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Mathematical models of infection transmission in healthcare settings: recent advances from the use of network structured data

Assab, Raniaa,b,*; Nekkab, Narimanea,b,c,*; Crépey, Pascalc,d,e; Astagneau, Pascalf; Guillemot, Didierg,h,i,j; Opatowski, Lullag,h,i; Temime, Lauraa,b

Current Opinion in Infectious Diseases: August 2017 - Volume 30 - Issue 4 - p 410–418
doi: 10.1097/QCO.0000000000000390

Purpose of review: Mathematical modeling approaches have brought important contributions to the study of pathogen spread in healthcare settings over the last 20 years. Here, we conduct a comprehensive systematic review of mathematical models of disease transmission in healthcare settings and assess the application of contact and patient transfer network data over time and their impact on our understanding of transmission dynamics of infections.

Recent findings: Recently, with the increasing availability of data on the structure of interindividual and interinstitution networks, models incorporating this type of information have been proposed, with the aim of providing more realistic predictions of disease transmission in healthcare settings. Models incorporating realistic data on individual or facility networks often remain limited to a few settings and a few pathogens (mostly methicillin-resistant Staphylococcus aureus).

Summary: To respond to the objectives of creating improved infection prevention and control measures and better understanding of healthcare-associated infections transmission dynamics, further innovations in data collection and parameter estimation in modeling is required.

aLaboratoire MESuRS, Conservatoire National des Arts et Métiers, Paris

bUnité PACRI, Institut Pasteur, Paris

cDépartement d’Epidémiologie et de Biostatistiques, Ecole des Hautes Etudes en Santé Publique, Rennes

dUMR IRD 190, INSERM, EHESP, Aix-Marseille University, Marseille

eUPRES-EA 7449 REPERES, Recherche en Pharmaco-Epidémiologie et Recours aux Soins, EHESP, Université de Rennes 1, Rennes

fCentre de prévention des infections associées aux soins (C-CLIN), APHP, Paris

gUniversité Versailles St Quentin, Versailles

hInstitut Pasteur, Paris


jUnité Fonctionnelle de Santé Publique, APHP, Hôpital Raymond-Poincare, Garches, Paris France

Correspondence to Rania Assab, 292 Rue Saint-Martin, F-75003 Paris, France. Tel: +33153018069; e-mail:,

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