Objectives The Centers for Disease Control and Prevention considers carbapenem-resistant Enterobacteriaceae (CRE) an urgent public health threat; however, its economic burden is unknown. Methods We developed a CRE clinical and economics outcomes model to determine the cost of CRE infection from the hospital, third-party payer, and societal, perspectives and to evaluate the health and economic burden of CRE to the USA. Results Depending on the infection type, the median cost of a single CRE infection can range from $22 484 to $66 031 for hospitals, $10 440 to $31 621 for third-party payers, and $37 778 to $83 512 for society. An infection incidence of 2.93 per 100 000 population in the USA (9418 infections) would cost hospitals $275 million (95% CR $217–334 million), third-party payers $147 million (95% CR $129–172 million), and society $553 million (95% CR $303–1593 million) with a 25% attributable mortality, and would result in the loss of 8841 (95% CR 5805–12 420) quality-adjusted life years. An incidence of 15 per 100 000 (48 213 infections) would cost hospitals $1.4 billion (95% CR $1.1–1.7 billion), third-party payers $0.8 billion (95% CR $0.6–0.8 billion), and society $2.8 billion (95% CR $1.6–8.2 billion), and result in the loss of 45 261 quality-adjusted life years. Conclusions The cost of CRE is higher than the annual cost of many chronic diseases and of many acute diseases. Costs rise proportionally with the incidence of CRE, increasing by 2.0 times, 3.4 times, and 5.1 times for incidence rates of 6, 10, and 15 per 100 000 persons.

Abstract Background Multidrug-resistant organisms (MDROs) spread between hospitals, nursing homes (NHs), and long-term acute care facilities (LTACs) via patient transfers. The Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County is a regional public health collaborative involving decolonization at 38 healthcare facilities selected based on their high degree of patient sharing. We report baseline MDRO prevalence in 21 NHs/LTACs. Methods A random sample of 50 adults for 21 NHs/LTACs (18 NHs, 3 LTACs) were screened for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), extended-spectrum β-lactamase–producing organisms (ESBL), and carbapenem-resistant Enterobacteriaceae (CRE) using nares, skin (axilla/groin), and peri-rectal swabs. Facility and resident characteristics associated with MDRO carriage were assessed using multivariable models clustering by person and facility. Results Prevalence of MDROs was 65% in NHs and 80% in LTACs. The most common MDROs in NHs were MRSA (42%) and ESBL (34%); in LTACs they were VRE (55%) and ESBL (38%). CRE prevalence was higher in facilities that manage ventilated LTAC patients and NH residents (8% vs <1%, P < .001). MDRO status was known for 18% of NH residents and 49% of LTAC patients. MDRO-colonized adults commonly harbored additional MDROs (54% MDRO+ NH residents and 62% MDRO+ LTACs patients). History of MRSA (odds ratio [OR] = 1.7; confidence interval [CI]: 1.2, 2.4; P = .004), VRE (OR = 2.1; CI: 1.2, 3.8; P = .01), ESBL (OR = 1.6; CI: 1.1, 2.3; P = .03), and diabetes (OR = 1.3; CI: 1.0, 1.7; P = .03) were associated with any MDRO carriage. Conclusions The majority of NH residents and LTAC patients harbor MDROs. MDRO status is frequently unknown to the facility. The high MDRO prevalence highlights the need for prevention efforts in NHs/LTACs as part of regional efforts to control MDRO spread.

A standard four-tier design template may have been followed for most countries and raises the possibility that simpler and more tailored designs may be warranted.

BackgroundWhen addressing the urgent task of improving vaccine supply chains, especially to accommodate the introduction of new vaccines, there is often a heavy emphasis on stationary storage. Currently, donations to vaccine supply chains occur largely in the form of storage equipment.MethodsThis study utilized a HERMES-generated detailed, dynamic, discrete event simulation model of the Niger vaccine supply chain to compare the impacts on vaccine availability of adding stationary cold storage versus transport capacity at different levels and to determine whether adding stationary storage capacity alone would be enough to relieve potential bottlenecks when pneumococcal and rotavirus vaccines are introduced by 2015.ResultsRelieving regional level storage bottlenecks increased vaccine availability (by 4%) more than relieving storage bottlenecks at the district (1% increase), central (no change), and clinic (no change) levels alone. Increasing transport frequency (or capacity) yielded far greater gains (e.g., 15% increase in vaccine availability when doubling transport frequency to the district level and 18% when tripling). In fact, relieving all stationary storage constraints could only increase vaccine availability by 11%, whereas doubling the transport frequency throughout the system led to a 26% increase and tripling the frequency led to a 30% increase. Increasing transport frequency also reduced the amount of stationary storage space needed in the supply chain. The supply chain required an additional 61,269L of storage to relieve constraints with the current transport frequency, 55,255L with transport frequency doubled, and 51,791L with transport frequency tripled.ConclusionsWhen evaluating vaccine supply chains, it is important to understand the interplay between stationary storage and transport. The HERMES-generated dynamic simulation model showed how augmenting transport can result in greater gains than only augmenting stationary storage and can reduce stationary storage needs.

OBJECTIVE To evaluate the potential impact and value of applications (e.g., ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country’s vaccine supply chain with different levels of population change to urban areas. MATERIALS AND METHODS Using our software, HERMES, we generated a detailed discrete event simulation model of Niger’s entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement. RESULTS Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances. DISCUSSION The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems. CONCLUSION Demand forecasting systems have the potential to greatly improve vaccine demand fulfillment, and decrease logistics cost/dose when implemented with storage and transportation increases direct vaccines. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements.

Vaccines reside in a complex multiscale system that includes biological, clinical, behavioral, social, operational, environmental, and economical relationships. Not accounting for these systems when making decisions about vaccines can result in changes that have little effect rather than solutions, lead to unsustainable solutions, miss indirect (e.g., secondary, tertiary, and beyond) effects, cause unintended consequences, and lead to wasted time, effort, and resources. Mathematical and computational modeling can help better understand and address complex systems by representing all or most of the components, relationships, and processes. Such models can serve as “virtual laboratories” to examine how a system operates and test the effects of different changes within the system. Here are ten lessons learned from using computational models to bring more of a systems approach to vaccine decision making: (i) traditional single measure approaches may overlook opportunities; (ii) there is complex interplay among many vaccine, population, and disease characteristics; (iii) accounting for perspective can identify synergies; (iv) the distribution system should not be overlooked; (v) target population choice can have secondary and tertiary effects; (vi) potentially overlooked characteristics can be important; (vii) characteristics of one vaccine can affect other vaccines; (viii) the broader impact of vaccines is complex; (ix) vaccine administration extends beyond the provider level; (x) and the value of vaccines is dynamic.

g Delays often occur between CLSI and FDA revisions of antimicrobial interpretive criteria. Using our Regional Healthcare Ecosystem Analyst (RHEA) simulation model, we found that the 32-month delay in changing carbapenem-resistant Enterobacteriaceae (CRE) breakpoints might have resulted in 1,821 additional carriers in Orange County, CA, an outcome that could have been avoided by identifying CRE and initiating contact precautions. Policy makers should aim to minimize the delay in the adoption of new breakpoints for antimicrobials against emerging pathogens when containment of spread is paramount; delays of <1.5 years are ideal. Delays often occur between the issuance of new diagnostic interpretive criteria for microbiology laboratories by standardsetting organizations, such as the Clinical and Laboratory Standards Institute (CLSI), and their adoption by the Food and Drug Administration (FDA) to inform breakpoints for the manufacturers of diagnostic tests. Delays occur due to the FDA's required regulatory processes and the necessity of generating data from pharmaceutical companies to support interpretive criteria changes. Quantifying the impact of such delays could help determine the value of addressing and rectifying their causes. A recent example is the 32-to 42-month delay (depending on the antimicrobial) between CLSI's release of moresensitive criteria for diagnosing carbapenem-resistant Enterobacteriaceae (CRE), beginning with M100-S20 issuances in 2010, and the conveyance of these new criteria to manufacturers by the FDA (1). Such a delay could result in CRE transmission if CRE carriers are missed (because old criteria are still in use) and are not placed on contact precautions to reduce CRE spread (2). This is of concern because CRE are considered an urgent public health threat by the Centers for Disease Control and Prevention (CDC) (3), and few treatment options exist for CRE infection, which can result in high mortality. Using our Regional Healthcare Ecosystem Analyst (RHEA)-generated simulation model of Orange County, CA (OC) (4), we determined the impact of this delay on estimated (i.e., potential) CRE transmission within health care facilities. MATERIALS AND METHODSWe used our previously described Regional Healthcare Ecosystem Analyst (RHEA) software platform (4-6) to generate a detailed agent-based model of Orange County, CA, which included detailed representations of all 28 acute-care hospitals (including 5 long-term acute-care facilities [LTACs]) and 74 free-standing nursing homes serving adult patients, along with the patients flowing among these locations and the community at large. We utilized the RHEA OC model to simulate the spread of CRE (7, 8) and the impact of changing CRE breakpoints in the early stages of OC's epidemic (years 4 to 5). Our model drew from detailed 2011-2012 OC patient-level data for adult inpatient hospital and nursing home admissions (9, 10). Table 1 shows key model inputs.Briefly, the model represents each patient with a computational agent. As in real life, each virtual ...

IMPORTANCE Multidrug-resistant organisms (MDROs) can spread across health care facilities in a region. Because of limited resources, certain interventions can be implemented in only some facilities; thus, decision-makers need to evaluate which interventions may be best to implement. OBJECTIVE To identify a group of target facilities and assess which MDRO intervention would be best to implement in the Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County, a large regional public health collaborative in Orange County, California. DESIGN, SETTING, AND PARTICIPANTS An agent-based model of health care facilities was developed in 2016 to simulate the spread of methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Enterobacteriaceae (CRE) for 10 years starting in 2010 and to simulate the use of various MDRO interventions for 3 years starting in 2017. All health care facilities (23 hospitals, 5 long-term acute care hospitals, and 74 nursing homes) serving adult inpatients in Orange County, California, were included, and 42 target facilities were identified via network analyses.EXPOSURES Increasing contact precaution effectiveness, increasing interfacility communication about patients' MDRO status, and performing decolonization using antiseptic bathing soap and a nasal product in a specific group of target facilities. MAIN OUTCOMES AND MEASURES MRSA and CRE prevalence and number of new carriers (ie, transmission events).RESULTS Compared with continuing infection control measures used in Orange County as of 2017, increasing contact precaution effectiveness from 40% to 64% in 42 target facilities yielded relative reductions of 0.8% (range, 0.5%-1.1%) in MRSA prevalence and 2.4% (range, 0.8%-4.6%) in CRE prevalence in health care facilities countywide after 3 years, averting 761 new MRSA transmission events (95% CI, 756-765 events) and 166 new CRE transmission events (95% CI, 158-174 events).Increasing interfacility communication of patients' MDRO status to 80% in these target facilities produced no changes in the prevalence or transmission of MRDOs. Implementing decolonization procedures (clearance probability: 39% in hospitals, 27% in long-term acute care facilities, and 3% in nursing homes) yielded a relative reduction of 23.7% (range, 23.5%-23.9%) in MRSA prevalence, averting 3515 new transmission events (95% CI, 3509-3521 events). Increasing the effectiveness of antiseptic bathing soap to 48% yielded a relative reduction of 39.9% (range, 38.5%-41.5%) in CRE prevalence, averting 1435 new transmission events (95% CI, 1427-1442 events). CONCLUSIONS AND RELEVANCEThe findings of this study highlight the ways in which modeling can inform design of regional interventions and suggested that decolonization would be the best (continued) Key Points Question Which multidrug-resistant organism (MDRO) intervention is best to implement in a set of health care facilities to reduce the spread of MDROs regionwide? Findings In this computational simulation modeling study...