Outbreak of Nontuberculous Mycobacteria Joint Prosthesis Infections, Oregon, USA, 2010-2016.

We investigated a cluster of Mycobacterium fortuitum and M. goodii prosthetic joint surgical site infections occurring during 2010-2014. Cases were defined as culture-positive nontuberculous mycobacteria surgical site infections that had occurred within 1 year of joint replacement surgery performed on or after October 1, 2010. We identified 9 cases by case finding, chart review, interviews, surgical observations, matched case-control study, pulsed-field gel electrophoresis of isolates, and environmental investigation; 6 cases were diagnosed >90 days after surgery. Cases were associated with a surgical instrument vendor representative being in the operating room during surgery; other potential sources were ruled out. A tenth case occurred during 2016. This cluster of infections associated with a vendor reinforces that all personnel entering the operating suite should follow infection control guidelines; samples for mycobacterial culture should be collected early; and postoperative surveillance for <90 days can miss surgical site infections caused by slow-growing organisms requiring specialized cultures, like mycobacteria.

Escherichia coli O157:H7 infections associated with consumption of locally grown strawberries contaminated by deer.

BACKGROUND: An outbreak of Escherichia coli O157:H7 was identified in Oregon through an increase in Shiga toxin-producing E. coli cases with an indistinguishable, novel pulsed-field gel electrophoresis (PFGE) subtyping pattern. METHODS: We defined confirmed cases as persons from whom E. coli O157:H7 with the outbreak PFGE pattern was cultured during July-August 2011, and presumptive cases as persons having a household relationship with a case testing positive for E. coli O157:H7 and coincident diarrheal illness. We conducted an investigation that included structured hypothesis-generating interviews, a matched case-control study, and environmental and traceback investigations. RESULTS: We identified 15 cases. Six cases were hospitalized, including 4 with hemolytic uremic syndrome (HUS). Two cases with HUS died. Illness was significantly associated with strawberry consumption from roadside stands or farmers' markets (matched odds ratio, 19.6; 95% confidence interval, 2.9-∞). A single farm was identified as the source of contaminated strawberries. Ten of 111 (9%) initial environmental samples from farm A were positive for E. coli O157:H7. All samples testing positive for E. coli O157:H7 contained deer feces, and 5 tested farm fields had ≥ 1 sample positive with the outbreak PFGE pattern. CONCLUSIONS: The investigation identified fresh strawberries as a novel vehicle for E. coli O157:H7 infection, implicated deer feces as the source of contamination, and highlights problems concerning produce contamination by wildlife and regulatory exemptions for locally grown produce. A comprehensive hypothesis-generating questionnaire enabled rapid identification of the implicated product. Good agricultural practices are key barriers to wildlife fecal contamination of produce.

Statin treatment and mortality: propensity score-matched analyses of 2007-2008 and 2009-2010 laboratory-confirmed influenza hospitalizations.

Background. Annual influenza epidemics are responsible for substantial morbidity and mortality. The use of immunomodulatory agents such as statins to target host inflammatory responses in influenza virus infection has been suggested as an adjunct treatment, especially during pandemics, when antiviral quantities are limited or vaccine production can be delayed. Methods. We used population-based, influenza hospitalization surveillance data, propensity score-matched analysis, and Cox regression to determine whether there was an association between mortality (within 30 days of a positive influenza test) and statin treatment among hospitalized cohorts from 2 influenza seasons (October 1, 2007 to April 30, 2008 and September 1, 2009 to April 31, 2010). Results. Hazard ratios for death within the 30-day follow-up period were 0.41 (95% confidence interval [CI], .25-.68) for a matched sample from the 2007-2008 season and 0.77 (95% CI, .43-1.36) for a matched sample from the 2009 pandemic. Conclusions. The analysis suggests a protective effect against death from influenza among patients hospitalized in 2007-2008 but not during the pandemic. Sensitivity analysis indicates the findings for 2007-2008 may be influenced by unmeasured confounders. This analysis does not support using statins as an adjunct treatment for preventing death among persons hospitalized for influenza.

Estimating influenza disease burden from population-based surveillance data in the United States.

Annual estimates of the influenza disease burden provide information to evaluate programs and allocate resources. We used a multiplier method with routine population-based surveillance data on influenza hospitalization in the United States to correct for under-reporting and estimate the burden of influenza for seasons after the 2009 pandemic. Five sites of the Influenza Hospitalization Surveillance Network (FluSurv-NET) collected data on the frequency and sensitivity of influenza testing during two seasons to estimate under-detection. Population-based rates of influenza-associated hospitalization and Intensive Care Unit admission from 2010-2013 were extrapolated to the U.S. population from FluSurv-NET and corrected for under-detection. Influenza deaths were calculated using a ratio of deaths to hospitalizations. We estimated that influenza-related hospitalizations were under-detected during 2010-11 by a factor of 2.1 (95%CI 1.7-2.9) for age < 18 years, 3.1 (2.4-4.5) for ages 18-64 years, and 5.2 (95%CI 3.8-8.3) for age 65+. Results were similar in 2011-12. Extrapolated estimates for 3 seasons from 2010-2013 included: 114,192-624,435 hospitalizations, 18,491-95,390 ICU admissions, and 4,915-27,174 deaths per year; 54-70% of hospitalizations and 71-85% of deaths occurred among adults aged 65+. Influenza causes a substantial disease burden in the U.S. that varies by age and season. Periodic estimation of multipliers across multiple sites and age groups improves our understanding of influenza detection in sentinel surveillance systems. Adjusting surveillance data using a multiplier method is a relatively simple means to estimate the impact of influenza and the subsequent value of interventions to prevent influenza.