Dynamic transmission models for economic analysis applied to health care-associated infections: A review of the literature

The Efficiency of Increased HCV Testing and Treatment Strategies in Spain to Achieve Elimination Goals

BACKGROUND

In 2015, Spain launched a national eradication strategy for hepatitis C virus (HCV), resulting in the highest treatment rate in Europe and substantial reductions in HCV prevalence. However, to achieve the goal of HCV elimination, it is necessary to scale-up the diagnosis, treatment, and management of HCV infection.

OBJECTIVE

Our aim was to assess the prevalence, incidence, and cost effectiveness of scaling-up compared with status quo scenarios.

METHODS

A compartmental dynamic transmission model was developed comprising of a cascade of care and a liver progression module. Cost and quality-of-life inputs were sourced from the literature. Key outcomes were the prevalence and incidence of HCV and the incremental cost per quality-adjusted life-year (QALY) and per life-year (LY). Outcomes for a hypothetical elimination strategy were compared with the status quo.

RESULTS

The base-case analysis found that scaling-up testing and treatment reduced both the prevalence and incidence of HCV over time, resulting in incremental costs per QALY and LY of €13,291 and €12,285 respectively, compared with the status quo. The main drivers of the cost-effectiveness results included cost of diagnosis, cost of treatment, proportion of people who are unaware, percentage of population who inject drugs, and calibration parameters related to HCV infection prevalence.

CONCLUSIONS

This analysis demonstrated that scaling-up testing and treatment with direct-acting antivirals may be an efficient strategy for reducing the incidence and prevalence of HCV and may help achieve HCV elimination goals in Spain.

Economic Evaluations of New Antibiotics: The High Potential Value of Reducing Healthcare Transmission Through Decolonization

Background

Antibiotics designed to decolonize carriers of drug-resistant organisms could offer substantial population health benefits, particularly if they can help avert outbreaks by interrupting person-to-person transmission chains. However, cost effectiveness of an antibiotic is typically evaluated only according to its benefits to recipients, which can be difficult to demonstrate for carriers of an organism that may not pose an immediate health threat to the carrier.

Methods

We developed a mathematical transmission model to quantify the effects of 2 hypothetical antibiotics targeting carbapenem-resistant Enterobacteriaceae (CRE) among long-term acute care hospital inpatients: one assumed to decrease the death rate of patients with CRE bloodstream infections (BSIs) and the other assumed to decolonize CRE carriers after clinical detection. We quantified the effect of each antibiotic on the number of BSIs and deaths among patients receiving the drug (direct effect) and among all patients (direct and indirect effect) compared to usual care. We applied these results to a cost-effectiveness analysis with effectiveness outcome of life-years gained and assumed costs for antibiotic doses and for CRE BSI.

Results

The decolonizing antibiotic, once indirect effects were included, produced increased relative effectiveness and decreased relative costs compared to both usual care and the BSI treatment antibiotic. In fact, in most scenarios, the decolonizing drug was the dominant treatment strategy (ie, less costly and more effective).

Conclusions

Antibiotics that decolonize carriers of drug-resistant organisms can be highly cost-effective when considering indirect benefits within populations vulnerable to outbreaks. Public health could benefit from finding ways to incentivize development of decolonizing antibiotics in the US, where drugs with unclear direct benefits to recipients would pose difficulties in achieving FDA approval and financial benefit to the developer.

Clinical and Economic Outcomes of Genome Sequencing Availability on Containing a Hospital Outbreak of Resistant Escherichia coli in Australia

OBJECTIVES

To evaluate the outbreak size and hospital cost effects of bacterial whole-genome sequencing availability in managing a large-scale hospital outbreak.

METHODS

We built a hybrid discrete event/agent-based simulation model to replicate a serious bacterial outbreak of resistant Escherichia coli in a large metropolitan public hospital during 2017. We tested the 3 strategies of using whole-genome sequencing early, late (actual outbreak), or not using it and assessed their associated outbreak size and hospital cost. The model included ward dynamics, pathogen transmission, and associated hospital costs during a 5-month outbreak. Model parameters were determined using data from the Queensland Hospital Admitted Patient Data Collection (N = 4809 patient admissions) and local clinical knowledge. Sensitivity analyses were performed to address model and parameter uncertainty.

RESULTS

An estimated 197 patients were colonized during the outbreak, with 75 patients detected. The total outbreak cost was A$460 137 (US$317 117), with 6.1% spent on sequencing. Without sequencing, the outbreak was estimated to result in 352 colonized patients, costing A$766 921 (US$528 547). With earlier detection from use of routine sequencing, the estimated outbreak size was 3 patients and cost A$65 374 (US$45 054).

CONCLUSIONS

Using whole-genome sequencing in hospital outbreak management was associated with smaller outbreaks and cost savings, with sequencing costs as a small fraction of total hospital costs, supporting the further investigation of the use of routine whole-genome sequencing in hospitals.

Simulation models for transmission of health care-associated infection: A systematic review

BACKGROUND

Health care-associated infections (HAIs) are a global health burden because of their significant impact on patient health and health care systems. Mechanistic simulation modeling that captures the dynamics between patients, pathogens, and the environment is increasingly being used to improve understanding of epidemiological patterns of HAIs and to facilitate decisions on infection prevention and control (IPC). The purpose of this review is to present a systematic review to establish (1) how simulation models have been used to investigate HAIs and their mitigation and (2) how these models have evolved over time, as well as identify (3) gaps in their adoption and (4) useful directions for their future development.

METHODS

The review involved a systematic search and identification of studies using system dynamics, discrete event simulation, and agent-based model to study HAIs.

RESULTS

The complexity of simulation models developed for HAIs significantly increased but heavily concentrated on transmission dynamics of methicillin-resistant Staphylococcus aureus in the hospitals of high-income countries. Neither HAIs in other health care settings, the influence of contact networks within a health care facility, nor patient sharing and referring networks across health care settings were sufficiently understood.

CONCLUSIONS

This systematic review provides a broader overview of existing simulation models in HAIs to identify the gaps and to direct and facilitate further development of appropriate models in this emerging field.