Animal Health Syndromic Surveillance Research Articles

Using farmer observations for animal health syndromic surveillance: Participation and performance of an online enhanced passive surveillance system

The challenge of animal health surveillance is to provide the information necessary to appropriately inform disease prevention and control activities within the constraints of available resources. Syndromic surveillance of farmers’ disease observations can improve animal health data capture from extensive livestock farming systems, especially where data are not otherwise being systematically collected or when data on confirmed aetiological diagnoses are unavailable at the disease level. As it is rarely feasible to recruit a truly random sample of farmers to provide observational reports, directing farmer sampling to align with the surveillance objectives is a reasonable and practical approach. As long as potential bias is recognised and managed, farmers who will report reliably can be desirable participants in a surveillance system. Thus, one early objective of a surveillance program should be to identify characteristics associated with reporting behaviour. Knowledge of the demographic and managerial characteristics of good reporters can inform efforts to recruit additional farms into the system or aid understanding of potential bias of system reports.We describe the operation of a farmer syndromic surveillance system in Victoria, Australia, over its first two years from 2014 to 2016. Survival analysis and classification and regression tree analysis were used to identify farm level factors associated with ‘reliable’ participation (low non-response rates in longitudinal reporting). Response rate and timeliness were not associated with whether farmers had disease to report, or with different months of the year. Farmers keeping only sheep were the most reliable and timely respondents. Farmers < 43 years of age had lower response rates than older farmers. Farmers with veterinary qualifications and those working full-time on-farm provided less timely reports than other educational backgrounds and farmers who worked part-time on-farm. These analyses provide a starting point to guide recruitment of participants for surveillance of farmers’ observations using syndromic surveillance, and provide examples of strengths and weaknesses of syndromic surveillance systems for extensively-managed livestock. Once farm characteristics associated with reliable participation are known, they can be incorporated into surveillance system design in accordance with the objectives of the system.

Enhancing the monitoring of fallen stock at different hierarchical administrative levels: an illustration on dairy cattle from regions with distinct husbandry, demographical and climate traits

BackgroundThe automated collection of non-specific data from livestock, combined with techniques for data mining and time series analyses, facilitates the development of animal health syndromic surveillance (AHSyS). An example of AHSyS approach relates to the monitoring of bovine fallen stock. In order to enhance part of the machinery of a complete syndromic surveillance system, the present work developed a novel approach for modelling in near real time multiple mortality patterns at different hierarchical administrative levels. To illustrate its functionality, this system was applied to mortality data in dairy cattle collected across two Spanish regions with distinct demographical, husbandry, and climate conditions.ResultsThe process analyzed the patterns of weekly counts of fallen dairy cattle at different hierarchical administrative levels across two regions between Jan-2006 and Dec-2013 and predicted their respective expected counts between Jan-2014 and Jun- 2015. By comparing predicted to observed data, those counts of fallen dairy cattle that exceeded the upper limits of a conventional 95% predicted interval were identified as mortality peaks. This work proposes a dynamic system that combines hierarchical time series and autoregressive integrated moving average models (ARIMA). These ARIMA models also include trend and seasonality for describing profiles of weekly mortality and detecting aberrations at the region, province, and county levels (spatial aggregations). Software that fitted the model parameters was built using the R statistical packages.ConclusionsThe work builds a novel tool to monitor fallen stock data for different geographical aggregations and can serve as a means of generating early warning signals of a health problem. This approach can be adapted to other types of animal health data that share similar hierarchical structures.

Dog health and demographic surveillance survey in Western Kenya: Demography and management practices relevant for rabies transmission and control

Background: Domestic dogs transmit 99% of the estimated 59,000 human rabies deaths occurring globally annually. To achieve the global target of zero human deaths from rabies by 2030, effective mass dog vaccination campaigns that break rabies transmission cycles in dog populations are required. This study describes the design of a dog health and demographic surveillance study established within a human health and demographic surveillance study in Western Kenya. Using baseline data from the dog cohort study, we quantify demographic parameters and describe management practices relevant for rabies transmission. Methods: All dogs in 1213 households participating in a linked human and animal health syndromic surveillance study were recruited. Data on household demographics, dog ownership, dog age and sex ratios, reproductive indices, rabies vaccination, management practices, dog movement and health status were collected at least monthly. Results: 460 of 1213 (38%) of the study households owned dogs (mean 2 dogs/household), and 526 (70%) of those without dogs had owned dogs previously. 802 dogs were recruited into the study, more than half (52%) of those with known ages were ≤ 1 year old. The dog:human ratio in the study population was 1:7, the dog density 54 dogs/km2, and the female: male dog sex ratio was 1:1.3. Rabies vaccination was low (5% coverage), and only 48 (12%) male dogs and 13 (5%) female dogs were castrated and spayed, respectively. Dogs were predominantly local breed (99%), mainly kept for security purposes, almost always (97%) left to scavenge for leftovers and 61% roamed freely. Conclusion: Low vaccination coverage, unrestricted dog movement, and high dog population turnover with a large proportion of dogs below one-year-old support endemic rabies circulation in this population. These gaps present opportunities for the design of effective dog rabies control plans to break rabies transmission cycles in this part of Kenya.

Animal health syndromic surveillance: a systematic literature review of the progress in the last 5 years (2011-2016).

This review presents the current initiatives and potential for development in the field of animal health surveillance (AHSyS), 5 years on from its advent to the front of the veterinary public health scene. A systematic review approach was used to document the ongoing AHSyS initiatives (active systems and those in pilot phase) and recent methodological developments. Clinical data from practitioners and laboratory data remain the main data sources for AHSyS. However, although not currently integrated into prospectively running initiatives, production data, mortality data, abattoir data, and new media sources (such as Internet searches) have been the objective of an increasing number of publications seeking to develop and validate new AHSyS indicators. Some limitations inherent to AHSyS such as reporting sustainability and the lack of classification standards continue to hinder the development of automated syndromic analysis and interpretation. In an era of ubiquitous electronic collection of animal health data, surveillance experts are increasingly interested in running multivariate systems (which concurrently monitor several data streams) as they are inferentially more accurate than univariate systems. Thus, Bayesian methodologies, which are much more apt to discover the interplay among multiple syndromic data sources, are foreseen to play a big part in the future of AHSyS. It has become clear that early detection of outbreaks may not be the principal expected benefit of AHSyS. As more systems will enter an active prospective phase, following the intensive development stage of the last 5 years, the study envisions AHSyS, in particular for livestock, to significantly contribute to future international-, national-, and local-level animal health intelligence, going beyond the detection and monitoring of disease events by contributing solid situation awareness of animal welfare and health at various stages along the food-producing chain, and an understanding of the risk management involving actors in this value chain.

A practical approach to designing syndromic surveillance systems for livestock and poultry

The field of animal syndromic surveillance (SyS) is growing, with many systems being developed worldwide. Now is an appropriate time to share ideas and lessons learned from early SyS design and implementation. Based on our practical experience in animal health SyS, with additions from the public health and animal health SyS literature, we put forward for discussion a 6-step approach to designing SyS systems for livestock and poultry.The first step is to formalise policy and surveillance goals which are considerate of stakeholder expectations and reflect priority issues (1). Next, it is important to find consensus on national priority diseases and identify current surveillance gaps. The geographic, demographic, and temporal coverage of the system must be carefully assessed (2). A minimum dataset for SyS that includes the essential data to achieve all surveillance objectives while minimizing the amount of data collected should be defined. One can then compile an inventory of the data sources available and evaluate each using the criteria developed (3). A list of syndromes should then be produced for all data sources. Cases can be classified into syndrome classes and the data can be converted into time series (4). Based on the characteristics of the syndrome-time series, the length of historic data available and the type of outbreaks the system must detect, different aberration detection algorithms can be tested (5). Finally, it is essential to develop a minimally acceptable response protocol for each statistical signal produced (6).Important outcomes of this pre-operational phase should be building of a national network of experts and collective action and evaluation plans. While some of the more applied steps (4 and 5) are currently receiving consideration, more emphasis should be put on earlier conceptual steps by decision makers and surveillance developers (1–3).

Factors associated with offal, partial and whole carcass condemnation in ten French cattle slaughterhouses

The proportion of cattle with offal, partial or whole carcass condemnation could be a useful indicator for animal health syndromic surveillance purposes. It requires first highlighting the factors associated with condemnation in order to include them in a modeling process. This study aims to identify and quantify these factors. It was based on data from ten French cattle slaughterhouses from 2006 to 2010 (n=1,439,868 cattle). Multivariable multinomial logistic regression analyses were performed. Sex, age and slaughterhouse were the main effects for offal, partial and whole carcass condemnation and have to be taken into account when implementing syndromic surveillance systems based on meat inspection data. The presence of an error in cattle identification was identified as a potential indicator for a higher risk of condemnation and should be explored as a potential factor for risk-based meat inspection.

Syndromic surveillance in Europe: current situation in human and animal health and possible synergies

Background The Triple-S project (Syndromic Surveillance (SyS) Systems in Europe), co-financed by the European Commission, was launched in September 2010 for a three year period. This study presents and discusses the results of the Triple-S inventory of the European animal and human health SyS systems or initiatives as well as the advantages of synergies between human and animal health SyS. Methods European SyS systems were identified …

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.

Synergies Between Human and Animal Health Syndromic Surveillance: Triple-S Outputs

Existing synergies between human and animal health syndromic surveillance (SyS) in Europe and proposal to enhance this collaboration are presented based on the outputs of the European Triple-S project. For the time being, collaborations are limited to regular meetings to discuss outputs of the human and animal health systems. Two reasons for enhancing synergies were highlighted. First, experts on both sides face common statistical and epidemiological issues when dealing with SyS and could thus share their experiences. Second, animal and human SyS systems can target similar health threats. Triple-S guidelines for implementation of SyS systems will aim at promoting synergy.