Adaptive guidelines for the treatment of gonorrhea to increase the effective life span of antibiotics among men who have sex with men in the United States: A mathematical modeling study

Cyr SB, Yaesoubi R. Personalizing the empiric treatment of gonorrhea using machine learning models

Despite the emergence of antimicrobial-resistant (AMR) strains of Neisseria gonorrhoeae, the treatment of gonorrhea remains empiric and according to standardized guidelines, which are informed by the national prevalence of resistant strains. Yet, the prevalence of AMR varies substantially across geographic and demographic groups. We investigated whether data from the national surveillance system of AMR gonorrhea in the US could be used to personalize the empiric treatment of gonorrhea. We used data from the Gonococcal Isolate Surveillance Project collected between 2000-2010 to train and validate machine learning models to identify resistance to ciprofloxacin (CIP), one of the recommended first-line antibiotics until 2007. We used these models to personalize empiric treatments based on sexual behavior and geographic location and compared their performance with standardized guidelines, which recommended treatment with CIP, ceftriaxone (CRO), or cefixime (CFX) between 2005-2006, and either CRO or CFX between 2007-2010. Compared with standardized guidelines, the personalized treatments could have replaced 33% of CRO and CFX use with CIP while ensuring that 98% of patients were prescribed effective treatment during 2005-2010. The models maintained their performance over time and across geographic regions. Predictive models trained on data from national surveillance systems of AMR gonorrhea could be used to personalize the empiric treatment of gonorrhea based on patients' basic characteristics at the point of care. This approach could reduce the unnecessary use of newer antibiotics while maintaining the effectiveness of first-line therapy.

Assessing thresholds of resistance prevalence at which empiric treatment of gonorrhea should change among men who have sex with men in the US: A cost-effectiveness analysis

BACKGROUND

Since common diagnostic tests for gonorrhea do not provide information about susceptibility to antibiotics, treatment of gonorrhea remains empiric. Antibiotics used for empiric therapy are usually changed once resistance prevalence exceeds a certain threshold (e.g., 5%). A low switch threshold is intended to increase the probability that an infection is successfully treated with the first-line antibiotic, but it could also increase the pace at which recommendations are switched to newer antibiotics. Little is known about the impact of changing the switch threshold on the incidence of gonorrhea, the rate of treatment failure, and the overall cost and quality-adjusted life-years (QALYs) associated with gonorrhea.

METHODS AND FINDINGS

We developed a transmission model of gonococcal infection with multiple resistant strains to project gonorrhea-associated costs and loss in QALYs under different switch thresholds among men who have sex with men (MSM) in the United States. We accounted for the costs and disutilities associated with symptoms, diagnosis, treatment, and sequelae, and combined costs and QALYs in a measure of net health benefit (NHB). Our results suggest that under a scenario where 3 antibiotics are available over the next 50 years (2 suitable for the first-line therapy of gonorrhea and 1 suitable only for the retreatment of resistant infections), changing the switch threshold between 1% and 10% does not meaningfully impact the annual number of gonorrhea cases, total costs, or total QALY losses associated with gonorrhea. However, if a new antibiotic is to become available in the future, choosing a lower switch threshold could improve the population NHB. If in addition, drug-susceptibility testing (DST) is available to inform retreatment regimens after unsuccessful first-line therapy, setting the switch threshold at 1% to 2% is expected to maximize the population NHB. A limitation of our study is that our analysis only focuses on the MSM population and does not consider the influence of interventions such as vaccine and common use of rapid drugs susceptibility tests to inform first-line therapy.

CONCLUSIONS

Changing the switch threshold for first-line antibiotics may not substantially change the health and financial outcomes associated with gonorrhea. However, the switch threshold could be reduced when newer antibiotics are expected to become available soon or when in addition to future novel antibiotics, DST is also available to inform retreatment regimens.

Estimating Partnership Duration among MSM in Belgium-A Modeling Study

Mathematical modeling is widely used for describing infection transmission and evaluating interventions. The lack of reliable social parameters in the literature has been mentioned by many modeling studies, leading to limitations in the validity and interpretation of the results. Using data from the European MSM Internet survey 2017, we developed a network model to describe sex acts among MSM in Belgium. The model simulates daily sex acts among steady, persistent casual and one-off partners in a population of 10,000 MSM, grouped as low- or high-activity by using three different definitions. Model calibration was used to estimate partnership duration and homophily rates to match the distribution of cumulative sex partners over 12 months. We estimated an average duration between 1065 and 1409 days for steady partnerships, 4-6 and 251-299 days for assortative high- and low-activity individuals and 8-13 days for disassortative persistent casual partnerships, respectively, varying across the three definitions. High-quality data on social network and behavioral parameters are scarce in the literature. Our study addresses this lack of information by providing a method to estimate crucial parameters for network specification.

Cyr SB, Rönn MM, Salomon JA, Grad YH. The Impact of Rapid Drug Susceptibility Tests on Gonorrhea Burden and the Life Span of Antibiotic Treatments: A Modeling Study Among Men Who Have Sex With Men in the United States

Rapid point-of-care tests that diagnose gonococcal infections and identify susceptibility to antibiotics enable individualized treatment. This could improve patient outcomes and slow the emergence and spread of antibiotic resistance. However, little is known about the long-term impact of such diagnostics on the burden of gonorrhea and the effective life span of antibiotics. We used a mathematical model of gonorrhea transmission among men who have sex with men in the United States to project the annual rate of reported gonorrhea cases and the effective life span of ceftriaxone, the recommended antibiotic for first-line treatment of gonorrhea, as well as 2 previously recommended antibiotics, ciprofloxacin and tetracycline, when a rapid drug susceptibility test that estimates susceptibility to ciprofloxacin and tetracycline is available. The use of a rapid drug susceptibility test with ≥50% sensitivity and ≥95% specificity, defined in terms of correct ascertainment of drug susceptibility and nonsusceptibility status, could increase the combined effective life span of ciprofloxacin, tetracycline, and ceftriaxone by at least 2 years over 25 years of simulation. If test specificity is imperfect, however, the increase in the effective life span of antibiotics is accompanied by an increase in the rate of reported gonorrhea cases even under perfect sensitivity.

Cyr SB, Salomon JA, Grad YH. Evaluating spatially adaptive guidelines for the treatment of gonorrhea to reduce the incidence of gonococcal infection and increase the effective lifespan of antibiotics

In the absence of point-of-care gonorrhea diagnostics that report antibiotic susceptibility, gonorrhea treatment is empiric and determined by standardized guidelines. These guidelines are informed by estimates of resistance prevalence from national surveillance systems. We examined whether guidelines informed by local, rather than national, surveillance data could reduce the incidence of gonorrhea and increase the effective lifespan of antibiotics used in treatment guidelines. We used a transmission dynamic model of gonorrhea among men who have sex with men (MSM) in 16 U.S. metropolitan areas to determine whether spatially adaptive treatment guidelines based on local estimates of resistance prevalence can extend the effective lifespan of hypothetical antibiotics. The rate of gonorrhea cases in these metropolitan areas was 5,548 cases per 100,000 MSM in 2017. Under the current strategy of updating the treatment guideline when the prevalence of resistance exceeds 5%, we showed that spatially adaptive guidelines could reduce the annual rate of gonorrhea cases by 200 cases (95% uncertainty interval: 169, 232) per 100,000 MSM population while extending the use of a first-line antibiotic by 0.75 (0.55, 0.95) years. One potential strategy to reduce the incidence of gonorrhea while extending the effective lifespan of antibiotics is to inform treatment guidelines based on local, rather than national, resistance prevalence.

Antimicrobial resistance threatens the effective treatment of a growing number of infections worldwide. In the absence of rapid point-of-care diagnostics that determine antibiotic susceptibility, the treatment of several infections caused by bacteria (e.g., gonorrhea and tuberculosis) remain empiric and informed by guidelines. These guidelines are usually determined at the national level and based on the estimated resistance prevalence nationally. Here, we show that more cases of gonorrhea could be prevented and the effective lifespan of antibiotics suitable for the treatment of gonorrhea could be extended if treatment guidelines are determined locally and based on the regional resistance prevalence rather than on a single nationwide recommendation. Our analysis provides evidence to highlight the importance of 1) maintaining local surveillance systems of antimicrobial resistance and 2) engaged policymakers who use the data from these surveillance systems to inform timely and effective decisions at the local level.

Adaptive Policies to Balance Health Benefits and Economic Costs of Physical Distancing Interventions during the COVID-19 Pandemic

Policy makers need decision tools to determine when to use physical distancing interventions to maximize the control of COVID-19 while minimizing the economic and social costs of these interventions. We describe a pragmatic decision tool to characterize adaptive policies that combine real-time surveillance data with clear decision rules to guide when to trigger, continue, or stop physical distancing interventions during the current pandemic. In model-based experiments, we find that adaptive policies characterized by our proposed approach prevent more deaths and require a shorter overall duration of physical distancing than alternative physical distancing policies. Our proposed approach can readily be extended to more complex models and interventions.