Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting

BACKGROUND

Globally, detections of carbapenemase-producing Enterobacterales (CPE) colonisations and infections are increasing. The spread of these highly resistant bacteria poses a serious threat to public health. However, understanding of CPE transmission and evidence on effectiveness of control measures is severely lacking. This paper provides evidence to inform effective admission screening protocols, which could be important in controlling nosocomial CPE transmission.

METHODS

CPE transmission within an English hospital setting was simulated with a data-driven individual-based mathematical model. This model was used to evaluate the ability of the 2016 England CPE screening recommendations, and of potential alternative protocols, to identify patients with CPE-colonisation on admission (including those colonised during previous stays or from elsewhere). The model included nosocomial transmission from colonised and infected patients, as well as environmental contamination. Model parameters were estimated using primary data where possible, including estimation of transmission using detailed epidemiological data within a Bayesian framework. Separate models were parameterised to represent hospitals in English areas with low and high CPE risk (based on prevalence).

RESULTS

The proportion of truly colonised admissions which met the 2016 screening criteria was 43% in low-prevalence and 54% in high-prevalence areas respectively. Selection of CPE carriers for screening was improved in low-prevalence areas by adding readmission as a screening criterion, which doubled how many colonised admissions were selected. A minority of CPE carriers were confirmed as CPE positive during their hospital stay (10 and 14% in low- and high-prevalence areas); switching to a faster screening test pathway with a single-swab test (rather than three swab regimen) increased the overall positive predictive value with negligible reduction in negative predictive value.

CONCLUSIONS

Using a novel within-hospital CPE transmission model, this study assesses CPE admission screening protocols, across the range of CPE prevalence observed in England. It identifies protocol changes-adding readmissions to screening criteria and a single-swab test pathway-which could detect similar numbers of CPE carriers (or twice as many in low CPE prevalence areas), but faster, and hence with lower demand on pre-emptive infection-control resources. Study findings can inform interventions to control this emerging threat, although further work is required to understand within-hospital transmission sources.

Forecasting local hospital bed demand for COVID-19 using on-request simulations

Accurate forecasting of hospital bed demand is crucial during infectious disease epidemics to avoid overwhelming healthcare facilities. To address this, we developed an intuitive online tool for individual hospitals to forecast COVID-19 bed demand. The tool utilizes local data, including incidence, vaccination, and bed occupancy data, at customizable geographical resolutions. Users can specify their hospital's catchment area and adjust the initial number of COVID-19 occupied beds. We assessed the model's performance by forecasting ICU bed occupancy for several university hospitals and regions in Germany. The model achieves optimal results when the selected catchment area aligns with the hospital's local catchment. While expanding the catchment area reduces accuracy, it improves precision. However, forecasting performance diminishes during epidemic turning points. Incorporating variants of concern slightly decreases precision around turning points but does not significantly impact overall bed occupancy results. Our study highlights the significance of using local data for epidemic forecasts. Forecasts based on the hospital's specific catchment area outperform those relying on national or state-level data, striking a better balance between accuracy and precision. These hospital-specific bed demand forecasts offer valuable insights for hospital planning, such as adjusting elective surgeries to create additional bed capacity promptly.

Automated mobile virtual reality cognitive behavior therapy for aviophobia in a natural setting: a randomized controlled trial

BACKGROUND

Access to evidence-based psychological treatment is a challenge worldwide. We assessed the effectiveness of a fully automated aviophobia smartphone app treatment delivered in combination with a $5 virtual reality (VR) viewer.

METHODS

In total, 153 participants from the Dutch general population with aviophobia symptoms and smartphone access were randomized in a single-blind randomized controlled trial to either an automated VR cognitive behavior therapy (VR-CBT) app treatment condition (n = 77) or a wait-list control condition (n = 76). The VR-CBT app was delivered over a 6-week period in the participants' natural environment. Online self-report assessments were completed at baseline, post-treatment, at 3-month and at 12-month follow-up. The primary outcome measure was the Flight Anxiety Situations Questionnaire (FAS). Analyses were based on intent-to-treat.

RESULTS

A significant reduction of aviophobia symptoms at post-test for the VR-CBT app compared with the control condition [p < 0.001; d = 0. 98 (95% CI 0.65-1.32)] was demonstrated. The dropout rate was 21%. Results were maintained at 3-month follow-up [within-group d = 1.14 (95% CI 0.46-1.81)] and at 12-month follow-up [within-group d = 1.12 (95% CI 0.46-1.79)]. Six participants reported adverse effects of cyber sickness symptoms.

CONCLUSIONS

This study is the first to show that fully automated mobile VR-CBT therapy delivered in a natural setting can maintain long-term effectiveness in reducing aviophobia symptoms. In doing so, it offers an accessible and scalable evidence-based treatment solution that can be applied globally at a fraction of the cost of current treatment alternatives.

A coupled experimental and statistical approach for an assessment of SARS-CoV-2 infection risk at indoor event locations

Indoor event locations are particularly affected by the SARS-CoV-2 pandemic. At large venues, only incomplete risk assessments exist, whereby no suitable measures can be derived. In this study, a physical and data-driven statistical model for a comprehensive infection risk assessment has been developed. At venues displacement ventilation concepts are often implemented. Here simplified theoretical assumptions fail for the prediction of relevant airflows for airborne transmission processes. Thus, with locally resolving trace gas measurements infection risks are computed more detailed. Coupled with epidemiological data such as incidences, vaccination rates, test sensitivities, and audience characteristics such as masks and age distribution, predictions of new infections (mean), situational R-values (mean), and individual risks on- and off-seat can be achieved for the first time. Using the Stuttgart State Opera as an example, the functioning of the model and its plausibility are tested and a sensitivity analysis is performed with regard to masks and tests. Besides a reference scenario on 2022-11-29, a maximum safety scenario with an obligation of FFP2 masks and rapid antigen tests as well as a minimum safety scenario without masks and tests are investigated. For these scenarios the new infections (mean) are 10.6, 0.25 and 13.0, respectively. The situational R-values (mean) - number of new infections caused by a single infectious person in a certain situation - are 2.75, 0.32 and 3.39, respectively. Besides these results a clustered consideration divided by age, masks and whether infections occur on-seat or off-seat are presented. In conclusion this provides an instrument that can enable policymakers and operators to take appropriate measures to control pandemics despite ongoing mass gathering events.

An appeal for strengthening genomic pathogen surveillance to improve pandemic preparedness and infection prevention: the German perspective

The SARS-CoV-2 pandemic has highlighted the importance of viable infection surveillance and the relevant infrastructure. From a German perspective, an integral part of this infrastructure, genomic pathogen sequencing, was at best fragmentary and stretched to its limits due to the lack or inefficient use of equipment, human resources, data management and coordination. The experience in other countries has shown that the rate of sequenced positive samples and linkage of genomic and epidemiological data (person, place, time) represent important factors for a successful application of genomic pathogen surveillance. Planning, establishing and consistently supporting adequate structures for genomic pathogen surveillance will be crucial to identify and combat future pandemics as well as other challenges in infectious diseases such as multi-drug resistant bacteria and healthcare-associated infections. Therefore, the authors propose a multifaceted and coordinated process for the definition of procedural, legal and technical standards for comprehensive genomic pathogen surveillance in Germany, covering the areas of genomic sequencing, data collection and data linkage, as well as target pathogens. A comparative analysis of the structures established in Germany and in other countries is applied. This proposal aims to better tackle epi- and pandemics to come and take action from the "lessons learned" from the SARS-CoV-2 pandemic.

[Establishment of genomic pathogen surveillance to strengthen pandemic preparedness and infection prevention in Germany]

The SARS-CoV‑2 pandemic has shown a deficit of essential epidemiological infrastructure, especially with regard to genomic pathogen surveillance in Germany. In order to prepare for future pandemics, the authors consider it urgently necessary to remedy this existing deficit by establishing an efficient infrastructure for genomic pathogen surveillance. Such a network can build on structures, processes, and interactions that have already been initiated regionally and further optimize them. It will be able to respond to current and future challenges with a high degree of adaptability.The aim of this paper is to address the urgency and to outline proposed measures for establishing an efficient, adaptable, and responsive genomic pathogen surveillance network, taking into account external framework conditions and internal standards. The proposed measures are based on global and country-specific best practices and strategy papers. Specific next steps to achieve an integrated genomic pathogen surveillance include linking epidemiological data with pathogen genomic data; sharing and coordinating existing resources; making surveillance data available to relevant decision-makers, the public health service, and the scientific community; and engaging all stakeholders. The establishment of a genomic pathogen surveillance network is essential for the continuous, stable, active surveillance of the infection situation in Germany, both during pandemic phases and beyond.

[Online schema therapy: a cross-sectional survey among Dutch therapists]

BACKGROUND

Long waiting lists exist for the treatment of personality disorders, which can be shortened by using videoconference treatment. During the COVID-19 pandemic, by necessity, videoconferencing was used to provide schema therapy, a specific treatment for personality disorders.

AIM

To investigate therapist experience of schema therapy via videoconferencing during the pandemic.

METHOD

In an observational cross-sectional study, 83 schema therapists completed a questionnaire about the period prior to, and during the COVID-19 pandemic. We investigated their experience, use of, and attitude toward videoconferencing, as well as the extent to which the effectiveness of videoconferencing and face to face (F2F) schema therapy for personality disorders was found to be comparable.

RESULTS

Schema therapists rated their experience with videoconferencing therapy for personality disorders during the COVID-19 pandemic positively, its use increased during this period, and therapists&rsquo; attitudes became more positive. However, the majority found videoconferencing therapy less effective than F2F treatment. Almost half of the therapists used shorter sessions or adapted exercises during videoconferencing therapy.

CONCLUSION

Although therapists were increasingly positive about video conferencing therapy, they believed that F2F treatment is more effective. Randomized efficacy studies of videoconferencing therapy compared to F2F therapy are needed, also examining patients&rsquo; experiences with both forms.

Impact of hospital antibiotic use on patient-level risk of death among 36,124,372 acute and medical admissions in England

OBJECTIVES

Initiatives to curb hospital antibiotic use might be associated with harm from under-treatment. We examined the extent to which variation in hospital antibiotic prescribing is associated with mortality risk in acute/general medicine inpatients.

METHODS

This ecological analysis examined Hospital Episode Statistics from 36,124,372 acute/general medicine admissions (≥16y) to 135 acute hospitals in England, 01/April/2010-31/March/2017. Random-effects meta-regression was used to investigate whether heterogeneity in adjusted 30-day mortality was associated with hospital-level antibiotic use, measured in defined-daily-doses (DDD)/1,000 bed-days. Models also considered DDDs/1,000 admissions and DDDs for narrow-spectrum/broad-spectrum antibiotics, parenteral/oral, and local interpretations of World Health Organization Access, Watch, and Reserve antibiotics.

RESULTS

Hospital-level antibiotic DDDs/1,000 bed-days varied 15-fold with comparable variation in broad-spectrum, parenteral, and Reserve antibiotic use. After extensive adjusting for hospital case-mix, the probability of 30-day mortality changed -0.010% (95% CI: -0.064,+0.044) for each increase of 500 hospital-level antibiotic DDDs/1,000 bed-days. Analyses of other metrics of antibiotic use showed no consistent association with mortality risk.

CONCLUSIONS

We found no evidence that wide variation in hospital antibiotic use is associated with adjusted mortality risk in acute/general medicine inpatients. Using low-prescribing hospitals as benchmarks could help drive safe and substantial reductions in antibiotic consumption of up-to one-third in this population.

Navigating hospitals safely through the COVID-19 epidemic tide: Predicting case load for adjusting bed capacity

BACKGROUND

The pressures exerted by the coronavirus disease 2019 (COVID-19) pandemic pose an unprecedented demand on healthcare services. Hospitals become rapidly overwhelmed when patients requiring life-saving support outpace available capacities.

OBJECTIVE

We describe methods used by a university hospital to forecast case loads and time to peak incidence.

METHODS

We developed a set of models to forecast incidence among the hospital catchment population and to describe the COVID-19 patient hospital-care pathway. The first forecast utilized data from antecedent allopatric epidemics and parameterized the care-pathway model according to expert opinion (ie, the static model). Once sufficient local data were available, trends for the time-dependent effective reproduction number were fitted, and the care pathway was reparameterized using hazards for real patient admission, referrals, and discharge (ie, the dynamic model).

RESULTS

The static model, deployed before the epidemic, exaggerated the bed occupancy for general wards (116 forecasted vs 66 observed), ICUs (47 forecasted vs 34 observed), and predicted the peak too late: general ward forecast April 9 and observed April 8 and ICU forecast April 19 and observed April 8. After April 5, the dynamic model could be run daily, and its precision improved with increasing availability of empirical local data.

CONCLUSIONS

The models provided data-based guidance for the preparation and allocation of critical resources of a university hospital well in advance of the epidemic surge, despite overestimating the service demand. Overestimates should resolve when the population contact pattern before and during restrictions can be taken into account, but for now they may provide an acceptable safety margin for preparing during times of uncertainty.

Modelling how antimicrobial resistance spreads between wards

Moving patients between wards and prescribing high levels of antibiotics increases the spread of bacterial infections that are resistant to treatment in hospitals.

Mathematical modelling for antibiotic resistance control policy: do we know enough?

BACKGROUND

Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base.

MAIN TEXT

One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy.

CONCLUSIONS

We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research.

Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting

Hospital performance is often measured using self-reported statistics, such as the incidence of hospital-transmitted micro-organisms or those exhibiting antimicrobial resistance (AMR), encouraging hospitals with high levels to improve their performance. However, hospitals that increase screening efforts will appear to have a higher incidence and perform poorly, undermining comparison between hospitals and disincentivising testing, thus hampering infection control. We propose a surveillance system in which hospitals test patients previously discharged from other hospitals and report observed cases. Using English National Health Service (NHS) Hospital Episode Statistics data, we analysed patient movements across England and assessed the number of hospitals required to participate in such a reporting scheme to deliver robust estimates of incidence. With over 1.2 million admissions to English hospitals previously discharged from other hospitals annually, even when only a fraction of hospitals (41/155) participate (each screening at least 1000 of these admissions), the proposed surveillance system can estimate incidence across all hospitals. By reporting on other hospitals, the reporting of incidence is separated from the task of improving own performance. Therefore the incentives for increasing performance can be aligned to increase (rather than decrease) screening efforts, thus delivering both more comparable figures on the AMR problems across hospitals and improving infection control efforts.

0Phobia - towards a virtual cure for acrophobia: study protocol for a randomized controlled trial

BACKGROUND

Virtual reality exposure therapy (VRET) has been shown to be as effective as traditional forms of in vivo exposure therapy for the treatment of specific phobias. However, as with in vivo exposure, VRET still involves relatively high costs and limited accessibility which makes it prohibitive for a large part of the population. Innovative methods using smartphone applications (apps) may improve accessibility and scalability of VRET. The aim of this study is to evaluate 0Phobia, a gamified self-guided VRET for acrophobia that is delivered through a smartphone app in combination with rudimentary cardboard virtual reality (VR) goggles.

METHODS/DESIGN

Participants (N = 180, aged 18-65 years) with acrophobia symptoms will be recruited from the Dutch general population and randomized to either 0Phobia (n = 90) or a waitlist control condition (n = 90). 0Phobia will be delivered over a period of 3 weeks and includes psychoeducation, VR exposure, cognitive techniques, monitoring of symptoms, and relapse prevention. The primary outcome measure will be the Acrophobia Questionnaire. Secondary outcome measures will include user-friendliness, symptoms of anxiety, depression, and mastery. Assessments will take place online at baseline, directly after the intervention (post test) and at follow-up (3 months).

DISCUSSION

This study capitalizes on novel technology and recent scientific advances to develop an affordable and scalable treatment modality.

TRIAL REGISTRATION

Netherlands Trial Register: NTR6442 . Registered on 29 June 2017.

Population genetic structuring of methicillin-resistant Staphylococcus aureus clone EMRSA-15 within UK reflects patient referral patterns

Antibiotic resistance forms a serious threat to the health of hospitalised patients, rendering otherwise treatable bacterial infections potentially life-threatening. A thorough understanding of the mechanisms by which resistance spreads between patients in different hospitals is required in order to design effective control strategies. We measured the differences between bacterial populations of 52 hospitals in the United Kingdom and Ireland, using whole-genome sequences from 1085 MRSA clonal complex 22 isolates collected between 1998 and 2012. The genetic differences between bacterial populations were compared with the number of patients transferred between hospitals and their regional structure. The MRSA populations within single hospitals, regions and countries were genetically distinct from the rest of the bacterial population at each of these levels. Hospitals from the same patient referral regions showed more similar MRSA populations, as did hospitals sharing many patients. Furthermore, the bacterial populations from different time-periods within the same hospital were generally more similar to each other than contemporaneous bacterial populations from different hospitals. We conclude that, while a large part of the dispersal and expansion of MRSA takes place among patients seeking care in single hospitals, inter-hospital spread of resistant bacteria is by no means a rare occurrence. Hospitals are exposed to constant introductions of MRSA on a number of levels: (1) most MRSA is received from hospitals that directly transfer large numbers of patients, while (2) fewer introductions happen between regions or (3) across national borders, reflecting lower numbers of transferred patients. A joint coordinated control effort between hospitals, is therefore paramount for the national control of MRSA, antibiotic-resistant bacteria and other hospital-associated pathogens.

The relative importance of large problems far away versus small problems closer to home: insights into limiting the spread of antimicrobial resistance in England

BACKGROUND

To combat the spread of antimicrobial resistance (AMR), hospitals are advised to screen high-risk patients for carriage of antibiotic-resistant bacteria on admission. This often includes patients previously admitted to hospitals with a high AMR prevalence. However, the ability of such a strategy to identify introductions (and hence prevent onward transmission) is unclear, as it depends on AMR prevalence in each hospital, the number of patients moving between hospitals, and the number of hospitals considered 'high risk'.

METHODS

We tracked patient movements using data from the National Health Service of England Hospital Episode Statistics and estimated differences in regional AMR prevalences using, as an exemplar, data collected through the national reference laboratory service of Public Health England on carbapenemase-producing Enterobacteriaceae (CPE) from 2008 to 2014. Combining these datasets, we calculated expected CPE introductions into hospitals from across the hospital network to assess the effectiveness of admission screening based on defining high-prevalence hospitals as high risk.

RESULTS

Based on numbers of exchanged patients, the English hospital network can be divided into 14 referral regions. England saw a sharp increase in numbers of CPE isolates referred to the national reference laboratory over 7 years, from 26 isolates in 2008 to 1649 in 2014. Large regional differences in numbers of confirmed CPE isolates overlapped with regional structuring of patient movements between hospitals. However, despite these large differences in prevalence between regions, we estimated that hospitals received only a small proportion (1.8%) of CPE-colonised patients from hospitals outside their own region, which decreased over time.

CONCLUSIONS

In contrast to the focus on import screening based on assigning a few hospitals as 'high risk', patient transfers between hospitals with small AMR problems in the same region often pose a larger absolute threat than patient transfers from hospitals in other regions with large problems, even if the prevalence in other regions is orders of magnitude higher. Because the difference in numbers of exchanged patients, between and within regions, was mostly larger than the difference in CPE prevalence, it would be more effective for hospitals to focus on their own populations or region to inform control efforts rather than focussing on problems elsewhere.

E-care 4 caregivers - an online intervention for nonprofessional caregivers of patients with depression: study protocol for a pilot randomized controlled trial

Background

Nonprofessional caregivers are highly important in the everyday life of patients with depression. Yet, they may experience increased levels of burden, stress, depression, and anxiety. Therefore, there is a need for interventions that relieve symptoms and are accessible and time-efficient. This paper describes the protocol of a pilot study to evaluate (1) the feasibility of an online self-management intervention, E-care 4 caregivers, for the nonprofessional caregiver of patients with depression, and (2) the initial effects of E-care 4 caregivers on psychological distress, subjective burden, symptoms of anxiety and depression, and quality of life.

Methods/design

The study is a randomized controlled trial in which we are comparing the E-care 4 caregivers online intervention with a wait list control group. Eighty-four nonprofessional caregivers of patients with depression aged 18 years or older are being recruited from among the general population. Feasibility is determined by semistructured telephone interviews evaluating the subjects’ satisfaction with the intervention and by using a questionnaire on the user-friendliness of the system. The primary outcome measure used to examine the initial effects of the intervention is psychological distress. Secondary outcome measures are subjective burden, symptoms of anxiety and depression, level of mastery, and quality of life. Assessments will be done at baseline and 6 weeks later. Statistical analysis of the effects of the intervention will be carried out on the basis of the intention-to-treat principle.

Discussion

E-care 4 caregivers could potentially benefit nonprofessional caregivers, as well as patients and professionals indirectly.

Trial registration

Netherlands Trial Register identifier: NTR5268. Registered on 30 June 2015.

Monitoring the spread of meticillin-resistant Staphylococcus aureus in The Netherlands from a reference laboratory perspective

Background

In The Netherlands, efforts to control meticillin-resistant Staphylococcus aureus (MRSA) in hospitals have been largely successful due to stringent screening of patients on admission and isolation of those that fall into defined risk categories. However, Dutch hospitals are not free of MRSA, and a considerable number of cases are found that do not belong to any of the risk categories. Some of these may be due to undetected nosocomial transmission, whereas others may be introduced from unknown reservoirs.

Aim

Identifying multi-institutional clusters of MRSA isolates to estimate the contribution of potential unobserved reservoirs in The Netherlands.

Methods

We applied a clustering algorithm that combines time, place, and genetics to routine data available for all MRSA isolates submitted to the Dutch Staphylococcal Reference Laboratory between 2008 and 2011 in order to map the geo-temporal distribution of MRSA clonal lineages in The Netherlands.

Findings

Of the 2966 isolates lacking obvious risk factors, 579 were part of geo-temporal clusters, whereas 2387 were classified as MRSA of unknown origin (MUOs). We also observed marked differences in the proportion of isolates that belonged to geo-temporal clusters between specific multi-locus variable number of tandem repeat analysis (MLVA) clonal complexes, indicating lineage-specific transmissibility. The majority of clustered isolates (74%) were present in multi-institutional clusters.

Conclusion

The frequency of MRSA of unknown origin among patients lacking obvious risk factors is an indication of a largely undefined extra-institutional but genetically highly diverse reservoir. Efforts to understand the emergence and spread of high-risk clones require the pooling of routine epidemiological information and typing data into central databases.

Identifying the effect of patient sharing on between-hospital genetic differentiation of methicillin-resistant Staphylococcus aureus

Background

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most common healthcare-associated pathogens. To examine the role of inter-hospital patient sharing on MRSA transmission, a previous study collected 2,214 samples from 30 hospitals in Orange County, California and showed by spa typing that genetic differentiation decreased significantly with increased patient sharing. In the current study, we focused on the 986 samples with spa type t008 from the same population.

Methods

We used genome sequencing to determine the effect of patient sharing on genetic differentiation between hospitals. Genetic differentiation was measured by between-hospital genetic diversity, F_ST, and the proportion of nearly identical isolates between hospitals.

Results

Surprisingly, we found very similar genetic diversity within and between hospitals, and no significant association between patient sharing and genetic differentiation measured by F_ST. However, in contrast to F_ST, there was a significant association between patient sharing and the proportion of nearly identical isolates between hospitals. We propose that the proportion of nearly identical isolates is more powerful at determining transmission dynamics than traditional estimators of genetic differentiation (F_ST) when gene flow between populations is high, since it is more responsive to recent transmission events. Our hypothesis was supported by the results from coalescent simulations.

Conclusions

Our results suggested that there was a high level of gene flow between hospitals facilitated by patient sharing, and that the proportion of nearly identical isolates is more sensitive to population structure than F_ST when gene flow is high.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0274-3) contains supplementary material, which is available to authorized users.

Building a genomic framework for prospective MRSA surveillance in the United Kingdom and the Republic of Ireland

The correct interpretation of microbial sequencing data applied to surveillance and outbreak investigation depends on accessible genomic databases to provide vital genetic context. Our aim was to construct and describe a United Kingdom MRSA database containing over 1000 methicillin-resistant Staphylococcus aureus (MRSA) genomes drawn from England, Northern Ireland, Wales, Scotland, and the Republic of Ireland over a decade. We sequenced 1013 MRSA submitted to the British Society for Antimicrobial Chemotherapy by 46 laboratories between 2001 and 2010. Each isolate was assigned to a regional healthcare referral network in England and was otherwise grouped based on country of origin. Phylogenetic reconstructions were used to contextualize MRSA outbreak investigations and to detect the spread of resistance. The majority of isolates (n = 783, 77%) belonged to CC22, which contains the dominant United Kingdom epidemic clone (EMRSA-15). There was marked geographic structuring of EMRSA-15, consistent with widespread dissemination prior to the sampling decade followed by local diversification. The addition of MRSA genomes from two outbreaks and one pseudo-outbreak demonstrated the certainty with which outbreaks could be confirmed or refuted. We identified local and regional differences in antibiotic resistance profiles, with examples of local expansion, as well as widespread circulation of mobile genetic elements across the bacterial population. We have generated a resource for the future surveillance and outbreak investigation of MRSA in the United Kingdom and Ireland and have shown the value of this during outbreak investigation and tracking of antimicrobial resistance.

Economic evaluations of Internet interventions for mental health: a systematic review

BACKGROUND

Internet interventions are assumed to be cost-effective. However, it is unclear how strong this evidence is, and what the quality of this evidence is.

METHOD

A comprehensive literature search (1990-2014) in Medline, EMBASE, the Cochrane Central Register of Controlled Trials, NHS Economic Evaluations Database, NHS Health Technology Assessment Database, Office of Health Economics Evaluations Database, Compendex and Inspec was conducted. We included economic evaluations alongside randomized controlled trials of Internet interventions for a range of mental health symptoms compared to a control group, consisting of a psychological or pharmaceutical intervention, treatment-as-usual (TAU), wait-list or an attention control group.

RESULTS

Of the 6587 abstracts identified, 16 papers met the inclusion criteria. Nine studies featured a societal perspective. Results demonstrated that guided Internet interventions for depression, anxiety, smoking cessation and alcohol consumption had favourable probabilities of being more cost-effective when compared to wait-list, TAU, group cognitive behaviour therapy (CBGT), attention control, telephone counselling or unguided Internet CBT. Unguided Internet interventions for suicide prevention, depression and smoking cessation demonstrated cost-effectiveness compared to TAU or attention control. In general, results from cost-utility analyses using more generic health outcomes (quality of life) were less favourable for unguided Internet interventions. Most studies adhered reasonably to economic guidelines.

CONCLUSIONS

Results of guided Internet interventions being cost-effective are promising with most studies adhering to publication standards, but more economic evaluations are needed in order to determine cost-effectiveness of Internet interventions compared to the most cost-effective treatment currently available.

Predictors of treatment dropout in self-guided web-based interventions for depression: an 'individual patient data' meta-analysis

BACKGROUND

It is well known that web-based interventions can be effective treatments for depression. However, dropout rates in web-based interventions are typically high, especially in self-guided web-based interventions. Rigorous empirical evidence regarding factors influencing dropout in self-guided web-based interventions is lacking due to small study sample sizes. In this paper we examined predictors of dropout in an individual patient data meta-analysis to gain a better understanding of who may benefit from these interventions.

METHOD

A comprehensive literature search for all randomized controlled trials (RCTs) of psychotherapy for adults with depression from 2006 to January 2013 was conducted. Next, we approached authors to collect the primary data of the selected studies. Predictors of dropout, such as socio-demographic, clinical, and intervention characteristics were examined.

RESULTS

Data from 2705 participants across ten RCTs of self-guided web-based interventions for depression were analysed. The multivariate analysis indicated that male gender [relative risk (RR) 1.08], lower educational level (primary education, RR 1.26) and co-morbid anxiety symptoms (RR 1.18) significantly increased the risk of dropping out, while for every additional 4 years of age, the risk of dropping out significantly decreased (RR 0.94).

CONCLUSIONS

Dropout can be predicted by several variables and is not randomly distributed. This knowledge may inform tailoring of online self-help interventions to prevent dropout in identified groups at risk.

The population structure of Staphylococcus aureus in China and Europe assessed by multiple-locus variable number tandem repeat analysis; clues to geographical origins of emergence and dissemination

To compare the genetic population structure of Staphylococcus aureus from China and Europe, 1294 human isolates were characterized by multiple-locus variable number tandem repeat analysis (MLVA). In total, MLVA identified 17 MLVA complexes (MCs), comprising 260 MLVA types (MTs) among the Chinese isolates and 372 MTs among the European isolates. The five most frequent MCs among the Chinese isolates belonged to MC398, MC5 subclade a, MC8, MC437 and MC7 and made up 55% of the sample. For the European isolates, the five most frequent MCs consisted of MC5 subclade a, MC45, MC8, MC30 and MC22, which accounted for 64% of the sample. Phylogeographic analysis of the major MCs shared between China and Europe points to a European origin of MC8 but cannot provide a consistent signal for MC5 subclade a, probably indicating a different origin. Diversity and frequency distributions of other lineages were also compared. Altogether, this study provides the first snapshot of two extant populations of S. aureus from Europe and China, and important clues on the emergence and dissemination of different lineages of S. aureus.

[Analysis of patient flows: basis for regional control of antibiotic resistance]

Antibiotic resistance is a worldwide threat to health care as it impairs the effective treatment of bacterial infections. Measures against the spread of resistance are mainly focused on individual health care institutions as these are viewed as the main source of resistance. However, health care institutions are not completely independent in their control of the prevalence of resistance, as movement of patients between hospitals and care institutions can induce movement of resistant micro-organisms. In other words, antibiotic resistance follows the flow of patients. Mapping this flow of patients results in a network that includes all health care institutions, and has a distinctive modular structure. Patients are moved primarily within regions, much less so between regions. We argue that the structure of this health care network should be used to design efficient and effective control strategies. To this end, we advocate (a) regional coordination of control measures, (b) differentiation of investment in infection prevention according to the network position of the institution, and

Efficient surveillance for healthcare-associated infections spreading between hospitals

Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10-20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort.

Predictors and moderators of response to internet-delivered Interpersonal Psychotherapy and Cognitive Behavior Therapy for depression

BACKGROUND

By identifying which predictors and moderators lead to beneficial outcomes, accurate selection of the best initial treatment will have significant benefits for depressed individuals.

METHOD

An automated, fully self-guided randomized controlled internet-delivered noninferiority trial was conducted comparing two new interventions (Interpersonal Psychotherapy [IPT; n=620] and Cognitive Behavioral Therapy [CBT; n=610]) to an active control intervention (MoodGYM; n=613) over a period of 4 weeks to spontaneous visitors of an internet-delivered therapy website (e-couch). A range of putative predictors and moderators (socio-demographic characteristics [age, gender, marital status, education level], clinical characteristics [depression/anxiety symptoms, disability, quality of life, medication use], skills [mastery and dysfunctional attitudes] and treatment preference) were assessed using internet-delivered self-report measures at baseline and immediately following treatment and at six months follow-up. Analyses were conducted using Mixed Model Repeated Measures (MMRM).

RESULTS

Female gender, lower mastery and lower dysfunctional attitudes predicted better outcome at post-test and/or follow-up regardless of intervention. No overall differential effects for condition on depression as a function of outcome were found. However, based on time-specific estimates, a significant interaction effect of age was found. For younger people, internet-delivered IPT may be the preferred treatment choice, whereas older participants derive more benefits from internet-delivered CBT programs.

LIMITATIONS

Although the sample of participants was large, power to detect moderator effects was still lacking.

CONCLUSIONS

Different e-mental health programs may be more beneficial for specific age groups. The findings raise important possibilities for increasing depression treatment effectiveness and improving clinical practice guidelines for depression treatment of different age groups.

Dispersal of antibiotic-resistant high-risk clones by hospital networks: changing the patient direction can make all the difference

BACKGROUND

Patients who seek treatment in hospitals can introduce high-risk clones of hospital-acquired, antibiotic-resistant pathogens from previous admissions. In this manner, different healthcare institutions become linked epidemiologically. All links combined form the national patient referral network, through which high-risk clones can propagate.

AIM

To assess the influence of changes in referral patterns and network structure on the dispersal of these pathogens.

METHODS

Hospital admission data were mapped to reconstruct the English patient referral network, and 12 geographically distinct healthcare collectives were identified. The number of patients admitted and referred to hospitals outside their collective was measured. Simulation models were used to assess the influence of changing network structure on the spread of hospital-acquired pathogens.

FINDINGS

Simulation models showed that decreasing the number of between-collective referrals by redirecting, on average, just 1.5 patients/hospital/day had a strong effect on dispersal. By decreasing the number of between-collective referrals, the spread of high-risk clones through the network can be reduced by 36%. Conversely, by creating supra-regional specialist centres that provide specialist care at national level, the rate of dispersal can increase by 48%.

CONCLUSION

The structure of the patient referral network has a profound effect on the epidemic behaviour of high-risk clones. Any changes that affect the number of referrals between healthcare collectives, inevitably affect the national dispersal of these pathogens. These effects should be taken into account when creating national specialist centres, which may jeopardize control efforts.

Finding evidence for local transmission of contagious disease in molecular epidemiological datasets

Surveillance systems of contagious diseases record information on cases to monitor incidence of disease and to evaluate effectiveness of interventions. These systems focus on a well-defined population; a key question is whether observed cases are infected through local transmission within the population or whether cases are the result of importation of infection into the population. Local spread of infection calls for different intervention measures than importation of infection. Besides standardized information on time of symptom onset and location of cases, pathogen genotyping or sequencing offers essential information to address this question. Here we introduce a method that takes full advantage of both the genetic and epidemiological data to distinguish local transmission from importation of infection, by comparing inter-case distances in temporal, spatial and genetic data. Cases that are part of a local transmission chain will have shorter distances between their geographical locations, shorter durations between their times of symptom onset and shorter genetic distances between their pathogen sequences as compared to cases that are due to importation. In contrast to generic clustering algorithms, the proposed method explicitly accounts for the fact that during local transmission of a contagious disease the cases are caused by other cases. No pathogen-specific assumptions are needed due to the use of ordinal distances, which allow for direct comparison between the disparate data types. Using simulations, we test the performance of the method in identifying local transmission of disease in large datasets, and assess how sensitivity and specificity change with varying size of local transmission chains and varying overall disease incidence.

Carbapenemase-producing Enterobacteriaceae in Europe: a survey among national experts from 39 countries, February 2013

The spread of carbapenemase-producing Enterobacteriaceae (CPE) is a threat to healthcare delivery, although its extent differs substantially from country to country. In February 2013, national experts from 39 European countries were invited to self-assess the current epidemiological situation of CPE in their country. Information about national management of CPE was also reported. The results highlight the urgent need for a coordinated European effort on early diagnosis, active surveillance, and guidance on infection control measures.

Infection prevention in a connected world: the case for a regional approach

Results from microbiological and epidemiological investigations, as well as mathematical modelling, show that the transmission dynamics of nosocomial pathogens, especially of multiple antibiotic-resistant bacteria, is not exclusively amenable to single-hospital infection prevention measures. Crucially, their extent of spread depends on the structure of an underlying "healthcare network", as determined by inter-institutional referrals of patients. The current trend towards centralized healthcare systems favours the spread of hospital-associated pathogens, and must be addressed by coordinated regional or national approaches to infection prevention in order to maintain patient safety. Here we review recent advances that support this hypothesis, and propose a "next-generation" network-approach to hospital infection prevention and control.

Hospital networks and the dispersal of hospital-acquired pathogens by patient transfer

Hospital-acquired infections (HAI) are often seen as preventable incidents that result from unsafe practices or poor hospital hygiene. This however ignores the fact that transmissibility is not only a property of the causative organisms but also of the hosts who can translocate bacteria when moving between hospitals. In an epidemiological sense, hospitals become connected through the patients they share. We here postulate that the degree of hospital connectedness crucially influences the rates of infections caused by hospital-acquired bacteria. To test this hypothesis, we mapped the movement of patients based on the UK-NHS Hospital Episode Statistics and observed that the proportion of patients admitted to a hospital after a recent episode in another hospital correlates with the hospital-specific incidence rate of MRSA bacteraemia as recorded by mandatory reporting. We observed a positive correlation between hospital connectedness and MRSA bacteraemia incidence rate that is significant for all financial years since 2001 except for 2008-09. All years combined, this correlation is positive and significantly different from zero (partial correlation coefficient r = 0.33 (0.28 to 0.38)). When comparing the referral pattern for English hospitals with referral patterns observed in the Netherlands, we predict that English hospitals more likely see a swifter and more sustained spread of HAIs. Our results indicate that hospitals cannot be viewed as individual units but rather should be viewed as connected elements of larger modular networks. Our findings stress the importance of cooperative effects that will have a bearing on the planning of health care systems, patient management and hospital infection control.

Nowcasting pandemic influenza A/H1N1 2009 hospitalizations in the Netherlands

During emerging epidemics of infectious diseases, it is vital to have up-to-date information on epidemic trends, such as incidence or health care demand, because hospitals and intensive care units have limited excess capacity. However, real-time tracking of epidemics is difficult, because of the inherent delay between onset of symptoms or hospitalizations, and reporting. We propose a robust algorithm to correct for reporting delays, using the observed distribution of reporting delays. We apply the algorithm to pandemic influenza A/H1N1 2009 hospitalizations as reported in the Netherlands. We show that the proposed algorithm is able to provide unbiased predictions of the actual number of hospitalizations in real-time during the ascent and descent of the epidemic. The real-time predictions of admissions are useful to adjust planning in hospitals to avoid exceeding their capacity.

Is guided self-help as effective as face-to-face psychotherapy for depression and anxiety disorders? A systematic review and meta-analysis of comparative outcome studies

BACKGROUND

Although guided self-help for depression and anxiety disorders has been examined in many studies, it is not clear whether it is equally effective as face-to-face treatments.MethodWe conducted a meta-analysis of randomized controlled trials in which the effects of guided self-help on depression and anxiety were compared directly with face-to-face psychotherapies for depression and anxiety disorders. A systematic search in bibliographical databases (PubMed, PsycINFO, EMBASE, Cochrane) resulted in 21 studies with 810 participants.

RESULTS

The overall effect size indicating the difference between guided self-help and face-to-face psychotherapy at post-test was d=-0.02, in favour of guided self-help. At follow-up (up to 1 year) no significant difference was found either. No significant difference was found between the drop-out rates in the two treatments formats.

CONCLUSIONS

It seems safe to conclude that guided self-help and face-to-face treatments can have comparable effects. It is time to start thinking about implementation in routine care.

Transmission of novel influenza A(H1N1) in households with post-exposure antiviral prophylaxis

Background

Despite impressive advances in our understanding of the biology of novel influenza A(H1N1) virus, little is as yet known about its transmission efficiency in close contact places such as households, schools, and workplaces. These are widely believed to be key in supporting propagating spread, and it is therefore of importance to assess the transmission levels of the virus in such settings.

Methodology/Principal Findings

We estimate the transmissibility of novel influenza A(H1N1) in 47 households in the Netherlands using stochastic epidemic models. All households contained a laboratory confirmed index case, and antiviral drugs (oseltamivir) were given to both the index case and other households members within 24 hours after detection of the index case. Among the 109 household contacts there were 9 secondary infections in 7 households. The overall estimated secondary attack rate is low (0.075, 95%CI: 0.037–0.13). There is statistical evidence indicating that older persons are less susceptible to infection than younger persons (relative susceptibility of older persons: 0.11, 95%CI: 0.024–0.43. Notably, the secondary attack rate from an older to a younger person is 0.35 (95%CI: 0.14–0.61) when using an age classification of ≤12 versus >12 years, and 0.28 (95%CI: 0.12–0.50) when using an age classification of ≤18 versus >18 years.

Conclusions/Significance

Our results indicate that the overall household transmission levels of novel influenza A(H1N1) in antiviral-treated households were low in the early stage of the epidemic. The relatively high rate of adult-to-child transmission indicates that control measures focused on this transmission route will be most effective in minimizing the total number of infections.

Surveillance of hospitalisations for 2009 pandemic influenza A(H1N1) in the Netherlands, 5 June - 31 December 2009

We analysed and reported on a weekly basis clinical and epidemiological characteristics of patients hospitalised in the Netherlands for the 2009 pandemic influenza A(H1N1) using information from the national mandatory notification system. The notification criteria changed on 15 August 2009 from all possible, probable and confirmed cases to only laboratory-confirmed pandemic influenza hospitalisations and deaths. In the period of comprehensive case-based surveillance (until 15 August), 2% (35/1,622) of the patients with pandemic influenza were hospitalised. From 5 June to 31 December 2009, a total of 2,181 patients were hospitalised. Of these, 10% (219/2,181) were admitted to an intensive care unit (ICU) and 53 died. Among non-ICU hospitalised patients, 56% (961/1,722) had an underlying medical condition compared with 70% (147/211) of the patients in ICU and 46 of the 51 fatal cases for whom this information was reported. Most common complications were dehydration among non-ICU hospitalised patients and acute respiratory distress syndrome among patients in ICU and patients who died. Children under the age of five years had the highest age-specific hospitalisation rate (62.7/100,000), but relatively few were admitted to an ICU (1.7/100,000). Characteristics and admission rates of hospitalised patients were comparable with reports from other countries and previous influenza seasons. The national notification system was well suited to provide weekly updates of relevant monitoring information on the severity of the pandemic for professionals, decision makers, the media and the public, and could be rapidly adapted to changing information requirements.

Epidemiology and control of influenza A(H1N1)v in the Netherlands: the first 115 cases

Introductions of the new influenza A(H1N1) variant virus in the Netherlands led to enhanced surveillance and infection control. By 24 June 2009, 115 cases were reported, of whom 44% were indigenously acquired. Severity of disease is similar to reports elsewhere. Our point estimate of the effective reproductive number (Re) for the initial phase of the influenza A(H1N1)v epidemic in the Netherlands was below one. Given that the Re estimate is based on a small number of indigenous cases and a limited time period, it needs to be interpreted cautiously.