TY - JOUR T1 - Informed Switching Strongly Decreases the Prevalence of Antibiotic Resistance in Hospital Wards A1 - Kouyos, Roger D. A1 - Abel zur Wiesch, Pia A1 - Bonhoeffer, Sebastian Y1 - 2011/03/03 N2 - Author Summary Infections with bacterial pathogens that are resistant against antibiotics are an important cause of mortality and morbidity in hospitals. One possibility to minimize this burden of antibiotic resistance is to coordinate the use of several drugs at the level of a single hospital ward. Here, we use a computational model of a hospital ward in order to assess the performance of several such strategies that take into account the frequency of antibiotic resistance in the hospital ward. We assume that information on resistance frequencies stems from microbiological tests, which are performed routinely in order to optimize individual therapy. Thus the strategy proposed here represents an optimization at population-level, which comes as a free byproduct of optimizing treatment at the individual level. We find that in most cases our informed strategy can substantially reduce the prevalence of antibiotic resistance. We show that the performance of an informed strategy can be improved substantially if information on resistance tests is integrated over a period of one to two weeks. Overall, our results suggest that switching between different antibiotics might be a valuable strategy in small patient populations, if the switching strategies take the frequencies of resistance alleles into account. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 3 UR - https://doi.org/10.1371/journal.pcbi.1001094 SP - e1001094 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1001094 ER -