The One Health approach calls for collaboration across various sectors and different scales to improve understanding of complex health issues. Regarding epidemiological surveillance, this implies the development of integrated systems that link several surveillance components operating in different domains (human, domestic animals, environment) and involving several actor networks. However, surveillance continues to operate in a very compartmentalized way, with little interaction between sectoral institutions and with the community for the governance and operation of surveillance activities. This is partly explained by the insufficient consideration of the local context and the late involvement of national stakeholders when developing programmes that aimed at strengthening the integration of surveillance. In low- and middle-income countries in particular, there is a strong influence of external partners on the development of intersectoral programmes, including surveillance systems. In this context, we developed and implemented a participatory planning process to support stakeholders of the surveillance system of anthrax in Burkina Faso, in the definition of the One Health surveillance system they wish for and of the pathway to reach it. The workshop produced an action plan that reflects the views and perspectives of representatives of the different categories of stakeholders and beneficiaries of surveillance. In addition, the participation of stakeholders in this participatory co-construction process has also improved their knowledge and mutual understanding, fostering a climate of trust conducive to further collaboration for surveillance activities. However, the quality of the participation raises some questions over the results, and contextual factors may have influenced the process. This underlines the need to include a monitoring and evaluation plan in the process to assess its implementation and ability to produce One Health surveillance modalities that are appropriate, accepted and applied over the long term.

Background Anthrax is a zoonotic disease that causes frequent outbreaks in livestock and fatal human cases in Burkina Faso. Effective surveillance of this disease calls for the establishment of an integrated surveillance system, in line with the One Health concept. However, despite a strong technical and financial support from international partners, surveillance is still poorly conducted within an integrated approach. Based on stakeholder perspectives, the study has for objective to deepen our understanding of the anthrax surveillance system and to identify the obstacles and levers towards a more integrated approach to anthrax surveillance in Burkina Faso. Methods The data was collected from a literature review and interviews with surveillance stakeholders. We first conducted a qualitative descriptive analysis of the data to characterize the surveillance system (programmes, actors, collaboration). In a second step, we conducted a thematic analysis of the informants' discourse in order to identify what represents an obstacle or, conversely, a lever for a more integrated approach to anthrax surveillance. Results The surveillance system of anthrax in Burkina Faso includes three programmes (in the livestock, wildlife and human sectors), which involves 30 actors. These sectoral programmes operate almost independently from one another, although some collaborations are existing for the governance and implementation of surveillance activities. Analysis of the discourse of key stakeholders led to the identification of four categories of factors that may influence the implementation of an integrated surveillance system in the country: knowledge; technical, organizational and social capacities; motivation; intersectoral governance. Conclusions This study highlights the difficulty of translating One Health governance to the national level and the need to better articulate the visions of all categories of stakeholders. This study also reveals the need to develop specific evaluation systems for integrated policies in order to provide credible evidence of their added value for a better management of zoonotic diseases. Finally, our study underlines the need to act upstream the emergence of zoonoses and allocate more resources to the prevention of zoonoses than to their control.

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

This article presents a participative and iterative qualitative risk assessment framework that can be used to evaluate the spatial variation of the risk of infectious animal disease introduction and spread on a national scale. The framework was developed through regional training action workshops and field activities. The active involvement of national animal health services enabled the identification, collection and hierarchization of risk factors. Quantitative data were collected in the field, and expert knowledge was integrated to adjust the available data at regional level. Experts categorized and combined the risk factors into ordinal levels of risk per epidemiological unit to ease implementation of risk-based surveillance in the field. The framework was used to perform a qualitative assessment of the risk of introduction and spread of foot-and-mouth disease (FMD) in Tunisia as part of a series of workshops held between 2015 and 2018. The experts in attendance combined risk factors such as epidemiological status, transboundary movements, proximity to the borders and accessibility to assess the risk of FMD outbreaks in Tunisia. Out of the 2,075 Tunisian imadas, 23 were at a very high risk of FMD introduction, mainly at the borders; and 59 were at a very high risk of FMD spread. To validate the model, the results were compared to the FMD outbreaks notified by Tunisia during the 2014 FMD epizootic. Using a spatial Poisson model, a significant alignment between the very high and high-risk categories of spread and the occurrence of FMD outbreaks was shown. The relative risk of FMD occurrence was thus 3.2 higher for imadas in the very high and high spread risk categories than for imadas in the low and negligible spread risk categories. Our results show that the qualitative risk assessment framework can be a useful decision support tool for risk-based disease surveillance and control, in particular in scarce-data environments.

Rift Valley fever (RVF) has been reported in the sub-Saharan region of Africa, Egypt and Arabian Peninsula Yemen and Saudi Arabia, over the past 20 years and is a threat to both the animal and human populations in Tunisia. Tunisia is considered as a high-risk country for the introduction of RVF due to the informal movements of diseased animals already reported in the neighboring countries. The objective of this study was to assess the status of RVF in small ruminants and camels in Tunisia. A risk-based serological survey was conducted to evaluate the presence of RVF based on spatial qualitative risk analysis (SQRA). Samples were collected from small ruminants (sheep and goats) (n = 1,114), and camels (n = 173) samples, belonging to 18 breeders in 14 governorates between November 2017 and January 2018. Samples were tested using an RVF specific multispecies competitive ELISA. Out of the 1,287 samples tested for the presence of RVF IgG antibodies by ELISA, only one positive sample 0.07% (1/1 287) was detected but not confirmed with the virus neutralization test (VNT) used for confirmation. So far, no RVF outbreaks have been reported in Tunisia and our study confirmed the absence of RVF in livestock up to January 2018. Further investigations are needed to confirm the RVF-free status of Tunisia today.

The international community and governmental organizations are actively calling for the implementation of One Health (OH) surveillance systems to target health hazards that involve humans, animals, and their environment. In our view, the main characteristic of a OH surveillance system is the collaboration across institutions and disciplines operating within the different sectors to plan, coordinate, and implement the surveillance process. However, the multisectoral organizational models and possible collaborative modalities implemented throughout the surveillance process are multi-fold and depend on the objective and context of the surveillance. The purpose of this study is to define a matrix to evaluate the quality and appropriateness of multisectoral collaboration through an in-depth analysis of its organization, implementation, and functions. We developed a first list of evaluation attributes based on (i) the characteristics of the organization, implementation, and functionality of multisectoral surveillance systems; and (ii) the existing attributes for the evaluation of health surveillance systems and OH initiatives. These attributes were submitted to two rounds of expert-opinion elicitation for review and validation. The final list of attributes consisted of 23 organizational attributes and 9 functional attributes, to which 3 organizational indexes were added measuring the overall organization of collaboration. We then defined 75 criteria to evaluate the level of satisfaction for the attributes and indexes. The criteria were scored following a four-tiered scoring grid. Graphical representations allowed for an easy overview of the evaluation results for both attributes and indexes. This evaluation matrix is the first to allow an in-depth analysis of collaboration in a multisectoral surveillance system and is the preliminary step toward the creation of a fully standalone tool for the evaluation of collaboration. After its practical application and adaptability to different contexts are field-tested, this tool could be very useful in identifying the strengths and weaknesses of collaboration occurring in a multisectoral surveillance system.

The French surveillance network for causes of equine mortality (Resumeq) was created in 2015 for the qualitative surveillance of equine mortality through the centralization in a national database of necropsy data and their subsequent epidemiological analysis. It was designed to identify the causes of equine mortality, monitor their evolution over time and space, and detect emerging diseases as early as possible. Resumeq is an event-based surveillance system involving various players and structures. It is organized around a steering body, a scientific and technical support committee and a coordination unit. Different tools have been developed specifically for Resumeq. These include standardized necropsy protocols, a thesaurus for the anatomopathological terms and the causes of equine death, and an interactive web application so that network contributors can display data analysis results. The four French veterinary schools, seventeen veterinary laboratories, and ten veterinary clinics already contribute to the production and centralization of standardized data. To date, the data from around 1,000 equine necropsies have been centralized. While most deaths were located in western France, the geographic coverage is gradually improving. Data analysis allows the main causes of death to be ranked and major threats identified on a local, regional or national level. Initial results demonstrate the feasibility and benefits of this national surveillance tool. Moreover, in the future, this surveillance could take an international dimension if several countries decided to jointly capitalize on their necropsy data.

Summary Unravelling the ecological structure of emerging plant pathogens persisting in multi‐host systems is challenging. In such systems, observations are often heterogeneous with respect to time, space and host species, and may lead to biases of perception. The biased perception of pathogen ecology may be exacerbated by hidden fractions of the whole host population, which may act as infection reservoirs. We designed a mechanistic‐statistical approach to help understand the ecology of emerging pathogens by filtering out some biases of perception. This approach, based on SIR (Susceptible–Infected–Removed) models and a Bayesian framework, disentangles epidemiological and observational processes underlying temporal counting data. We applied our approach to French surveillance data on Xylella fastidiosa, a multi‐host pathogenic bacterium recently discovered in Corsica, France. A model selection led to two diverging scenarios: one scenario without a hidden compartment and an introduction around 2001, and the other with a hidden compartment and an introduction around 1985. Thus, Xylella fastidiosa was probably introduced into Corsica much earlier than its discovery, and its control could be arduous under the hidden compartment scenario. From a methodological perspective, our approach provides insights into the dynamics of emerging plant pathogens and, in particular, the potential existence of infection reservoirs.

Mycobacterium bovis infection was first described in free-ranging wildlife in France in 2001, with subsequent detection in hunter-harvested ungulates and badgers in areas where outbreaks of bovine tuberculosis (TB) were also detected in cattle. Increasing concerns regarding TB in wildlife led the French General Directorate for Food (DGAL) and the main institutions involved in animal health and wildlife management, to establish a national surveillance system for TB in free-ranging wildlife. This surveillance system is known as "Sylvatub." The system coordinates the activities of various national and local partners. The main goal of Sylvatub is to detect and monitor M. bovis infection in wildlife through a combination of passive and active surveillance protocols adapted to the estimated risk level in each area of the country. Event-base surveillance relies on M. bovis identification (molecular detection) (i) in gross lesions detected in hunter-harvested ungulates, (h) in ungulates that are found dead or dying, and (iii) in road-killed badgers. Additional targeted surveillance in badgers, wild boars and red deer is implemented on samples from trapped or hunted animals in at-risk areas. With the exception of one unexplained case in a wild boar, M. bovis infection in free-living wildlife has always been detected in the vicinity of cattle TB outbreaks with the same genotype of the infectious M. bovis strains. Since 2012, M. bovis was actively monitored in these infected areas and detected mainly in badgers and wild boars with apparent infection rates of 4.57-5.14% and 2.37-3.04%, respectively depending of the diagnostic test used (culture or PCR), the period and according to areas. Sporadic infection has also been detected in red deer and roe deer. This surveillance has demonstrated that M. bovis infection, in different areas of France, involves a multi-host system including cattle and wildlife. However, infection rates are lower than those observed in badgers in the United Kingdom or in wild boars in Spain.

Bovine tuberculosis (bTB) is a common disease of cattle and wildlife, with economic repercussions and implications for animal and human health. The surveillance of bTB in wildlife is particularly important, to shed light on the epidemiological role of wild species and for the adaptation of control measures. In France, a bTB surveillance system for free-ranging wildlife, the Sylvatub system, was launched in 2011 on wild boars, red deer, roe deer and badgers. It relies on active and passive surveillance activities, constrained by practical difficulties, such as the accessibility of wild animals, and regulatory rules for the trapping of badgers, for example. We report here the first assessment of stakeholders’ perceptions of the Sylvatub system and its acceptability, based on 20 individual semi-structured interviews with three types of stakeholder (collectors, coordinators, officers) in areas with different rates of bTB infection. With the caveat that these findings cannot be assumed to be representative of the national situation, we found that the Sylvatub system was considered useful by all the stakeholders interviewed. Those from the world of hunting participate in surveillance mostly to help livestock farmers, who are not systematically involved in bTB surveillance in wildlife. Many practical and regulatory constraints were raised, which could be offset by recognition of the work done by the “hunting community”, to maintain the willingness of these individuals to participate. We also identified a need for improvements in communication and information. Qualitative information, such as that collected here, is essential to improve our understanding of the reasons favoring and disfavoring participation in surveillance, and should be taken into account in the evaluation process. These results are relevant to hunters and to veterinary authorities wishing to identify the determinants of participation in the Sylvatub system. They could provide support for decision-making processes to improve surveillance strategies.

The concept of One Health (OH) promotes the decompartmentalisation of human, animal, and ecosystem health for the more efficient and sustainable governance of complex health issues. This means that traditional boundaries between disciplines and sectors must be transgressed and that all relevant stakeholders must be involved in the definition and management of health problems. International efforts have been made to strengthen collaboration across sectors and disciplines and OH surveillance is strongly encouraged at global, national and local-level to efficiently manage hazards involving humans, animals and ecosystems. This concept is intuitively appealing and would suggest the enhanced performance and cost-effectiveness of surveillance systems, as compared to more conventional approaches. Nevertheless, confusion and uncertainty regarding the practical application, outcomes and impacts prevail. We believe that this is due to the lack of a conceptual and methodological framework which would (i) define the characteristics of OH surveillance, and (ii) identify the appropriate mechanisms for inter-sectoral and multi-disciplinary collaboration, to ensure that the surveillance system performs well, with regard to the objective, the context and the health hazard under surveillance. The objective of the study is to define the organisational and functional characteristics of OH surveillance systems, the context in which they are implemented, as well as the influential factors which may obstruct or support their implementation and performance. To achieve this, a systematic literature review of existing OH surveillance systems was conducted using the Prisma guidelines. The selected systems were assessed according to 38 predetermined variables. These allowed the characterisation of their objectives, organisation, functioning, performance and benefits. Data extraction was conducted using a spreadsheet and a database was built using an electronic multiple-choice questionnaire. The literature search identified a total of 1635 records. After the screening phase, 31 references were kept and 22 additional references retrieved from bibliographies were added. From these 53 selected documents, we retrieved 41 different surveillance systems in line with the definition proposed in this study. The analysis of this database enabled the identification of different dimensions and areas of collaboration. Barriers and levers for the implementation of OH surveillance systems were also identified and discussed. Based on our results, we propose a framework to characterise the organisation of collaboration for the governance and operation of an effective OH surveillance system.

The optimization of management strategies for plant diseases is a difficult task because of the complexity and variability of epidemic dynamics. Thanks to their ability to numerically simulate many scenarios, models can be used to estimate epidemiological parameters, assess the effectiveness of different management strategies and optimize them. This article presents the PESO (parameter estimation–simulation–optimization) modelling framework to help improve plant disease management strategies. This framework is based on (i) the characterization of the epidemic dynamics to estimate key epidemiological parameters, (ii) the use of spatially explicit models to simulate epidemic dynamics and disease management, and (iii) the use of numerical optimization methods to identify better management strategies. This approach is generic and can be applied to many diseases. The work presented here focuses on sharka (caused by Plum pox virus), which has a worldwide impact on the Prunus industry, and is associated with huge disease management costs in many countries, especially in France.

Bovine tuberculosis (bTB) is a common disease in cattle and wildlife, with health, zoonotic and economic implications. Infected wild animals, and particularly reservoirs, could hinder eradication of bTB from cattle populations, which could have an important impact on international cattle trade. Therefore, surveillance of bTB in wildlife is of particular importance to better understand the epidemiological role of wild species and to adapt the control measures. In France, a bTB surveillance system for free-ranging wildlife, the Sylvatub system, has been implemented since 2011. It relies on three surveillance components (SSCs) (passive surveillance on hunted animals (EC-SSC), passive surveillance on dead or dying animals (SAGIR-SSC) and active surveillance (PSURV-SSC)). The effectiveness of the Sylvatub system was previously assessed, through the estimation of its sensitivity (i.e. the probability of detecting at least one case of bTB infection by each SSC, specie and risk-level area). However, to globally assess the performance of a surveillance system, the measure of its sensitivity is not sufficient, as other factors such as economic or socio-economic factors could influence the effectiveness. We report here an estimation of the costs of the surveillance activities of the Sylvatub system, and of the cost-effectiveness of each surveillance component, by specie and risk-level, based on scenario tree modelling with the same tree structure as used for the sensitivity evaluation. The cost-effectiveness of the Sylvatub surveillance is better in higher-risk departments, due in particular to the higher probability of detecting the infection (sensitivity). Moreover, EC-SSC, which has the highest unit cost, is more efficient than the surveillance enhanced by the SAGIR-SSC, due to its better sensitivity. The calculation of the cost-effectiveness ratio shows that PSURV-SSC remains the most cost-effective surveillance component of the Sylvatub system, despite its high cost in terms of coordination, sample collection and laboratory analysis.

Reports of honey bee population decline has spurred many national efforts to understand the extent of the problem and to identify causative or associated factors. However, our collective understanding of the factors has been hampered by a lack of joined up trans-national effort. Moreover, the impacts of beekeeper knowledge and beekeeping management practices have often been overlooked, despite honey bees being a managed pollinator. Here, we established a standardised active monitoring network for 5 798 apiaries over two consecutive years to quantify honey bee colony mortality across 17 European countries. Our data demonstrate that overwinter losses ranged between 2% and 32%, and that high summer losses were likely to follow high winter losses. Multivariate Poisson regression models revealed that hobbyist beekeepers with small apiaries and little experience in beekeeping had double the winter mortality rate when compared to professional beekeepers. Furthermore, honey bees kept by professional beekeepers never showed signs of disease, unlike apiaries from hobbyist beekeepers that had symptoms of bacterial infection and heavy Varroa infestation. Our data highlight beekeeper background and apicultural practices as major drivers of honey bee colony losses. The benefits of conducting trans-national monitoring schemes and improving beekeeper training are discussed.

Whether surveillance is based on serological tests, the exact number of detected cases may remain unknown because identifying seroconversion can be difficult. Moreover, incomplete cases / outbreaks detection is a recurrent issue in surveillance. Our study addresses these two issues, regarding equine viral arteritis (EVA) surveillance. Our goals were to establish suitable rules for identifying seroconversion to estimate the number of EVA outbreaks detected by the French breeding stock surveillance system between 2006 and 2013, and to assess surveillance sensitivity by estimating the total number of outbreaks that occurred during this period using a capture-recapture model. Data from mares with at least one positive result using viral neutralization test between 2006 and 2013 were used for analysis (n=1,645). Data consisted of annual antibody titers and mares’ location (towns). Seroconversion was defined as a change in antibody titer from negative to at least 32 or a three-fold increase. The number of seroconversions was counted for each town and modeled using a zero-truncated binomial capture-recapture model with R software. From 2006 to 2013, 239 cases of seroconversion located in 177 towns (outbreaks) were identified. Total number of outbreaks in breeding stock was estimated at 215 (CrI95% 195249) and the surveillance sensitivity at the town level at 82% (CrI95% 71%-91%). The estimated surveillance sensitivity is relatively high. The proposed rules may be used to analyze other serological surveillance data, including testing before sales or international trade. This study shows how capture-recapture methods may help to estimate surveillance sensitivity and to valorize surveillance data. Introduction Equine viral arteritis (EVA) is an equine respiratory and reproductive disease which can lead to abortions and neonatal deaths. EVA is caused by a virus of the Arteriviridae family and is mainly transmitted horizontally by aerosols or venereal contact, including frozen semen (1, 2). EVA is monitored in many countries in breeding stock to avoid its spread during breeding activities (3). In France, the breeding stock surveillance (BSS) is mainly based on serological tests, but difficulties in interpreting certain series of results may impair the estimation of the number of outbreaks. Moreover, only a part of breeding horses are tested, depending on the studbooks’ regulations. The first objective of this study was to establish suitable rules for identifying seroconversion in order to estimate the number of EVA cases and outbreaks detected by the BSS between 2006 and 2013. The second goal was to estimate the sensitivity of the BSS, after having estimated the total number of out-breaks that occurred in breeding stock during this period (including undetected outbreaks) using a capture-recapture method.