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Background: Effectively addressing the coronavirus disease 2019 (COVID-19) pandemic caused by the new pathogen requires continuous generation of evidence to inform decision-making. Despite an unprecedented amount of research occurring globally, the need to identify gaps in knowledge and prioritize a research agenda that is linked to public health action is indisputable. The WHO South-East Asia Region (SEAR) is likely to have region-specific research needs., Methods: We aimed to identify a priority research agenda for guiding the regional and national response to the COVID-19 pandemic in SEAR countries. An online, anonymous research prioritization exercise using recent WHO guidance was conducted among the technical staff of WHO's country and regional offices engaged with the national COVID-19 response during October 2020. They were each asked to contribute up to five priority research ideas across seven thematic areas. These research ideas were reviewed, consolidated and scored by a core group on six parameters: regional specificity, relevance to the COVID-19 response, feasibility within regional research capacity, time to availability for decision-making, likely impact on practice, and promoting equity and gender responsiveness. The total scores for individual suggestions were organized in descending order, and ideas in the upper tertile were considered to be of high priority., Results: A total of 203 priority research ideas were received from 48 respondents, who were primarily research and emergency response focal points in country and regional offices. These were consolidated into 78 research ideas and scored. The final priority research agenda of 27 items covered all thematic areas-health system (n=10), public health interventions (n=6), disease epidemiology (n=5), socioeconomic and equity (n=3), basic sciences (n=1), clinical sciences (n=1) and pandemic preparedness (n=1)., Conclusions: This exercise, a part of WHO's mandate to "shape the research agenda", can help build a research roadmap ensuring efficient use of limited resources. This prioritized research agenda can act as a catalyst for Member States to accelerate research that could impact the COVID-19 response in SEAR., (© 2022. The Author(s).)

Objectives: This study aims to assess the trade-offs between vulnerability and efficiency attributes of contact tracing programmes based on preferences of COVID-19 contact tracing practitioners, researchers and other relevant stakeholders at the global level. Methods: We conducted an online discrete choice experiment (DCE). Respondents were recruited globally to explore preferences according to country income level and the prevailing epidemiology of COVID-19 in the local setting. The DCE attributes represented efficiency (timeliness, completeness, number of contacts), vulnerability (vulnerable population), cooperation and privacy. A mixed-logit model and latent class analysis were used. Results: The number of respondents was 181. Timeliness was the most important attribute regardless of country income level and COVID-19 epidemiological condition. Vulnerability of contacts was the second most important attribute for low-to-lower-middle-income countries and third for upper-middle-to-high income countries. When normalised against conditional relative importance of timeliness, conditional relative importance of vulnerability ranged from 0.38 to 0.42. Conclusion: Vulnerability and efficiency criteria were both considered to be important attributes of contact tracing programmes. However, the relative values placed on these criteria varied significantly between epidemiological and economic context., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Faradiba, Del Rio Vilas, Asaria, Chen, Babigumira, Dabak and Wee.)

The COVID-19 pandemic exemplifies a One Health issue at the intersection of human, animal, and environmental health that requires collaboration across sectors to manage it successfully. The global One Health community includes professionals working in many different fields including human medicine, veterinary medicine, public health, ecosystem health, and, increasingly, social sciences. The aims of this cross-sectional study were to describe the involvement of the global One Health community in COVID-19 pandemic response activities. One Health networks (OHNs) have formed globally to serve professionals with common interests in collaborative approaches. We assessed the potential association between being part of an OHN and involvement in COVID-19 response activities. Data were collected in July-August 2020 using an online questionnaire that addressed work characteristics, perceived connection to OHNs, involvement in COVID-19 pandemic response activities, and barriers and facilitators to the involvement. The sample included 1,050 respondents from 94 countries across a range of organizations and work sectors including, but not restricted to, those typically associated with a One Health approach. Sixty-four percent of survey respondents indicated involvement in pandemic response activities. Being part of an OHN was positively associated with being involved in the COVID-19 response (odds ratio: 1.8, 95% confidence interval: 1.3-2.4). Lack of opportunities was a commonly reported barrier to involvement globally, with lack of funding the largest barrier in the WHO African region. This insight into diverse workforce involvement in the pandemic helps fill a gap in the global health workforce and public health education literature. An expanded understanding of the perceived roles and value of OHNs can inform targeted interventions to improve public health education and workforce capacity to prepare for and respond to public health emergencies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Streichert, Sepe, Jokelainen, Stroud, Berezowski and Del Rio Vilas.)

Background: We investigate the completeness of contact tracing for COVID-19 during the first wave of the COVID-19 pandemic in Thailand, from early January 2020 to 30 June 2020., Methods: Uni-list capture-recapture models were applied to the frequency distributions of index cases to inform two questions: (1) the unobserved number of index cases with contacts, and (2) the unobserved number of index cases with secondary cases among their contacts., Results: Generalized linear models (using Poisson and logistic families) did not return any significant predictor (age, sex, nationality, number of contacts per case) on the risk of transmission and hence capture-recapture models did not adjust for observed heterogeneity. Best fitting models, a zero truncated negative binomial for question 1 and zero-truncated Poisson for question 2, returned sensitivity estimates for contact tracing performance of 77.6% (95% CI = 73.75-81.54%) and 67.6% (95% CI = 53.84-81.38%), respectively. A zero-inflated negative binomial model on the distribution of index cases with secondary cases allowed the estimation of the effective reproduction number at 0.14 (95% CI = 0.09-0.22), and the overdispersion parameter at 0.1., Conclusion: Completeness of COVID-19 contact tracing in Thailand during the first wave appeared moderate, with around 67% of infectious transmission chains detected. Overdispersion was present suggesting that most of the index cases did not result in infectious transmission chains and the majority of transmission events stemmed from a small proportion of index cases., (© 2022. The Author(s).)

Background : Antimicrobial resistance (AMR) is a growing public health threat in Africa. AMR prevention and control requires coordination across multiple sectors of government and civil society partners. Objectives : To assess the current role, needs, and capacities of CSOs working in AMR in Africa. Methods : We conducted an online survey of 35 CSOs working in 37 countries across Africa. The survey asked about priorities for AMR, current AMR-specific activities, monitoring practices, training needs, and preferences for sharing information on AMR. Further data were gathered on the main roles of the organisations, the length of time engaged in and budget spent on AMR-related activities, and their involvement in the development and implementation of National Action Plans (NAPs). Results were assessed against The Africa Centres for Disease Control and Prevention (Africa CDC) Framework for Antimicrobial Resistance (2018-2023). Results : CSOs with AMR-related activities are working in all four areas of Africa CDC's Framework: improving surveillance, delaying emergence, limiting transmission, and mitigating harm from infections caused by AMR microorganisms. Engagement with the four objectives is mainly through advocacy, followed by accountability and service delivery. There were limited monitoring activities reported by CSOs, with only seven (20%) providing an example metric used to monitor their activities related to AMR, and 27 (80%) CSOs reporting having no AMR-related strategy. Half the CSOs reported engaging with the development and implementation of NAPs; however, only three CSOs are aligning their work with these national strategies. Conclusion : CSOs across Africa are supporting AMR prevention and control, however, there is potential for more engagement. Africa CDC and other government agencies should support the training of CSOs in strategies to control AMR. Tailored training programmes can build knowledge of AMR, capacity for monitoring processes, and facilitate further identification of CSOs' contribution to the AMR Framework and alignment with NAPs and regional strategies.

The analysis of zoonotic disease risk requires the consideration of both human and animal geo-referenced disease incidence data. Here we show an application of joint Bayesian analyses to the study of echinococcosis granulosus (EG) in the province of Rio Negro, Argentina. We focus on merging passive and active surveillance data sources of animal and human EG cases using joint Bayesian spatial and spatio-temporal models. While similar spatial clustering and temporal trending was apparent, there appears to be limited lagged dependence between animal and human outcomes. Beyond the data quality issues relating to missingness at different times, we were able to identify relations between dog and human data and the highest 'at risk' areas for echinococcosis within the province., Competing Interests: The authors have declared that no competing interests exist.

Background: The inappropriate use of antibiotics is a major issue in clinical practice in Greece with serious implications for public health and animal health. The purpose of the present study was to provide a first insight into the use of antibiotics by small animal practitioners in Greece and assess their compliance with general rules for the rational use of antibiotics. This is the first survey of its kind in Greece., Methods: A questionnaire was designed to collect basic information on the use of antibiotics by pet veterinarians. The questionnaire was sent to a total of 70 veterinarians mainly operating in the region of Attica, a region that comprises almost 50% of the Greek population and where veterinarians are engaged solely in small animal practice. The questionnaire consisted of 37 closed questions dealing with various aspects on the use of antibiotics., Results: The majority of practitioners report cases where the pet owner initiated antibiotic treatment without veterinary prescription. Almost every clinician reported owner-compliance challenges. Regarding microbiological analysis, 73% of respondents initiate empirical treatment while waiting for laboratory results or use antibiogram only when the treatment is unsuccessful. Eighty-eight per cent declared to use antimicrobials postoperatively in clean surgical procedures. Different types of antimicrobials and treatment durations than the ones proposed by guidelines on rational use of antibiotics are preferred for various organ systems e.g. in urinary and gastrointestinal infections., Conclusions: Our findings suggest the need for guidelines on antibiotic use in small animal practice in Greece, and the deployment of systematic surveillance on antimicrobials use and resistance to inform the initial choice of antibiotics upon local antimicrobial resistance profiles. Targeting the other end of the problem, pet owners, our findings indicate the need to educate them on the rational use of antibiotics and, critically, stop antibiotic availability without prescription., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2020.)

Objective: To compare the performance of polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) tests for diagnosing Echinococcus granulosus in dog feces among national reference laboratories in Argentina, Chile, Peru, and Uruguay., Methods: National laboratories affiliated with the Ministry of Health/Agriculture of each country exchanged panels of 10 positive/negative samples obtained from their regular national surveillance programs in November 2015 - November 2016. All laboratories applied PCR; two also applied ELISA techniques. Sensitivity and specificity were determined for each laboratory and concordance of results among the laboratories was evaluated by Cohen Kappa coefficient., Results: Poor concordance (3 of 10 paired comparisons had values of Kappa > 0.4), low sensitivity and specificity across all laboratories, and poor performance of both techniques in detecting E. granulosus in canine feces was demonstrated in this study. An ex-post comparison of the laboratories' test protocols showed substantial heterogeneity that could partially explain poor concordance of results., Conclusion: The results underscore the heterogeneity of canine echinococcosis diagnosis across the region and indicate possible sources of variability. Efforts to standardize canine echinococcosis testing must be included in the plan of action for the Regional Initiative for the Control of Cystic Echinococcosis. Future comparisons with fecal samples of known parasite load are needed., Competing Interests: Conflict of interests. None declared.

The large number of activities contributing to zoonoses surveillance and control capability, on both human and animal domains, and their likely heterogeneous implementation across administrative units make assessment and comparisons of capability performance between such units a complex task. Such comparisons are important to identify gaps in capability development, which could lead to clusters of vulnerable areas, and to rank and subsequently prioritize resource allocation toward the least capable administrative units. Area-level preparedness is a multidimensional entity and, to the best of our knowledge, there is no consensus on a single comprehensive indicator, or combination of indicators, in a summary metric. We use Bayesian spatial factor analysis models to jointly estimate and rank disease control and surveillance capabilities against visceral leishmaniasis (VL) at the municipality level in Brazil. The latent level of joint capability is informed by four variables at each municipality, three reflecting efforts to monitor and control the disease in humans, and one variable informing surveillance capability on the reservoir, the domestic dog. Because of the large volume of missing data, we applied imputation techniques to allow production of comprehensive rankings. We were able to show the application of these models to this sparse dataset and present a ranked list of municipalities based on their overall VL capability. We discuss improvements to our models, and additional applications.

One Health Surveillance (OHS) implements the One Health approach to improving health by collecting data and producing information to support integrated action across the animal health, human health and environment sectors. The purpose of this study was to survey the biosurveillance community to assess its OHS practices and capabilities, its attitudes towards OHS (perceived value), and the factors that motivate its members to implement OHS practices. The authors used a convenience sample of 185 professionals from multiple domains and 44 nations. They examined the extent to which these professionals implemented OHS, gathered their opinions on the value of OHS, assessed their perceptions of the capacity to perform specific OHS tasks and identified their priorities for change. Over 85% of all respondents said that they considered OHS to be beneficial, with no significant differences between work domains or country income groups; over 50% indicated that they already applied OHS. Obtaining access to data collected by other domains was both the most frequent challenge and the most difficult to improve. The highest priority for improvement was having the ability to send and receive electronic data. Respondents from low-income or middle-income countries were more motivated to make improvements than stakeholders from high-income countries. These findings provide a snapshot of current opinions and practices and, together with suggestions for improvements from professionals in the field, can help to target priority needs for OHS information, training and resources., (© World Organisation for Animal Health (OIE), 2019)

Background: Visceral leishmaniasis (VL) is a neglected tropical disease of public health relevance in Brazil. To prioritize disease control measures, the Secretaria de Vigilância em Saúde of Brazil's Ministry of Health (SVS/MH) uses retrospective human case counts from VL surveillance data to inform a municipality-based risk classification. In this study, we compared the underlying VL risk, using a spatiotemporal explicit Bayesian hierarchical model (BHM), with the risk classification currently in use by the Brazil's Ministry of Health. We aim to assess how well the current risk classes capture the underlying VL risk as modelled by the BHM., Methods: Annual counts of human VL cases and the population at risk for all Brazil's 5564 municipalities between 2004 and 2014 were used to fit a relative risk BHM. We then computed the predicted counts and exceedence risk for each municipality and classified them into four categories to allow comparison with the four risk categories by the SVS/MH., Results: Municipalities identified as high-risk by the model partially agreed with the current risk classification by the SVS/MH. Our results suggest that counts of VL cases may suffice as general indicators of the underlying risk, but can underestimate risks, especially in areas with intense transmission., Conclusion: According to our BHM the SVS/MH risk classification underestimated the risk in several municipalities with moderate to intense VL transmission. Newly identified high-risk areas should be further evaluated to identify potential risk factors and assess the needs for additional surveillance and mitigation efforts.

Rabies is still one of the deadliest diseases known to exist in the 21st century, and yet it remains irresponsibly neglected and underestimated. In light of this, this paper discusses the principles of governance as they relate to rabies control, using examples of global intersectoral coordination programmes for the control of canine rabies and for the elimination of human rabies transmitted by dogs. The first of these programmes was the Meeting of Rabies Program Directors of the Americas (REDIPRA), which has served as a model of intersectoral success for rabies elimination in other regions. Examples of intersectoral cooperation on several continents, mainly between the health and agriculture sectors, are detailed to discuss various methods of achieving better technical cooperation. These cooperation programmes follow the 'coalition model' set by REDIPRA. They bring together various actors, such as governments, non-governmental organisations, the private sector, the science and research community, international cooperation agencies and donors, under a common umbrella for advocacy and for the implementation of local projects for the elimination of human rabies transmitted by dogs. Networking is the main intersectoral governance mechanism presented in this review.

Rabies is one of the oldest recorded pathogens, with the broadest distribution of any known viral zoonosis. Antarctica is believed to be free of all lyssaviruses, but no laboratory-based surveillance has taken place to support this supposition. Re-introduction of the disease is possible in Pacific Oceania, as evidenced by a historical outbreak in Guam and the translocation of rabid bats to Hawaii. Australia is the only inhabited continent with enzootic rabies, without the presence of rabies virus. Europe and North America have broken the cycle of dog-mediated rabies, with a few remaining focal points in Latin America and the Caribbean, but wildlife rabies predominates. The greatest burden resides in the 'Old World'. The elimination of human rabies mediated via dogs by 2030 in Africa, Asia and the Middle East will not be simple, rapid or inexpensive, but it may be achievable through the use of widely available tools and the application of lessons learned during the course of the 20th century.

Background: There are an increasing number of geo-coded information streams available which could improve public health surveillance accuracy and efficiency when properly integrated. Specifically, for zoonotic diseases, knowledge of spatial and temporal patterns of animal host distribution can be used to raise awareness of human risk and enhance early prediction accuracy of human incidence., Methods: To this end, we develop a spatiotemporal joint modeling framework to integrate human case data and animal host data to offer a modeling alternative for combining multiple surveillance data streams in a novel way. A case study is provided of spatiotemporal modeling of human tularemia incidence and rodent population data from Finnish health care districts during years 1995-2012., Results: Spatial and temporal information of rodent abundance was shown to be useful in predicting human cases and in improving tularemia risk estimates in 40 and 75% of health care districts, respectively. The human relative risk estimates' standard deviation with rodent's information incorporated are smaller than those from the model that has only human incidence., Conclusions: These results support the integration of rodent population variables to reduce the uncertainty of tularemia risk estimates. However, more information on several covariates such as environmental, behavioral, and socio-economic factors can be investigated further to deeper understand the zoonotic relationship.

Through national efforts and regional cooperation under the umbrella of the Regional Program for the Elimination of Rabies, dog and human rabies have decreased significantly in Latin America and Caribbean (LAC) countries over the last three decades. To achieve this decline, LAC countries had to develop national plans, and consolidate capabilities such as regular mass dog vaccination, opportune post-exposure prophylaxis and sensitive surveillance. This paper presents longitudinal data for 21 LAC countries on dog vaccination, PEP and rabies surveillance collected from the biannual regional meeting for rabies directors from 1998-2014 and from the Regional Epidemiologic Surveillance System for Rabies (SIRVERA). Differences in human and dog rabies incidence rates and dog vaccination rates were shown between low, middle and high-income countries. At the peak, over 50 million dogs were vaccinated annually in national campaigns in the countries represented. The reported number of animal exposures remained fairly stable during the study period with an incidence rate ranging from 123 to 191 reported exposures per 100,000 people. On average, over 2 million doses of human vaccine were applied annually. In the most recent survey, only 37% of countries reported that they had sufficient financial resources to meet the program objectives. The data show a sufficient and sustained effort of the LAC countries in the area of dog vaccination and provide understanding of the baseline effort required to reduce dog-mediated rabies incidence.

Emerging zoonoses with pandemic potential are a stated priority for the global health security agenda, but endemic zoonoses also have a major societal impact in low-resource settings. Although many endemic zoonoses can be treated, timely diagnosis and appropriate clinical management of human cases is often challenging. Preventive 'One Health' interventions, e.g. interventions in animal populations that generate human health benefits, may provide a useful approach to overcoming some of these challenges. Effective strategies, such as animal vaccination, already exist for the prevention, control and elimination of many endemic zoonoses, including rabies, and several livestock zoonoses (e.g. brucellosis, leptospirosis, Q fever) that are important causes of human febrile illness and livestock productivity losses in low- and middle-income countries. We make the case that, for these diseases, One Health interventions have the potential to be more effective and generate more equitable benefits for human health and livelihoods, particularly in rural areas, than approaches that rely exclusively on treatment of human cases. We hypothesize that applying One Health interventions to tackle these health challenges will help to build trust, community engagement and cross-sectoral collaboration, which will in turn strengthen the capacity of fragile health systems to respond to the threat of emerging zoonoses and other future health challenges. One Health interventions thus have the potential to align the ongoing needs of disadvantaged communities with the concerns of the broader global community, providing a pragmatic and equitable approach to meeting the global goals for sustainable development and supporting the global health security agenda.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'., (© 2017 The Authors.)

The direct fluorescent antibody test (DFA), is performed in all rabies reference laboratories across Latin America and the Caribbean (LAC). Despite DFA being a critical capacity in the control of rabies, there is not a standardized protocol in the region. We describe the results of the first inter-laboratory proficiency exercise of national rabies laboratories in LAC countries as part of the regional efforts towards dog-maintained rabies elimination in the American region. Twenty three laboratories affiliated to the Ministries of Health and Ministries of Agriculture participated in this exercise. In addition, the laboratories completed an online questionnaire to assess laboratory practices. Answers to the online questionnaire indicated large variability in the laboratories throughput, equipment used, protocols availability, quality control standards and biosafety requirements. Our results will inform actions to improve and harmonize laboratory rabies capacities across LAC in support for the regional efforts towards elimination of dog-maintained rabies.

Background: In recent years, global public health security has been threatened by zoonotic disease emergence as exemplified by outbreaks of H5N1 and H1N1 influenza, SARS, and most recently Ebola and Zika. Additionally, endemic zoonoses, such as rabies, burden countries year after year, placing demands on limited finances and personnel. To survey the baseline status of the emerging and endemic zoonoses programmes of the Latin American and the Caribbean (LAC) countries, the Pan American Health Organization (PAHO) conducted a survey of priority emerging and endemic zoonoses, countries´ prioritization criteria and methodologies, and suggestions to strengthen countries capacities and regional approaches to zoonoses control., Methods: A fillable online questionnaire was sent to the zoonoses programme managers of the Ministries of Health (MOH) and Ministries of Agriculture (MAg) of 33 LAC countries from January to April of 2015. The questionnaire comprised 36 single, multiple choice and open-ended questions to inform the objectives of the survey. A descriptive exploratory analysis was completed., Results: Fifty-four ministries (26 MOH, 25 MAg, and 3 combined responses) in 31 LAC countries responded to the survey. Within the ministries, 22 (85%) MOH, 5 (20%) MAg, and 2 (67%) combined entities indicated they had specialized zoonoses units. For endemic zoonoses, 32 of 54 ministries responded that they conduct formal prioritization exercises, most of them annually (69%). The three priority endemic zoonoses for the MOHs were leptospirosis, rabies, and brucellosis while the three priorities for the MAgs were brucellosis, rabies, and tuberculosis. Diagnosis for rabies and leptospirosis were cited as the capacities most in need of development. The most needed cross-cutting capacity was coordination between stakeholders. For emerging zoonoses, 28 ministries performed formal prioritization exercises. The top prioritization criteria were probability of introduction into the country and impact. The three priority emerging zoonoses for the MOHs were Ebola viral disease, avian influenza, and Chikungunya while for the MAgs were avian influenza, bovine spongiform encephalopathy and West Nile virus disease. Surveillance for avian influenza and Ebola, and diagnosis for BSE were quoted as the capacities most needed. For all zoonoses, the majority of respondents (69%) ranked their relationship with the other Ministry as productive or very productive, and 31% minimally productive. Many countries requested a formal regional network, better regional communication and collaboration, and integrated surveillance., Conclusions: The survey is the first comprehensive effort to date to inform the status of zoonoses programmes in LAC. The information collected here will be used to develop a regional strategy for zoonoses (both endemic and emerging), increase efforts, advocacy, and promote prompt identification and management of EIDs and improvement of endemic programmes.

In Latin American and Caribbean (LAC) countries, the number of cases of dog-mediated human rabies is at its lowest since the onset of the Regional Program for Rabies Elimination in 1983, a commitment from LAC countries to eliminate dog-mediated rabies coordinated by the Pan American Health Organization. Despite minor setbacks, the decline in the number of human cases has been constant since 1983. While many LAC countries have significantly reduced rabies to a level where it is no longer significant public health concern, elimination has proven elusive and pockets of the disease remain across the region. In the 33-year period since 1983, the region has set and committed to four dates for elimination (1990, 2000, 2012, and 2015). In this paper, we ponder on the multiple causes behind the elusive goal of rabies elimination, such as blanket regional goals oblivious to the large heterogeneity in national rabies capacities. Looking ahead to the elimination of dog-mediated rabies in the region, now established for 2022, we also review the many challenges and questions that the region faces in the last mile of the epidemic. Given the advanced position of the Americas in the race toward elimination, our considerations could provide valuable knowledge to other regions pursuing elimination goals.

Disease prioritization is motivated by the need to ensure that limited resources are targeted at the most important problems to achieve the greatest benefit in improving and maintaining human and animal health. Studies have prioritized a range of disease types, for example, zoonotic and foodborne diseases, using a range of criteria that describe potential disease impacts. This review describes the progression of disease prioritization methodology from ad hoc techniques to decision science methods (including multi-criteria decision analysis, conjoint analysis and probabilistic inversion), and describes how these methods aid defensible resource allocation. We discuss decision science in the context of disease prioritization to then review the development of disease prioritization studies. Structuring the prioritization and assessing decision-makers' preferences through value trade-offs between criteria within the decision context are identified as key factors that ensure transparency and reproducibility. Future directions for disease prioritization include the development of validation techniques, guidelines for model selection and neuroeconomics to gain a deeper understanding of decision-making.

In disease surveillance, capture-recapture approaches have been used to estimate the frequency of endemic diseases monitored by imperfect surveillance systems. A standard output of these techniques is an estimate of the sensitivity of the surveillance. In addition, capture-recapture applications contribute to a better understanding of the disease detection processes and of the relationships between different surveillance data sources, and help identify variables associated with the under-detection of diseases. Although capture-recapture approaches have long been used in public health, their application to livestock disease surveillance is only recent. In this paper, we review the different capture-recapture approaches applied in livestock disease surveillance, and discuss their benefits and limitations in the light of the characteristics of the surveillance and control practices used in animal health., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The American region has pledged to eliminate dog-mediated human rabies by 2015. As part of these efforts, we describe the findings of a desk and field mission review of Haiti's rabies situation by the end of 2013. While government officials recognize the importance of dog-mediated rabies control, and the national rabies plan adequately contemplates the basic capacities to that effect, regular and sufficient implementation, for example, of dog vaccination, is hampered by limited funding. Compounding insufficient funding and human resources, official surveillance figures do not accurately reflect the risk to the population, as evidenced by the large number of rabid dogs detected by focalized and enhanced surveillance activities conducted by the Ministry of Agriculture, Natural Resources and Rural Development (MARNDR) and the Health and Population Ministry (MSPP) with the technical assistance of the United States Centers for Disease Control and Prevention. Although international support is common, either in the form of on-the-ground technical support or donations of immunobiologicals, it is not comprehensive. In addition, there is limited coordination with MARNDR/MSPP and with other actors at the strategic or operational level due to human resources limitations. Given these findings, the 2015 elimination goal in the region is compromised by the situation in Haiti where control of the disease is not yet in sight despite the best efforts of the resolute national officials. More importantly, dog-mediated rabies is still a threat to the Haitian population.

The region of the Americas pledged to eliminate dog-transmitted human rabies by 2015. After 30 years of sustained efforts, regional elimination appears possible as dog-mediated human rabies cases are at an all-time low, and a number of countries and territories have already eliminated the disease. In this setting, there is an opportunity to generate a framework to support countries strategies in the achievement and maintenance of rabies-free status (RFS). To this end, we describe the development of a multi-criteria decision analysis (MCDA) model to help the evaluation of rabies programmes and the identification of the best investment strategy for countries and territories to improve and efficiently maintain their rabies status. The model contemplates human and animal related capacities, six in each area, to comprehensively assess the wide scope of rabies programmes. An initial elicitation of expert opinion of values and weights for the MCDA model was performed via a web-based questionnaire. Even at this pilot stage, the model produces comparable capacity-scores, and overall (combined for public and animal health areas) as well as area-specific investment strategies. The model is being developed by the Pan American Health Organization (PAHO) as part of the regional efforts towards dog-mediated human rabies elimination and will be presented to the countries for review, refinement, contextualization, and testing. The aspiration is that countries use the model to identify the best allocation of resources towards the elimination of dog-mediated human rabies.

The UK's Department for Environment, Food and Rural Affairs supports the use of systematic tools for the prioritisation of known and well defined animal diseases to facilitate long and medium term planning of surveillance and disease control activities. The recognition that emerging events were not covered by the existing disease-specific approaches led to the establishment of the Veterinary Risk Group (VRG), constituted of government officials, and supporting structures such as the Risk Management Cycle and the Emerging Threat Highlight Report (ETHiR), to facilitate the identification, reporting and assessment of emerging threats to UK's animal health. Since its inception in November 2009 to the end of February 2011, the VRG reviewed 111 threats and vulnerabilities (T&V) reported through ETHiR. In July 2010 a decision support system (DSS) based on multi-criteria-decision-analysis (MCDA) improved ETHiR to allow the systematic prioritisation of emerging T&V. The DSS allows the regular ranking of emerging T&V by calculating a set of measurement indices related to the actual impact, possible impact on public perception and level of available capabilities associated with every T&V. The systematic characterisation of the processes leading to the assessment of T&V by the VRG has led to a consistent, auditable and transparent approach to the identification and assessment of emerging risks. The regular use of MCDA to manage a portfolio of emerging risks represents a different and novel application of MCDA in a health related context., (Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.)

When analyzing the geographical variations of disease risk, one common problem is data sparseness. In such a setting, we investigate the possibility of using Bayesian shared spatial component models to strengthen inference and correct for any spatially structured sources of bias, when distinct data sources on one or more related diseases are available. Specifically, we apply our models to analyze the spatial variation of risk of two forms of scrapie infection affecting sheep in Wales (UK) using three surveillance sources on each disease. We first model each disease separately from the combined data sources and then extend our approach to jointly analyze diseases and data sources. We assess the predictive performances of several nested joint models through pseudo cross-validatory predictive model checks., (© Crown copyright 2011.)

Several surveillance techniques have been used to quantify the prevalence of both classical and atypical scrapie in British sheep, namely the recording of clinical suspects (RC) and the testing of animals slaughtered at abattoir (AS) or reported as fallen stock (FS). Any estimate of prevalence based on a particular source is likely to have been affected by demographic differences in the populations sampled. In this study, the demographic characteristics of scrapie-affected holdings detected by each of the surveillance streams (RC, AS, FS) in Great Britain were compared. Analyses of all three streams indicated that the probability of an affected holding being detected by a particular stream differed by geographical area, the number of animals brought onto the holding, the type of scrapie identified (classical vs. atypical) and the year. More detailed analysis of AS and FS suggested that the annual and regional differences between these surveys could be explained by differences in sampling effort., (Crown Copyright © 2009. Published by Elsevier Ltd. All rights reserved.)

We describe the application of Bayesian hierarchical models (BHM) to the analysis of risk of sheep scrapie using data from multiple surveillance sources. More specifically, we analysed data from the test results of three surveillance sources on classical and atypical scrapie in Wales for the period 2002-2006. For each form of scrapie, a BHM was fitted to assess the occurrence of spatial patterns of risk shared by the multiple surveillance sources and the association between covariates and disease. We defined a shared-component model whereby the two types of data sources: exhaustive lists (e.g. reports of clinical cases) and sample-based data sources (e.g. abattoir survey) shared a common spatial pattern of risks at parish level. This shared component was adjusted by a risk-gradient parameter that moderated the individual contribution of the datasets. For both forms of scrapie, the risk-gradient was not significantly different indicating that the sensitivity of the two types of dataset was similar for the two diseases. The spatial patterns of the combinations of data sources appeared similar within disease. However, our results suggest that classical and atypical scrapie differ in their spatial patterns and disease determinants. The joint approach permitted inference from all the available evidence and resulted in robust and less biased estimates of risk, particularly for atypical scrapie where the number of observations was very limited., (Crown Copyright © 2010. Published by Elsevier B.V. All rights reserved.)

Wide-scale scrapie surveillance started in 2002 in the EU. As a result, a new form of scrapie was detected which has been referred to as atypical scrapie. Here we present a case-control study conducted on British sheep farms to increase our understanding of the disease and potential risk factors at holding level. Forty case and 120 control holdings were traced from the confirmed atypical results in the scrapie surveillance programme in Great Britain during the period 2002-2007. A detailed questionnaire was completed by interview to record data on holding-specific management variables. A combination of generalized additive, generalized linear and Bayesian models returned 3 variables clearly associated with an increase in the odds of atypical scrapie: presence of two sheep breeds (Welsh Mountain and Cheviot) and flock type (store/fattening flocks). A fourth variable, the number of visits by veterinarians to the holding exerted a protective effect. Various other variables were significantly associated with the outcome, but at a somewhat lower level of confidence; for example, the size of the holding and the presence on the farm of concentrates intended for animals other than sheep., (Crown Copyright 2010. Published by Elsevier B.V. All rights reserved.)

Evaluation of surveillance systems is a common practice in the context of human health, but only recently has been applied in the veterinary field. Commonly, a series of attributes are monitored to assess the system. Suboptimal performance of the surveillance in relation to any of these attributes may lead to bias in the surveillance results. The intensity of scrapie surveillance has increased considerably in recent years as a result of public health concerns. In this paper, a number of approaches described in the literature for the evaluation of surveillance systems are reviewed, with a focus on the sensitivity and representativeness attributes of scrapie surveillance systems in the European Union. Many of the methods applied in other fields, such as ecology and public health, are exchangeable and relevant for scrapie surveillance., (Crown Copyright 2009. Published by Elsevier Ltd. All rights reserved.)

Movement records are often used to identify animal sample provenance by retracing the movements of individuals. Here we present an alternative method, which uses the same identity tags and movement records as are used to retrace movements, but ignores individual movement paths. The first step uses a simple query to identify the most likely birth holding for every identity tag included in a database recording departures from agricultural holdings. The second step rejects a proportion of the birth holding locations to leave a list of birth holding locations that are relatively reliable. The method was used to trace the birth locations of sheep sampled for scrapie in abattoirs, or on farm as fallen stock. Over 82% of the sheep sampled in the fallen stock survey died at the holding of birth. This lack of movement may be an important constraint on scrapie transmission. These static sheep provided relatively reliable birth locations, which were used to define criteria for selecting reliable traces. The criteria rejected 16.8% of fallen stock traces and 11.9% of abattoir survey traces. Two tests provided estimates that selection reduced error in fallen stock traces from 11.3% to 3.2%, and in abattoir survey traces from 8.1% to 1.8%. This method generated 14,591 accepted traces of fallen stock from samples taken during 2002-2005 and 83,136 accepted traces from abattoir samples. The absence or ambiguity of flock tag records at the time of slaughter prevented the tracing of 16-24% of abattoir samples during 2002-2004, although flock tag records improved in 2005. The use of internal scoring to generate and evaluate results from the database query, and the confirmation of results by comparison with other database fields, are analogous to methods used in web search engines. Such methods may have wide application in tracing samples and in adding value to biological datasets., (Crown Copyright 2010. Published by Elsevier B.V. All rights reserved.)

Background: This paper explores the spatial distribution of sampling within the active surveillance of sheep scrapie in Great Britain. We investigated the geographic distribution of the birth holdings of sheep sampled for scrapie during 2002 - 2005, including samples taken in abattoir surveys (c. 83,100) and from sheep that died in the field ("fallen stock", c. 14,600). We mapped the birth holdings by county and calculated the sampling rate, defined as the proportion of the holdings in each county sampled by the surveys. The Moran index was used to estimate the global spatial autocorrelation across Great Britain. The contributions of each county to the global Moran index were analysed by a local indicator of spatial autocorrelation (LISA)., Results: The sampling rate differed among counties in both surveys, which affected the distribution of detected cases of scrapie. Within each survey, the county sampling rates in different years were positively correlated during 2002-2005, with the abattoir survey being more strongly autocorrelated through time than the fallen stock survey. In the abattoir survey, spatial indices indicated that sampling rates in neighbouring counties tended to be similar, with few significant contrasts. Sampling rates were strongly correlated with sheep density, being highest in Wales, Southwest England and Northern England. This relationship with sheep density accounted for over 80% of the variation in sampling rate among counties. In the fallen stock survey, sampling rates in neighbouring counties tended to be different, with more statistically significant contrasts. The fallen stock survey also included a larger proportion of holdings providing many samples., Conclusion: Sampling will continue to be uneven unless action is taken to make it more uniform, if more uniform sampling becomes a target. Alternatively, analyses of scrapie occurrence in these datasets can take account of the distribution of sampling. Combining the surveys only partially reduces uneven sampling. Adjusting the distribution of sampling between abattoirs to reduce the bias in favour of regions with high sheep densities could probably achieve more even sampling. However, any adjustment of sampling should take account of the current understanding of the distribution of scrapie cases, which will be improved by further analysis of this dataset.

Background: The present paper investigates the question of a suitable basic model for the number of scrapie cases in a holding and applications of this knowledge to the estimation of scrapie-affected holding population sizes and adequacy of control measures within holding. Is the number of scrapie cases proportional to the size of the holding in which case it should be incorporated into the parameter of the error distribution for the scrapie counts? Or, is there a different - potentially more complex - relationship between case count and holding size in which case the information about the size of the holding should be better incorporated as a covariate in the modeling?, Methods: We show that this question can be appropriately addressed via a simple zero-truncated Poisson model in which the hypothesis of proportionality enters as a special offset-model. Model comparisons can be achieved by means of likelihood ratio testing. The procedure is illustrated by means of surveillance data on classical scrapie in Great Britain. Furthermore, the model with the best fit is used to estimate the size of the scrapie-affected holding population in Great Britain by means of two capture-recapture estimators: the Poisson estimator and the generalized Zelterman estimator., Results: No evidence could be found for the hypothesis of proportionality. In fact, there is some evidence that this relationship follows a curved line which increases for small holdings up to a maximum after which it declines again. Furthermore, it is pointed out how crucial the correct model choice is when applied to capture-recapture estimation on the basis of zero-truncated Poisson models as well as on the basis of the generalized Zelterman estimator. Estimators based on the proportionality model return very different and unreasonable estimates for the population sizes., Conclusion: Our results stress the importance of an adequate modelling approach to the association between holding size and the number of cases of classical scrapie within holding. Reporting artefacts and speculative biological effects are hypothesized as the underlying causes of the observed curved relationship. The lack of adjustment for these artefacts might well render ineffective the current strategies for the control of the disease.

Estimation of a population size by means of capture-recapture techniques is an important problem occurring in many areas of life and social sciences. We consider the frequencies of frequencies situation, where a count variable is used to summarize how often a unit has been identified in the target population of interest. The distribution of this count variable is zero-truncated since zero identifications do not occur in the sample. As an application we consider the surveillance of scrapie in Great Britain. In this case study holdings with scrapie that are not identified (zero counts) do not enter the surveillance database. The count variable of interest is the number of scrapie cases per holding. For count distributions a common model is the Poisson distribution and, to adjust for potential heterogeneity, a discrete mixture of Poisson distributions is used. Mixtures of Poissons usually provide an excellent fit as will be demonstrated in the application of interest. However, as it has been recently demonstrated, mixtures also suffer under the so-called boundary problem, resulting in overestimation of population size. It is suggested here to select the mixture model on the basis of the Bayesian Information Criterion. This strategy is further refined by employing a bagging procedure leading to a series of estimates of population size. Using the median of this series, highly influential size estimates are avoided. In limited simulation studies it is shown that the procedure leads to estimates with remarkable small bias., (((c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).)

Estimation of population size with missing zero-class is an important problem that is encountered in epidemiological assessment studies. Fitting a Poisson model to the observed data by the method of maximum likelihood and estimation of the population size based on this fit is an approach that has been widely used for this purpose. In practice, however, the Poisson assumption is seldom satisfied. Zelterman (1988) has proposed a robust estimator for unclustered data that works well in a wide class of distributions applicable for count data. In the work presented here, we extend this estimator to clustered data. The estimator requires fitting a zero-truncated homogeneous Poisson model by maximum likelihood and thereby using a Horvitz-Thompson estimator of population size. This was found to work well, when the data follow the hypothesized homogeneous Poisson model. However, when the true distribution deviates from the hypothesized model, the population size was found to be underestimated. In the search of a more robust estimator, we focused on three models that use all clusters with exactly one case, those clusters with exactly two cases and those with exactly three cases to estimate the probability of the zero-class and thereby use data collected on all the clusters in the Horvitz-Thompson estimator of population size. Loss in efficiency associated with gain in robustness was examined based on a simulation study. As a trade-off between gain in robustness and loss in efficiency, the model that uses data collected on clusters with at most three cases to estimate the probability of the zero-class was found to be preferred in general. In applications, we recommend obtaining estimates from all three models and making a choice considering the estimates from the three models, robustness and the loss in efficiency., ((c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

In this paper, we apply one-list capture-recapture models to estimate the number of scrapie-affected holdings in Great Britain. We applied this technique to the Compulsory Scrapie Flocks Scheme dataset where cases from all the surveillance sources monitoring the presence of scrapie in Great Britain, the abattoir survey, the fallen stock survey and the statutory reporting of clinical cases, are gathered. Consequently, the estimates of prevalence obtained from this scheme should be comprehensive and cover all the different presentations of the disease captured individually by the surveillance sources. Two estimators were applied under the one-list approach: the Zelterman estimator and Chao's lower bound estimator. Our results could only inform with confidence the scrapie-affected holding population with clinical disease; this moved around the figure of 350 holdings in Great Britain for the period under study, April 2005-April 2006. Our models allowed the stratification by surveillance source and the input of covariate information, holding size and country of origin. None of the covariates appear to inform the model significantly.

The abattoir and the fallen stock surveys constitute the active surveillance component aimed at improving the detection of scrapie across the European Union. Previous studies have suggested the occurrence of significant differences in the operation of the surveys across the EU. In the present study we assessed the standardisation of the surveys throughout time across the EU and identified clusters of countries with similar underlying characteristics allowing comparisons between them. In the absence of sufficient covariate information to explain the observed variability across countries, we modelled the unobserved heterogeneity by means of non-parametric distributions on the risk ratios of the fallen stock over the abattoir survey. More specifically, we used the profile likelihood method on 2003, 2004 and 2005 active surveillance data for 18 European countries on classical scrapie, and on 2004 and 2005 data for atypical scrapie separately. We extended our analyses to include the limited covariate information available, more specifically, the proportion of the adult sheep population sampled by the fallen stock survey every year. Our results show that the between-country heterogeneity dropped in 2004 and 2005 relative to that of 2003 for classical scrapie. As a consequence, the number of clusters in the last two years was also reduced indicating the gradual standardisation of the surveillance efforts across the EU. The crude analyses of the atypical data grouped all the countries in one cluster and showed non-significant gain in the detection of this type of scrapie by any of the two sources. The proportion of the population sampled by the fallen stock appeared significantly associated with our risk ratio for both types of scrapie, although in opposite directions: negative for classical and positive for atypical. The initial justification for the fallen stock, targeting a high-risk population to increase the likelihood of case finding, appears compromised for both types of scrapie in some countries.

Background: So-called atypical scrapie was first identified in Great Britain (GB) in 2002 following the introduction of wide-scale scrapie surveillance. In particular, abattoir and fallen stock surveys have been carried out in GB since 2002, with a total of 147 atypical positives identified by the end of 2006. The results of these surveys provide data with which to assess temporal trends in the prevalence of atypical scrapie in sheep in Great Britain between 2002 and 2006., Results: Using the results of abattoir and fallen stock surveys, the prevalence of atypical scrapie (percentage of samples positive) was estimated. The prevalence in the abattoir and fallen stock surveys, for all years combined, was 0.09% (95% confidence interval (CI): 0.08%-0.11%) and 0.07% (95% CI: 0.05%-0.11%), respectively. There were no significant temporal trends in either survey. Comparing the surveys' results, there were no significant differences in annual prevalence or the prevalence within PrP genotypes. For the abattoir survey, the PrP genotype with the highest prevalence was AHQ/AHQ, which was significantly higher than all other genotypes, except ARR/AHQ, AHQ/ARH and ARH/ARQ., Conclusion: The estimated prevalence of atypical scrapie was similar in both the abattoir and fallen stock surveys. Our results indicate there was no significant temporal trend in prevalence, adding to evidence that this atypical form of scrapie may be a sporadic condition or, if it is infectious, that the force of infection is very low.

Following the bovine spongiform encephalopathy (BSE) crisis, the European Union has introduced policies for eradicating transmissible spongiform encephalopathies (TSEs), including scrapie, from large ruminants. However, recent European Union surveillance has identified a novel prion disease, 'atypical' scrapie, substantially different from classical scrapie. It is unknown whether atypical scrapie is naturally transmissible or zoonotic, like BSE. Furthermore, cases have occurred in scrapie-resistant genotypes that are targets for selection in legislated selective breeding programmes. Here, the first epidemiological study of British cases of atypical scrapie is described, focusing on the demographics and trading patterns of farms and using databases of recorded livestock movements. Triplet comparisons found that farms with atypical scrapie stock more sheep than those of the general, non-affected population. They also move larger numbers of animals than control farms, but similar numbers to farms reporting classical scrapie. Whilst there is weak evidence of association through sheep trading of farms reporting classical scrapie, atypical scrapie shows no such evidence, being well-distributed across regions of Great Britain and through the sheep-trading network. Thus, although cases are few in number so far, our study suggests that, should natural transmission of atypical scrapie be occurring at all, it is doing so slowly.

Scrapie is a neuro-degenerative disease in small ruminants. A data set of 3113 records of sheep reported to the Scrapie Notifications Database in Great Britain has been studied. Clinical signs were recorded as present/absent in each animal by veterinary officials (VO) and a post-mortem diagnosis was made. In an attempt to detect healthy animals within the set of suspects using only the clinical signs, 18 classification methods were applied ranging from simple linear classifiers to classifier ensembles such as Bagging, AdaBoost and Random Forests. The results suggest that the clinical classification by the VO was adequate as no further differentiation within the set of suspects was feasible.

Background: Two annual surveys, the abattoir and the fallen stock, monitor the presence of scrapie across Europe. A simple comparison between the prevalence estimates in different countries reveals that, in 2003, the abattoir survey appears to detect more scrapie in some countries. This is contrary to evidence suggesting the greater ability of the fallen stock survey to detect the disease. We applied meta-analysis techniques to study this apparent heterogeneity in the behaviour of the surveys across Europe. Furthermore, we conducted a meta-regression analysis to assess the effect of country-specific characteristics on the variability. We have chosen the odds ratios between the two surveys to inform the underlying relationship between them and to allow comparisons between the countries under the meta-regression framework. Baseline risks, those of the slaughtered populations across Europe, and country-specific covariates, available from the European Commission Report, were inputted in the model to explain the heterogeneity., Results: Our results show the presence of significant heterogeneity in the odds ratios between countries and no reduction in the variability after adjustment for the different risks in the baseline populations. Three countries contributed the most to the overall heterogeneity: Germany, Ireland and The Netherlands. The inclusion of country-specific covariates did not, in general, reduce the variability except for one variable: the proportion of the total adult sheep population sampled as fallen stock by each country. A large residual heterogeneity remained in the model indicating the presence of substantial effect variability between countries., Conclusion: The meta-analysis approach was useful to assess the level of heterogeneity in the implementation of the surveys and to explore the reasons for the variation between countries.

Reports of clinical scrapie in Great Britain between January 1, 1993 and December 31, 2002 were reviewed. Scrapie was confirmed in 4142 sheep on 1099 holdings. The cumulative case and holding incidence risks decreased in 2001, probably owing to the outbreak of foot-and-mouth disease, although there were regional variations. Sheep aged between three and four years old constituted the largest affected group. In the period between 1998 and 2002, 51.3 per cent of the cases had the genotype ARQ/VRQ, 19.3 per cent were ARQ/ARQ and 18.9 per cent were VRQ/VRQ; Swaledale, Shetland and Welsh mountain sheep were the most common pure breeds reported. The areas at highest risk were the Shetland Islands, followed by the south and east of England.

We applied capture-recapture methodology (CRC) to data from three surveillance sources (statutory notification, abattoir survey (AS) and fallen stock (FS) survey) to estimate the number of holdings infected with scrapie in Great Britain and to assess the sensitivity of the surveillance network. Between January 1, 2002 and March 31, 2003, 144 holdings were identified by the three sources. Using CRC modelling techniques, we estimated a minimum lower bound for the total number of holdings infected as 642. A biologically plausible positive dependence between the statutory reporting and the fallen stock survey was found statistically significant. The sensitivity of the three sources combined was very low. The integration of the three overlapping sources provided a better understanding of the interactions within the surveillance network. However, the scarcity of the data and reduced overlapping among sources only allowed for very cautious inferences to be drawn about the true proportion of scrapie affected holdings in the national population. Future surveys and surveillance activities should be planned such that the resulting data can be used more effectively as part of CRC modelling approaches.