Biography
Benjamin Kung is the Program Manager of IPAC for the CPSA and additionally serves as Governance Committee Chair on the Board of Directors, Alberta Public Health Association. He has completed his undergraduate training in Microbiology/Biology from University of Victoria and Environmental Public Health from British Columbia Institute of Technology, followed by graduate studies in IPAC from University of British Columbia and Epidemiology at London School of Hygiene & Tropical Medicine.
Abstract
Historically in Alberta, responsibility for monitoring infection prevention & control (IPAC) in non-governmental, unaccredited medical clinics had fallen on the business owner and/or physicians. In 2007, a sentinel event triggered a government directed review of IPAC in these settings. A program was created under the direction of a 10-member Advisory Committee: Infectious disease specialists, medical officers of health, senior infection control practitioners, and community physicians and surgeons. CPSA has since actively monitored IPAC with a priority on standards for MDR (cleaning, disinfection and sterilization of medical devices). Alberta has approximately 1700 medical facilities in the “non-governmental, unaccredited†category. Over 600 (>35%) perform some type of MDR and these were assessed for adherence to standards during 2008-2015. In 2013, a provincial policy for reporting the most critical deficiencies was formalized. From 2013-15, 131 assessments identified 17 (13.0%) with risks exceeding the reporting threshold to public health. Deficiencies contributing to the likelihood of reporting included but were not limited to inadequate device cleaning, lack of monitoring sterilization cycles for physical (time, temperature), chemical and/or biological parameters, use of unlicensed sterilizers and inadequate level of reprocessing given device risk classification (Spaulding’s). Post-exposure risk assessment deemed four (3.0%, n=131) a sufficient threat to initiate look backs for blood-borne pathogen exposure (HIV, HBV & HCV). Formal reporting and post-exposure risk assessment confirmed initial observations suggesting clinics performing MDR are at elevated risk of breaching IPAC principles that may jeopardize patient safety. The logistics and value of providing clinic support via robust regulatory controls is worth exploring.
Biography
Veronika Szaboova is affiliated to the Comenius University, Slovakia.
Abstract
Recently, thanks to immunization, no cases of measles have been reported in Slovakia. Information on the immune status of the population is important to prevent possible re-emergence of the disease. However, the last nationwide immunological survey in Slovakia was carried out in 2002. This work estimates current (2014) measles susceptibility in individual age groups using mathematic modeling. The analysis is based on administrative data on vaccination coverage, the immunological survey from 2002 and demographic data on age structure of the Slovak population. The cohort model considered changes since 2002: new single dose vaccinated cohorts (born 2000-2012) and cohorts vaccinated with the second dose (born 1989-2002). In other cohorts, immunity naturally partially waned and the proportion of cohorts with more effective post-infection immunity (naturally infected) declined. In 2002, there were approximately 241,000 susceptible individuals (approximately 4.5% of the population) in Slovakia. Most of them, besides children aged below one year and yet not vaccinated, were aged 17-34. In 2014, there were approximately 383,000 susceptible individuals (approximately 7.1% of the population), mostly non-vaccinated children up to one year and adults aged 30-45 years. These adults constituted the most prevalent susceptible cohort. The increased proportion of susceptible population is partially attributable to natural waning of the immunity in vaccinated individuals without natural contact with the disease. Therefore, in a potential epidemic outbreak, alongside the unvaccinated, 30-45 year old individuals (cohort born 1969-1984) will be the most endangered. Although the mathematic modeling, due to its limitations, cannot fully substitute the immunological survey, the estimations can sufficiently identify the endangered population cohorts to adjust the vaccination policy appropriately.