Fig 1.
Patients are categorized as either Susceptible (S), Exposed (E), or Infectious (I), while the available device may either be new (QN) and sterile, previously used but uncontaminated (QU), or previously used and contaminated (QC). The ward network reflects the structure of Ain Shams hospital and is used as an illustrative example to apply our model. Hospital wards are depicted as blue (for internal medicine wards), yellow (for surgery wards), or purple (for other wards visited by internal medicine and surgery patients) circles, with circle size proportional to the number of beds in the ward. The width of between-ward edges is proportional to the corresponding number of patient movements. The full list of ward names associated with each ward number is provided in S1 Table.
Table 1.
Hospital-associated parameters. “Data” refers to data collected in Ain Shams hospital. More details are provided in S3–S10 Tables.
Table 2.
Pathogen-associated parameters.
Fig 2.
Results of the model for baseline scenarios (HCV case).
(A) and (C): Daily incidence rate for the high- and low-resource hospitals, respectively. (B) and (D) Yearly cumulative incidence (mean and 95% PI) and average number of cases for each ward, ranked by mean cumulative incidence values.
Fig 3.
Yearly attributable portion to new cases for each device, in (A) Baseline scenario for the high-resource and (B) Baseline scenario for the low-resource hospital.
Fig 4.
Reduction in the predicted yearly cumulative incidence, by comparison with the baseline scenarios, obtained by two different intervention strategies implemented in (A) high-resource and (B) low-resource hospitals.
Baseline scenarios correspond to the no-intervention scenarios. For both high-resource and low-resource settings, on average, 53,640 patients (72%) were screened (i) either systematically (in the three most at-risk wards) or (ii) randomly upon admission. Median relative reductions computed over 100 simulations, along with the first and third quantiles (boxes) of the associated distributions and the 95% prediction intervals, are depicted.