No abstract

-While shedding routes of Coxiella burnetii are identified, the characteristics of Coxiella shedding are still widely unknown, especially in dairy cattle. However, this information is crucial to assess the natural course of Coxiella burnetii infection within a herd and then to elaborate strategies to limit the risks of transmission between animals and to humans. The present study aimed at (i) describing the characteristics of Coxiella burnetii shedding by dairy cows (in milk, vaginal mucus, faeces) in five infected dairy herds, and at (ii) investigating the possible relationships between shedding patterns and serological responses. A total of 145 cows were included in a follow-up consisting of seven concomitant samplings of milk, vaginal mucus, faeces and blood (Day 0, D7, D14, D21, D28, D63, D90). Detection and quantification of Coxiella burnetii titres were performed in milk, vaginal mucus and faeces samples using real-time PCR assay, while antibodies against Coxiella were detected using an ELISA technique. For a given shedding route, and a given periodicity (weekly or monthly), cows were gathered into different shedding kinetic patterns according to the sequence of PCR responses. Distribution of estimated titres in Coxiella burnetii was described according to shedding kinetic patterns. Coxiella burnetii shedding was found scarcely and sporadically in faeces. Vaginal mucus shedding concerned almost 50% of the cows studied and was found intermittently or sporadically, depending on the periodicity considered. Almost 40% of cows were detected as milk shedders, with two predominant shedding patterns: persistent and sporadic, regardless of the sampling periodicity. Significantly higher estimated titres in Coxiella burnetii were observed in cows with persistent shedding patterns suggesting the existence of heavy shedder cows. These latter cows were mostly, persistently highly-seropositive, suggesting that repeated serological testings could be a reliable tool to screen heavy shedders, before using PCR assays. dairy cow / Coxiella burnetii / shedding / antibodies / kinetics

This study assesses the potential for a detection algorithm to identify discriminating analysis-based statistical predictors of a few relevant parameters that can be used to capture heavy precipitation events (HPEs), or, at least, their associated largescale circulation (LSC) patterns in a climate scenario. HPEs are defined from a sample combining 'large-scale' fields from the ECMWF ERA-40 reanalysis with local observations from the Météo-France rain-gauge network. In a first step, LSC patterns considered as significantly favouring HPE over southern France are identified and described with the greatest robustness possible. For that purpose, an objective automatic clustering of the unfiltered 500 hPa geopotential height field is performed. Four clusters are obtained. Among them, the most discriminating for heavy precipitation is characterised by a synoptic-scale deep upper-level low northwest of the area of interest, inducing a southerly flow over the western Mediterranean Sea and southern France. In a second step, other lower-scale parameters are used to refine the characteristics of the clusters. It has been found that the low-level moisture transport is a relevant low-level ingredient to regionally characterise heavy precipitation. Indeed, 'Cévennes' cases are related to more south to southeasterly flows over the Gulf of Lion, whereas 'Languedoc-Roussillon' events occurred preferentially within a more pronounced easterly wind component with two streams of low-level moisture transport. Moreover, in-depth examination of the low-level features reveals that HPEs tend to occur when the wind blows in a specific direction and for the greatest low-level moisture flux over the Gulf of Lion. Finally, the predictive skill of a detection tool for HPEs over southern France, with only synoptic-scale favourable parameters as predictors, is discussed. It is shown that this tool allows selection of HPE situations in more than 70% of cases.