Designing a Syndromic Bovine Mortality Surveillance System: Lessons Learned From the 1-Year Test of the French OMAR Alert Tool.

Between May 2018 and 2019, a syndromic bovine mortality surveillance system (OMAR) was tested in 10 volunteer French départements (French intermediate-level administrative unit) to assess its performance in real conditions, as well as the human and financial resources needed to ensure normal functioning. The system is based on the automated weekly analysis of the number of cattle deaths reported by renderers in the Fallen Stock Data Interchange Database established in January 2011. In our system, every Thursday, the number of deaths is grouped by ISO week and small surveillance areas and then analyzed using traditional time-series analysis steps (cleaning, prediction, signal detection). For each of the five detection algorithms implemented (i.e., the exponentially weighted moving average chart, cumulative sum chart, Shewhart chart, Holt-Winters, and historical limits algorithms), seven detection limits are applied, giving a signal score from 1 (low excess mortality) to 7 (high excess mortality). The severity of excess mortality (alarm) is then classified into four categories, from very low to very high, by combining the signal scores, the relative excess mortality, and the persistence of the signal(s) over the previous 4 weeks. Detailed and interactive weekly reports and a short online questionnaire help pilot départements and the OMAR central coordination cell assess the performance of the system. During the 1-year test, the system showed highly variable sensitivity among départements. This variability was partly due not only to the demographic distribution of cattle (very few signals in low-density areas) but also to the renderer's delay in reporting to the Fallen Stock Data Interchange Database (on average, only 40% of the number of real deaths had been transmitted within week, with huge variations among départements). As a result, in the pilot départements, very few alarms required on-farm investigation and excess mortality often involved a small number of farms already known to have health or welfare problems. Despite its perfectibility, the system nevertheless proved useful in the daily work of animal health professionals for collective and individual surveillance. The test is still ongoing for a second year in nine départements to evaluate the effectiveness of the improvements agreed upon at the final meeting.

Impact of heat and cold waves on female cattle mortality beyond the effect of extreme temperatures.

Although heat and cold temperatures are known to have an impact on cattle mortality, no study has evidenced and quantified the influence of the prolonged exposure to extreme temperatures beyond the single effect of daily temperatures. We defined a heat (or cold) wave by a continuous variable indicating the number of successive days with temperatures above (or below) a given threshold. For heat wave, the threshold was set to the 95th or 99th percentile of the mean daily temperature distribution and for cold wave to the 1st or 5th percentile. We collected female cattle mortality data by type of production and age classes between 2001 and 2015 for 100 iso-hygro-thermal areas in France. We used time-series analyses to estimate the area-specific heat wave- and cold wave-mortality relationships. Then, we applied meta-analyses to pool area-specific effects at the country level for each definition of heat and cold wave. For each type of production and age classes, our models predicted symmetrical relationships between temperature and mortality, with a temperature range of minimum mortality located approximately between 15 and 20 °CTHI in most categories. Outside that range, relative risks between 1.3 and 2.5 were estimated for extreme cold temperatures and relative risks between 1.1 and 1.5 were estimated for extreme hot temperatures depending on age categories and production type. Our results indicated that a prolonged exposure to high (or low) temperatures caused a significant increase on mortality (up to 40% during heat waves and 23% for cold waves, depending on type of production and age classes), in addition to the effect of extreme temperature alone. This additional mortality risk increased along with the duration and intensity of the exposure. Our results suggest that not discriminating the effect of the prolonged exposure to extreme temperature, may overestimate the effect of temperature alone on mortality.

Quantifying the influence of ambient temperature on dairy and beef cattle mortality in France from a time-series analysis.

In the context of climate change, the frequency and severity of extreme weather events are expected to increase in temperate regions, and potentially have a severe impact on farmed cattle through production losses or deaths. In this study, we used distributed lag non-linear models to describe and quantify the relationship between a temperature-humidity index (THI) and cattle mortality in 12 areas in France. THI incorporates the effects of both temperature and relative humidity and was already used to quantify the degree of heat stress on dairy cattle because it does reflect physical stress deriving from extreme conditions better than air temperature alone. Relationships between daily THI and mortality were modeled separately for dairy and beef cattle during the 2003-2006 period. Our general approach was to first determine the shape of the THI-mortality relationship in each area by modeling THI with natural cubic splines. We then modeled each relationship assuming a three-piecewise linear function, to estimate the critical cold and heat THI thresholds, for each area, delimiting the thermoneutral zone (i.e. where the risk of death is at its minimum), and the cold and heat effects below and above these thresholds, respectively. Area-specific estimates of the cold or heat effects were then combined in a hierarchical Bayesian model to compute the pooled effects of THI increase or decrease on dairy and beef cattle mortality. A U-shaped relationship, indicating a mortality increase below the cold threshold and above the heat threshold was found in most of the study areas for dairy and beef cattle. The pooled estimate of the mortality risk associated with a 1°C decrease in THI below the cold threshold was 5.0% for dairy cattle [95% posterior interval: 4.4, 5.5] and 4.4% for beef cattle [2.0, 6.5]. The pooled mortality risk associated with a 1°C increase above the hot threshold was estimated to be 5.6% [5.0, 6.2] for dairy and 4.6% [0.9, 8.7] for beef cattle. Knowing the thermoneutral zone and temperature effects outside this zone is of primary interest for farmers because it can help determine when to implement appropriate preventive and mitigation measures.

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.

Defining syndromes using cattle meat inspection data for syndromic surveillance purposes: a statistical approach with the 2005-2010 data from ten French slaughterhouses.

BACKGROUND: The slaughterhouse is a central processing point for food animals and thus a source of both demographic data (age, breed, sex) and health-related data (reason for condemnation and condemned portions) that are not available through other sources. Using these data for syndromic surveillance is therefore tempting. However many possible reasons for condemnation and condemned portions exist, making the definition of relevant syndromes challenging.The objective of this study was to determine a typology of cattle with at least one portion of the carcass condemned in order to define syndromes. Multiple factor analysis (MFA) in combination with clustering methods was performed using both health-related data and demographic data. RESULTS: Analyses were performed on 381,186 cattle with at least one portion of the carcass condemned among the 1,937,917 cattle slaughtered in ten French abattoirs. Results of the MFA and clustering methods led to 12 clusters considered as stable according to year of slaughter and slaughterhouse. One cluster was specific to a disease of public health importance (cysticercosis). Two clusters were linked to the slaughtering process (fecal contamination of heart or lungs and deterioration lesions). Two clusters respectively characterized by chronic liver lesions and chronic peritonitis could be linked to diseases of economic importance to farmers. Three clusters could be linked respectively to reticulo-pericarditis, fatty liver syndrome and farmer's lung syndrome, which are related to both diseases of economic importance to farmers and herd management issues. Three clusters respectively characterized by arthritis, myopathy and Dark Firm Dry (DFD) meat could notably be linked to animal welfare issues. Finally, one cluster, characterized by bronchopneumonia, could be linked to both animal health and herd management issues. CONCLUSION: The statistical approach of combining multiple factor analysis with cluster analysis showed its relevance for the detection of syndromes using available large and complex slaughterhouse data. The advantages of this statistical approach are to i) define groups of reasons for condemnation based on meat inspection data, ii) help grouping reasons for condemnation among a list of various possible reasons for condemnation for which a consensus among experts could be difficult to reach, iii) assign each animal to a single syndrome which allows the detection of changes in trends of syndromes to detect unusual patterns in known diseases and emergence of new diseases.

Assessing the mandatory bovine abortion notification system in France using unilist capture-recapture approach.

The mandatory bovine abortion notification system in France aims to detect as soon as possible any resurgence of bovine brucellosis. However, under-reporting seems to be a major limitation of this system. We used a unilist capture-recapture approach to assess the sensitivity, i.e. the proportion of farmers who reported at least one abortion among those who detected such events, and representativeness of the system during 2006-2011. We implemented a zero-inflated Poisson model to estimate the proportion of farmers who detected at least one abortion, and among them, the proportion of farmers not reporting. We also applied a hurdle model to evaluate the effect of factors influencing the notification process. We found that the overall surveillance sensitivity was about 34%, and was higher in beef than dairy cattle farms. The observed increase in the proportion of notifying farmers from 2007 to 2009 resulted from an increase in the surveillance sensitivity in 2007/2008 and an increase in the proportion of farmers who detected at least one abortion in 2008/2009. These patterns suggest a raise in farmers' awareness in 2007/2008 when the Bluetongue Virus (BTV) was detected in France, followed by an increase in the number of abortions in 2008/2009 as BTV spread across the country. Our study indicated a lack of sensitivity of the mandatory bovine abortion notification system, raising concerns about the ability to detect brucellosis outbreaks early. With the increasing need to survey the zoonotic Rift Valley Fever and Q fever diseases that may also cause bovine abortions, our approach is of primary interest for animal health stakeholders to develop information programs to increase abortion notifications. Our framework combining hurdle and ZIP models may also be applied to estimate the completeness of other clinical surveillance systems.

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.