Early detection of West Nile virus in France: quantitative assessment of syndromic surveillance system using nervous signs in horses.

West Nile virus (WNV) is a growing public health concern in Europe and there is a need to develop more efficient early detection systems. Nervous signs in horses are considered to be an early indicator of WNV and, using them in a syndromic surveillance system, might be relevant. In our study, we assessed whether or not data collected by the passive French surveillance system for the surveillance of equine diseases can be used routinely for the detection of WNV. We tested several pre-processing methods and detection algorithms based on regression. We evaluated system performances using simulated and authentic data and compared them to those of the surveillance system currently in place. Our results show that the current detection algorithm provided similar performances to those tested using simulated and real data. However, regression models can be easily and better adapted to surveillance objectives. The detection performances obtained were compatible with the early detection of WNV outbreaks in France (i.e. sensitivity 98%, specificity >94%, timeliness 2·5 weeks and around four false alarms per year) but further work is needed to determine the most suitable alarm threshold for WNV surveillance in France using cost-efficiency analysis.

[Experimental assessment of the possible significance of argasid ticks in preserving the natural foci of West Nile virus infection].

Experiments indicated that the argasid ticks Alveonasus lahorensis were highly susceptible to West Nile virus when inoculated in the hemocoel. The virus concentration in the ticks reached high values when very low doses (0.01 PFU) of the pathogen were administered. The ticks kept at 3.0 +/- 1.0 degrees C retained the pathogen up to 116 days (a follow-up period). The infection rate of the ticks depending on the virus dose administered was in the range from 12 to 80%. The contaminated specimens successfully transmitted the virus to rabbits by blood suckling. The findings suggest that the argasid ticks may be involved in the preservation of West Nile virus in the interepidemic period and be responsible for the outbreak of this infection in summer and autumn months.

Critical assessment of automated flow cytometry data analysis techniques.

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.