Bayesian estimation of the prevalence of antimicrobial resistance: a mathematical modelling study.

BACKGROUND: Estimates of the prevalence of antimicrobial resistance (AMR) underpin effective antimicrobial stewardship, infection prevention and control, and optimal deployment of antimicrobial agents. Typically, the prevalence of AMR is determined from real-world antimicrobial susceptibility data that are time delimited, sparse, and often biased, potentially resulting in harmful and wasteful decision-making. Frequentist methods are resource intensive because they rely on large datasets. OBJECTIVES: To determine whether a Bayesian approach could present a more reliable and more resource-efficient way to estimate population prevalence of AMR than traditional frequentist methods. METHODS: Retrospectively collected, open-source, real-world pseudonymized healthcare data were used to develop a Bayesian approach for estimating the prevalence of AMR by combination with prior AMR information from a contextualized review of literature. Iterative random sampling and cross-validation were used to assess the predictive accuracy and potential resource efficiency of the Bayesian approach compared with a standard frequentist approach. RESULTS: Bayesian estimation of AMR prevalence made fewer extreme estimation errors than a frequentist estimation approach [n = 74 (6.4%) versus n = 136 (11.8%)] and required fewer observed antimicrobial susceptibility results per pathogen on average [mean = 28.8 (SD = 22.1) versus mean = 34.4 (SD = 30.1)] to avoid any extreme estimation errors in 50 iterations of the cross-validation. The Bayesian approach was maximally effective and efficient for drug-pathogen combinations where the actual prevalence of resistance was not close to 0% or 100%. CONCLUSIONS: Bayesian estimation of the prevalence of AMR could provide a simple, resource-efficient approach to better inform population infection management where uncertainty about AMR prevalence is high.

Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review.

Antimicrobial resistance (AMR) emerges when disease-causing microorganisms develop the ability to withstand the effects of antimicrobial therapy. This phenomenon is often fueled by the human-to-human transmission of pathogens and the overuse of antibiotics. Over the past 50 years, increased computational power has facilitated the application of Bayesian inference algorithms. In this comprehensive review, the basic theory of Markov Chain Monte Carlo (MCMC) and Sequential Monte Carlo (SMC) methods are explained. These inference algorithms are instrumental in calibrating complex statistical models to the vast amounts of AMR-related data. Popular statistical models include hierarchical and mixture models as well as discrete and stochastic epidemiological compartmental and agent based models. Studies encompassed multi-drug resistance, economic implications of vaccines, and modeling AMR in vitro as well as within specific populations. We describe how combining these topics in a coherent framework can result in an effective antimicrobial stewardship. We also outline recent advancements in the methodology of Bayesian inference algorithms and provide insights into their prospective applicability for modeling AMR in the future.

Simulation to optimize the laboratory diagnosis of bacteremia.

Blood cultures are central to the management of patients with sepsis and bloodstream infection. Clinical decisions depend on the timely availability of laboratory information, which, in turn, depends on the optimal laboratory processing of specimens. Discrete event simulation (DES) offers insights into where optimization efforts can be targeted. Here, we generate a detailed process map of blood culture processing within a laboratory and use it to build a simulator. Direct observation of laboratory staff processing blood cultures was used to generate a flowchart of the blood culture laboratory pathway. Retrospective routinely collected data were combined with direct observations to generate probability distributions over the time taken for each event. These data were used to inform the DES model. A sensitivity analysis explored the impact of staff availability on turnaround times. A flowchart of the blood culture pathway was constructed, spanning labeling, incubation, organism identification, and antimicrobial susceptibility testing. Thirteen processes in earlier stages of the pathway, not otherwise captured by routinely collected data, were timed using direct observations. Observations revealed that specimen processing is predominantly batched. Another eight processes were timed using retrospective data. A simulator was built using DES. Sensitivity analysis revealed that specimen progression through the simulation was especially sensitive to laboratory technician availability. Gram stain reporting time was also sensitive to laboratory scientist availability. Our laboratory simulation model has wide-ranging applications for the optimization of laboratory processes and effective implementation of the changes required for faster and more accurate results. IMPORTANCE: Optimization of laboratory pathways and resource availability has a direct impact on the clinical management of patients with bloodstream infection. This research offers an insight into the laboratory processing of blood cultures at a system level and allows clinical microbiology laboratories to explore the impact of changes to processes and resources.

Finding the "Right-Size" Physical Therapy Workforce: International Perspective Across 4 Countries.

Finding the "right-size" physical therapy workforce is an increasingly important issue, but it has had limited study, particularly across nations. This perspective article provides a comprehensive examination of physical therapy workforce issues across 4 countries (United States, Singapore, Portugal, and Bangladesh), which were deliberately selected to allow consideration of key contextual factors. This investigation provides a theoretical model uniquely adapted to focus on variables most likely to affect physical therapy workforce needs. This theoretical model was used to guide acquisition of public domain data across the respective countries. The data then were used to provide a contextualized interpretation about the physical therapy workforce supply (ie, physical therapists per capita) across the 4 countries in light of the following factors: indicators of physical therapy need, financial and administrative barriers affecting physical therapy access and demand, the proportion of physical therapy graduates (with varying trends over time across the countries), and the role of emigration/immigration in supply inequalities among countries of lower and higher income. In addition, both the physical therapy workforce supply and scope of practice were analyzed in the context of other related professions across the 4 countries. This international comparison indicated that there may not be a "one-size-fits-all" recommendation for physical therapy workforce supply across countries or an ideal formula for its determination. The optimal, country-specific physical therapy workforce supply appears to be affected by discipline-specific health care and contextual factors that may vary across countries, and even within the same country. This article provides a conceptual framework and basis for such contextualized evaluations of the physical therapy workforce.

Secretion of a collectin-like protein in tunicates is enhanced during inflammatory responses.

The sub-cellular and humoral concentrations of a collectin-like protein from the solitary tunicate, Styela plicata, were measured after in vivo challenge with the inflammatory agent, zymosan. Tunicates were injected with zymosan before hemocytes and serum were harvested, subjected to western blotting and immunostained with an anti-S. plicata collectin antibody to determine the relative titers of collectin-like proteins. Concentrations of the predominant 43kDa collectin polypeptide were found to decrease in hemocytes immediately after zymosan injection, before rising to levels that were six times higher than controls within 96h. Similarly, immunohistochemistry showed that the frequency of collectin-positive hemocytes in the circulating hemolymph increased significantly within 96h of injection. Levels of the 43kDa polypeptide in serum mirrored those of hemocytes. Humoral collectin concentrations decreased immediately after zymosan injection before rising, within 96h post-injection, to levels three times higher than controls. This response to an inflammatory stimulus resembles that of mammalian collectins like mannose-binding lectin. The data suggest that, like its mammalian counterparts, the tunicate collectin acts as an acute phase antigen recognition protein.