = 1.73, EP = 1.75, TFI = 1.76). A total of 131,500 women were diagnosed with PID, 64,225 had EP, and 41,507 had TFI. Women with gonorrhea diagnoses had greater incidence per 1000 person-years for all outcomes (PID = 33.5, EP = 9.4, TFI = 5.3) compared to women without gonorrhea diagnoses (PID = 13.9, EP = 6.7, TFI = 4.3). After adjustment, HRs were higher in women with a gonorrhea diagnosis vs. those without [PID = 2.29 (95% confidence interval, CI: 2.15–2.44), EP = 1.57, (95% CI: 1.41–1.76), TFI = 1.70 (95% CI: 1.47–1.97)]. The interaction of gonorrhea diagnosis and test year was not significant, indicating no change in relationship by initial test year. Conclusion: The relationship between gonorrhea and reproductive outcomes has persisted, suggesting a higher disease burden. [ABSTRACT FROM AUTHOR]

Experiencing housing instability, food insecurity, and financial stress can negatively impact retention in care and treatment adherence for people living with HIV. Expanding services that support socioeconomic needs could help improve HIV outcomes. Our objective was to investigate barriers, opportunities, and costs of expanding socioeconomic support programs. Semi-structured interviews were conducted with organizations serving U.S. Ryan White HIV/AIDS Program clients. Costs were estimated from interviews, organization documents, and city-specific wages. Organizations reported complex patient, organization, program, and system challenges as well as several opportunities for expansion. The average one-year per-person cost for engaging new clients was $196 for transportation, $612 for financial aid, $650 for food aid, and $2498 for short-term housing (2020 USD). Understanding potential expansion costs is important for funders and local stakeholders. This study provides a sense of magnitude for costs to scale-up programs to better meet socioeconomic needs of low-income patients living with HIV. [ABSTRACT FROM AUTHOR]

In an introductory tutorial, we illustrated building cohort state-transition models (cSTMs) in R, where the state transition probabilities were constant over time. However, in practice, many cSTMs require transitions, rewards, or both to vary over time (time dependent). This tutorial illustrates adding 2 types of time dependence using a previously published cost-effectiveness analysis of multiple strategies as an example. The first is simulation-time dependence, which allows for the transition probabilities to vary as a function of time as measured since the start of the simulation (e.g., varying probability of death as the cohort ages). The second is state-residence time dependence, allowing for history by tracking the time spent in any particular health state using tunnel states. We use these time-dependent cSTMs to conduct cost-effectiveness and probabilistic sensitivity analyses. We also obtain various epidemiological outcomes of interest from the outputs generated from the cSTM, such as survival probability and disease prevalence, often used for model calibration and validation. We present the mathematical notation first, followed by the R code to execute the calculations. The full R code is provided in a public code repository for broader implementation. [ABSTRACT FROM AUTHOR]

Decision models can combine information from different sources to simulate the long-term consequences of alternative strategies in the presence of uncertainty. A cohort state-transition model (cSTM) is a decision model commonly used in medical decision making to simulate the transitions of a hypothetical cohort among various health states over time. This tutorial focuses on time-independent cSTM, in which transition probabilities among health states remain constant over time. We implement time-independent cSTM in R, an open-source mathematical and statistical programming language. We illustrate time-independent cSTMs using a previously published decision model, calculate costs and effectiveness outcomes, and conduct a cost-effectiveness analysis of multiple strategies, including a probabilistic sensitivity analysis. We provide open-source code in R to facilitate wider adoption. In a second, more advanced tutorial, we illustrate time-dependent cSTMs. [ABSTRACT FROM AUTHOR]

Background Both the American College of Gastroenterology and the Infectious Diseases Society of America (IDSA)/Society for Healthcare Epidemiology of America 2021 Clostridioides difficile infection (CDI) guidelines recommend fecal microbiota transplantation (FMT) for persons with multiple recurrent CDI. Emerging data suggest that FMT may have high cure rates when used for first recurrent CDI. The aim of this study was to assess the cost-effectiveness of FMT for first recurrent CDI. Methods We developed a Markov model to simulate a cohort of patients presenting with initial CDI infection. The model estimated the costs, effectiveness, and cost-effectiveness of different CDI treatment regimens recommended in the 2021 IDSA guidelines, with the additional option of FMT for first recurrent CDI. The model includes stratification by the severity of initial infection, estimates of cure, recurrence, and mortality. Data sources were taken from IDSA guidelines and published literature on treatment outcomes. Outcome measures were quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). Results When FMT is available for first recurrent CDI, the optimal cost-effective treatment strategy is fidaxomicin for initial nonsevere CDI, vancomycin for initial severe CDI, and FMT for first and subsequent recurrent CDI, with an ICER of $27 135/QALY. In probabilistic sensitivity analysis at a $100 000 cost-effectiveness threshold, FMT for first and subsequent CDI recurrence was cost-effective 90% of the time given parameter uncertainty. Conclusions FMT is a cost-effective strategy for first recurrent CDI. Prospective evaluation of FMT for first recurrent CDI is warranted to determine the efficacy and risk of recurrence. [ABSTRACT FROM AUTHOR]

Engagement in lifelong HIV care is critical for both patient and public health, yet there are limited resources to invest in improving HIV outcomes. We systematically reviewed evidence on the cost-effectiveness of retention and re-engagement interventions. We searched five databases for peer-reviewed studies published between 2010 and 2020. We assessed reporting and methods quality, extracted data on target populations, interventions, and cost-effectiveness, and evaluated overall strength of evidence. Eleven studies met inclusion criteria, and eight had moderate-high quality. Cost-effectiveness estimates ranged from cost-saving to over $1,000,000/quality-adjusted life year (QALY) gained. Of the 73 cost-effectiveness ratios reported, 64% were < $100,000/QALY gained. Interventions were more likely to be cost-effective when targeted to high-risk groups, implemented in locations where baseline retention levels were low, and when used in combination with other high-impact HIV interventions (such as prevention). Overall, existing evidence is moderately strong that retention and/or re-engagement interventions can be cost-effective in high-income countries. [ABSTRACT FROM AUTHOR]

Background: University students have higher average number of contacts than the general population. Students returning to university campuses may exacerbate COVID-19 dynamics in the surrounding community. Methods: We developed a dynamic transmission model of COVID-19 in a mid-sized city currently experiencing a low infection rate. We evaluated the impact of 20,000 university students arriving on September 1 in terms of cumulative COVID-19 infections, time to peak infections, and the timing and peak level of critical care occupancy. We also considered how these impacts might be mitigated through screening interventions targeted to students. Results: If arriving students reduce their contacts by 40% compared to pre-COVID levels, the total number of infections in the community increases by 115% (from 3,515 to 7,551), with 70% of the incremental infections occurring in the general population, and an incremental 19 COVID-19 deaths. Screening students every 5 days reduces the number of infections attributable to the student population by 42% and the total COVID-19 deaths by 8. One-time mass screening of students prevents fewer infections than 5-day screening, but is more efficient, requiring 196 tests needed to avert one infection instead of 237. Interpretation: University students are highly inter-connected with the surrounding off-campus community. Screening targeted at this population provides significant public health benefits to the community through averted infections, critical care admissions, and COVID-19 deaths. [ABSTRACT FROM AUTHOR]

Background: Analyses of the effectiveness of infectious disease control interventions often rely on dynamic transmission models to simulate intervention effects. We aim to understand how the choice of network or compartmental model can influence estimates of intervention effectiveness in the short and long term for an endemic disease with susceptible and infected states in which infection, once contracted, is lifelong. Methods: We consider 4 disease models with different permutations of socially connected network versus unstructured contact (mass-action mixing) model and heterogeneous versus homogeneous disease risk. The models have susceptible and infected populations calibrated to the same long-term equilibrium disease prevalence. We consider a simple intervention with varying levels of coverage and efficacy that reduces transmission probabilities. We measure the rate of prevalence decline over the first 365 d after the intervention, long-term equilibrium prevalence, and long-term effective reproduction ratio at equilibrium. Results: Prevalence declined up to 10% faster in homogeneous risk models than heterogeneous risk models. When the disease was not eradicated, the long-term equilibrium disease prevalence was higher in mass-action mixing models than in network models by 40% or more. This difference in long-term equilibrium prevalence between network versus mass-action mixing models was greater than that of heterogeneous versus homogeneous risk models (less than 30%); network models tended to have higher effective reproduction ratios than mass-action mixing models for given combinations of intervention coverage and efficacy. Conclusions: For interventions with high efficacy and coverage, mass-action mixing models could provide a sufficient estimate of effectiveness, whereas for interventions with low efficacy and coverage, or interventions in which outcomes are measured over short time horizons, predictions from network and mass-action models diverge, highlighting the importance of sensitivity analyses on model structure. Highlights: • We calibrate 4 models—socially connected network versus unstructured contact (mass-action mixing) model and heterogeneous versus homogeneous disease risk—to 10% preintervention disease prevalence. • We measure the short- and long-term intervention effectiveness of all models using the rate of prevalence decline, long-term equilibrium disease prevalence, and effective reproduction ratio. • Generally, in the short term, prevalence declined faster in the homogeneous risk models than in the heterogeneous risk models. • Generally, in the long term, equilibrium disease prevalence was higher in the mass-action mixing models than in the network models, and the effective reproduction ratio was higher in network models than in the mass-action mixing models. [ABSTRACT FROM AUTHOR]

Background: Relapsing-onset multiple sclerosis (MS) typically starts in early- to mid-adulthood, yet the trajectory of disease activity over the subsequent lifetime remains poorly defined. Previous studies have not quantified the age-specific portion of decreases in annualized relapse rates (ARR). Objective: The aim of this article is to determine, under a range of disease-related assumptions, the age-specific component of decreases in ARR over time among adults with relapsing-onset MS. Methods: We used a simulation modeling approach to examine a range of assumptions about changes in ARR due to age versus disability status. Scenarios included variations in initial ARR and rate of worsening on the Expanded Disability Status Scale. Model parameters were developed through analysis of MS patients in British Columbia, Canada, and literature review. Results: We found a substantial age-specific decrease in ARR in all simulated scenarios, independent of disability worsening. Under a range of clinically plausible assumptions, 88%–97% of the decrease was attributed to age and 3%–13% to disability. The age-specific decrease ranged from 22% to 37% per 5 years for a wide range of initial ARR (0.33–1.0). Conclusion: Decreases in ARR were due mostly to age rather than disability status. To facilitate informed decision making in MS, it is important to quantify the dynamic relationship between relapses and age. [ABSTRACT FROM AUTHOR]

Background In 2018, the Infectious Diseases Society of America (IDSA) published guidelines for diagnosis and treatment of Clostridioides (formerly Clostridium) difficile infection (CDI). However, there is little guidance regarding which treatments are cost-effective. Methods We used a Markov model to simulate a cohort of patients presenting with an initial CDI diagnosis. We used the model to estimate the costs, effectiveness, and cost-effectiveness of different CDI treatment regimens recommended in the recently published 2018 IDSA guidelines. The model includes stratification by the severity of the initial infection, and subsequent likelihood of cure, recurrence, mortality, and outcomes of subsequent recurrences. Data sources were taken from IDSA guidelines and published literature on treatment outcomes. Outcome measures were discounted quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). Results Use of fidaxomicin for nonsevere initial CDI, vancomycin for severe CDI, fidaxomicin for first recurrence, and fecal microbiota transplantation (FMT) for subsequent recurrence (strategy 44) cost an additional $478 for 0.009 QALYs gained per CDI patient, resulting in an ICER of $31 751 per QALY, below the willingness-to-pay threshold of $100 000/QALY. This is the optimal, cost-effective CDI treatment strategy. Conclusions Metronidazole is suboptimal for nonsevere CDI as it is less beneficial than alternative strategies. The preferred treatment regimen is fidaxomicin for nonsevere CDI, vancomycin for severe CDI, fidaxomicin for first recurrence, and FMT for subsequent recurrence. The most effective treatments, with highest cure rates, are also cost-effective due to averted mortality, utility loss, and costs of rehospitalization and/or further treatments for recurrent CDI. [ABSTRACT FROM AUTHOR]

Background: For older adults with relapsing-onset multiple sclerosis (MS), limited information is available to inform if, or when, disease-modifying drugs (DMDs) may be safely discontinued. Objective: The aim of this study was to project the outcomes of DMD discontinuation among older adults with relapsing-onset MS. Methods: We projected the 10-year outcomes of discontinuation of a DMD (interferon-β, fingolimod, or natalizumab) among older adults (aged 55 or 70 years) who were relapse-free for 5 or more years and had not reached an Expanded Disability Status Scale (EDSS) score of 6. Outcomes included the percentage of people who had at least one relapse or reached EDSS 6, and quality-adjusted life-years (QALYs), which incorporated both relapses and disability. We used a simulation modeling approach. With increased age, relapses decreased and the effectiveness of DMDs for disability outcomes also decreased. Results: We found lower projected benefits for DMD continuation at 70 years of age than at 55 years of age. Compared with discontinuation, the projected benefit of DMD continuation ranged from 0.007 to 0.017 QALYs at 55 years of age and dropped to 0.002–0.006 at 70 years of age. The annual projected benefits of DMD continuation (0.1–3.0 quality-adjusted life-days) were very low compared with typical patient preferences regarding treatment burden. Conclusion: The benefits of DMDs may not be substantial among older adults with relapsing-onset MS. Direct clinical evidence remains limited and the decision of whether to discontinue a DMD should also take into account patient preferences. It is important to gain a better understanding of how age-related changes in the trajectory of relapsing-onset MS affect treatment effectiveness among older adults. [ABSTRACT FROM AUTHOR]

Background: It is well established that network structure strongly influences infectious disease dynamics. However, little is known about how the network structure impacts the cost-effectiveness of disease control strategies. We evaluated partner management strategies to address bacterial sexually transmitted infections (STIs) as a case study to explore the influence of the network structure on the optimal disease management strategy.Methods: We simulated a hypothetical bacterial STI spread through 4 representative network structures: random, community-structured, scale-free, and empirical. We simulated disease outcomes (prevalence, incidence, total infected person-months) and cost-effectiveness of 4 partner management strategies in each network structure: routine STI screening alone (no partner management), partner notification, expedited partner therapy, and contact tracing. We determined the optimal partner management strategy following a cost-effectiveness framework and varied key compliance parameters of partner management in sensitivity analysis.Results: For the same average number of contacts and disease parameters in our setting, community-structured networks had the lowest incidence, prevalence, and total infected person-months, whereas scale-free networks had the highest without partner management. The highly connected individuals were more likely to be reinfected in scale-free networks than in the other network structures. The cost-effective partner management strategy depended on the network structures, the compliance in partner management, the willingness-to-pay threshold, and the rate of external force of infection.Conclusions: Our findings suggest that contact network structure matters in determining the optimal disease control strategy in infectious diseases. Information on a population's contact network structure may be valuable for informing optimal investment of limited resources. [ABSTRACT FROM AUTHOR]

Cost-effectiveness analyses often rely on cohort state-transition models (cSTMs). The cohort trace is the primary outcome of cSTMs, which captures the proportion of the cohort in each health state over time (state occupancy). However, the cohort trace is an aggregated measure that does not capture information about the specific transitions among health states (transition dynamics). In practice, these transition dynamics are crucial in many applications, such as incorporating transition rewards or computing various epidemiological outcomes that could be used for model calibration and validation (e.g., disease incidence and lifetime risk). In this article, we propose an alternative approach to compute and store cSTMs outcomes that capture both state occupancy and transition dynamics. This approach produces a multidimensional array from which both the state occupancy and the transition dynamics can be recovered. We highlight the advantages of the multidimensional array over the traditional cohort trace and provide potential applications of the proposed approach with an example coded in R to facilitate the implementation of our method. [ABSTRACT FROM AUTHOR]

Antimicrobial use contributes to the growing public health challenge of infectious diseases that are resistant to all but a few remaining treatments via natural selection. When few treatment options remain, should the last effective treatment be reserved for controlling larger outbreaks in the future? In "Dynamics of Drug Resistance: Optimal Control of an Infectious Disease," N. Chehrazi, L. E. Cipriano, and E. A. Enns formulate this important policy question as a control problem with two state variables—disease prevalence and the level of treatment resistance—for an established family of SIS infectious disease models with resistance. They prove that when the disease transmission rate is constant, it is optimal to treat everyone until the level of resistance is so high that it is no longer economical to treat anyone. Public health policies and social distancing can cause a nonconstant disease transmission rate; in these cases, it may be optimal to preserve the drug for relatively larger outbreaks or to use the drug to treat some, but not all, infected individuals. Antimicrobial resistance is a significant public health threat. In the United States alone, two million people are infected, and 23,000 die each year from antibiotic-resistant bacterial infections. In many cases, infections are resistant to all but a few remaining drugs. We examine the case in which a single drug remains and solve for the optimal treatment policy for a susceptible–infected–susceptible infectious disease model, incorporating the effects of drug resistance. The problem is formulated as an optimal control problem with two continuous state variables: the disease prevalence and drug's "quality" (the fraction of infections that are drug-susceptible). The decision maker's objective is to minimize the discounted cost of the disease to society over an infinite horizon. We provide a new generalizable solution approach that allows us to thoroughly characterize the optimal treatment policy analytically. We prove that the optimal treatment policy is a bang-bang policy with a single switching time. The action/inaction regions can be described by a single boundary that is strictly increasing when viewed as a function of drug quality, indicating that, when the disease transmission rate is constant, the policy of withholding treatment to preserve the drug for a potentially more serious future outbreak is not optimal. We show that the optimal value function and/or its derivatives are neither C1 nor Lipschitz continuous, suggesting that numerical approaches to this family of dynamic infectious disease models may not be computationally stable. Furthermore, we demonstrate that relaxing the standard assumption of a constant disease transmission rate can fundamentally change the shape of the action region, add a singular arc to the optimal control, and make preserving the drug for a serious outbreak optimal. In addition, we apply our framework to the case of antibiotic-resistant gonorrhea. [ABSTRACT FROM AUTHOR]