Background.: Change from nonmolecular to molecular testing techniques is thought to contribute to the increasing trend in incidence of Clostridium difficile infection (CDI); however the degree of effect attributed to this versus other time-related epidemiologic factors is unclear.Methods.: We compared the relative change in incidence rate (IRR) of healthcare facility–associated (HCFA) CDI among hospitals in the Duke Infection Control Outreach Network before and after the date of switch from nonmolecular tests to polymerase chain reaction (PCR) using prospectively collected surveillance data from July 2009 to December 2011. Data from 10 hospitals that switched and 22 control hospitals were included. Individual hospital estimates were determined using Poisson regression. We used an interrupted time series approach to develop a Poisson mixed-effects model. Additional regression adjustments were made for clustering and proportion of intensive care unit patient-days. The variable for PCR was treated as a fixed effect; other modeled variables were random effects.Results.: For those hospitals that switched to PCR, mean incidence rate of HCFA CDI before the switch was 6.0 CDIs per 10,000 patient-days compared with 9.6 CDIs per 10,000 patient-days after the switch. Estimates of hospital-specific IRR that compared after the switch with before the switch ranged from 0.89 (95% confidence interval [CI], 0.32–2.44) to 6.91 (95% CI, 1.12–42.54). After adjustment in the mixed-effects model, the overall IRR comparing CDI incidence after the switch to before the switch was 1.56 (95% CI, 1.28–1.90). Time-trend variables did not reach statistical significance.Conclusion.: Hospitals that switched from nonmolecular to molecular tests experienced an approximate 56% increase in the rate of HCFA CDI after testing change.

Background: Clostridium difficile is a health care-associated infection of increasing importance. The purpose of this study was to estimate the time until death from any cause and time until release among patients with C. difficile, comparing the burden of those in the intensive care unit (ICU) with those in the general hospital population. Methods: A parametric mixture model was used to estimate event times, as well as the case-fatality ratio in ICU and non-ICU patients within a cohort of 609 adult incident cases of C. difficile in the Southeastern United States between 1 July 2009 and 31 December 2010. Results: ICU patients had twice the median time to death (relative time = 1.97 [95% confidence interval (CI) = 0.96-4.01]) and nearly twice the median time to release (1.88 [1.40-2.51]) compared with non-ICU patients. ICU patients also experienced 3.4 times the odds of mortality (95% CI = 1.8-6.2). Cause-specific competing risks analysis underestimated the relative survival time until death (0.65 [0.36-1.17]) compared with the mixture model. Conclusions: Patients with C. difficile in the ICU experienced higher mortality and longer lengths of stay within the hospital. ICU patients with C. difficile infection represent a population in need of particular attention, both to prevent adverse patient outcomes and to minimize transmission of C. difficile to other hospitalized patients.

Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging pathogen, first recognized in 2012, with a high case fatality risk, no vaccine, and no treatment beyond supportive care. We estimated the relative risks of death and severe disease among MERS-CoV patients in the Middle East between 2012 and 2015 for several risk factors, using Poisson regression with robust variance and a bootstrap-based expectation maximization algorithm to handle extensive missing data. Increased age and underlying comorbidity were risk factors for both death and severe disease, while cases arising in Saudi Arabia were more likely to be severe. Cases occurring later in the emergence of MERS-CoV and among health-care workers were less serious. This study represents an attempt to estimate risk factors for an emerging infectious disease using open data and to address some of the uncertainty surrounding MERS-CoV epidemiology.

Please cite this paper as: Chu et al. (2011) Performance of rapid influenza H1N1 diagnostic tests: a meta‐analysis. Influenza and Other Respiratory Viruses DOI: 10.1111/j.1750‐2659.2011.00284.x.Background  Following the outbreaks of 2009 pandemic H1N1 infection, rapid influenza diagnostic tests have been used to detect H1N1 infection. However, no meta‐analysis has been undertaken to assess the diagnostic accuracy when this manuscript was drafted.Methods  The literature was systematically searched to identify studies that reported the performance of rapid tests. Random effects meta‐analyses were conducted to summarize the overall performance.Results  Seventeen studies were selected with 1879 cases and 3477 non‐cases. The overall sensitivity and specificity estimates of the rapid tests were 0·51 (95%CI: 0·41, 0·60) and 0·98 (95%CI: 0·94, 0·99). Studies reported heterogeneous sensitivity estimates, ranging from 0·11 to 0·88. If the prevalence was 30%, the overall positive and negative predictive values were 0·94 (95%CI: 0·85, 0·98) and 0·82 (95%CI: 0·79, 0·85). The overall specificities from different manufacturers were comparable, while there were some differences for the overall sensitivity estimates. BinaxNOW had a lower overall sensitivity of 0·39 (95%CI: 0·24, 0·57) compared with all the others (P‐value <0·001), whereas QuickVue had a higher overall sensitivity of 0·57 (95%CI: 0·50, 0·63) compared with all the others (P‐value = 0·005).Conclusions  Rapid tests have high specificity but low sensitivity and thus limited usefulness.