Sarah R Deeny

Modelling the transmission of healthcare associated infections: a systematic review.

BackgroundDynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time.MethodsMEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings.ResultsIn total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data.ConclusionsTransmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models.

Association between continuity of care in general practice and hospital admissions for ambulatory care sensitive conditions: cross sectional study of routinely collected, person level data

Objective To assess whether continuity of care with a general practitioner is associated with hospital admissions for ambulatory care sensitive conditions for older patients. Design Cross sectional study. Setting Linked primary and secondary care records from 200 general practices participating in the Clinical Practice Research Datalink in England. Participants 230 472 patients aged between 62 and 82 years and who experienced at least two contacts with a general practitioner between April 2011 and March 2013. Main outcome measure Number of hospital admissions for ambulatory care sensitive conditions (those considered manageable in primary care) per patient between April 2011 and March 2013. Results We assessed continuity of care using the usual provider of care index, which we defined as the proportion of contacts occurring between April 2011 and March 2013 that were with the most frequently seen general practitioner. On average, the usual provider of care index score was 0.61. Continuity of care was lower among practices with more doctors (average score 0.59 in large practices versus 0.70 in small practices). Higher continuity of care was associated with fewer admissions for ambulatory care sensitive conditions. When modelled, controlling for demographic and clinical patient characteristics, an increase in the usual provider of care index of 0.2 for all patients would reduce these admissions by 6.22% (95% confidence interval 4.87% to 7.55%). There was greater evidence for an association among patients who were heavy users of primary care. Heavy users also experienced more admissions for ambulatory care sensitive conditions than other patients (0.36 admissions per patient for those with ≥18 contacts with a general practitioner, compared with 0.04 admissions per patient for those with 2-4 contacts). Conclusions Strategies that improve the continuity of care in general practice may reduce secondary care costs, particularly for the heaviest users of healthcare. Promoting continuity might also improve the experience of patients and those working in general practice.

Targeted versus universal screening and decolonization to reduce healthcare-associated meticillin-resistant Staphylococcus aureus infection.

BACKGROUND The benefits of universal meticillin-resistant Staphylococcus aureus (MRSA) admission screening, compared with screening targeted patient groups and the additional impact of discharge screening, are uncertain. AIMS To quantify the impact of MRSA screening plus decolonization treatment on MRSA infection rates. To compare universal with targeted screening policies, and to evaluate the additional impact of screening and decolonization on discharge. METHODS A stochastic, individual-based model of MRSA transmission was developed that included patient movements between general medical and intensive care unit (ICU) wards, and between the hospital and community, informed by 18 months of individual patient data from a 900-bed tertiary care hospital. We simulated the impact of universal and targeted [for ICU, acute care of the elderly (ACE) or readmitted patients] MRSA screening and decolonization policies, both on admission and discharge. FINDINGS Universal admission screening plus decolonization resulted in 77% (95% confidence interval: 76-78) reduction in MRSA infections over 10 years. Screening only ACE specialty or ICU patients yielded 62% (61-63) and 66% (65-67) reductions, respectively. Targeted policies reduced the number of screens by up to 95% and courses of decolonization by 96%. In addition to screening on admission, screening on discharge had little impact, with a maximum 7% additional reduction in infection. CONCLUSIONS Compared with universal screening, targeted screening substantially reduced the amount of screening and decolonization required to achieve only 12% lower reduction in infection. Targeted screening and decolonization could lower the risk of resistance emerging as well as offer a more efficient use of resources.

Impact of mupirocin resistance on the transmission and control of healthcare-associated MRSA

Objectives The objectives of this study were to estimate the relative transmissibility of mupirocin-resistant (MupR) and mupirocin-susceptible (MupS) MRSA strains and evaluate the long-term impact of MupR on MRSA control policies. Methods Parameters describing MupR and MupS strains were estimated using Markov chain Monte Carlo methods applied to data from two London teaching hospitals. These estimates parameterized a model used to evaluate the long-term impact of MupR on three mupirocin usage policies: ‘clinical cases’, ‘screen and treat’ and ‘universal’. Strategies were assessed in terms of colonized and infected patient days and scenario and sensitivity analyses were performed. Results The transmission probability of a MupS strain was 2.16 (95% CI 1.38–2.94) times that of a MupR strain in the absence of mupirocin usage. The total prevalence of MupR in colonized and infected MRSA patients after 5 years of simulation was 9.1% (95% CI 8.7%–9.6%) with the ‘screen and treat’ mupirocin policy, increasing to 21.3% (95% CI 20.9%–21.7%) with ‘universal’ mupirocin use. The prevalence of MupR increased in 50%–75% of simulations with ‘universal’ usage and >10% of simulations with ‘screen and treat’ usage in scenarios where MupS had a higher transmission probability than MupR. Conclusions Our results provide evidence from a clinical setting of a fitness cost associated with MupR in MRSA strains. This provides a plausible explanation for the low levels of mupirocin resistance seen following ‘screen and treat’ mupirocin usage. From our simulations, even under conservative estimates of relative transmissibility, we see long-term increases in the prevalence of MupR given ‘universal’ use.

Making sense of the shadows: priorities for creating a learning healthcare system based on routinely collected data

Socrates described a group of people chained up inside a cave, who mistook shadows of objects on a wall for reality. This allegory comes to mind when considering ‘routinely collected data’—the massive data sets, generated as part of the routine operation of the modern healthcare service. There is keen interest in routine data and the seemingly comprehensive view of healthcare they offer, and we outline a number of examples in which they were used successfully, including the Birmingham OwnHealth study, in which routine data were used with matched control groups to assess the effect of telephone health coaching on hospital utilisation. Routine data differ from data collected primarily for the purposes of research, and this means that analysts cannot assume that they provide the full or accurate clinical picture, let alone a full description of the health of the population. We show that major methodological challenges in using routine data arise from the difficulty of understanding the gap between patient and their ‘data shadow’. Strategies to overcome this challenge include more extensive data linkage, developing analytical methods and collecting more data on a routine basis, including from the patient while away from the clinic. In addition, creating a learning health system will require greater alignment between the analysis and the decisions that will be taken; between analysts and people interested in quality improvement; and between the analysis undertaken and public attitudes regarding appropriate use of data.

The National One Week Prevalence Audit of Universal Meticillin-Resistant Staphylococcus aureus (MRSA) Admission Screening 2012

Introduction The English Department of Health introduced universal MRSA screening of admissions to English hospitals in 2010. It commissioned a national audit to review implementation, impact on patient management, admission prevalence and extra yield of MRSA identified compared to “high-risk” specialty or “checklist-activated” screening (CLAS) of patients with MRSA risk factors. Methods National audit May 2011. Questionnaires to infection control teams in all English NHS acute trusts, requesting number patients admitted and screened, new or previously known MRSA; MRSA point prevalence; screening and isolation policies; individual risk factors and patient management for all new MRSA patients and random sample of negatives. Results 144/167 (86.2%) trusts responded. Individual patient data for 760 new MRSA patients and 951 negatives. 61% of emergency admissions (median 67.3%), 81% (median 59.4%) electives and 47% (median 41.4%) day-cases were screened. MRSA admission prevalence: 1% (median 0.9%) emergencies, 0.6% (median 0.4%) electives, 0.4% (median 0%) day-cases. Approximately 50% all MRSA identified was new. Inpatient MRSA point prevalence: 3.3% (median 2.9%). 104 (77%) trusts pre-emptively isolated patients with previous MRSA, 63 (35%) pre-emptively isolated admissions to “high-risk” specialties; 7 (5%) used PCR routinely. Mean time to MRSA positive result: 2.87 days (±1.33); 37% (219/596) newly identified MRSA patients discharged before result available; 55% remainder (205/376) isolated post-result. In an average trust, CLAS would reduce screening by 50%, identifying 81% of all MRSA. “High risk” specialty screening would reduce screening by 89%, identifying 9% of MRSA. Conclusions Implementation of universal screening was poor. Admission prevalence (new cases) was low. CLAS reduced screening effort for minor decreases in identification, but implementation may prove difficult. Cost effectiveness of this and other policies, awaits evaluation by transmission dynamic economic modelling, using data from this audit. Until then trusts should seek to improve implementation of current policy and use of isolation facilities.

Seasonal changes in the incidence of Escherichia coli bloodstream infection: variation with region and place of onset

Previous research has shown that Escherichia coli infection rates peak in the summer; however, to date there has been no investigation as to whether this is seen in both hospital and community-onset cases, and how this differs across regions. We investigated and quantified E. coli bloodstream infection (BSI) seasonality. A generalized additive Poisson model was fitted to mandatory E. coli BSI surveillance data reported in England. There was no impact of seasonality in hospital-onset cases; however, for the community-onset cases, there was statistically significant seasonal variation over time nationally. When examined regionally, seasonality was significant in the North of England only. This variation resulted in an absolute increase of 0.06 (95% CI 0.02-0.1) cases above the mean (3.25) in each hospital trust for each week of the peak summer season, and a decrease of (-) 0.07 (95% CI -0.1 to -0.03) in the autumn. We estimate that fewer than one hospital bed-day per week per hospital is lost because of seasonal increases during the summer. Our findings highlight the need to understand the distinct community and hospital dynamics of E. coli BSI, and to explore the regional differences driving the variation in incidence, in order to design and implement effective control measures.

Use of mathematical modelling to assess the impact of vaccines on antibiotic resistance

Antibiotic resistance is a major global threat to the provision of safe and effective health care. To control antibiotic resistance, vaccines have been proposed as an essential intervention, complementing improvements in diagnostic testing, antibiotic stewardship, and drug pipelines. The decision to introduce or amend vaccination programmes is routinely based on mathematical modelling. However, few mathematical models address the impact of vaccination on antibiotic resistance. We reviewed the literature using PubMed to identify all studies that used an original mathematical model to quantify the impact of a vaccine on antibiotic resistance transmission within a human population. We reviewed the models from the resulting studies in the context of a new framework to elucidate the pathways through which vaccination might impact antibiotic resistance. We identified eight mathematical modelling studies; the state of the literature highlighted important gaps in our understanding. Notably, studies are limited in the range of pathways represented, their geographical scope, and the vaccine-pathogen combinations assessed. Furthermore, to translate model predictions into public health decision making, more work is needed to understand how model structure and parameterisation affects model predictions and how to embed these predictions within economic frameworks.

The projected effectiveness of Clostridium difficile vaccination as part of an integrated infection control strategy

BACKGROUND Early clinical trials of a Clostridium difficile toxoid vaccine show efficacy in preventing C. difficile infection (CDI). The optimal patient group to target for vaccination programmes remains unexplored. This study performed a model-based evaluation of the effectiveness of different CDI vaccination strategies, within the context of existing infection prevention and control strategies such as antimicrobial stewardship. METHODS An individual-based transmission model of CDI in a high-risk hospital setting was developed. The model incorporated data on patient movements between the hospital, and catchment populations from the community and long-term care facilities (LTCF), using English national and local level data for model-parameterisation. We evaluated vaccination of: (1) discharged patients who had an CDI-occurrence in the ward; (2) LTCF-residents; (3) Planned elective surgical admissions and (4) All three strategies combined. RESULTS Without vaccination, 10.9 [Interquartile range: 10.0-11.8] patients per 1000 ward admissions developed CDI, of which 31% were ward-acquired. Immunising all three patient groups resulted in a 43% [42-44], reduction of ward-onset CDI on average. Among the strategies restricting vaccination to one target group, vaccinating elective surgical patients proved most effective (35% [34-36] reduction), but least efficient, requiring 146 [133-162] courses to prevent one ICU-onset case. Immunising LTCF residents was most efficient, requiring just 13 [11-16] courses to prevent one case, but considering this only comprised a small group of our hospital population, it only reduced ICU-onset CDI by 9% [8-11]. Vaccination proved most efficient when ward-based transmission rates and antimicrobial consumption were high. CONCLUSIONS Strategy success depends on the interaction between hospital and catchment populations, and importantly, consideration of importations of CDI from outside the hospital which we found to substantially impact hospital dynamics. Vaccination may be most desirable in settings or patient groups where levels of broad-spectrum antimicrobial use are high and difficult to reduce.

Impact of long-term care facility residence on the antibiotic resistance of urinary tract Escherichia coli and Klebsiella.

Background Long-term care facilities (LTCFs) are thought to be important reservoirs of antimicrobial-resistant (AMR) bacteria; however, there is no routine surveillance of resistance in LTCF residents, or large population-based studies comparing AMR in LTCFs with the community, so the relative burden of AMR in LTCFs remains unknown. Objectives To compare the frequency of antibiotic resistance of urinary tract bacteria from residents of LTCFs for the elderly and adults aged 70 years or older living in the community. Methods Positive urine specimens reported to any diagnostic microbiology laboratory in the West Midlands region (England) from 1 April 2010 to 31 March 2014 collected from individuals aged 70 years or older were analysed. The resistance of Escherichia coli and Klebsiella to trimethoprim, nitrofurantoin, third-generation cephalosporins and ciprofloxacin and the rate of laboratory-confirmed E. coli and Klebsiella urinary tract infection (UTI) were assessed in LTCF residents and in the community. Results LTCF residents had a laboratory-confirmed E. coli and Klebsiella UTI rate of 21 per 100 person years compared with 8 per 100 person years in the elderly living in the community [rate ratio (RR)=2.66, 95% CI = 2.58-2.73] and a higher rate of developing E. coli and Klebsiella UTIs caused by bacteria resistant to trimethoprim (RR = 4.41, 95% CI = 4.25-4.57), nitrofurantoin (RR = 4.38, 95% CI = 3.98-4.83), ciprofloxacin (RR = 5.18, 95% CI = 4.82-5.57) and third-generation cephalosporins (RR = 4.49, 95% CI = 4.08-4.94). Conclusions Residents of LTCFs for the elderly had more than double the rate of E. coli and Klebsiella UTI and more than four times the rate of E. coli and Klebsiella UTI caused by antibiotic-resistant bacteria compared with those living in the community.