Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus

Pei, Sen; Morone, Flaviano; Liljeros, Fredrik; Makse, Hernán; Shaman, Jeffrey L

In the MRSA transmission model, some quantities, for example colonization importation, infection importation, and weekly incidence, are macroscopic values aggregated from the individual-level states. In model simulation, we first need to lift these macroscopic quantities to consistent microscopic realizations. To do this, we maintained multiple realizations (300 ensemble members) of individual-level states. For each new patient entering the hospitals, a random number r was generated from a uniform distribution ~U½0; 1. If I 0 , I 0 I 0 þ C 0 , or ! I 0 þ C 0 , and used to designate the new patient as infected, colonized or susceptible, respectively. This lifting procedure was performed for all realizations and produced an ensemble of possible microscopic states. These individual-level states were then evolved following the rules defined in the model over the time-varying contact network GðV; E; tÞ. The model estimate of the observed state, that is 4 week incidence, was obtained by aggregating the total number of new infections across the entire population in the study hospitals. This aggregated, macroscopic state is then used in conjunction with the EAKF algorithm to update the parameter vector z ¼ ðb; I 0 ; C 0 Þ T (see Materials and methods in main text). This multi-scale method enables system-level analysis directly from microscopic simulations, which bypasses the need to derive macroscopic evolution equations.