Assessing biases in phylodynamic inferences in the presence of super-spreaders.

Phylodynamic analyses using pathogen genetic data have become popular for making epidemiological inferences. However, many methods assume that the underlying host population follows homogenous mixing patterns. Nevertheless, in real disease outbreaks, a small number of individuals infect a disproportionately large number of others (super-spreaders). Our objective was to quantify the degree of bias in estimating the epidemic starting date in the presence of super-spreaders using different sample selection strategies. We simulated 100 epidemics of a hypothetical pathogen (fast evolving foot and mouth disease virus-like) over a real livestock movement network allowing the genetic mutations in pathogen sequence. Genetic sequences were sampled serially over the epidemic, which were then used to estimate the epidemic starting date using Extended Bayesian Coalescent Skyline plot (EBSP) and Birth-death skyline plot (BDSKY) models. Our results showed that the degree of bias varies over different epidemic situations, with substantial overestimations on the epidemic duration occurring in some occasions. While the accuracy and precision of BDSKY were deteriorated when a super-spreader generated a larger proportion of secondary cases, those of EBSP were deteriorated when epidemics were shorter. The accuracies of the inference were similar irrespective of whether the analysis used all sampled sequences or only a subset of them, although the former required substantially longer computational times. When phylodynamic analyses need to be performed under a time constraint to inform policy makers, we suggest multiple phylodynamics models to be used simultaneously for a subset of data to ascertain the robustness of inferences

Farmers' Decision Making on Livestock Trading Practices: Cowshed Culture and Behavioral Triggers Amongst New Zealand Dairy Farmers.

Studies of farmers' failure to implement biosecurity practices frequently frame their behavior as a lack of intention. More recent studies have argued that farmers' behaviors should be conceptualized as emergent from farming experiences rather than a direct consequence of specific intentions. Drawing on the concepts of "cowshed" culture and the "Trigger Change Model," we explore how farmers' livestock purchasing behavior is shaped by farms' natural and physical environments and identify what triggers behavioral change amongst farmers. Using bovine tuberculosis (bTB) in New Zealand as a case example, qualitative research was conducted with 15 New Zealand dairy producers with varying bTB experiences. We show how farmers' livestock purchasing behavior evolve with culture under a given farm environment. However, established cultures may be disrupted by various triggers such as disease outbreaks, introductions of animals with undesired characteristics, and farm relocation. While dealing with economic and socio-emotional impacts posed by triggers, farmers reorganize their culture and trading behaviors, which may involve holistic biosecurity strategies. Nevertheless, we also show that these triggers instigate only small behavioral changes for some farmers, suggesting the role of the trigger is likely to be context-dependent. Using voluntary disease control schemes such as providing disease status of source farms has attracted great interest as a driver of behavioral change. One hopes such schemes are easily integrated into existing farm practices, however, we speculate such an integration is challenging for many farmers due to path-dependency. We therefore argue that these schemes may fail to bring their intended behavioral changes without a greater understanding of how different types of triggers work in different situations. We need a paradigm shift in how we frame farmers' livestock trading practices. Otherwise, we may not able to answer our questions about farm biosecurity if we continue to approaching these questions solely from a biosecurity point of view

Estimation of the within-herd transmission rates of bovine viral diarrhoea virus in extensively grazed beef cattle herds

International audienceMany research groups have developed mathematical models to simulate the dynamics of BVDV infections in cattle herds. However, most models use estimates for within-herd BVDV transmission rates that are either based on expert opinion or adapted from other dairy herd simulation models presented in the literature. There is currently little information on the transmission rates for BVDV in extensively grazed beef herds partly due to the logistical challenges in obtaining longitudinal data of individual animal’s seroconversion, and it may not be appropriate to apply the same transmission rates from intensive dairy herds given the significant differences in herd demographics and management. To address this knowledge gap, we measured BVDV antibody levels in 15 replacement heifers in each of 75 New Zealand beef breeding farms after their first calving and again at pregnancy scanning or weaning to check for seroconversion. Among these, data from 9 farms were used to infer the within-herd BVDV transmission rate with an approximate Bayesian computation method. The most probable within-herd BVDV transmission rate was estimated as 0.11 per persistently infected (PI) animal per day with a 95% highest posterior density interval between 0.03 and 0.34. This suggests that BVDV transmission in extensively grazed beef herds is generally slower than in dairy herds where the transmission rate has been estimated at 0.50 per PI animal per day and therefore may not be sufficient to ensure that all susceptible breeding females gain adequate immunity to the virus before the risk period of early pregnancy for generating new PI calves

Factors influencing the performance of voluntary farmer disease reporting in passive surveillance systems: a scoping review

The impacts of exotic disease incursions on livestock industries can be mitigated by having robust surveillance systems in place that decrease the time between disease introduction and detection. An important component of this is having farmers routinely observe their animals for indications of clinical disease, recognise the existence of problems, and then decide to notify their veterinarian or animal health authorities. However, as highlighted by this literature review, farmers are believed to be underreporting clinical events due to factors such as (1) uncertainty around the clinical signs and situations that warrant reporting, (2) fear over the social and economic consequences from both positive and false positive reports, (3) negative beliefs regarding the efficacy and outcomes of response measures, (4) mistrust and dissatisfaction with animal health authorities, (5) absence of sufficiently attractive financial and non-financial incentives for submitting reports, and (6) poor awareness of the procedures involved with the submission, processing, and response to reports. There have been few formal studies evaluating the efficacy of different approaches to increasing farmer engagement with disease reporting. However, there is a recognised need for any proposed solutions to account for farmer knowledge and experience with assessing their own farm situation as well as the different identities, motivations, and beliefs that farmers have about their role in animal health surveillance systems. Empowering farmers to take a more active role in developing these solutions is likely to become even more important as animal health authorities increasingly look to establish public-private partnerships for biosecurity governance

A systematic review of social research data collection methods used to investigate voluntary animal disease reporting behaviour

Voluntary detection of emerging disease outbreaks is considered essential for limiting their potential impacts on livestock industries. However, many of the strategies employed by animal health authorities to capture data on potential emerging disease threats rely on farmers and veterinarians identifying situations of concern and then voluntarily taking appropriate actions to notify animal health authorities. To improve the performance of these systems, it is important to understand the range of socio-cultural factors influencing the willingness of individuals to engage with disease reporting such as trust in government, perceived economic impacts, social stigma, and perceptions of ‘good farming’. The objectives of this systematic review were to assess how different social research methodologies have been employed to understand the role these socio-cultural dimensions play in voluntary disease reporting and to discuss limitations to address in future research. The review uncovered 39 relevant publications that employed a range of quantitative and qualitative methodologies including surveys, interviews, focus groups, scenarios, observations, mixed-methods, interventions, and secondary data analysis. While these studies provided valuable insights, one significant challenge remains eliciting accurate statements of behaviour and intentions rather than those that reflect desirable social norms. There is scope to develop methodological innovations to study the decision to report animal disease to help overcome the gap between what people say they do and their observable behaviour. A notable absence is studies exploring specific interventions designed to encourage disease reporting. Greater clarity in specifying the disease contexts, behavioural mechanisms and outcomes, and the relationships between them would provide a more theoretically informed and policy relevant understanding of how disease reporting works, for which farmers, and in which disease contexts

A Preliminary Description of Companion Cat, Managed Stray Cat, and Unmanaged Stray Cat Welfare in Auckland, New Zealand Using a 5-Component Assessment Scale

Free-roaming cats are a polarizing issue in New Zealand and there is strong need for a comprehensive evaluation of their welfare to better inform population management decisions. In this study, a 5-component visual health-related welfare assessment scale was developed and piloted on a convenience sample of 213 free-roaming companion cats (CC), 210 managed stray cats (MS), and 253 unmanaged stray cats (UMS) from various locations in Auckland, New Zealand. The welfare assessment was performed through distance observation and consisted of body condition score (BCS); coat condition score; nose and eye discharge score; ear crusting score; and injury score. The majority of cats in all groups appeared generally healthy with no nose or eye discharge, ear crusting, or injuries. Although there were no appreciable differences in the apparent welfare of CC and MS cats, future studies with more robust sampling designs are needed to draw accurate inferences. The scale also requires further validation by comparing the visual observations against more detailed physical examination and biochemical data. Nonetheless, the results from this study provide preliminary information about assessing the health and welfare of stray cats as well as considerations for developing and implementing robust assessment scales

Risk factors for bovine tuberculosis in low incidence regions related to the movements of cattle

BACKGROUND: Bovine tuberculosis (bTB) remains difficult to eradicate from low incidence regions partly due to the imperfect sensitivity and specificity of routine intradermal tuberculin testing. Herds with unconfirmed reactors that are incorrectly classified as bTB-negative may be at risk of spreading disease, while those that are incorrectly classified as bTB-positive may be subject to costly disease eradication measures. This analysis used data from Scotland in the period leading to Officially Tuberculosis Free recognition (1) to investigate the risks associated with the movements of cattle from herds with different bTB risk classifications and (2) to identify herd demographic characteristics that may aid in the interpretation of tuberculin testing results. RESULTS: From 2002 to 2009, for every herd with confirmed bTB positive cattle identified through routine herd testing, there was an average of 2.8 herds with at least one unconfirmed positive reactor and 18.9 herds with unconfirmed inconclusive reactors. Approximately 75% of confirmed bTB positive herds were detected through cattle with no known movements outside Scotland. At the animal level, cattle that were purchased from Scottish herds with unconfirmed positive reactors and a recent history importing cattle from endemic bTB regions were significantly more likely to react positively on routine intradermal tuberculin tests, while cattle purchased from Scottish herds with unconfirmed inconclusive reactors were significantly more likely to react inconclusively. Case-case comparisons revealed few demographic differences between herds with confirmed positive, unconfirmed positive, and unconfirmed inconclusive reactors, which highlights the difficulty in determining the true disease status of herds with unconfirmed tuberculin reactors. Overall, the risk of identifying reactors through routine surveillance decreased significantly over time, which may be partly attributable to changes in movement testing regulations and the volume of cattle imported from endemic regions. CONCLUSIONS: Although the most likely source of bTB infections in Scotland was cattle previously imported from endemic regions, we found indirect evidence of transmission within Scottish cattle farms and cannot rule out the possibility of low level transmission between farms. Further investigation is needed to determine whether targeting herds with unconfirmed reactors and a history of importing cattle from high risk regions would benefit control efforts

Opportunities for refinement in neuroscience: Indicators of wellness and post-operative pain in laboratory macaques

Being able to assess pain in nonhuman primates undergoing biomedical procedures is important for preventing and alleviating pain, and for developing better guidelines to minimise the impacts of research on welfare in line with the 3Rs principle of Refinement. Nonhuman primates are routinely used biomedical models however it remains challenging to recognise negative states, including pain, in these animals. This study aimed to identify behavioural and facial changes that could be used as pain or general wellness indicators in the rhesus macaque (Macaca mulatta). Thirty-six macaques scheduled for planned neuroscience procedures were opportunistically monitored at four times: Pre-Operative (PreOp), Post-Operative (PostOp) once the effects of anaesthesia had dissipated, Pre-Analgesia (PreAn) on the subsequent morning prior to repeating routine analgesic treatment, and Post-Analgesia (PostAn) following administration of analgesia. Pain states were expected to be absent in PreOp, moderate in PreAn, and mild or absent in PostOp and PostAn when analgesia had been administered. Three potential pain indicators were identified: lip tightening and chewing, which were most likely to occur in PreAn, and running which was least likely in PreAn. Arboreal behaviour indicated general wellness, while half-closed eyes, leaning of the head or body shaking indicated the opposite. Despite considerable individual variation, behaviour and facial expressions could offer important indicators of pain and wellness and should be routinely quantified, and appropriate interventions applied to prevent or alleviate pain, and promote positive welfare

Probing empirical contact networks by simulation of spreading dynamics

Disease, opinions, ideas, gossip, etc. all spread on social networks. How these networks are connected (the network structure) influences the dynamics of the spreading processes. By investigating these relationships one gains understanding both of the spreading itself and the structure and function of the contact network. In this chapter, we will summarize the recent literature using simulation of spreading processes on top of empirical contact data. We will mostly focus on disease simulations on temporal proximity networks -- networks recording who is close to whom, at what time -- but also cover other types of networks and spreading processes. We analyze 29 empirical networks to illustrate the methods

Controlling infectious disease through the targeted manipulation of contact network structure

AbstractIndividuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation