Efficient surveillance for healthcare-associated infections spreading between hospitals

Abstract

Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10-20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort.

Keywords: network; patient referrals.

Fig. 1.

Probability, estimated as relative frequency through time, of each individual hospital in England (A) and The Netherlands (B) becoming affected by a novel nosocomial pathogen, following single introduction in a randomly selected hospital at time t = 0. Results obtained in the baseline scenario (β = 0.001 and γ = 0). Hospitals have been sorted along the y axis according to increasing value of median time to first infection.

Fig. 2.

Mean detection time of a novel nosocomial pathogen (A), and mean number of affected hospitals at detection time (B), following emergence in a single, randomly selected hospital, versus fraction of hospitals participating in a sentinel surveillance program. The continuous lines correspond to results obtained using the greedy algorithm with the English (EN: greedy) and Dutch (NL: greedy) data sets. The optimization metric was time to detection (A) and number of affected hospitals at detection (B). The shaded region and the dashed lines (EN, random, and NL, random) correspond to 1,000 random selections of sentinel hospitals and their mean, respectively. (A and B, Upper) Information on hospital category for England (EN) and The Netherlands (NL): the symbol corresponding to the ith element in the priority list obtained with the greedy algorithm is displayed at position i/N along the x axis, with N the total number of hospitals in the country. All curves obtained in the baseline scenario (β = 0.001 and γ = 0).

Fig. 3.

Box plots of median HCAI-free time in the endemic regime in England (A) and The Netherlands (B). Results obtained with the baseline transmission probability β = 0.001. Median times have been grouped according to type of hospital. Different colors correspond to different values of γ. Box bottom and top represent the lower and upper quartiles, respectively. Lower and upper line ends represent 5th and 95th percentiles, respectively. The horizontal bar corresponds to the median. Elimination rates (γ) are expressed in units of y⁻¹.