Infection Control Dynamics in Hospital Networks

Hospital networks form complex, interconnected systems in which patients move between wards, units and institutions. These movements create pathways for hospital-acquired infections (HAIs) and antimicrobial-resistant organisms to disperse beyond single sites of care. Understanding the structural features of these networks—such as central hubs, regional clusters and referral patterns—permits targeted interventions that reduce transmission risk. Mathematical and computational models have elucidated how heterogeneity in patient contacts, length of stay, colonisation clearance rates and environmental contamination drive outbreak dynamics. Real-time surveillance, coupled with network analysis, enables early detection of emerging threats and optimisation of screening or isolation policies. Practical applications range from allocating ‘sensor’ hospitals for efficient monitoring to informing hand-hygiene campaigns and cohorting strategies. Globally, aligning infection control measures with the underlying network topology enhances resilience against multidrug-resistant pathogens and supports coordinated stewardship across healthcare systems.

Research from Nature Portfolio

Recent studies have quantified how inter-hospital transfer patterns shape pathogen spread. One analysis of four regional networks in Germany found that while direct transfers play a role, readmissions to the same hospital—particularly when decolonisation is delayed—pose a larger risk of onward transmission. Community links further modify the time to peak prevalence and final outbreak size. A complementary investigation of high-resolution patient contacts across hundreds of institutions in a national system revealed highly heterogeneous referral trajectories. Modelling of methicillin-resistant Staphylococcus aureus (MRSA) spread indicated the emergence of super-spreaders, non-exponential growth phases and rapid cross-ward dissemination. Simulation exercises suggested that admission screening may outperform moderate reductions in transmission probability for controlling endemic MRSA in low-prevalence settings.

Infection Control Dynamics in Hospital Networks publication trend

The graph below shows the total number of articles in infection control dynamics in hospital networks across all publications each year (not limited to Nature Index journals).

Technical terms

Hospital-acquired infection (HAI): An infection contracted by a patient during their stay in a healthcare facility, not present or incubating on admission.

Patient transfer network: A graph representation of hospitals linked by patient movements, used to study how pathogens traverse healthcare systems.

Colonisation clearance rate: The rate at which an individual naturally or through treatment eliminates carriage of a pathogen.

Bayesian inference: A statistical approach that updates the probability of a model or hypothesis as more data become available, often via Monte Carlo sampling.

Network centrality: A measure of a node’s importance within a network, indicating its potential influence on pathogen spread.

References

1. Bayesian Calibration to Address the Challenge of Antimicrobial Resistance: A Review. IEEE Access (2024).
2. Carbapenemase-producing enterobacterales colonisation status does not lead to more frequent admissions: a linked patient study. Antimicrobial Resistance & Infection Control (2024).
3. Hospital Networks and the Dispersal of Hospital-Acquired Pathogens by Patient Transfer. PLOS ONE (2012).
4. Patient Referral Patterns and the Spread of Hospital-Acquired Infections through National Health Care Networks. PLOS Computational Biology (2010).
5. Spread of hospital-acquired infections: A comparison of healthcare networks. PLOS Computational Biology (2017).
6. Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections. Scientific Reports (2017).
7. Dynamic contact networks of patients and MRSA spread in hospitals. Scientific Reports (2020).
8. Regional patient transfer patterns matter for the spread of hospital-acquired pathogens. Scientific Reports (2024).