Unmanned aircraft systems for studying spatial abundance of ungulates: relevance to spatial epidemiology

Movement-driven modelling reveals new patterns in disease transmission networks

Interspecific interactions are highly relevant in the potential transmission of shared pathogens in multi-host systems. In recent decades, several technologies have been developed to study pathogen transmission, such as proximity loggers, GPS tracking devices and/or camera traps. Despite the diversity of methods aimed at detecting contacts, the analysis of transmission risk is often reduced to contact rates and the probability of transmission given the contact. However, the latter process is continuous over time and unique for each contact, and is influenced by the characteristics of the contact and the pathogen's relationship with both the host and the environment. Our objective was to assess whether a more comprehensive approach, using a movement-based model which assigns a unique transmission risk to each contact by decomposing transmission into contact formation, contact duration and host characteristics, could reveal disease transmission dynamics that are not detected with more traditional approaches. The model was built from GPS-collar data from two management systems in Spain where animal tuberculosis (TB) circulates: a national park with extensively reared endemic cattle, and an area with extensive free-range pigs and cattle farms. In addition, we evaluated the effect of the GPS device fix rate on the performance of the model. Different transmission dynamics were identified between both management systems. Considering the specific conditions under which each contact occurs (i.e. whether the contact is direct or indirect, its duration, the hosts characteristics, the environmental conditions, etc.) resulted in the identification of different transmission dynamics compared to using only contact rates. We found that fix intervals greater than 30 min in the GPS tracking data resulted in missed interactions, and intervals greater than 2 h may be insufficient for epidemiological purposes. Our study shows that neglecting the conditions under which each contact occurs may result in a misidentification of the real role of each species in disease transmission. This study describes a clear and repeatable framework to study pathogen transmission from GPS data and provides further insights to understand how TB is maintained in multi-host systems in Mediterranean environments.

The method matters. A comparative study of biologging and camera traps as data sources with which to describe wildlife habitat selection

Habitat use is a virtually universal activity among animals and is highly relevant as regards designing wildlife management and conservation actions. This has led to the development of a great variety of methods to study it, of which resource selection functions combined with biologging-derived data (RSF) is the most widely used for this purpose. However this approach has some constraints, such as its invasiveness and high costs. Analytical approaches taking into consideration imperfect detection coupled with camera trap data (IDM) have, therefore, emerged as a non-invasive cost-effective alternative. However, despite the fact that both approaches (RSF and IDM) have been used in habitat selection studies, they should also be comparatively assessed. The objective of this work is consequently to assess them from two perspectives: explanatory and predictive. This has been done by analyzing data obtained from camera traps (60 sampling sites) and biologging (17 animals monitored: 7 red deer Cervus elaphus, 6 fallow deer Dama dama and 4 wild boar Sus scrofa) in the same periods using IDM and RSF, respectively, in Doñana National Park (southern Spain) in order to explain and predict habitat use patterns for three studied species. Our results showed discrepancies between the two approaches, as they identified different predictors as being the most relevant to determine species intensity of use, and they predicted spatial patterns of habitat use with a contrasted level of concordance, depending on species and scale. Given these results and the characteristics of each approach, we suggested that although partly comparable interpretations can be obtained with both approaches, they are not equivalent but rather complementary. The combination of data from biologging and camera traps would, therefore, appear to be suitable for the development of an analytical framework with which to describe and characterise the habitat use processes of wildlife.

Artificial intelligence for automated detection of large mammals creates path to upscale drone surveys

Imagery from drones is becoming common in wildlife research and management, but processing data efficiently remains a challenge. We developed a methodology for training a convolutional neural network model on large-scale mosaic imagery to detect and count caribou (Rangifer tarandus), compare model performance with an experienced observer and a group of naïve observers, and discuss the use of aerial imagery and automated methods for large mammal surveys. Combining images taken at 75 m and 120 m above ground level, a faster region-based convolutional neural network (Faster-RCNN) model was trained in using annotated imagery with the labels: "adult caribou", "calf caribou", and "ghost caribou" (animals moving between images, producing blurring individuals during the photogrammetry processing). Accuracy, precision, and recall of the model were 80%, 90%, and 88%, respectively. Detections between the model and experienced observer were highly correlated (Pearson: 0.96-0.99, P value < 0.05). The model was generally more effective in detecting adults, calves, and ghosts than naïve observers at both altitudes. We also discuss the need to improve consistency of observers' annotations if manual review will be used to train models accurately. Generalization of automated methods for large mammal detections will be necessary for large-scale studies with diverse platforms, airspace restrictions, and sensor capabilities.

Environmental factors driving fine-scale ixodid tick abundance patterns

Tick abundance is an essential demographic parameter to infer tick-borne pathogen transmission risks. Spatiotemporal patterns of tick abundance are heterogeneous, so its determinants at small spatial scales need to be understood to reduce their negative effects on hosts. Current knowledge of these determinants is scarce, especially in Mediterranean environments, limiting the possibilities for designing efficient tick control strategies. With the goal of unravelling tick abundance determinants and informing new tick management strategies, we estimated tick burdens on 1965 wild ungulates in Doñana National Park, Spain, annually between 2010 and 2020. Under the hypothesis of a predominant host influence on tick abundance, we modelled the burdens of Rhipicephalus annulatus, Hyalomma lusitanicum, and Ixodes ricinus with relevant predictors grouped into four factors: i) environment; ii) host population; iii) host individual; and iv) land-use. Generalized linear mixed models with a zero-inflated negative binomial distribution were built. Additionally, we analysed the differential contribution to abundance of each factor by deviance partitioning. We finally estimated the similarity in the environmental space of tick species by analysing their niche overlap with the environmental principal component analysis method. Our work hypothesis was confirmed for R. annulatus and H. lusitanicum, but we found that tick abundance at a fine spatial scale is jointly driven by multiple drivers, including all four factors considered in this study. This result points out that understanding the demography of ticks is a complex multifactorial issue, even at small spatial scales. We found no niche differences between the three tick species at the study spatial scale, thus showing similar host and environmental dependencies. Overall results identify that host aggregation areas displaying environmentally favourable traits for ticks are relevant tick and vector-borne pathogen transmission hotspots. Our findings will facilitate the design of new strategies to reduce the negative effects of tick parasitism.

Eyes on the herd: Quantifying ungulate density from satellite, unmanned aerial systems, and GPScollar data

Novel approaches to quantifying density and distributions could help biologists adaptively manage wildlife populations, particularly if methods are accurate, consistent, cost-effective, rapid, and sensitive to change. Such approaches may also improve research on interactions between density and processes of interest, such as disease transmission across multiple populations. We assess how satellite imagery, unmanned aerial system (UAS) imagery, and Global Positioning System (GPS) collar data vary in characterizing elk density, distribution, and count patterns across times with and without supplemental feeding at the National Elk Refuge (NER) in the US state of Wyoming. We also present the first comparison of satellite imagery data with traditional counts for ungulates in a temperate system. We further evaluate seven different aggregation metrics to identify the most consistent and sensitive metrics for comparing density and distribution across time and populations. All three data sources detected higher densities and aggregation locations of elk during supplemental feeding than non-feeding at the NER. Kernel density estimates (KDEs), KDE polygon areas, and the first quantile of interelk distances detected differences with the highest sensitivity and were most highly correlated across data sources. Both UAS and satellite imagery provide snapshots of density and distribution patterns of most animals in the area at lower cost than GPS collars. While satellite-based counts were lower than traditional counts, aggregation metrics matched those from UAS and GPS data sources when animals appeared in high contrast to the landscape, including brown elk against new snow in open areas. UAS counts of elk were similar to traditional ground-based counts on feed grounds and are the best data source for assessing changes in small spatial extents. Satellite, UAS, or GPS data can provide appropriate data for assessing density and changes in density from adaptive management actions. For the NER, where high elk densities are beneath controlled airspace, GPS collar data will be most useful for evaluating how management actions, including changes in the dates of supplemental feeding, influence elk density and aggregation across large spatial extents. Using consistent and sensitive measures of density may improve research on the drivers and effects of density within and across a wide range of species.

The emergence of marine recreational drone fishing: Regional trends and emerging concerns

Online evidence suggests that there has been an increase in interest of using unmanned aerial vehicles or drones during land-based marine recreational fishing. In the absence of reliable monitoring programs, this study used unconventional publicly available online monitoring methodologies to estimate the growing interest, global extent, catch composition and governance of this practice. Results indicated a 357% spike in interest during 2016 primarily in New Zealand, South Africa and Australia. From an ecological perspective, many species targeted by drone fishers are vulnerable to overexploitation, while released fishes may experience heightened stress and mortality. From a social perspective, the ethics of drone fishing are being increasingly questioned by many recreational anglers and we forecast the potential for increased conflict with other beach users. In terms of governance, no resource use legislation specifically directed at recreational drone fishing was found. These findings suggest that drone fishing warrants prioritised research and management consideration.

Noninvasive Technologies for Primate Conservation in the 21st Century

Observing and quantifying primate behavior in the wild is challenging. Human presence affects primate behavior and habituation of new, especially terrestrial, individuals is a time-intensive process that carries with it ethical and health concerns, especially during the recent pandemic when primates are at even greater risk than usual. As a result, wildlife researchers, including primatologists, have increasingly turned to new technologies to answer questions and provide important data related to primate conservation. Tools and methods should be chosen carefully to maximize and improve the data that will be used to answer the research questions. We review here the role of four indirect methods—camera traps, acoustic monitoring, drones, and portable field labs—and improvements in machine learning that offer rapid, reliable means of combing through large datasets that these methods generate. We describe key applications and limitations of each tool in primate conservation, and where we anticipate primate conservation technology moving forward in the coming years.

Comparing unmanned aerial systems with conventional methodology for surveying a wild white-tailed deer population

Abstract Context Ungulate populations are subject to fluctuations caused by extrinsic factors and require efficient and frequent surveying to monitor population sizes and demographics. Unmanned aerial systems (UAS) have become increasingly popular for ungulate research; however, little is understood about how this novel technology compares with conventional methodologies for surveying wild populations. Aims We examined the feasibility of using a fixed-wing UAS equipped with a thermal infrared sensor for estimating the population density of wild white-tailed deer (Odocoileus virginianus) at the Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota, USA. We compared UAS density estimates with those derived from faecal pellet-group counts. Methods We conducted UAS thermal survey flights from March to April of 2018 and January to March of 2019. Faecal pellet-group counts were conducted from April to May in 2018 and 2019. We modelled deer counts and detection probabilities and used these results to calculate point estimates and bootstrapped prediction intervals for deer density from UAS and pellet-group count data. We compared results of each survey approach to evaluate the relative efficacy of these two methodologies. Key results Our best-fitting model of certain deer detections derived from our UAS-collected thermal imagery produced deer density estimates (WR20204_IE1.gif, 95% prediction interval = 4.32–17.84 deer km−2) that overlapped with the pellet-group count model when using our mean pellet deposition rate assumption (WR20204_IE2.gif, 95% prediction interval = 4.14–11.29 deer km−2). Estimates from our top UAS model using both certain and potential deer detections resulted in a mean density of 13.77 deer km−2 (95% prediction interval = 6.64–24.35 deer km−2), which was similar to our pellet-group count model that used a lower rate of pellet deposition (WR20204_IE3.gif, 95% prediction interval = 6.46–17.65 deer km−2). The mean point estimates from our top UAS model predicted a range of 136.68–273.81 deer, and abundance point estimates using our pellet-group data ranged from 112.79 to 239.67 deer throughout the CCESR. Conclusions Overall, UAS yielded results similar to pellet-group counts for estimating population densities of wild ungulates; however, UAS surveys were more efficient and could be conducted at multiple times throughout the winter. Implications We demonstrated how UAS could be applied for regularly monitoring changes in population density. We encourage researchers and managers to consider the merits of UAS and how they could be used to enhance the efficiency of wildlife surveys.

Networked Unmanned Aerial Vehicles for Surveillance and Monitoring: A Survey

As a typical cyber-physical system, networked unmanned aerial vehicles (UAVs) have received much attention in recent years. Emerging communication technologies and high-performance control methods enable networked UAVs to operate as aerial sensor networks to collect more complete and consistent information with significantly improved mobility and flexibility than traditional sensing platforms. One of the main applications of networked UAVs is surveillance and monitoring, which constitute essential components of a well-functioning public safety system and many industrial applications. Although the existing literature on surveillance and monitoring UAVs is extensive, a comprehensive survey on this topic is lacking. This article classifies publications on networked UAVs for surveillance and monitoring using the targets of interest and analyzes several typical problems on this topic, including the control, navigation, and deployment optimization of UAVs. The related research gaps and future directions are also presented.

Progress in robotics for combating infectious diseases

The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities. We also address some of the open challenges for developing advanced robots that are application oriented, reliable, safe, and rapidly deployable when needed. Last, we look at the ethical use of robots and call for globally sustained efforts in order for robots to be ready for future outbreaks.

A survey of shared pathogens at the domestic-wild ruminants' interface in Doñana National Park (Spain)

A cross-sectional study was carried out to evaluate shared pathogens that can be transmitted by close or non-close contact at the domestic-wild ruminants' interface. During summer-autumn 2015, a total of 138 cattle and 203 wild ruminants (red deer, Cervus elaphus, and fallow deer, Dama dama) were sampled in Doñana National Park (DNP, south-western Spain), a Mediterranean ecosystem well known for the interaction network occurring in the ungulate host community. Pestiviruses, bovine respiratory syncytial virus (BRSV; Bovine orthopneumovirus), bovine herpesvirus 1 (BoHV-1; Bovine alphaherpesvirus 1) and Mycobacterium tuberculosis complex (MTC) were assessed using serological, microbiological and molecular techniques. The overall seroprevalence against viruses in cattle was 2.2% for pestiviruses, 11.6% for BRSV and 27.5% for BoHV-1. No virus-specific antibodies were found in wildlife. MTC incidence in cattle was 15.9%, and MTC seroprevalence in wild ruminants was 14.3%. The same Mycobacterium bovis spoligotypes (SB1232, SB1230 and SB1610) were identified in cattle, red deer and fallow deer. The serological results for the selected respiratory viruses suggest epidemiological cycles only in cattle. Surveillance efforts in multi-host epidemiological scenarios are needed to better drive and prioritize control strategies for shared pathogens.

Long-Term Determinants of the Seroprevalence of Toxoplasma gondii in a Wild Ungulate Community

Toxoplasma gondii is an obligate intracellular protozoan which infects warm-blooded vertebrates, including humans, worldwide. In the present study, the epidemiology of T. gondii was studied in the wild ungulate host community (wild boar, red deer, and fallow deer) of Doñana National Park (DNP, south-western Spain) for 13 years (2005-2018). We assessed several variables which potentially operate in the medium and long-term (environmental features, population, and stochastic factors). Overall, the wild ungulate host community of DNP had high seroprevalence values of T. gondii (STG; % ± confidence interval (CI) 95%; wild boar (Sus scrofa) 39 ± 3.3, n = 698; red deer (Cervus elaphus) 30.7 ± 4.4, n = 423; fallow deer (Dama dama) 29.7 ± 4.2, n = 452). The complex interplay of hosts and ecological/epidemiological niches, together with the optimal climatic conditions for the survival of oocysts that converge in this area may favor the spread of the parasite in its host community. The temporal evolution of STG oscillated considerably, mostly in deer species. The relationships shown by statistical models indicated that several factors determined species patterns. Concomitance of effects among species, indicated that relevant drivers of risk operated at the community level. Our focus, addressing factors operating at broad temporal scale, allows showing their impacts on the epidemiology of T. gondii and its trends. This approach is key to understanding the epidemiology and ecology to T. gondii infection in wild host communities in a context where the decline in seroprevalence leads to loss of immunity in humans.

The wildlife-livestock interface on extensive free-ranging pig farms in central Spain during the "montanera" period

The effective management of shared pathogens between wild ungulates and livestock requires the understanding of the processes of interaction between them. In this work, we studied the interspecific frequency of interaction (ifreq) and its spatiotemporal pattern between wild and domestic ungulates that coexist in free-ranging farms. For this purpose, 6 red deer, 6 wild boar, 8 Iberian pigs and 3 cattle were monitored using GPS devices during the "montanera" period (the period in which Iberian pigs are maintained in extensive conditions to feed on acorn). The ifreq was quantified for two spatiotemporal windows: 30 m - 10 min, for inferring potential direct interactions (short window), and 30 m - 12 days for indirect interactions (large window). Secondly, the variation in the ifreq was modelled with regard to 2 temporal (time of the day and week of the year) and 4 environmental factors (distance to water, distance to vegetation cover, Quercus density and distance to feeding points). The interactions at the short window were scarce (N = 13); however, they were very frequent at the large one (N = 37,429), with the red deer as the species with the greatest involvement in the interactions. Models showed that the time of the day and distance to water were the variables that best predicted the ifreq and they were conditioned by differences in the activity pattern of the targeted species. Food resource availability also predicted the ifreq, especially at the short window and between wild species. The results presented here highlight the role that wild ungulates may play in the transmission of pathogens to extensive livestock in general and pigs in particular and show the epidemiological risk of certain areas, periods of time and management practices (for wildlife and livestock) as well as providing useful information in the prevention of the transmission of shared pathogens.

Mycobacterium tuberculosis complex in wildlife: Review of current applications of antemortem and postmortem diagnosis

Tuberculosis (TB) is a chronic inflammatory and zoonotic disease caused by Mycobacterium tuberculosis complex (MTBC) members, which affects various domestic animals, wildlife, and humans. Some wild animals serve as reservoir hosts in the transmission and epidemiology of the disease. Therefore, the monitoring and surveillance of both wild and domestic hosts are critical for prevention and control strategies. For TB diagnosis, the single intradermal tuberculin test or the single comparative intradermal tuberculin test, and the gamma-interferon test, which is regarded as an ancillary test, are used. Postmortem examination can identify granulomatous lesions compatible with a diagnosis of TB. In contrast, smears of the lesions can be stained for acid-fast bacilli, and samples of the affected organs can be subjected to histopathological analyses. Culture is the gold standard test for isolating mycobacterial bacilli because it has high sensitivity and specificity compared with other methods. Serology for antibody detection allows the testing of many samples simply, rapidly, and inexpensively, and the protocol can be standardized in different laboratories. Molecular biological analyses are also applicable to trace the epidemiology of the disease. In conclusion, reviewing the various techniques used in MTBC diagnosis can help establish guidelines for researchers when choosing a particular diagnostic method depending on the situation at hand, be it disease outbreaks in wildlife or for epidemiological studies. This is because a good understanding of various diagnostic techniques will aid in monitoring and managing emerging pandemic threats of infectious diseases from wildlife and also preventing the potential spread of zoonotic TB to livestock and humans. This review aimed to provide up-to-date information on different techniques used for diagnosing TB at the interfaces between wildlife, livestock, and humans.

Measuring disturbance at swift breeding colonies due to the visual aspects of a drone: a quasi-experiment study

There is a growing body of research indicating that drones can disturb animals. However, it is usually unclear whether the disturbance is due to visual or auditory cues. Here, we examined the effect of drone flights on the behavior of great dusky swifts Cypseloides senex and white-collared swifts Streptoprocne zonaris in 2 breeding sites where drone noise was obscured by environmental noise from waterfalls and any disturbance must be largely visual. We performed 12 experimental flights with a multirotor drone at different vertical, horizontal, and diagonal distances from the colonies. From all flights, 17% caused <1% of birds to temporarily abandon the breeding site, 50% caused half to abandon, and 33% caused more than half to abandon. We found that the diagonal distance explained 98.9% of the variability of the disturbance percentage and while at distances >50 m the disturbance percentage does not exceed 20%, at <40 m the disturbance percentage increase to > 60%. We recommend that flights with a multirotor drone during the breeding period should be conducted at a distance of >50 m and that recreational flights should be discouraged or conducted at larger distances (e.g. 100 m) in nesting birds areas such as waterfalls, canyons, and caves.

Modeling quarantine during epidemics and mass-testing using drones

We extend the classical SIR epidemic spread model by introducing the "quarantined" compartment. We solve (numerically) the differential equations that govern the extended model and quantify how quarantining "flattens the curve" for the proportion of infected population over time. Furthermore, we explore the potential of using drones to deliver tests, enabling mass-testing for the infection; we give a method to estimate the drone fleet needed to deliver the tests in a metropolitan area. Application of our models to COVID-19 spread in Sweden shows how the proposed methods could substantially decrease the peak number of infected people, almost without increasing the duration of the epidemic.

Long-Term Determinants of Tuberculosis in the Ungulate Host Community of Doñana National Park

Animal tuberculosis (TB) is endemic in wild boar (Sus scrofa), red deer (Cervus elaphus), fallow deer (Dama dama) and cattle in south and central Spain. In order to clarify the processes that operate in the medium and long-term, we studied TB at the wildlife–livestock interface in Doñana National Park for 14 years (2006–2018) in relation to host density, stochastic factors (rainfall) and environmental features (e.g., aggregation points such as waterholes). Wild boar showed the highest prevalence of TB (76.7%), followed by red deer (42.5%), fallow deer (14.4%) and cattle (10.7%). We found evidence of relevant epidemiological processes which operate over the long-term and interact with host and community ecology. Interestingly, the effect of high wild boar population density on increased TB rates was mediated by sows, which could determine high incidence in young individuals already in maternal groups. Rainfall significantly determined a higher risk of TB in male red deer, probably mediated by sex-related differences in life history traits that determined more susceptibility and/or exposure in comparison to females. The positive association between the prevalence of TB in fallow deer and cattle may indicate significant interspecies transmission (in either direction) and/or similar exposure to risk factors mediated by ecological overlapping of grazing species. The identification of long-term drivers of TB provided evidence that its control in extensive pastoral systems can only be achieved by targeting all relevant hosts and integrating measures related to all the factors involved, such as: population abundance and the aggregation of wild and domestic ungulates, environmental exposure to mycobacteria, cattle testing and culling campaigns and adjustments of appropriate densities.

Dynamic Network of Interactions in the Wildlife-Livestock Interface in Mediterranean Spain: An Epidemiological Point of View

The correct management of diseases that are transmitted between wildlife and livestock requires a reliable estimate of the pathogen transmission rate. The calculation of this parameter is a challenge for epidemiologists, since transmission can occur through multiple pathways. The social network analysis is a widely used tool in epidemiology due to its capacity to identify individuals and communities with relevant roles for pathogen transmission. In the present work, we studied the dynamic network of interactions in a complex epidemiological scenario using information from different methodologies. In 2015, nine red deer, seven fallow deer, six wild boar and nine cattle were simultaneously monitored using GPS-GSM-Proximity collars in Doñana National Park. In addition, 16 proximity loggers were set in aggregation points. Using the social network analysis, we studied the dynamic network of interactions, including direct and indirect interactions, between individuals of different species and the potential transmission of pathogens within this network. The results show a high connection between species through indirect interactions, with a marked seasonality in the conformation of new interactions. Within the network, we differentiated four communities that included individuals of all the species. Regarding the transmission of pathogens, we observed the important role that fallow deer could be playing in the maintenance and transmission of pathogens to livestock. The present work shows the need to consider different types of methodologies in order to understand the complete functioning of the network of interactions at the wildlife/livestock interface. It also provides a methodological approach applicable to the management of shared diseases.

Free-Ranging Pig and Wild Boar Interactions in an Endemic Area of African Swine Fever

African swine fever virus (ASFV) is spreading throughout Eurasia and there is no vaccine nor treatment available, so the control is based on the implementation of strict sanitary measures. These measures include depopulation of infected and in-contact animals and export restrictions, which can lead to important economic losses, making currently African swine fever (ASF) the greatest threat to the global swine industry. ASF has been endemic on the island of Sardinia since 1978, the longest persistence of anywhere in Eurasia. In Sardinia, eradication programs have failed, in large part due to the lack of farm professionalism, the high density of wild boar and the presence of non-registered domestic pigs (free-ranging pigs). In order to clarify how the virus is transmitted from domestic to wild swine, we examined the interaction between free-ranging pigs and wild boar in an ASF-endemic area of Sardinia. To this end, a field study was carried out on direct and indirect interactions, using monitoring by camera trapping in different areas and risk points. Critical time windows (CTWs) for the virus to survive in the environment (long window) and remain infectious (short window) were estimated, and based on these, the number of indirect interactions were determined. Free-ranging pigs indirectly interacted often with wild boar (long window = 6.47 interactions/day, short window = 1.31 interactions/day) and these interactions (long window) were mainly at water sources. They also directly interacted 0.37 times per day, especially between 14:00 and 21:00 h, which is much higher than for other interspecific interactions observed in Mediterranean scenarios. The highly frequent interactions at this interspecific interface may help explain the more than four-decade-long endemicity of ASF on the island. Supporting that free-ranging pigs can act as a bridge to transmit ASFV between wild boar and registered domestic pigs. This study contributes broadly to improving the knowledge on the estimation of frequencies of direct and indirect interactions between wild and free-ranging domestic swine. As well as supporting the importance of the analysis of interspecific interactions in shared infectious diseases, especially for guiding disease management. Finally, this work illustrates the power of the camera-trapping method for analyzing interspecific interfaces.

Use of drones in clinical microbiology and infectious diseases: current status, challenges and barriers

BACKGROUND

Drones or unmanned aerial vehicles are autonomous or remotely controlled multipurpose aerial vehicles driven by aerodynamic forces and capable of carrying a payload. Whereas initially used exclusively for military purposes, the use of drones has gradually spread into other areas. Given their great flexibility and favourable costs, the use of drones has also been piloted in various healthcare settings.

OBJECTIVES

We briefly summarize current knowledge regarding the use of drones in healthcare, focusing on infectious diseases and/or microbiology when applicable.

SOURCES

Information was sought through PubMed and extracted from peer-reviewed literature published between January 2010 and August 2019 and from reliable online news sources. The search terms 'drones', 'unmanned aerial vehicles', 'microbiology' and 'medicine' were used.

CONTENT

Peer-reviewed literature on the use of drones in healthcare has steadily increased in recent years. Drones have been successfully evaluated in various pilot programmes and are already implemented in some settings for transporting samples and delivering blood, vaccines, medicines, organs, life-saving medical supplies and equipment. In addition, a promising proof-of-concept 'lab-on-a-drone' was recently presented, as well as several pilot studies showing the benefits of drone use in surveillance and epidemiology of infectious diseases.

IMPLICATIONS

The potential for drone use in clinical microbiology, infectious diseases and epidemiology is vast. Drones may help to increase access to healthcare for individuals that might otherwise not benefit from appropriate care due to remoteness and lack of infrastructure or funds. However, factors such as national airspace legislation and legal medical issues, differences in topography and climates, cost-effectiveness, and community attitudes and acceptance in different cultures and societies currently impede the widespread use of drones. Significant cost savings compared with ground transportation, speed and convenience of delivery, and the booming drone sector will probably drive drone implementation in various areas of medicine in the next 5 years.

Spatio-temporal trends in the frequency of interspecific interactions between domestic and wild ungulates from Mediterranean Spain

Controlling infections shared by wildlife and livestock requires the understanding and quantification of interspecific interactions between the species involved. This is particularly important in extensive multi-host systems, in which controlled domestic animals interact with uncontrolled, abundant and expanding wild species, such as wild ungulates. We have, therefore, quantified the interspecific interactions between wild boar (Sus scrofa) and free-ranging cattle in Mediterranean Spain, along with their spatio-temporal variability. GPS-GSM-collars were used to monitor 12 cows and 14 wild boar in the Doñana National Park between 2011 and 2013. Interactions were defined as encounters between cattle and wild boar within a spatio-temporal window of 52 m and 1 hour. On average, each wild boar interacted with one cow 1.5 ± (SE) 0.5 times per day, while each cow interacted with one wild boar 1.3 ± 0.4 times per day. The frequency of interaction was significantly higher during crepuscular hours owing to the overlap of both species’ activity, and also during spring and autumn, probably owing to a higher individual aggregation around shared resources. Finally, the frequency of interaction was higher near the most significant shared resources (e.g. water points) but was lower in areas with dense vegetation. The results presented here show the usefulness of GPS monitoring as regards quantifying interactions and helping to clarify the process of pathogen transmission at the wildlife-livestock interface in Mediterranean Spain, along with the main spatio-temporal risk factors. In a changing scenario in which European populations of wild ungulates are increasing, more efficient measures with which to control interactions are required to meet the demands of farmers and managers. Our results, therefore, provide directional hypotheses that could be used to design disease control programmes.

Drones for Conservation in Protected Areas: Present and Future

Park managers call for cost-effective and innovative solutions to handle a wide variety of environmental problems that threaten biodiversity in protected areas. Recently, drones have been called upon to revolutionize conservation and hold great potential to evolve and raise better-informed decisions to assist management. Despite great expectations, the benefits that drones could bring to foster effectiveness remain fundamentally unexplored. To address this gap, we performed a literature review about the use of drones in conservation. We selected a total of 256 studies, of which 99 were carried out in protected areas. We classified the studies in five distinct areas of applications: “wildlife monitoring and management”; “ecosystem monitoring”; “law enforcement”; “ecotourism”; and “environmental management and disaster response”. We also identified specific gaps and challenges that would allow for the expansion of critical research or monitoring. Our results support the evidence that drones hold merits to serve conservation actions and reinforce effective management, but multidisciplinary research must resolve the operational and analytical shortcomings that undermine the prospects for drones integration in protected areas.

Surgical and Medical Applications of Drones: A Comprehensive Review

Background:

Drones have the ability to gather real time data cost effectively, to deliver payloads and have initiated the rapid evolution of many industrial, commercial, and recreational applications. Unfortunately, there has been a slower expansion in the field of medicine. This article provides a comprehensive review of current and future drone applications in medicine, in hopes of empowering and inspiring more aggressive investigation.

Database:

A literature search was performed by EBSCO (Elton B. Stephens Company) Discovery Service, searching the phrases “drones,” “UAV,” “unmanned aerial vehicles,” “UAS,” and “unmanned aerial systems.” A second search was used to identify sources that contained “drone” in the subject or title and “medicine” in any of the text, yielding 60,260 results. After screening for irrelevant material, 1296 sources remained applicable. Major themes and number of sources were as follows: 116 public health and medical surveillance, 8 telemedicine, and 78 medical transport systems.

Conclusion:

Drones are used for surveillance of disaster sites and areas with biological hazards, as well as in epidemiology for research and tracking disease spread. Telecommunication drones are being used for diagnosis and treatment, perioperative evaluation, and telementoring in remote areas. Drones have the potential to be reliable medical delivery platforms for microbiological and laboratory samples, pharmaceuticals, vaccines, emergency medical equipment, and patient transport. Government agencies have placed drone use on the national agenda. The next steps include aggressive research initiatives in the areas of safety, industry expansion, increased public awareness, and participation.

Epidemics on dynamic networks

In many populations, the patterns of potentially infectious contacts are transients that can be described as a network with dynamic links. The relative timescales of link and contagion dynamics and the characteristics that drive their tempos can lead to important differences to the static case. Here, we propose some essential nomenclature for their analysis, and then review the relevant literature. We describe recent advances in they apply to infection processes, considering all of the methods used to record, measure and analyse them, and their implications for disease transmission. Finally, we outline some key challenges and opportunities in the field.

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): bovine tuberculosis

Bovine tuberculosis has been assessed according to the criteria of the Animal Health Law (AHL), in particular criteria of Article 7 on disease profile and impacts, Article 5 on the eligibility of bovine tuberculosis to be listed, Article 9 for the categorisation of bovine tuberculosis according to disease prevention and control rules as in Annex IV and Article 8 on the list of animal species related to bovine tuberculosis. The assessment has been performed following a methodology composed of information collection and compilation, expert judgement on each criterion at individual and, if no consensus was reached before, also at collective level. The output is composed of the categorical answer, and for the questions where no consensus was reached, the different supporting views are reported. Details on the methodology used for this assessment are explained in a separate opinion. According to the assessment performed, bovine tuberculosis can be considered eligible to be listed for Union intervention as laid down in Article 5(3) of the AHL. The disease would comply with the criteria as in Sections 2, 3, 4 and 5 of Annex IV of the AHL, for the application of the disease prevention and control rules referred to in points (b), (c), (d) and (e) of Article 9(1). The main animal species to be listed for bovine tuberculosis according to Article 8(3) criteria are several mammal species, as indicated in the present opinion.

Human influence and biotic homogenization drive the distribution of Escherichia coli virulence genes in natural habitats

Cattle are the main reservoirs for Shiga-toxin-producing Escherichia coli (STEC), the only known zoonotic intestinal E. coli pathotype. However, there are other intestinal pathotypes that can cause disease in humans, whose presence has been seldom investigated. Thus, our aim was to identify the effects of anthropic pressure and of wild and domestic ungulate abundance on the distribution and diversity of the main human E. coli pathotypes and nine of their representative virulence genes (VGs). We used a quantitative real-time PCR (qPCR) for the direct detection and quantification of the genus-specific gene uidA, nine E. coli VGs (stx1, sxt2, eae, ehxA, aggR, est, elt, bfpA, invA), as well as four genes related to O157:H7 (rfb_O157 , fliC_H7 ) and O104:H4 (wzx_O104 , fliC_H4 ) serotypes in animals (feces from deer, cattle, and wild boar) and water samples collected in three areas of Doñana National Park (DNP), Spain. Eight of the nine VGs were detected, being invA, eae, and stx2 followed by stx1, aggR, and ehxA the most abundant ones. In quantitative terms (gene copies per mg of sample), stx1 and stx2 gave the highest values. Significant differences were seen regarding VGs in the three animal species in the three sampled areas. The serotype-related genes were found in all but one sample types. In general, VGs were more diverse and abundant in the northern part of the Park, where the surface waters are more contaminated by human waste and farms. In the current study, we demonstrated that human influence is more relevant than host species in shaping the E. coli VGs spatial pattern and diversity in DNP. In addition, wildlife could be potential reservoirs for other pathotypes different from STEC, however further isolation steps would be needed to completely characterize those E. coli.

Emerging technologies to measure neighborhood conditions in public health: implications for interventions and next steps

Adverse neighborhood conditions play an important role beyond individual characteristics. There is increasing interest in identifying specific characteristics of the social and built environments adversely affecting health outcomes. Most research has assessed aspects of such exposures via self-reported instruments or census data. Potential threats in the local environment may be subject to short-term changes that can only be measured with more nimble technology. The advent of new technologies may offer new opportunities to obtain geospatial data about neighborhoods that may circumvent the limitations of traditional data sources. This overview describes the utility, validity and reliability of selected emerging technologies to measure neighborhood conditions for public health applications. It also describes next steps for future research and opportunities for interventions. The paper presents an overview of the literature on measurement of the built and social environment in public health (Google Street View, webcams, crowdsourcing, remote sensing, social media, unmanned aerial vehicles, and lifespace) and location-based interventions. Emerging technologies such as Google Street View, social media, drones, webcams, and crowdsourcing may serve as effective and inexpensive tools to measure the ever-changing environment. Georeferenced social media responses may help identify where to target intervention activities, but also to passively evaluate their effectiveness. Future studies should measure exposure across key time points during the life-course as part of the exposome paradigm and integrate various types of data sources to measure environmental contexts. By harnessing these technologies, public health research can not only monitor populations and the environment, but intervene using novel strategies to improve the public health.

Environmental Presence of Mycobacterium tuberculosis Complex in Aggregation Points at the Wildlife/Livestock Interface

The members of the Mycobacterium tuberculosis complex (MTC) cause tuberculosis (TB). Infection is transmitted within and between livestock and wildlife populations, thus hampering TB control. Indirect transmission might be facilitated if MTC bacteria persist in the environment long enough to represent a risk of exposure to different species sharing the same habitat. We have, for the first time, addressed the relationship between environmental MTC persistence and the use of water resources in two TB endemic areas in southern Spain with the objective of identifying the presence of environmental MTC and its driving factors at ungulates' water aggregation points. Camera-trap monitoring and MTC diagnosis (using a new MTC complex-specific PCR technique) were carried out at watering sites. Overall, 55.8% of the water points tested positive for MTC in mud samples on the shore, while 8.9% of them were positive in the case of water samples. A higher percentage of MTC-positive samples was found at those waterholes where cachectic animals were identified using camera-trap monitoring, and at the smallest waterholes. Our results help to understand the role of indirect routes of cross-species TB transmission and highlight the importance of certain environmental features in maintaining infection in multihost systems. This will help to better target actions and implement control strategies for TB at the wildlife/livestock interface.

DNA Detection Reveals Mycobacterium tuberculosis Complex Shedding Routes in Its Wildlife Reservoir the Eurasian Wild Boar

Since the intensity and frequency of pathogen shedding by hosts determine the probability of infection through direct and indirect contact, the shedding characterization of Mycobacterium tuberculosis complex (MTC) in the key host reservoir in Iberia, the Eurasian wild boar (Sus scrofa), is crucial. We aimed (i) to describe the natural shedding routes of MTC in free-ranging wild boar by a new semi-automated PCR method and (ii) to determine the association of MTC shedding pattern with tuberculosis (TB) progression and individual factors. MTC shedding (by any of the possible routes) was detected in a total of 30.8% (±7.5) out of the sampled individuals with valid or interpretable test results (n = 39). The proportion of TB-positive shedders according to the route was 13.6% (±7.5) for oral swabs, 4.5% (±4.5) for nasal swabs, 4.5% (±4.4) for faecal swabs and 13.6% (±7.5) for individuals being positive to all swabs concomitantly. The probability of shedding mycobacteria (by any route) statistically associated with TB generalization, and the TB score was significantly higher in individuals testing positive to at least one route compared to negatives. Overall, a diversity of shedding routes in wild boar is possible, and it is remarkable that for the first time, the faecal shedding is confirmed for naturally infected wild boar. Our results are consistent with the role wild boar plays for TB maintenance in host communities and environments in Iberia and confirm that it is an important source of mycobacteria infection by different routes. Finally, we evidenced the use of a new PCR technique to detect MTC DNA in excretions can be practical and defined the target routes for sampling wild boar shedding in future studies, such as interventions to control TB in wild boar that can be measured in terms of impact on mycobacteria excretion and transmission (i.e. vaccination).

Unmanned Aircraft Systems complement biologging in spatial ecology studies

The knowledge about the spatial ecology and distribution of organisms is important for both basic and applied science. Biologging is one of the most popular methods for obtaining information about spatial distribution of animals, but requires capturing the animals and is often limited by costs and data retrieval. Unmanned Aircraft Systems (UAS) have proven their efficacy for wildlife surveillance and habitat monitoring, but their potential contribution to the prediction of animal distribution patterns and abundance has not been thoroughly evaluated. In this study, we assess the usefulness of UAS overflights to (1) get data to model the distribution of free‐ranging cattle for a comparison with results obtained from biologged (GPS‐GSM collared) cattle and (2) predict species densities for a comparison with actual density in a protected area. UAS and biologging derived data models provided similar distribution patterns. Predictions from the UAS model overestimated cattle densities, which may be associated with higher aggregated distributions of this species. Overall, while the particular researcher interests and species characteristics will influence the method of choice for each study, we demonstrate here that UAS constitute a noninvasive methodology able to provide accurate spatial data useful for ecological research, wildlife management and rangeland planning.

Bears Show a Physiological but Limited Behavioral Response to Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) have the potential to revolutionize the way research is conducted in many scientific fields. UAVs can access remote or difficult terrain, collect large amounts of data for lower cost than traditional aerial methods, and facilitate observations of species that are wary of human presence. Currently, despite large regulatory hurdles, UAVs are being deployed by researchers and conservationists to monitor threats to biodiversity, collect frequent aerial imagery, estimate population abundance, and deter poaching. Studies have examined the behavioral responses of wildlife to aircraft (including UAVs), but with the widespread increase in UAV flights, it is critical to understand whether UAVs act as stressors to wildlife and to quantify that impact. Biologger technology allows for the remote monitoring of stress responses in free-roaming individuals, and when linked to locational information, it can be used to determine events or components of an animal's environment that elicit a physiological response not apparent based on behavior alone. We assessed effects of UAV flights on movements and heart rate responses of free-roaming American black bears. We observed consistently strong physiological responses but infrequent behavioral changes. All bears, including an individual denned for hibernation, responded to UAV flights with elevated heart rates, rising as much as 123 beats per minute above the pre-flight baseline. It is important to consider the additional stress on wildlife from UAV flights when developing regulations and best scientific practices.