Abstract: We examine the emergence, development, and value of regional infectious disease surveillance networks that neighboring countries worldwide are organizing to control cross-border outbreaks at their source. The regional perspective represented in the paper is intended to serve as an instructive framework for others who decide to launch such networks as new technologies and emerging threats bring countries even closer together. Distinct from more formal networks in geographic regions designated by the World Health Organization (WHO), these networks usually involve groupings of fewer countries chosen by national governments to optimize surveillance efforts. Sometimes referred to as sub-regional, these “self-organizing” networks complement national and local government recognition with informal relationships across borders among epidemiologists, scientists, ministry officials, health workers, border officers, and community members. Their development over time reflects both incremental learning and growing connections among network actors; and changing disease patterns, with infectious disease threats shifting over time from local to regional to global levels. Not only has this regional disease surveillance network model expanded across the globe, it has also expanded from a mostly practitioner-based network model to one that covers training, capacity-building, and multidisciplinary research. Today, several of these networks are linked through Connecting Organizations for Regional Disease Surveillance (CORDS). We explore how regional disease surveillance networks add value to global disease detection and response by complementing other systems and efforts, by harnessing their power to achieve other goals such as health and human security, and by helping countries adapt to complex challenges via multi-sectoral solutions. We note that governmental commitment and trust among participating individuals are critical to the success of regional infectious disease surveillance networks.
Abstract: Centrality parameters in animal trade networks typically have right-skewed distributions, implying that these networks are highly resistant against the random removal of holdings, but vulnerable to the targeted removal of the most central holdings. In the present study, we analysed the structural changes of an animal trade network topology based on the targeted removal of holdings using specific centrality parameters in comparison to the random removal of holdings. Three different time periods were analysed: the three-year network, the yearly and the monthly networks. The aim of this study was to identify appropriate measures for the targeted removal, which lead to a rapid fragmentation of the network. Furthermore, the optimal combination of the removal of three holdings regardless of their centrality was identified. The results showed that centrality parameters based on ingoing trade contacts, e.g. in-degree, ingoing infection chain and ingoing closeness, were not suitable for a rapid fragmentation in all three time periods. More efficient was the removal based on parameters considering the outgoing trade contacts. In all networks, a maximum percentage of 7.0% (on average 5.2%) of the holdings had to be removed to reduce the size of the largest component by more than 75%. The smallest difference from the optimal combination for all three time periods was obtained by the removal based on out-degree with on average 1.4% removed holdings, followed by outgoing infection chain and outgoing closeness. The targeted removal using the betweenness centrality differed the most from the optimal combination in comparison to the other parameters which consider the outgoing trade contacts. Due to the pyramidal structure and the directed nature of the pork supply chain the most efficient interruption of the infection chain for all three time periods was obtained by using the targeted removal based on out-degree.
Abstract: The worldwide growth of aquaculture has been accompanied by a rapid increase in therapeutic and prophylactic usage of antimicrobials including those important in human therapeutics. Approximately 80% of antimicrobials used in aquaculture enter the environment with their activity intact where they select for bacteria whose resistance arises from mutations or more importantly, from mobile genetic elements containing multiple resistance determinants transmissible to other bacteria. Such selection alters biodiversity in aquatic environments and the normal flora of fish and shellfish. The commonality of the mobilome (the total of all mobile genetic elements in a genome) between aquatic and terrestrial bacteria together with the presence of residual antimicrobials, biofilms, and high concentrations of bacteriophages where the aquatic environment may also be contaminated with pathogens of human and animal origin can stimulate exchange of genetic information between aquatic and terrestrial bacteria. Several recently found genetic elements and resistance determinants for quinolones, tetracyclines, and β-lactamases are shared between aquatic bacteria, fish pathogens, and human pathogens, and appear to have originated in aquatic bacteria. Excessive use of antimicrobials in aquaculture can thus potentially negatively impact animal and human health as well as the aquatic environment and should be better assessed and regulated.
Abstract: West Nile virus (WNV) and Rift Valley fever virus (RVFV) represent an important group of viral agents responsible for vector-borne zoonotic diseases constituting an emerging sanitary threat for the Mediterranean Basin and the neighbouring countries. WNV infection is present in several Mediterranean countries, whereas RVF has never been introduced into Europe, but it is considered a major threat for North African countries. Being vector-borne diseases, they cannot be prevented only through an animal trade control policy. Several approaches are used for the surveillance of WNV and RVFV. With the aim of assessing the surveillance systems in place in Mediterranean countries, two disease-specific questionnaires (WNV, RVFV) have been prepared and submitted to Public Health and Veterinary Authorities of six EU countries. This study presents the information gathered through the questionnaires and describes some critical points in the prevention and surveillance of these diseases as emerged by the answers received.
Abstract: Systems for animal disease mitigation involve both surveillance activities and interventions to control the disease. They are complex organizations that are described by partial or imprecise data, making it difficult to evaluate them or make decisions to improve them. A mathematical method, called loop analysis, can be used to model qualitatively the structure and the behavior of dynamic systems; it relies on the study of the sign of the interactions between the components of the system. This method, currently widely used by ecologists, has to our knowledge never been applied in the context of animal disease mitigation systems. The objective of the study was to assess whether loop analysis could be applied to this new context. We first developed a generic model that restricted the applicability of the method to event-based surveillance systems of endemic diseases, excluding the emergence and eradication phases. Then we chose the mitigation system of highly pathogenic avian influenza (HPAI) H5N1 in Cambodia as an example of such system to study the application of loop analysis to a real disease mitigation system.
Abstract: The use of models in the life sciences has greatly expanded in scope and advanced in technique in recent decades. However, the range, type and complexity of models used in farm animal welfare is comparatively poor, despite the great scope for use of modeling in this field of research. In this paper, we review the different modeling approaches used in farm animal welfare science to date, discussing the types of questions they have been used to answer, the merits and problems associated with the method, and possible future applications of each technique. We find that the most frequently published types of model used in farm animal welfare are conceptual and assessment models; two types of model that are frequently (though not exclusively) based on expert opinion. Simulation, optimization, scenario, and systems modeling approaches are rarer in animal welfare, despite being commonly used in other related fields. Finally, common issues such as a lack of quantitative data to parameterize models, and model selection and validation are discussed throughout the review, with possible solutions and alternative approaches suggested.
Abstract: Exotic animal diseases (EADs) are characterized by their capacity to spread global distances, causing impacts on animal health and welfare with significant economic consequences. We offer a critique of current import risk analysis approaches employed in the EAD field, focusing on their capacity to assess complex systems at a policy level. To address the shortcomings identified, we propose a novel method providing a systematic analysis of the likelihood of a disease incursion, developed by reference to the multibarrier system employed for the United Kingdom. We apply the network model to a policy-level risk assessment of classical swine fever (CSF), a notifiable animal disease caused by the CSF virus. In doing so, we document and discuss a sequence of analyses that describe system vulnerabilities and reveal the critical control points (CCPs) for intervention, reducing the likelihood of U.K. pig herds being exposed to the CSF virus.
Abstract: Increasing incidences of emerging and re-emerging diseases that are mostly zoonotic (e.g. severe acute respiratory syndrome, avian influenza H5N1, pandemic influenza) has led to the need for a multidisciplinary approach to tackling these threats to public and animal health. Accordingly, a global movement of ‘One-Health/One-Medicine’ has been launched to foster collaborative efforts amongst animal and human health officials and researchers to address these problems. Historical evidence points to the fact that pandemics caused by influenza A viruses remain a major zoonotic threat to mankind. Recently, a range of mathematical and computer simulation modelling methods and tools have increasingly been applied to improve our understanding of disease transmission dynamics, contingency planning and to support policy decisions on disease outbreak management. This review provides an overview of methods, approaches and software used for modelling the spread of zoonotic influenza viruses in animals and humans, particularly those related to the animal-human interface. Modelling parameters used in these studies are summarized to provide references for future work. This review highlights the limited application of modelling research to influenza in animals and at the animal-human interface, in marked contrast to the large volume of its research in human populations. Although swine are widely recognized as a potential host for generating novel influenza viruses, and that some of these viruses, including pandemic influenza A/H1N1 2009, have been shown to be readily transmissible between humans and swine, only one study was found related to the modelling of influenza spread at the swine-human interface. Significant gaps in the knowledge of frequency of novel viral strains evolution in pigs, farm-level natural history of influenza infection, incidences of influenza transmission between farms and between swine and humans are clearly evident. Therefore, there is a need to direct additional research to the study of influenza transmission dynamics in animals and at the animal-human interface.
Abstract: 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.
Abstract: Live animal trade is considered a major mode of introduction of viruses from enzootic foci into disease-free areas. Due to societal and behavioural changes, some wild animal species may nowadays be considered as pet species. The species diversity of animals involved in international trade is thus increasing. This could benefit pathogens that have a broad host range such as arboviruses. The objective of this study was to analyze the risk posed by live animal imports for the introduction, in the European Union (EU), of four arboviruses that affect human and horses: Eastern and Western equine encephalomyelitis, Venezuelan equine encephalitis and Japanese encephalitis. Importation data for a five-years period (2005-2009, extracted from the EU TRACES database), environmental data (used as a proxy for the presence of vectors) and horses and human population density data (impacting the occurrence of clinical cases) were combined to derive spatially explicit risk indicators for virus introduction and for the potential consequences of such introductions. Results showed the existence of hotspots where the introduction risk was the highest in Belgium, in the Netherlands and in the north of Italy. This risk was higher for Eastern equine encephalomyelitis (EEE) than for the three other diseases. It was mainly attributed to exotic pet species such as rodents, reptiles or cage birds, imported in small-sized containments from a wide variety of geographic origins. The increasing species and origin diversity of these animals may have in the future a strong impact on the risk of introduction of arboviruses in the EU.
Abstract: Connecting Organizations for Regional Disease Surveillance (CORDS) is an international non-governmental organization focused on information exchange between disease surveillance networks in different areas of the world. By linking regional disease surveillance networks, CORDS builds a trust-based social fabric of experts who share best practices, surveillance tools and strategies, training courses, and innovations. CORDS exemplifies the shifting patterns of international collaboration needed to prevent, detect, and counter all types of biological dangers – not just naturally occurring infectious diseases, but also terrorist threats. Representing a network-of-networks approach, the mission of CORDS is to link regional disease surveillance networks to improve global capacity to respond to infectious diseases. CORDS is an informal governance cooperative with six founding regional disease surveillance networks, with plans to expand; it works in complement and cooperatively with the World Health Organization (WHO), the World Organization for Animal Health (OIE), and the Food and Animal Organization of the United Nations (FAO). As described in detail elsewhere in this special issue of Emerging Health Threats, each regional network is an alliance of a small number of neighboring countries working across national borders to tackle emerging infectious diseases that require unified regional efforts. Here we describe the history, culture and commitment of CORDS; and the novel and necessary role that CORDS serves in the existing international infectious disease surveillance framework.
Abstract: Background. Pig keeping is becoming increasingly common across sub-Saharan Africa. Domestic pigs from the Arusha region of northern Tanzania were screened for trypanosomes using PCR-based methods to examine the role of pigs as a reservoir of human and animal trypanosomiasis. Methods. A total of 168 blood samples were obtained from domestic pigs opportunistically sampled across four districts in Tanzania (Babati, Mbulu, Arumeru and Dodoma) during December 2004. A suite of PCR-based methods was used to identify the species and sub-species of trypanosomes including: Internally Transcribed Sequence to identify multiple species; species specific PCR to identify T. brucei s. l. and T. godfreyi and a multiplex PCR reaction to distinguish T. b. rhodesiense from T. brucei s. l. Results. Of the 168 domestic pigs screened for animal and human infective trypanosome DNA, 28 (16.7%) were infected with one or more species of trypanosome; these included: six pigs infected with Trypanosoma vivax (3.6%); three with Trypanosoma simiae (1.8%); two with Trypanosoma congolense (Forest) (1%) and four with Trypanosoma godfreyi (2.4%). Nineteen pigs were infected with Trypanosoma brucei s. l. (10.1%) of which eight were identified as carrying the human infective sub-species Trypanosoma brucei rhodesiense (4.8%). Conclusion. These results show that in Tanzania domestic pigs may act as a significant reservoir for animal trypanosomiasis including the cattle pathogens T. vivax and T. congolense, the pig pathogen T. simiae, and provide a significant reservoir for T. b. rhodesiense, the causative agent of acute Rhodesian sleeping sickness.
Abstract: The information provided by animal-health surveillance helps to reduce the impact of animal diseases. The widespread movement of animals and their products around the world results in an increasing risk that disease will spread. There is, therefore, a need for exchange between countries of comparable information about disease incidence; the exchange must be based on a common understanding of surveillance approaches and how surveillance systems are designed and implemented. Establishing agreed-upon definitions of surveillance terms would be a first step in achieving this standardisation, and will enhance transparency and confidence. To this end, a workshop was held with the aim of agreeing upon key terms and concepts for animal-health surveillance. In this paper, we describe the methods used at the workshop and summarise the discussions. A complete list of all the proposed definitions including lists of characteristics that can be used to describe surveillance activities and attributes for evaluation of surveillance is available in the workshop report (available at http://www.defra.gov.uk/ahvla-en/disease-control/surveillance/icahs-workshop/). Some important issues were highlighted during these discussions; of particular note was the importance of economic efficiency as an evaluation attribute. Some remaining inconsistencies in the proposed use of terms are highlighted (including the definition of ‘risk-based surveillance’ and the use of the term ‘event-based surveillance’).
- Kshirsagar DP, Savalia CV, Kalyani IH, Kumar R, Nayak DN. Disease alerts and forecasting of zoonotic diseases: An overview. Veterinary World. 6(11):889–896.
Abstract: Epidemiologists are adopting new techniques by the use of Geographical Information System (GIS) to study a variety of animal and zoonotic diseases. Associations between satellite-derived environmental variables such as temperature, humidity, land cover type and vector density is used for disease prediction. Early warning systems rapidly detect the introduction or sudden increase in incidence of any disease of livestock which has the potential to develop into epidemic proportions and/or cause serious socioeconomic consequences or public health concerns. Early warning activities, mainly based on disease surveillance, reporting, and epidemiological analysis, are supported by information systems that enable integration, analysis and sharing of animal health data combined with relevant layers of information such as socioeconomic, production and climatic data. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced epidemiological data, collaboration between scientists, biologists and the availability of sophisticated, statistical GIS creates a fertile research environment. In this paper, we review the Global Early Warning System (GLEWS) that formally brings together human and veterinary public health systems and application of environmental data for study of diseases like avian influenza and Rift valley fever which offers the capability to demonstrate vector-environment relationships and potentially forecast the risk of disease outbreaks or epidemics. An emphasis is also given on components of early warning system and its use for forecasting of animal and zoonotic diseases in India.
- National association of state public health veterinarians animal contact compendium committee 2013. Compendium of measures to prevent disease associated with animals in public settings, 2013. Journal of the American Veterinary Medical Association. 2013;243(9):1270–1288.
- Oidtmann B, Peeler E, Lyngstad T, Brun E, Bang Jensen B, Stärk KDC. Risk-based methods for fish and terrestrial animal disease surveillance. Preventive Veterinary Medicine. 2013;112(1–2):13–26. doi:10.1016/j.prevetmed.2013.07.008.
Abstract: Over recent years there have been considerable methodological developments in the field of animal disease surveillance. The principles of risk analysis were conceptually applied to surveillance in order to further develop approaches and tools (scenario tree modelling) to design risk-based surveillance (RBS) programmes. In the terrestrial animal context, examples of risk-based surveillance have demonstrated the substantial potential for cost saving, and a similar benefit is expected also for aquatic animals. RBS approaches are currently largely absent for aquatic animal diseases. A major constraint in developing RBS designs in the aquatic context is the lack of published data to assist in the design of RBS: this applies to data on (i) the relative risk of farm sites becoming infected due to the presence or absence of a given risk factor; (ii) the sensitivity of diagnostic tests (specificity is often addressed by follow-up investigation and re-testing and therefore less of a concern); (iii) data on the variability of prevalence of infection for fish within a holding unit, between holding units and at farm level. Another constraint is that some of the most basic data for planning surveillance are missing, e.g. data on farm location and animal movements. In Europe, registration or authorisation of fish farms has only recently become a requirement under EU Directive 2006/88. Additionally, the definition of the epidemiological unit (at site or area level) in the context of aquaculture is a challenge due to the often high level of connectedness (mainly via water) of aquaculture facilities with the aquatic environment. This paper provides a review of the principles, methods and examples of RBS in terrestrial, farmed and wild animals. It discusses the special challenges associated with surveillance for aquatic animal diseases (e.g. accessibility of animals for inspection and sampling, complexity of rearing systems) and provides an overview of current developments relevant for the design of RBS for fish diseases. Suggestions are provided on how the current constraints to applying RBS to fish diseases can be overcome.
Abstract: This is a retrospective study of the outbreaks of foot-and-mouth disease (FMD) in Peninsular Malaysia between 2001 and May 2007. In total, 270 outbreaks of FMD were recorded. Serotype O virus (89.95 %) and serotype A (7.7 %) had caused the outbreaks. Significant differences on the occurrence of FMD were found between the years (t = 5.73, P = 0.000, df = 11), months (t = 4.7, P = 0.000, df = 11), monsoon season (t = 2.63, P = 0.025, df = 10) and states (t = 4.84, P = 0.001, df = 10). A peak of outbreaks observed in 2003 could be due to increased animal movement and the other peak in 2006 could be due to a compromised FMD control activities due to activities on the eradication of highly pathogenic avian influenza. Cattle (86 % of outbreaks) suffered the most. However, no difference in disease occurrence between species was observed. The populations of cattle (r = 0.672, P = 0.023) and sheep (r = 0.678, P = 0.022) were significantly correlated with occurrence of FMD. Movement of animals (66 % of outbreaks) was the main source for outbreaks. A combination of control measures were implemented during outbreaks. In conclusion, the findings of this study show that FMD is endemic in Peninsular Malaysia, and information gained could be used to improve the existing control strategy.
Abstract: Aim: A study was undertaken to develop a forecasting model for predicting bluetongue outbreaks in North-west agroclimatic zone of Tamil Nadu, India. Materials and Methods: Eleven bluetongue outbreaks were characterised by active and passive surveillances for a period of twelve years and used in this study. Meteorological data comprising of maximum and minimum temperatures, relative humidity, rainfall and wind speed were collected and used as the multiple predictor variables in the multiple liner regression model. Results: A multiple liner regression model was developed for the North-west zone of Tamil Nadu. Values of the dependant variables were less than or greater than one, and indicated remote or greater chances of bluetongue outbreaks respectively. The monthly mean maximum and minimum temperatures, relative humidity at 8.30 h and at 17.00 h IST, wind speed, and monthly total rainfall of 29.1 – 31.0°C, 20.1 – 22.0°C, 80.1 – 85.0%, 65.1 – 70.0%, 3.1 – 5.0 km/h and < 200 mm respectively, were identified as the ideal climatic conditions for increased numbers of bluetongue outbreaks in this zone. Conclusion: Based on the values obtained from the prediction model, stake holders can be warned timely through the media to institute suitable prophylactic measures against bluetongue, to avoid economic losses due to disease.
Abstract: This article focuses on social media and interactive challenges for emergency organizations during a bioterrorism or agroterrorism incident, and it outlines the dual-use dilemma of social media. Attackers or terrorists can use social media as their modus operandi, and defenders, including emergency organizations in law enforcement and public and animal health, can use it for peaceful purposes. To get a better understanding of the uses of social media in these situations, a workshop was arranged in Stockholm, Sweden, to raise awareness about social media and animal bioterrorism threats. Fifty-six experts and crisis communicators from international and national organizations participated. As a result of the workshop, it was concluded that emergency organizations can collect valuable information and monitor social media before, during, and after an outbreak. In order to make use of interactive communication to obtain collective intelligence from the public, emergency organizations must adapt to social networking technologies, requiring multidisciplinary knowledge in the fields of information, communication, IT, and biopreparedness. Social network messaging during a disease outbreak can be visualized in stream graphs and networks showing clusters of Twitter and Facebook users. The visualization of social media can be an important preparedness tool in the response to bioterrorism and agroterrorism.
Abstract: Background. The aim of this study was to assess the sensitivity of the four major bluetongue surveillance components implemented in Belgium in 2007 for farmed animals and prescribed by the European Union regulation; winter serological screening, sentinel system, passive clinical surveillance, export testing. Scenario tree methodology was used to evaluate the relative sensitivity of detection and targeted approach of each component in terms of early detection and freedom of infection substantiation. Field data collected from the previous year’s outbreaks in Belgium were used to determine the risk groups to be considered. Results. The best sensitivities at herd level, taking into account the diagnostic test sensitivity, design prevalence and the number of animals tested within a herd were obtained with the winter screening and sentinel component. The sensitivities at risk group level, taking into account the obtained herd sensitivity, effective probabilities of infection and number of herds tested were high in all components, except for the export component. Component sensitivities ranged between 0.77 and 1 for all components except for the export component with a mean value of 0.22 (0.17–0.26). In terms of early detection, the probability of detection was best using the passive clinical component or the sentinel component. Sensitivity analysis showed that the passive clinical component sensitivity was mostly affected by the diagnostic process and the number of herds sampled. The sentinel and export components sensitivity were mainly affected by the relative risk estimates whereas the winter screening component was mainly affected by the assumptions about the design prevalence. Conclusions. This study revealed interesting features regarding the sensitivity of detection and early detection of infection in the different surveillance components and their risk based approach as requested by the international standards.
Abstract: Bluetongue (BT) is a vector-borne viral disease of ruminants. The infection is widespread globally with major implications for international animal trade and production. In 2006, BT virus serotype 8 (BTV-8) was encountered in Europe for the first time, causing extensive production losses and death in susceptible livestock. Following the appearance of BTV-8 in Switzerland in 2007, a compulsory vaccination programme was launched in the subsequent year. Due to social factors and difficulties to reach animals on high pasture, the regional vaccination coverage varied across the country in both 2008 and 2009. In this study, the effect of vaccination on the spatial occurrence of BTV-8 and the associated relative disease risk in Switzerland in 2008 and 2009 were investigated by a spatial Bayesian hierarchical approach. Bayesian posterior distributions were obtained by integrated nested Laplace approximations, a promising alternative to commonly used Markov chain Monte Carlo methods. The number of observed BTV-8 outbreaks in Switzerland decreased notably from 2008 to 2009. However, only a non-significant association between vaccination coverage and the probability of a spatial unit being infected with BTV-8 was identified using the model developed for this study. The relative disease risk varied significantly across the country, with a higher relative risk of BTV-8 infection in western and north-western Switzerland where environmental conditions are more suitable for vector presence and viral transmission. Examination of the spatial correlation between disease occurrence, control measures and associated ecological factors can be valuable in the evaluation and development of disease control programmes, allowing prioritisation of areas with a high relative risk of disease.
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