Jean-Baptiste Perrin

Assessment of the utility of routinely collected cattle census and disposal data for syndromic surveillance

Census and disposal data provide a multipurpose source of information on cattle mortality. The retrospective analyses we conducted on the data gathered in the National Cattle Register produced relevant information for describing and modelling the cattle mortality baseline and evaluating the impact of the 2007-2008 Blue Tongue epidemic on the French cattle population. This work was conducted retrospectively but showed that monitoring cattle mortality near real time could help detecting unexpected events. We are thus currently working on a timely and automated system to monitor cadaver disposal requests received by rendering plants, thanks to a data interchange system recently implemented between the Ministry of Agriculture and the fallen stock companies. Besides technical and methodological challenges, using these data for surveillance purposes raises epidemiological questions that still need to be answered. The question remains notably as to whether an abnormal increased mortality is a sensitive and timely signal for detecting unexpected health events. It appears also very challenging to identify the most adequate surveillance scale (time, space and population) and the most adequate anomaly detection algorithms to apply when the characteristics of the signals to be detected (shape, amplitude, etc.) are not known a priori. In Human health, similar systems have not yet proven their ability to detect unexpected events earlier than classical surveillance systems currently in place, but they have already demonstrated their value for real time assessment of identified and potentially dangerous events. Combined with traditional surveillance systems, we think that monitoring routinely collected data could improve the surveillance of the animal population health. Even if not used for detection purposes, cattle mortality monitoring could be used to rapidly produce information on the impact and evolution of identified events, what would facilitate decision-making regarding management measures and improve the communication.

Using the National Cattle Register to estimate the excess mortality during an epidemic: application to an outbreak of Bluetongue serotype 8.

National Cattle Registers have been widely used to examine animal movements and their role in disease transmission, but less frequently for other epidemiological applications. Our study shows how routinely collected identification data can be used to evaluate the population impact of an epidemic in cattle and to derive an indirect estimate of the associated mortality. We adapted a method developed by Human health agencies, based on the modelling of historical mortality fluctuations, to analyze the evolution of mortality in a cattle population subjected to a Bluetongue serotype 8 (BT8) outbreak. Between 01/07/2007 and 01/07/2008, 21,017 cattle died in the considered population whereas 16,691 deaths were expected according to the model. 43% of the 4326 extra deaths were found in calves less than 7 days of age, but excess mortality was found in each age group. The temporal distribution of extra-deaths, described at a weekly scale, suggests that they were related to the BT8 epidemic. The presented method could be an appreciable tool for estimating the global burden of epidemics since it is based on data already routinely collected in each European Member State. This study was conducted retrospectively but considering the promptness of the notification system, the method could be used to monitor the evolution of epidemics in near-real time.

Assessment of the impact of the 2003 and 2006 heat waves on cattle mortality in France.

Objectives While several studies have highlighted and quantified human mortality during the major heat waves that struck Western Europe in 2003 and 2006, the impact on farm animals has been overlooked. The aim of this study was to assess the effect of these two events on cattle mortality in France, one of the most severely impacted countries. Methods Poisson regressions were used to model the national baseline for cattle mortality between 2004 and 2005 and predict the weekly number of expected deaths in 2003 and 2006 for the whole cattle population and by subpopulation based on age and type of production. Observed and estimated values were compared to identify and quantify excess mortality. The same approach was used at a departmental scale (a French department being an administrative and territorial division) to assess the spatio-temporal evolution of the mortality pattern. Results Overall, the models estimated relative excess mortality of 24% [95% confidence interval: 22–25%] for the two-week heat wave of 2003, and 12% [11–14%] for the three-week heat wave of 2006. In 2003, most cattle subpopulations were impacted during the heat wave and some in the following weeks too. In 2006, cattle subpopulations were impacted for a limited time only, with no excess mortality at the beginning or after the heat wave. No marked differences in cattle mortality were found among the different subpopulations by age and type of production. The implications of these results for risk prevention are discussed.

Inventory of veterinary syndromic surveillance initiatives in Europe (Triple-S project): current situation and perspectives.

Within the current context that favours the emergence of new diseases, syndromic surveillance (SyS) appears increasingly more relevant tool for the early detection of unexpected health events. The Triple-S project (Syndromic Surveillance Systems in Europe), co-financed by the European Commission, was launched in September 2010 for a three year period to promote both human and animal health SyS in European countries. Objectives of the project included performing an inventory of current and planned European animal health SyS systems and promoting knowledge transfer between SyS experts. This study presents and discusses the results of the Triple-S inventory of European veterinary SyS initiatives. European SyS systems were identified through an active process based on a questionnaire sent to animal health experts involved in SyS in Europe. Results were analyzed through a descriptive analysis and a multiple factor analysis (MFA) in order to establish a typology of the European SyS initiatives. Twenty seven European SyS systems were identified from twelve countries, at different levels of development, from project phase to active systems. Results of this inventory showed a real interest of European countries for SyS but also highlighted the novelty of this field. This survey highlighted the diversity of SyS systems in Europe in terms of objectives, population targeted, data providers, indicators monitored. For most SyS initiatives, statistical analysis of surveillance results was identified as a limitation in using the data. MFA results distinguished two types of systems. The first one belonged to the private sector, focused on companion animals and had reached a higher degree of achievement. The second one was based on mandatory collected data, targeted livestock species and is still in an early project phase. The exchange of knowledge between human and animal health sectors was considered useful to enhance SyS. In the same way that SyS is complementary to traditional surveillance, synergies between human and animal health SyS could be an added value, most notably to enhance timeliness, sensitivity and help interpreting non-specific signals.

Spread and impact of the Schmallenberg virus epidemic in France in 2012-2013

BackgroundThe Schmallenberg virus (SBV) emerged in Europe in 2011 and caused a widespread epidemic in ruminants.In France, SBV emergence was monitored through a national multi-stakeholder surveillance and investigation system. Based on the monitoring data collected from January 2012 to August 2013, we describe the spread of SBV in France during two seasons of dissemination (vector seasons 2011 and 2012) and we provide a large-scale assessment of the impact of this new disease in ruminants.ResultsSBV impact in infected herds was primarily due to the birth of stillborns or deformed foetuses and neonates. Congenital SBV morbidity level was on average moderate, although higher in sheep than in other ruminant species. On average, 8% of lambs, 3% of calves and 2% of kids born in SBV-infected herds showed typical congenital SBV deformities. In addition, in infected herds, farmers reported retrospectively a lower prolificacy during the vector season, suggesting a potential impact of acute SBV infection during mating and early stages of gestation.ConclusionsDue to the lack of available control and prevention measures, SBV spread quickly in the naive ruminant population. France continues to monitor for SBV, and updated information is made available online on a regular basis [http://www.plateforme-esa.fr/]. Outbreaks of congenital SBV are expected to occur sporadically from now on, but further epidemics may also occur if immunity at population level declines.

Simulation-Based Evaluation of the Performances of an Algorithm for Detecting Abnormal Disease-Related Features in Cattle Mortality Records

We performed a simulation study to evaluate the performances of an anomaly detection algorithm considered in the frame of an automated surveillance system of cattle mortality. The method consisted in a combination of temporal regression and spatial cluster detection which allows identifying, for a given week, clusters of spatial units showing an excess of deaths in comparison with their own historical fluctuations. First, we simulated 1,000 outbreaks of a disease causing extra deaths in the French cattle population (about 200,000 herds and 20 million cattle) according to a model mimicking the spreading patterns of an infectious disease and injected these disease-related extra deaths in an authentic mortality dataset, spanning from January 2005 to January 2010. Second, we applied our algorithm on each of the 1,000 semi-synthetic datasets to identify clusters of spatial units showing an excess of deaths considering their own historical fluctuations. Third, we verified if the clusters identified by the algorithm did contain simulated extra deaths in order to evaluate the ability of the algorithm to identify unusual mortality clusters caused by an outbreak. Among the 1,000 simulations, the median duration of simulated outbreaks was 8 weeks, with a median number of 5,627 simulated deaths and 441 infected herds. Within the 12-week trial period, 73% of the simulated outbreaks were detected, with a median timeliness of 1 week, and a mean of 1.4 weeks. The proportion of outbreak weeks flagged by an alarm was 61% (i.e. sensitivity) whereas one in three alarms was a true alarm (i.e. positive predictive value). The performances of the detection algorithm were evaluated for alternative combination of epidemiologic parameters. The results of our study confirmed that in certain conditions automated algorithms could help identifying abnormal cattle mortality increases possibly related to unidentified health events.