Changes in isolation guidelines for CPE patients results in only mild reduction in required hospital beds.

Background: Carbapenemase-producing Enterobacterales (CPE) are an emerging public health concern globally as they are resistant to a broad spectrum of antibiotics. Colonisation with CPE typically requires patients to be managed under 'contact precautions', which creates additional physical bed demands in healthcare facilities.

Methods: This study examined the potential impact of revised isolation guidelines introduced in late 2023 in Victoria, Australia, that relaxed the requirement for indefinite isolation of CPE-colonised patients in contact precautions, based on admission of CPE-diagnosed cases prior to the guideline change.

Carbapenemase-producing enterobacterales colonisation status does not lead to more frequent admissions: a linked patient study.

Background: Hospitals in any given region can be considered as part of a network, where facilities are connected to one another - and hospital pathogens potentially spread - through the movement of patients between them. We sought to describe the hospital admission patterns of patients known to be colonised with carbapenemase-producing Enterobacterales (CPE), and compare them with CPE-negative patient cohorts, matched on comorbidity information.

Methods: We performed a linkage study in Victoria, Australia, including datasets with notifiable diseases (CPE notifications) and hospital admissions (admission dates and diagnostic codes) for the period 2011 to 2020.

Estimation of SARS-CoV-2 fitness gains from genomic surveillance data without prior lineage classification.

The emergence of SARS-CoV-2 variants with increased fitness has had a strong impact on the epidemiology of COVID-19, with the higher effective reproduction number of the viral variants leading to new epidemic waves. Tracking such variants and their genetic signatures, using data collected through genomic surveillance, is therefore crucial for forecasting likely surges in incidence. Current methods of estimating fitness advantages of variants rely on tracking the changing proportion of a particular lineage over time, but describing successful lineages in a rapidly evolving viral population is a difficult task.

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.

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.

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.

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.

[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.

Impact of antibiotic use on patient-level risk of death in 36 million hospital 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.

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.

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.

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.

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.

Population genetic structuring of methicillin-resistant 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.

Measuring distance through dense weighted networks: The case of hospital-associated pathogens.

Hospital networks, formed by patients visiting multiple hospitals, affect the spread of hospital-associated infections, resulting in differences in risks for hospitals depending on their network position. These networks are increasingly used to inform strategies to prevent and control the spread of hospital-associated pathogens. However, many studies only consider patients that are received directly from the initial hospital, without considering the effect of indirect trajectories through the network.

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'.

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.

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.

[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.

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.

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.

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.

Estimating the generation interval of influenza A (H1N1) in a range of social settings.

A proper understanding of the infection dynamics of influenza A viruses hinges on the availability of reliable estimates of key epidemiologic parameters such as the reproduction number, intrinsic growth rate, and generation interval. Often the generation interval is assumed to be similar in different settings although there is little evidence justifying this. Here we estimate the generation interval for stratifications based on age, cluster size, and social setting (camp, school, workplace, household) using data from 16 clusters of Novel Influenza A (H1N1) in the Netherlands.