Bite Events Research Articles

Retrospective exploratory evaluation of individual pigs' behaviour involved in tail biting during rearing and fattening.

Tail biting is one of the biggest welfare problems in pigs. However, depending on the individuals involved (e.g., tail biter/victim), pigs seem to change their behaviour prior to tail biting events, which raises the possibility of early detection and thus prediction and prevention of tail biting. In this retrospective explorative study, we used datasets from four different studies with 9 trials of rearing (4 pens/trial with 24 pigs/pen) and fattening (8 pens/trial with 12 pigs/pen) that focused on the exploration behaviour of undocked pigs towards plant-based enrichment materials. From this dataset, we identified 8 pens from rearing (n = 192 pigs) and 6 pens from fattening (n = 72 pigs) in which individual tail biters were identified. From this dataset, we investigated whether any a priori behavioural changes in exploration or feeding could be identified with respect to tail biting. Furthermore, the effects of weight parameters from suckling to fattening were examined. Using linear mixed effects models, we found that exploration duration was linked to days prior to tail biting in rearing, depending on CatPig (category of pigs: biter, victim, neutral pig) (P = 0.001), in fattening independent of CatPig (P<0.0001), and by duration, amount and frequency of feed consumption in fattening (P<0.0001). Some weight parameters covaried with CatPig in rearing (weight-gain suckling: P = 0.0018; weaning weight: P = 0.019) and fattening (weaning weight: P = 0.07; start weight at fattening: P = 0.03; weight-gain rearing: P = 0.02). Suitable indicators for future early detection trials of tail biting could be exploration duration in rearing and fattening and feeding data in fattening. Moreover, weight parameters in rearing and fattening and exploration duration in rearing may be used to identify individual pigs that might become tail biters in an upcoming tail biting event. The retrospective explorative nature of our analysis revealed interesting patterns; however, further studies are needed to confirm our findings.

Exposing tail biters by automatic scream detection

Tail biting is a major problem in pig husbandry and early intervention is essential to maintain animal health and welfare. To facilitate early identification of tail biters a detector software was created that can detect scream-linked biting events through analyzing video and audio recordings.Undocked weaner pigs housing in different pens and batches were recorded for a duration of 39 days. Scream-linked tail biting events were firstly identified manually and then automatically through the developed detector by analyzing the audio track of the video recordings. The detector's performance was evaluated by testing different sensitivity parameters (e.g., loudness threshold, call duration, frequency range).In four pens (748 h), a total of 2,898 screams were manually detected, with 52.8 % caused by tail biting. In the second step, 89.9 % of the detected screams were classified correctly as screams by the detector (precision 0.81–1.00). From the detected screams, 64.0 % were caused by tail biting. The detector automatically analyzes the latest videos in user-defined periods and sends warning messages if a threshold of screams per hour is exceeded. Then, biters can be identified manually using the detector extracted incidence video clips.In conclusion, automatic analysis of pig screams has high potential as an early intervention tool by detecting tail biting events followed by evaluation of time synchronized video clips for biter identification.

Detecting tail biters by monitoring pig screams in weaning pigs

Early identification of tail biting and intervention are necessary to reduce tail lesions and their impact on animal health and welfare. Removal of biters has become an effective intervention strategy, but finding them can be difficult and time-consuming. The aim of this study was to investigate whether tail biting and, in particular, individual biters could be identified by detecting pig screams in audio recordings. The study included 288 undocked weaner pigs housed in six pens in two batches. Once a tail biter (n = 7) was identified by visual inspection in the stable and removed by the farm staff, the previous days of video and audio recordings were analyzed for pig screams (sudden increase in loudness with frequencies above 1 kHz) and tail biting events until no biting before the removal was observed anymore. In total, 2893 screams were detected in four pens where tail biting occurred. Of these screams, 52.9% were caused by tail biting in the observed pen, 25.6% originated from other pens, 8.8% were not assignable, and 12.7% occurred due to other reasons. In case of a tail biting event, screams were assigned individually to biter and victim pigs. Based on the audio analysis, biters were identified between one and nine days prior to their removal from the pen after visual inspection. Screams were detected earlier than the increase in hanging tails and could therefore be favored as an early warning indicator. Analyzing animal vocalization has potential for monitoring and early detection of tail biting events. In combination with individual marks and automatic analysis algorithms, biters could be identified and tail biting efficiently reduced. In this way, biters can be removed earlier to increase animal health and welfare.

DENTAL APPROACH IN ONCOLOGICAL INTENSIVE CARE UNIT: A MOUTH PROTECTOR FOR A PATIENT WITH NEUROLOGICAL METASTASIS.

This report demonstrates the role of the dental surgeon in the diagnosis and treatment of trauma to the oral mucosa, in a 55-year-old male patient admitted to an oncology intensive care unit after removal of a metastatic tumor. He needed neuromuscular beta-blockers, sedation, vasoactive drugs, and orotracheal intubation. During the inpatient period, he developed involuntary biting, leading to bleeding ulcers on the mucous membranes and tongue, even though he was sedated. After the dental procedure, the diagnosis was carried out through clinical and laboratory tests, and a mouthpiece was made to protect the oral structures and conserve the tracheal tube. This procedure was associated with hygiene, using 0.12% chlorhexidine, an application of vitamin E, and photobiomodulation using a low-level laser. In conclusion, the installation of the protector leads to more comfort and fewer bite events, but it does not reduce the lesions resulting from the clinical condition. This report demonstrates the role of the dental surgeon in the diagnosis and treatment of trauma to the oral mucosa, in a 55-year-old male patient admitted to an oncology intensive care unit after removal of a metastatic tumor. He needed neuromuscular beta-blockers, sedation, vasoactive drugs, and orotracheal intubation. During the inpatient period, he developed involuntary biting, leading to bleeding ulcers on the mucous membranes and tongue, even though he was sedated. After the dental procedure, the diagnosis was carried out through clinical and laboratory tests, and a mouthpiece was made to protect the oral structures and conserve the tracheal tube. This procedure was associated with hygiene, using 0.12% chlorhexidine, an application of vitamin E, and photobiomodulation using a low-level laser. In conclusion, the installation of the protector leads to more comfort and fewer bite events, but it does not reduce the lesions resulting from the clinical condition.

Machine learning algorithms can predict tail biting outbreaks in pigs using feeding behaviour records.

Tail biting is a damaging behaviour that impacts the welfare and health of pigs. Early detection of precursor signs of tail biting provides the opportunity to take preventive measures, thus avoiding the occurrence of the tail biting event. This study aimed to build a machine-learning algorithm for real-time detection of upcoming tail biting outbreaks, using feeding behaviour data recorded by an electronic feeder. Prediction capacities of seven machine learning algorithms (Generalized Linear Model with Stepwise Feature Selection, random forest, Support Vector Machines with Radial Basis Function Kernel, Bayesian Generalized Linear Model, Neural network, K-nearest neighbour, and Partial Least Squares Discriminant Analysis) were evaluated from daily feeding data collected from 65 pens originating from two herds of grower-finisher pigs (25-100kg), in which 27 tail biting events occurred. Data were divided into training and testing data in two different ways, either by randomly splitting data into 75% (training set) and 25% (testing set), or by randomly selecting pens to constitute the testing set. In the first data splitting, the model is regularly updated with previous data from the pen, whereas in the second data splitting, the model tries to predict for a pen that it has never seen before. The K-nearest neighbour algorithm was able to predict 78% of the upcoming events with an accuracy of 96%, when predicting events in pens for which it had previous data. Our results indicate that machine learning models can be considered for implementation into automatic feeder systems for real-time prediction of tail biting events.

Antimicrobials in dog-to-dog bite wounds: A retrospective study of 1526 dog bite events (1999-2019).

Although dog-to-dog bite wounds (DBW) are common, few studies worldwide have evaluated antimicrobial usage patterns or appropriateness of use. Report frequency and results of DBW cultures, including antimicrobial susceptibility patterns. Determine the most commonly prescribed antimicrobials and their appropriateness for the treatment of DBW, and if antimicrobial importance is associated with wound severity, clinic type or year. One thousand five hundred twenty-six dog bite events involving 1436 dogs presenting with DBW from 3 Australian university clinics from 1999 to 2019. Retrospective study. Medical records were reviewed for presenting signs, culture and susceptibility testing, antimicrobial treatment, and outcome. A partial proportional odds model was used to determine if use of higher importance antimicrobials was associated with wound severity, clinic, or year. Antimicrobials were prescribed in 88.1% (1344/1526) of DBW. Amoxicillin-clavulanic acid was prescribed in 73.4% (1121/1526) of dogs, followed by first-generation cephalosporins, 18.1% (277/1526). Of a total of 1647 antimicrobial prescriptions, underdosing occurred in 13.4% for AMC (220/1647) and 26.1% (81/310) of dogs prescribed first generation cephalosporins. There was an association between the increased use of high-importance antimicrobials and wound severity (P < .001), antimicrobial polytherapy (P < .001) and year (P < .001). The odds of the clinic with specialists prescribing high-importance antimicrobials compared to those of medium importance for DBW was 82% less than that of a semi-rural, mixed and general practice. Culture and susceptibility (C&S) testing was performed in 1.8% of dogs. Empirical use of amoxicillin-clavulanic acid was common for DBW. Increasing wound severity was associated with greater use of high-importance antimicrobials. While C&S testing was rarely performed, routine susceptibility profiles are recommended to optimize antimicrobial stewardship.

Forensic Death Investigations of Dog Bite Injuries in 31 Cats.

Simple SummaryFatal dog bite injuries are common in free-ranging cats in Taiwan. The causes of death of these cats are sometimes speculated to be animal cruelty by the general public. To persuade the public and ease speculation, we document and summarize the features of dog bite injuries and further develop a method for canine DNA identification. Performing forensic necropsies on 31 cats with dog bite injuries, we found that puncture wounds, linear or small, round contusions/abrasions, and lacerations/avulsions are characteristic bite-related injuries. A preference for specific body regions was not observed. Using DNA samples from wound swabs and hair remains, we identified canine DNA in 27.3% of cases. This study provides an applicable method for canine DNA identification in cats and reference data for future veterinary forensic investigations of dog bite injuries.Animal bite injuries are common in free-ranging cats in Taiwan, and most fatal animal bite events are presumed to be caused by dogs. However, speculation regarding animal abuse may occur when carcasses with prominent injuries are found by members of the general public. Local animal protection offices and veterinary clinicians sometimes face difficulties in convincing these individuals by identifying specific features of dog bite injuries in cat carcasses. Therefore, the present study analyzed injury patterns and distribution in 31 necropsied cats with animal bite injuries, and applied deoxyribonucleic acid (DNA) analysis for canine DNA identification in 13 cats. The main necropsy findings included puncture wounds (26 (83.9%)), linear or small, round contusions/abrasions (20 (64.5%)), lacerations/avulsions (17 (54.8%)), abdominal wall rupture/laceration (19 (61.3%)), herniation (16 (51.6%)), fractures (21 (67.7%)), broken claws (16 (51.6%)), and hair tufts on the body surface (28 (90.3%)). The most-commonly injured regions were the ventral thorax and axilla (23 (74.2%)), hind limbs (22 (71.0%)), shoulder-to-dorsal thorax (21 (67.7%)), back and flank (20 (64.5%)), abdomen (19 (61.3%)), neck (19 (61.3%)), and hip/tail/perineum (17 (54.8%)). Canine mitochondrial DNA was identified in 3 out of 11 cases (27.3%) that were sampled using wound swabs and in 4 out of 5 cases that had hair entrapped in broken claws. In conclusion, this study determined the distribution and features of dog bite injuries in cats and developed an elemental method using trace evidence for DNA identification in animal bites.

Bite traces in a sauropod rib from the Upper Cretaceous São José do Rio Preto Formation (Bauru Basin), Brazil

ABSTRACT By studying fossil bite traces, we can reconstruct the behaviour of extinct organisms and better understand past communities, environments, and ecosystems. In this paper, we analyse bite traces on a fragmented sauropod rib from the Upper Cretaceous of the Bauru Basin, southeastern Brazil. The fossil was collected in the Ibirá municipality, São Paulo State, in the strata of the São José do Rio Preto Formation (Santonian-?Maastrichtian). The analysed specimen displays nine tooth drag traces on its external surface, produced by six or seven biting events. The traces consist of shallow linear grooves, with tapered ends and a serrated or smooth edge morphology. They can be classified as Linichnus serratus, Linichnus bromleyi, and Knethichnus parallelum and were produced by an organism with ziphodont dentition, probably an Abelisauridae. This work adds to the knowledge of the Bauru Basin palaeoecology and palaeobiology and expands the record of Mordichnia of Gondwana.

Diurnal biting of malaria mosquitoes in the Central African Republic indicates residual transmission may be “out of control”

Malaria control interventions target nocturnal feeding of the Anopheles vectors indoors to reduce parasite transmission. Mass deployment of insecticidal bed nets and indoor residual spraying with insecticides, however, may induce mosquitoes to blood-feed at places and at times when humans are not protected. These changes can set a ceiling to the efficacy of these control interventions, resulting in residual malaria transmission. Despite its relevance for disease transmission, the daily rhythmicity of Anopheles biting behavior is poorly documented, most investigations focusing on crepuscular hours and nighttime. By performing mosquito collections 48-h around the clock, both indoors and outdoors, and by modeling biting events using circular statistics, we evaluated the full daily rhythmicity of biting in urban Bangui, Central African Republic. While the bulk of biting by Anopheles gambiae, Anopheles coluzzii, Anopheles funestus, and Anopheles pharoensis occurred from sunset to sunrise outdoors, unexpectedly ∼20 to 30% of indoor biting occurred during daytime. As biting events did not fully conform to any family of circular distributions, we fitted mixtures of von Mises distributions and found that observations were consistent with three compartments, corresponding indoors to populations of early-night, late-night, and daytime-biting events. It is not known whether these populations of biting events correspond to spatiotemporal heterogeneities or also to distinct mosquito genotypes/phenotypes belonging consistently to each compartment. Prevalence of Plasmodium falciparum in nighttime- and daytime-biting mosquitoes was the same. As >50% of biting occurs in Bangui when people are unprotected, malaria control interventions outside the domiciliary environment should be envisaged.

Network analysis of tail-biting in pigs – the impact of missed biting events on centrality parameters

AbstractWith social network analysis, group structures of animals can be studied. However, underlying behavioural observations face problems of missing events or deviations between observers. The current study analysed the robustness of node-level network parameters based on tail-biting observations in pigs affected by missed events. Real observations of one observer were used as a gold standard to build true networks and to compare two sets of erroneous networks to them. The first set consisted of networks from different observers of the same data basis. The second set consisted of networks with a fixed error rate (random samples of the gold standard). The stability of the ranking order was used as an indication of accuracy (range 0–1; ≥0.49 good accuracy; ≥0.81 very good accuracy). Comparing observers with true networks yielded overall bad accuracy scores. Generally, outgoing network parameters (active: biting) provided better accuracy scores than ingoing network parameters (passive: being bitten). The results of sampled networks showed decreasing accuracy scores with increasing error rates. At the same error rate, longer observation periods yielded better accuracy scores. For sampled networks, differences between outgoing and ingoing network parameters were more distinct and local parameters (direct contacts) provided better accuracy scores than global parameters (direct and indirect contacts). Overall, sampled networks with 3/10 missed events yielded good to very good accuracy. As networks with more observations handle missed events better, studies of behavioural observations always need to evaluate the required accuracy and feasible workload. The current study gives insights in the accurate estimation of behavioural observations.

A VetCompass Australia Study of Antimicrobial Use in Dog-to-Dog Bite Wounds (1998-2018).

Although dog-to-dog bite wounds (DBW) are a common presentation to veterinary clinics, antimicrobial prescribing habits of Australian clinics have not been reported. This study determined the frequency and results of DBW cultures; antimicrobial selection; and importance class of antimicrobials prescribed relative to wound severity, geographic location, or year. A systematic sample of 72,507 patient records was retrieved from the VetCompass Australia database. Records for 1713 dog bite events involving 1655 dogs were reviewed for presenting signs, results of culture and susceptibility testing (C&S), antimicrobial treatment, geographical location, and outcome. A crossed random effects multivariable logistic regression model was used to determine if antimicrobial importance was associated with wound severity, year, and location, and to assess the differences in antimicrobial prescription between geographical locations, clinics, and veterinarians. Antimicrobials were prescribed in 86.1% of DBW. Amoxicillin-clavulanic acid was prescribed in 70% (1202/1713) with underdosing in 15.8% (191/1202). High-importance antimicrobial use was associated with wound severity (p < 0.001), year category (p = 0.007), and surgery (p = 0.03). C&S testing was recorded as having been performed in only one case. Differences in individual veterinarian prescribing habits were stronger than the clinic culture, suggesting that education utilizing clinic-wide antimicrobial guidelines may aid in improving antimicrobial stewardship.

Análise retrospectiva de mordidas de cães no sul da Itália

ABSTRACT: Dog bite is one of the major public health problems involving people worldwide. Although, several studies have investigated this phenomenon in different countries, little information about the incidence of dog bite episodes in Italy is available. We analysed data about dog biting events between 2010 and 2019 provided by the CRIUV, the Regional Reference Centre for Veterinary Urban Hygiene in the largest city of Southern Italy, namely. Naples. We observed severe and profound inconsistencies in the data collection that reveal structural and significant weaknesses of the current data collection system. Given the multifactorial nature of dog bite, we highlight the need to improve the gathering of all the information related to the factors affecting the occurrence of biting episodes for an accurate assessment of the biting phenomenon.

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso

BackgroundImproving the knowledge and understanding of the environmental determinants of malaria vector abundance at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work is aimed at exploring the environmental tenets of human-biting activity in the main malaria vectors (Anopheles gambiae s.s., Anopheles coluzzii and Anopheles funestus) in the health district of Diébougou, rural Burkina Faso.MethodsAnopheles human-biting activity was monitored in 27 villages during 15 months (in 2017–2018), and environmental variables (meteorological and landscape) were extracted from high-resolution satellite imagery. A two-step data-driven modeling study was then carried out. Correlation coefficients between the biting rates of each vector species and the environmental variables taken at various temporal lags and spatial distances from the biting events were first calculated. Then, multivariate machine-learning models were generated and interpreted to (i) pinpoint primary and secondary environmental drivers of variation in the biting rates of each species and (ii) identify complex associations between the environmental conditions and the biting rates.ResultsMeteorological and landscape variables were often significantly correlated with the vectors’ biting rates. Many nonlinear associations and thresholds were unveiled by the multivariate models, for both meteorological and landscape variables. From these results, several aspects of the bio-ecology of the main malaria vectors were identified or hypothesized for the Diébougou area, including breeding site typologies, development and survival rates in relation to weather, flight ranges from breeding sites and dispersal related to landscape openness.ConclusionsUsing high-resolution data in an interpretable machine-learning modeling framework proved to be an efficient way to enhance the knowledge of the complex links between the environment and the malaria vectors at a local scale. More broadly, the emerging field of interpretable machine learning has significant potential to help improve our understanding of the complex processes leading to malaria transmission, and to aid in developing operational tools to support the fight against the disease (e.g. vector control intervention plans, seasonal maps of predicted biting rates, early warning systems).Graphical abstract

Horse foraging behavior detection using sound recognition techniques and artificial intelligence

Wearable sensing technologies can be used for precision livestock production and to study foraging strategies to better understand the relationships between herbivores, vegetation, and landscape. In this context, monitoring grazing behavior (i.e. chew and bite events) can provide critical information for livestock management. This study presents a computational tool that utilizes wearable sensing and deep learning to distinguish chew and bite events in horses. A micro camera equipped with a microphone (0–18 kHz) was used to obtain video/audio data from horses during grazing. The collected audio data were treated in a pre-processing filtering step, then used to train a recurrent neural network (RNN) with a long short-term memory (LSTM) layer to detect and distinguish chews, bites, and noise events. A post-processing sliding window technique was used to filter events with low confidence levels and lengths. Initial evaluation of this system showed an accuracy of 88.64% for bite identification and an accuracy of 94.13% for chew identification. The distinction between events and evaluation of responses to different pasture species and structure can provide useful information on the plant-animal interface. That is aligned to information such as bite rate, bite mass, and grazing time, and can help determine management strategies that optimize intake and provide data for modeling foraging behavior to predict pasture use and animal performance.

Marine spatial planning provides a comprehensive framework for building evidence-based shark risk management policies with sea-users

Marine spatial planning (MSP), a process aimed at negotiating the spatial allocation of human activities at sea, has to integrate new challenges arising from growing human activities and their impacts on threatened marine ecosystems. Yet, human–wildlife interactions that result in threat to humans are rarely explicitly addressed in planning and almost not at all in MSP. Rare events of unprovoked shark bites can significantly impact local economies while leading to polarized social debates that often hinder the development of evidence-based shark risk public policy. Here, we suggest an approach for integrating shark risk and its management into MSP. The method addresses simultaneously the spatial, social, and ecological components of shark risk and its inherent uncertainties. The approach is applied on Reunion Island case study where shark risk management is implemented as a response to a rapid increase in the frequency of shark bite events over the past decade. Similar to other countries where shark risk management is implemented, sharks’ removal is in the heart of social debate in Reunion Islands (3860 shark fishing operations in 5 years) and data gaps provide a fertile ground for alternative discourses and social conflicts about shark risk. Through a structured public consultation involving 200 stakeholders we demonstrate how MSP can be used to address shark risk while considering multiple sea-uses and conservation objectives. The results suggest that the approach is ideal, both for integrating shark risk as a driver to the MSP process, and for developing a transparent, sustainable and evidence-based shark risk public policy as it places shark risk management within a broader social-ecological spectrum of stakes.

Prediction of Tail Biting Events in Finisher Pigs from Automatically Recorded Sensor Data.

Simple SummaryTail biting is a major animal welfare issue within modern pig production, and tail biting should be prevented whenever possible. If the farmer could get an alarm when a pen of pigs is at high risk of developing tail damage, the farmer would be able to take timely action to prevent tail damage in specific pens. In the current investigation, a method for prediction of tail biting events was developed and tested in a real-life setting. The method used changes in pigs’ drinking behaviour and in the temperature of the pen. The method was able to alarm the farmer about 12 of the 14 tail biting events prior to serious tail damage. However, the farmer did also get false alarms on 30% of the days without tail biting events, which is not optimal. Thus, the farmer could use the alarms as indications of which pens to pay greater attention to. The next step could be to expand the method to include behavioural changes that are more specific to tail biting such as changes in the pigs’ tail posture.Tail biting in pigs is an animal welfare problem, and tail biting should be prevented from developing into tail damage. One strategy could be to predict events of tail biting so that the farmer can make timely interventions in specific pens. In the current investigation, sensor data on water usage (water flow and activation frequency) and pen temperature (above solid and slatted floor) were included in the development of a prediction algorithm for tail biting. Steps in the development included modelling of data sources with dynamic linear models, optimisation and training of artificial neural networks and combining predictions of the single data sources with a Bayesian ensemble strategy. Lastly, the Bayesian ensemble combination was tested on a separate batch of finisher pigs in a real-life setting. The final prediction algorithm had an AUC > 0.80, and thus it does seem possible to predict events of tail biting from already available sensor data. However, around 30% of the no-event days were false alarms, and more event-specific predictors are needed. Thus, it was suggested that farmers could use the alarms to point out pens that need greater attention.

Detecting Meals In the Wild Using the Inertial Data of a Typical Smartwatch.

Automated and objective monitoring of eating behavior has received the attention of both the research community and the industry over the past few years. In this paper we present a method for automatically detecting meals in free living conditions, using the inertial data (acceleration and orientation velocity) from commercially available smartwatches. The proposed method operates in two steps. In the first step we process the raw inertial signals using an End-to-End Neural Network with the purpose of detecting the bite events throughout the recording. During the next step, we process the resulting bite detections using signal processing algorithms to obtain the final meal start and end timestamp estimates. Evaluation results obtained from our Leave One Subject Out experiments using our publicly available FIC and FreeFIC datasets, exhibit encouraging results by achieving an F1/Average Jaccard Index of 0.894/0.804.

The influence of poverty and rabies knowledge on healthcare seeking behaviors and dog ownership, Cameroon.

BackgroundRabies is a fatal encephalitis caused by lyssaviruses, with most human cases worldwide resulting from rabid dog bites. Although effective animal and human vaccines have been available for over 100 years, control efforts have not been adequately implemented on the global scale and rabies remains one of the greatest global zoonotic threats to human health. We conducted a knowledge, attitudes and practices survey in Northern Cameroon to describe dog ownership characteristics, rates of dog bites, and post-bite healthcare seeking behaviors.MethodsThe survey was performed in four rural Cameroonian communities. A structured community-based questionnaire was conducted over a 20-day period in April 2010, and focused on socio-economic factors correlated with gaps in rabies knowledge. Information pertaining to socio-demographics, as well as attitudes and practices with regard to animal bites and bite treatment practices were recorded. Characteristics of dog ownership such as dog confinement, resources provided to dogs, and dog vaccination status were examined. Human to dog ratios were compared on a linear scale to poverty scores by community. When applicable, 2-tailed Chi-square tests or Fisher’s exact tests were calculated to determine relationships between variables. We also used One-way Analysis of Variance (ANOVA) to identify associations between rabies knowledge and wealth with dog ownership, dog vaccination, and human healthcare seeking behaviors. Independent variables were evaluated using multivariate logistic regression analysis.ResultsA total of 208 households were enrolled. Respondents were predominantly male (68.3%), with a median age of 43.6 years. Eighty-four households (39.9%) reported owning a total of 141 dogs (human dog ratio 10.4:1). The majority of dogs (61%) were allowed to roam freely. A history of rabies vaccination was reported for 30.8% of owned dogs. Respondents reported 11 bites during the two years preceding the survey (annual bite incidence was 2.6% [95% CI 1.4%– 4.6%]). Only one person (9.1%) received rabies post-exposure prophylaxis (PEP), and none described symptoms of clinical illness consistent with rabies. Respondents who indicated that they would seek medical care and PEP after a dog bite had higher average wealth and rabies knowledge index scores (p = 0.01 and 0.04, respectively). Respondents who indicated that they would seek care from a traditional healer had significantly lower wealth scores, but not significantly different knowledge scores (p < 0.01 and p = 0.49, respectively).ConclusionsIn the communities evaluated, the majority of dogs were allowed to roam freely and had no history of rabies vaccination; factors that favor enzootic transmission of canine rabies virus. We also identified a strong relationship between poverty and dog ownership. Bite events were relatively common among respondents, and very few victims reported utilizing health services to treat wounds. Increased wealth and knowledge were significantly associated with increased likelihood that a respondent would seek medical care and post-exposure prophylaxis. These findings indicate the need for educational outreach to raise awareness of dog rabies and proper prevention measures.

Environmental and anthropogenic factors affecting the increasing occurrence of shark-human interactions around a fast-developing Indian Ocean island

Understanding the environmental drivers of interactions between predators and humans is critical for public safety and management purposes. In the marine environment, this issue is exemplified by shark-human interactions. The annual shark bite incidence rate (SBIR) in La Réunion (Indian Ocean) is among the highest in the world (up to 1 event per 24,000 hours of surfing) and has experienced a 23-fold increase over the 2005–2016 period. Since 1988, 86% of shark bite events on surfers involved ocean-users off the leeward coast, where 96% of surfing activities took place. We modeled the SBIR as a function of environmental variables, including benthic substrate, sea temperature and period of day. The SBIR peaked in winter, during the afternoon and dramatically increased on coral substrate since the mid-2000s. Seasonal patterns of increasing SBIR followed similar fluctuations of large coastal shark occurrences (particularly the bull shark Carcharhinus leucas), consistent with the hypothesis that higher shark presence may result in an increasing likelihood of shark bite events. Potential contributing factors and adaptation of ocean-users to the increasing shark bite hazard are discussed. This interdisciplinary research contributes to a better understanding of shark-human interactions. The modeling method is relevant for wildlife hazard management in general.

Estimation of Dog-Bite Risk and Related Morbidity Among Personnel Working With Military Dogs.

Soldiers serving in the Israel Defense Force Military Working Dogs (MWD) Unit spend many hours taming dogs' special skills, taking them on combat missions, and performing various dogkeeping activities. During this intensive work with the aggressive military dogs, bites are common, and some of them result in permanent disability. However, this phenomenon has not been quantified or reported as an occupational hazard. This was a retrospective cohort study based on self-administered questionnaires. Information was collected about soldiers' baseline demographics, duration of the experience of working with dogs, total number of bites they had, circumstances of bite events, and complications and medical treatment of each bite. Bite risk was quantified by incidence, mean time to first bite, and a Cox proportional hazards model. Rates of complications and the medical burden of bites were compared between combat soldiers and noncombat dogkeepers. Bite locations were presented graphically. Seventy-eight soldiers participated and reported on 139 bites. Mean time of working with dogs was 16 months (standard deviation, ±9.4 months). Overall bite incidence was 11 bites per 100 person-months; the mean time to first bite event was 6.3 months. The Cox proportional hazards model showed that none of baseline characteristics significantly increased bite hazard. About 90% of bites occurred during routine activities, and 3.3% occurred on combat missions. Only in 9% of bite events did soldiers observed the safety precautions code. Bite complications included fractures, need for intravenous antibiotic treatment and surgical repair, prominent scarring, diminished sensation, and stiffness of proximal joints. Bite complications were similar between combat soldiers and dogkeepers. Most bites (57%) were located on hands and arms. MWD bites are an occupational hazard resulting in significant medical burden. Hands and arms were most common bite locations. Observance of safety precautions may be the most appropriate first-line preventive intervention. Barrier protection of upper extremities may reduce bite severity and complication rates.