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As of 8 July 2022, the World Health Organization (WHO) have reported 1010 probable cases of acute hepatitis of unknown aetiology in children worldwide, including approximately 250 cases in the United Kingdom (UK). Clinical presentations have often been severe, with liver transplantation a frequent clinical outcome. Human adenovirus F41 (HAdV-F41) has been detected in most children with acute hepatitis, but its role in the pathogenesis of this infection has yet to be established. Wastewater-based epidemiology (WBE) has become a well-established tool for monitoring the community spread of SARS-CoV-2, as well as other pathogens and chemicals. In this study, we adopted a WBE approach to monitoring levels of HAdV-F40/41 in wastewater before and during an acute hepatitis outbreak in Northern Ireland. We report increasing detection of HAdV-F40/41 in wastewater, concomitant with increasing numbers of clinical cases. Amplicon whole genome sequencing further classified the wastewater-derived HAdV as belonging to the F41 genotype which in turn was homologous to clinically derived sequences. We propose that WBE has the potential to inform community surveillance of HAdV-F41 and can further contribute to the ongoing global discussion supporting HAdV-F41 involvement in acute hepatitis cases.

The combined use of global positioning system (GPS) technology and motion sensors within the discipline of movement ecology has increased over recent years. This is particularly the case for instrumented wildlife, with many studies now opting to record parameters at high (infra-second) sampling frequencies. However, the detail with which GPS loggers can elucidate fine-scale movement depends on the precision and accuracy of fixes, with accuracy being affected by signal reception. We hypothesized that animal behaviour was the main factor affecting fix inaccuracy, with inherent GPS positional noise (jitter) being most apparent during GPS fixes for non-moving locations, thereby producing disproportionate error during rest periods. A movement-verified filtering (MVF) protocol was constructed to compare GPS-derived speed data with dynamic body acceleration, to provide a computationally quick method for identifying genuine travelling movement. This method was tested on 11 free-ranging lions ( Panthera leo ) fitted with collar-mounted GPS units and tri-axial motion sensors recording at 1 and 40 Hz, respectively. The findings support the hypothesis and show that distance moved estimates were, on average, overestimated by greater than 80% prior to GPS screening. We present the conceptual and mathematical protocols for screening fix inaccuracy within high-resolution GPS datasets and demonstrate the importance that MVF has for avoiding inaccurate and biased estimates of movement.

Animal-attached devices have transformed our understanding of vertebrate ecology. To minimize any associated harm, researchers have long advocated that tag masses should not exceed 3% of carrier body mass. However, this ignores tag forces resulting from animal movement. Using data from collar-attached accelerometers on 10 diverse free-ranging terrestrial species from koalas to cheetahs, we detail a tag-based acceleration method to clarify acceptable tag mass limits. We quantify animal athleticism in terms of fractions of animal movement time devoted to different collar-recorded accelerations and convert those accelerations to forces (acceleration × tag mass) to allow derivation of any defined force limits for specified fractions of any animal's active time. Specifying that tags should exert forces that are less than 3% of the gravitational force exerted on the animal's body for 95% of the time led to corrected tag masses that should constitute between 1.6% and 2.98% of carrier mass, depending on athleticism. Strikingly, in four carnivore species encompassing two orders of magnitude in mass ( ca 2–200 kg), forces exerted by ‘3%' tags were equivalent to 4–19% of carrier body mass during moving, with a maximum of 54% in a hunting cheetah. This fundamentally changes how acceptable tag mass limits should be determined by ethics bodies, irrespective of the force and time limits specified.

Chemical methods of virus inactivation are used routinely to prevent viral transmission in both a personal hygiene capacity but also in at-risk environments like hospitals. Several ‘virucidal’ products exist, including hand soaps, gels and surface disinfectants. Resin acids, which can be derived from Tall oil produced from trees, have been shown to exhibit anti-bacterial activity. However, whether these products or their derivatives have virucidal activity is unknown. Here, we assessed the capacity of Rosin soap to inactivate a panel of pathogenic mammalian viruses in vitro. We show that Rosin soap can inactivate the human enveloped viruses: influenza A virus (IAV), respiratory syncytial virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For IAV, rosin soap could provide a 100,000-fold reduction in infectivity. However, Rosin soap failed to affect the non-enveloped encephalomyocarditis virus (EMCV). The inhibitory effect of Rosin soap against IAV infectivity was dependent on its concentration but not dependent on incubation time nor temperature. Together, we demonstrate a novel chemical inactivation method against enveloped viruses, which could be of use in preventing virus infections in certain settings.ImportanceViruses remain a significant cause of human disease and death, most notably illustrated through the current Covid-19 pandemic. Control of virus infection continues to pose a significant global health challenge to the human population. Viruses can spread through multiple routes, including via environmental and surface contamination where viruses can remain infectious for days. Methods to inactivate viruses on such surfaces may help mitigate infection. Here we present evidence identifying a novel ‘virucidal’ product in Rosin soap, which is produced from Tall oil from coniferous trees. Rosin soap was able to rapidly and potently inactivate influenza virus and other enveloped viruses.

The combined use of Global Positioning System (GPS) technology and motion sensors within the discipline of movement ecology has increased over recent years. This is particularly the case for instrumented wildlife, with many studies now opting to record parameters at high (infra-second) sampling frequency. However, the detail with which GPS loggers can elucidate fine-scale movement depends on the precision and accuracy of fixes, with accuracy (specifically, location error and fix success rate) being affected by signal reception. We hypothesised that animal behaviour was the main factor affecting fix inaccuracy (particularly for collar-mounted tags sampling at high frequency). In conjunction to this, inherent GPS positional noise (‘jitter’), would be most apparent during GPS fixes for non-moving locations, thereby producing disproportionate error during rest periods. A Movement Verified Filtering (MVF) protocol was constructed to compare GPS-derived speed data to dynamic body acceleration (DBA). This was collected by a simultaneously deployed tri-axial accelerometer, to provide a computationally quick method for identifying genuine travelling movement. This method was tested on 11 free-ranging lions ( Panthera leo ) within the Kgalagadi Transfrontier park in the Kalahari Desert, fitted with collar-mounted GPS units and tri-axial motion sensors (Daily Diary; DD) recording at 1 and 40 Hz, respectively. The findings support the hypothesis and show that distance moved estimates were, on average, overestimated by > 80 % prior to GPS screening. We present the conceptual and mathematical protocols for screening fix inaccuracy within high resolution GPS datasets. We demonstrate the importance that MVF has for avoiding inaccurate and biased estimates of movement and caution the accuracy of findings from previous studies that employed minimal GPS pre-processing . Throughout, we address the applicability of comparing fine-scale indices of GPS- and motion sensor-borne data in tandem to qualify animal behaviour.

Background Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, ‘GPS’) is typically used to verify an animal’s location periodically. Straight lines are typically drawn between these ‘Verified Positions’ (‘VPs’) so the interpolation of space-use is limited by the temporal and spatial resolution of the system’s measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. Methods and results Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. Conclusions We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal–barrier interactions and foraging strategies.

Animal-attached devices have transformed our understanding of vertebrate ecology. To minimize tag-related harm for these studies, researchers have long advocated that tag masses should not exceed 3% of the animal’s body mass. However, this proposition ignores tag forces generated as a result of animal movement.Using data from collar-attached accelerometers on diverse free-ranging terrestrial animals, we detail a tag-based acceleration method (TbAM) in which we quantify animal athleticism in terms of fractions of animal movement time devoted to different collar-recorded accelerations. The varying accelerations are converted to forces imposed on the animals based on the acceleration and tag mass and allow derivation of defined force limits, including those amounting to 3% of the animal’s mass, for specified fractions of any animal’s active time.We demonstrate how species athleticism is the principal determinant of tag forces, whereas body mass is of little importance. Forces exerted by ‘3%’ tags were mostly equivalent to 4-19% of the animals’ masses during moving, with a maximum of 54% in a hunting cheetah. Cumulative frequency curves of tag acceleration for periods when animals were active, all showed a characteristic sigmoid pattern, which was displaced further to the right as higher acceleration activities accounted for an increasing proportion of any animal’s time. Specifying that tags should exert forces that are less than 3% of the animal’s body mass for 95% of the time led to corrected tag masses constituting between 1.6% and 2.98% of our study animals’ masses, with values depending on animal athleticism.Recognition that animal athleticism affects tag forces of their carriers fundamentally changes how acceptable tag mass limits should be determined by ethics bodies. In order to have a scientifically robust acceptable threshold to limit the forces experienced by an animal carrier, we suggest practitioners derive a similar cumulative acceleration profile for their study species and use a minimum of the 95% limits on the plot (although higher limits may be more appropriate).

Background Fine-scale data on animal position are increasingly enabling us to understand the details of animal movement ecology and dead-reckoning, a technique integrating motion sensor-derived information on heading and speed, can be used to reconstruct fine-scale movement paths at sub-second resolution, irrespective of the environment. On its own however, the dead-reckoning process is prone to cumulative errors, so that position estimates quickly become uncoupled from true location. Periodic ground-truthing with aligned location data (e.g., from global positioning technology) can correct for this drift between Verified Positions (VPs). We present step-by-step instructions for implementing Verified Position Correction (VPC) dead-reckoning in R using the tilt-compensated compass method, accompanied by the mathematical protocols underlying the code and improvements and extensions of this technique to reduce the trade-off between VPC rate and dead-reckoning accuracy. These protocols are all built into a user-friendly, fully annotated VPC dead-reckoning R function; Gundog.Tracks, with multi-functionality to reconstruct animal movement paths across terrestrial, aquatic, and aerial systems, provided within the Additional file 4 as well as online (GitHub). Results The Gundog.Tracks function is demonstrated on three contrasting model species (the African lion Panthera leo, the Magellanic penguin Spheniscus magellanicus, and the Imperial cormorant Leucocarbo atriceps) moving on land, in water and in air. We show the effect of uncorrected errors in speed estimations, heading inaccuracies and infrequent VPC rate and demonstrate how these issues can be addressed. Conclusions The function provided will allow anyone familiar with R to dead-reckon animal tracks readily and accurately, as the key complex issues are dealt with by Gundog.Tracks. This will help the community to consider and implement a valuable, but often overlooked method of reconstructing high-resolution animal movement paths across diverse species and systems without requiring a bespoke application.

Animal-attached devices have transformed our understanding of vertebrate ecology. However, to be acceptable, researchers must minimize tag-related harm. The long-standing recommendation that tag masses should not exceed 3% of the animal’s body mass ignores tag forces generated by movement. We used collar-attached accelerometers on four free-ranging carnivores, spanning two orders of magnitude in mass, to reveal that during movement, forces exerted by ‘3%’ tags were generally equivalent to 4-19% of the animals’ masses, with a record of 54% in a hunting cheetah. Controlled studies on domestic dogs revealed how the tag forces are dictated by animal gait and speed but appear largely invariant of body mass. This fundamentally changes how acceptable tag mass limits should be determined, requiring cognizance of animal athleticism.One Sentence SummaryThere can be no universal rule for collar-tag masses as a percentage of carrier mass since tag forces depend on lifestyle.

Although randomized experiments are lauded for their high internal validity, they have been criticized for the limited external validity of their results. This chapter describes research strategies for investigating how much nonrepresentative site selection may limit external validity and bias impact findings. The magnitude of external validity bias is potentially much larger than what is thought of as an acceptable level of internal validity bias. The chapter argues that external validity bias should always be investigated by the best available means and addressed directly when presenting evaluation results. These observations flag the importance of making external validity a priority in evaluation planning.

Evaluations of the impact of social programs are often carried out in multiple “sites,” such as school districts, housing authorities, local TANF offices, or One-Stop Career Centers. Most evaluations select sites purposively following a process that is nonrandom. Unfortunately, purposive site selection can produce a sample of sites that is not representative of the population of interest for the program. In this paper, we propose a conceptual model of purposive site selection. We begin with the proposition that a purposive sample of sites can usefully be conceptualized as a random sample of sites from some well-defined population, for which the sampling probabilities are unknown and vary across sites. This proposition allows us to derive a formal, yet intuitive, mathematical expression for the bias in the pooled impact estimate when sites are selected purposively. This formula helps us to better understand the consequences of selecting sites purposively, and the factors that contribute to the bias. Additional research is needed to obtain evidence on how large the bias tends to be in actual studies that select sites purposively, and to develop methods to increase the external validity of these studies.

The authors begin with a thorough assessment of the many nonexperimental employment and training program evaluation techniques based on non-random comparison groups. These techniques typically use econometric methods to estimate the effects of employment and training programs by using comparison groups from non-program "external" sources. Then, recognizing the inherent drawbacks in these methods, Bell, Orr, Blomquist and Cain respond by reintroducing an evaluation method first implemented in the 1960s, the use of "internal" comparison groups consisting of nonparticipating program applicants.