Dynamic contact networks of patients and MRSA spread in hospitals.

Abstract:

:Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult-to-treat infection. Increasing efforts have been taken to mitigate the epidemics and to avoid potential outbreaks in low endemic settings. Understanding the population dynamics of MRSA is essential to identify the causal mechanisms driving the epidemics and to generalise conclusions to different contexts. Previous studies neglected the temporal structure of contacts between patients and assumed homogeneous behaviour. We developed a high-resolution data-driven contact network model of interactions between 743,182 patients in 485 hospitals during 3,059 days to reproduce the exact contact sequences of the hospital population. Our model captures the exact spatial and temporal human contact behaviour and the dynamics of referrals within and between wards and hospitals at a large scale, revealing highly heterogeneous contact and mobility patterns of individual patients. A simulation exercise of epidemic spread shows that heterogeneous contacts cause the emergence of super-spreader patients, slower than exponential polynomial growth of the prevalence, and fast epidemic spread between wards and hospitals. In our simulated scenarios, screening upon hospital admittance is potentially more effective than reducing infection probability to reduce the final outbreak size. Our findings are useful to understand not only MRSA spread but also other hospital-acquired infections.

journal_name

Sci Rep

journal_title

Scientific reports

authors

Rocha LEC,Singh V,Esch M,Lenaerts T,Liljeros F,Thorson A

doi

10.1038/s41598-020-66270-9

subject

Has Abstract

pub_date

2020-06-09 00:00:00

pages

9336

issue

1

issn

2045-2322

pii

10.1038/s41598-020-66270-9

journal_volume

10

pub_type

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