A hierarchical spatial modelling approach to investigate MRSA transmission in a tertiary hospital

Distribution of pathogens and antimicrobial resistance in bacteraemia according to hospitalization duration: a nationwide surveillance study in Switzerland

OBJECTIVES

Changing microorganism distributions and decreasing antibiotic susceptibility with increasing length of hospital stay have been demonstrated for the colonization or infection of selected organ systems. We wanted to describe microorganism distribution or antibiotic resistance in bacteraemia according to duration of the hospitalization using a large national epidemiological/microbiological database (ANRESIS) in Switzerland.

METHODS

We conducted a nationwide, observational study on bacteraemia using ANRESIS data from 1 January 2008 to 31 December 2017. We analysed data on bacteraemia from those Swiss hospitals that sent information on a regular basis during the entire study period. We described the pathogen distribution and specific trends of resistance during hospitalization for Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Serratia marcescens and Staphylococcus aureus.

RESULTS

We included 28 318 bacteraemia isolates from 90 Swiss hospitals. The most common aetiology was E. coli (33.4%, 9459), followed by S. aureus (16.7%, 4721), K. pneumoniae (7.1%, 2005), Enterococcus faecalis (5.2%, 1473), P. aeruginosa (4.3%, 1228), Streptococcus pneumoniae (4.3%, 1208) and Enterococcus faecium (3.9%, 1101). We observed 489 (1.73%) S. marcescens isolates. We observed an increasing trend for E. faecium (from 1.5% at day 0 to 13.7% at day 30; p < 0.001), K. pneumoniae (from 6.1% to 7.8%, p < 0.001) and P. aeruginosa (from 2.9% to 13.7%, p < 0.001) with increasing duration of hospitalization; and decreasing trends for E. coli (from 41.6% to 21.6%; p < 0.001) and S. aureus (p < 0.001). Ceftriaxone resistance among E. coli remained stable for the first 15 days of hospitalization and then increased. Ceftriaxone resistance among K. pneumoniae and S. marcescens and oxacillin resistance among S. aureus increased linearly during the hospitalization. Cefepime resistance among P. aeruginosa remained stable during the hospitalization.

DISCUSSION

We showed that hospitalization duration is associated with a species- and antibiotic class-dependent pattern of antimicrobial resistance.

Repurposing Geographic Information Systems for Routine Hospital Infection Control

This chapter discusses the potential role of geographic information systems (GIS) for infection control within the hospital system. The chapter provides a brief overview of the role of GIS in public health and reviews current work applying these methods to the hospital setting. Finally, it outlines the potential opportunities and challenges for adapting GIS for use in the hospital setting for infection prevention. A targeted literature review is used to illustrate current use of GIS in the hospital setting. The discussion of complexity was compiled using the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework. Challenges and opportunities were then extracted from this exercise by the authors. There are multiple challenges to implementation of a Hospital GIS for infection prevention, mainly involving the domains of technology, organization, and adaptation. Use of a transdisciplinary approach can address many of these challenges. More research, specifically prospective, reproducible clinical trials, needs to be done to better assess the potential impact and effectiveness of a Hospital GIS in real-world settings. This chapter highlights a powerful but rarely used tool for infection prevention within the hospital. Given the importance of reducing hospital-acquired infection rates, it is vital to identify relevant methods from other fields that could be translated into the field of hospital epidemiology.

Population-level mathematical modeling of antimicrobial resistance: a systematic review

BACKGROUND

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006-2016) to gauge the state of research and identify gaps warranting further work.

METHODS

We performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.

RESULTS

We identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.

CONCLUSIONS

The AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

Characterizing non-linear effects of hospitalisation duration on antimicrobial resistance in respiratory isolates: an analysis of a prospective nationwide surveillance system

OBJECTIVES

Our objective was to systematically study the influence of length of hospital stay on bacterial resistance in relevant respiratory tract isolates.

METHODS

Using prospective epidemiological data from the National Swiss Antibiotic Resistance Surveillance System, susceptibility testing results for respiratory isolates retrospectively retrieved from patients hospitalised between 2008 and 2014 were compiled. Generalized additive models were used to illustrate resistance rates relative to hospitalisation duration and to adjust for co-variables.

RESULTS

In all, 19 622 isolates of six relevant and predominant species were included. Resistance patterns for the predominant species showed a species-specific and antibiotic-resistance-specific profile in function of hospitalisation duration. The oxacillin resistance profile in Staphylococcus aureus isolates was constantly increasing (monophasic). The pattern of resistance to cefepime in Pseudomonas aeruginosa was biphasic with a decreasing resistance rate for the first 5 days of hospitalisation and an increase for days 6-30. A different biphasic pattern occurred in Escherichia coli regarding amoxicillin-clavulanic acid resistance: odds/day increased for the first 7 days of hospitalisation and then remained stable for days 8-30. In the adjusted models epidemiological characteristics such as age, ward type, hospital type and linguistic region were identified as relevant co-variables for the resistance rates. The contribution of these confounders was specific to the individual species/antibiotic resistance models.

CONCLUSIONS

Resistance rates do not follow a dichotomic pattern (early versus late nosocomial) as suggested by current hospital-acquired pneumonia treatment guidelines. Duration of hospitalisation rather appears to have a more complex and non-linear relationship with bacterial resistance in hospital-acquired pneumonia, also depending on host and environmental factors.