Transmission Dynamics of Antimocrobial-resistant bacteria in dialysis units

Beth Israel Deaconess Medical Center, Boston MA

Investigators

Linked publications & trials

Abstract

[unreadable] DESCRIPTION (provided by applicant): Infections are the second most common cause of death in patients requiring chronic hemodialysis (CHD). Those caused by antibiotic-resistant bacteria (ARB) are associated with up to 5-fold higher mortality rates. Rates of ARB continue to rise among CHD patients and are implicated in 1/3 of infections in this population. Novel control strategies aimed at decreasing ARB acquisition and ultimately ARB infections are urgently needed. The goal of this proposal is to characterize the unique aspects of ARB transmission in the out- patient hemodialysis setting in order to develop innovative, effective and practical applications of existing or novel control strategies. Population-level analysis of infectious agents, including SARS and HIV, document that a subgroup of individuals, termed the "superspreaders", are responsible for the majority of disease spread, and that control efforts focusing on this subgroup of patients is highly effective. Our preliminary data suggest that there is a subgroup of CHD patients in the out-patient setting characteristic of superspreaders. Focusing interventions to this subgroup may have considerably larger effects on preventing ARB acquisition than interventions currently in place. This multidisciplinary pilot application will combine clinical, molecular genotyping and mathematical modeling techniques that have been successfully applied by our group to characterize the transmission dynamics of ARB in dialysis units. In aim 1, we plan to extend an on-going single-unit pilot study into a multicenter prospective cohort study to characterize the group of superspreaders of ARB at the individual-level. In aim 2, a population-level analysis, using mathematical models, will characterize and quantify the contribution of the superspreaders to ARB spread and the efficacy of control strategies focusing on this subgroup. These models will build on individual-level data obtained from the cohort study and, will characterize the numerous interrelated and dynamic factors contributing to the spread of ARB. which clinical studies cannot capture. The research team is comprised of an infectious disease epidemiologist, a mathematician with expertise in ARB modeling and, a leader in the field of infections and ARB in the dialysis population. The data obtained from this proposal will allow the development and implementation of innovative control strategies targeted at the superspreaders of ARB. Limiting ARB spread will ultimately reduce infections caused by ARB and improve CHD patient outcomes. [unreadable] [unreadable] [unreadable]