Bovine mortality: the utility of two data sources for the provision of population-level surveillance intelligence.

Introduction: The use of existing data to provide surveillance intelligence is widely advocated but often presents considerable challenges. Two data sources could be used as proxies for the mortality experienced by the Scottish cattle population: deaths recorded in the mandatory register [Cattle Tracing System (CTS)] and fallen stock collections by the National Fallen Stock Company (NSFCo) with a nationwide voluntary membership. Methods: Data for the period 2011-2016 were described and compared to establish their strengths and limitations. Similarities and differences in their temporal, seasonal and spatial patterns were examined overall, at postcode area level and for different age groups. Temporal aberration detection algorithms (TADA) were fitted. Results: Broadly, similar patterns were observed in the two datasets; however, there were some notable differences. The observed seasonal, annual and spatial patterns match expectations, given knowledge of Scottish cattle production systems. The registry data provide more comprehensive coverage of all areas of Scotland, while collections data provide a more comprehensive measure of the mortality experienced in 0-1-month-old calves. Discussion: Consequently, estimates of early calf mortality and their impact on the livestock sector made using CTS, or successor registers, will be under-estimates. This may apply to other registry-based systems. Fitted TADA detected points of deviations from expected norms some of which coincided in the two datasets; one with a known external event that caused increased mortality. We have demonstrated that both data sources do have the potential to be utilized to provide measures of mortality in the Scottish cattle population that could inform surveillance activities. While neither is perfect, they are complementary. Each has strengths and weaknesses, so ideally, a system where they are analyzed and interpreted in parallel would optimize the information obtained for surveillance purposes for epidemiologists, risk managers, animal health policy-makers and the wider livestock industry sector. This study provides a foundation on which to build an operational system. Further development will require improvements in the timeliness of data availability and further investment of resources.

Production and performance evaluation of biodiesel from Elaeis guineensis using natural snail shell-based heterogeneous catalyst: kinetics, modeling and optimisation by artificial neural network.

This study presents an approach to produce biodiesel from Elaeis guineensis using natural heterogeneous catalysts derived from raw, calcined, and acid-activated forms of waste snail shells. The catalysts were thoroughly characterized using SEM, and process parameters were systematically evaluated during biodiesel production. Our results demonstrate a remarkable crop oil yield of 58.87%, with kinetic studies confirming second-order kinetics and activation energies of 43.70 kJ mol-1 and 45.70 kJ mol-1 for methylation and ethylation, respectively. SEM analysis identified the calcined catalyst as the most effective, exhibiting remarkable reusability for continuous reactions running up to five times. Moreover, the acid concentration from exhaust fumes yielded a low acid value (B100 0.0012 g dm-3), significantly lower than that of petroleum diesel, while the fuel properties and blends satisfied the ASTM standards. The sample-heavy metals were well within acceptable limits, confirming the quality and safety of the final product. Our modelling and optimization approach produced a remarkably low mean squared error (MSE) and a high coefficient of determination (R), providing strong evidence for the viability of this approach at an industrial scale. Our results represent a significant input in sustainable biodiesel production and underscore the enormous potential of natural heterogeneous catalysts derived from waste snail shells for achieving sustainable and environmentally friendly biodiesel production.

Corrigendum: Evaluations of the disease surveillance centre network in Scotland: what parts has it reached?

[This corrects the article DOI: 10.3389/fvets.2023.1099057.].

Evaluations of the Disease Surveillance Centre network in Scotland: What parts has it reached?

Regular evaluation is a prerequisite for systems that provide surveillance of animal populations. Scotland's Rural College Veterinary Services' Disease Surveillance Centre (DSC) network plays an integral part in surveillance to detect new and re-emerging threats within animal populations, predominantly livestock. In response to surveillance reviews and proposed changes to the network, an initial evaluation of diagnostic submissions data in 2010 to mid-2012 established a baseline "footprint," while highlighting challenges with the data. In this recent evaluation for the period 2013­2018, we developed a new denominator using a combination of agricultural census and movement data, to identify relevant holdings more accurately. Iterative discussions between those processing submissions data and those involved in collection at source took place to understand the intricacies of the data, establish the most appropriate dataset, and develop the processes required to optimise the data extraction and cleansing. The subsequent descriptive analysis identifies the number of diagnostic submissions, the number of unique holdings making submissions to the network and shows that both the surrounding geographic region of, and maximum distance to the closest DSC vary greatly between centres. Analysis of those submissions classed as farm animal post-mortems also highlights the effect of distance to the closest DSC. Whether specific differences between the time periods are due to changes in the behavior of the submitting holdings or the data extraction and cleaning processes was difficult to disentangle. However, with the improved techniques producing better data to work with, a new baseline footprint for the network has been created. This provides information that can help policy makers and surveillance providers make decisions about service provision and evaluate the impact of future changes. Additionally, the outputs of these analyses can provide feedback to those employed in the service, providing evidence of what they are achieving and why changes to data collection processes and ways of working are being made. In a different setting, other data will be available and different challenges may arise. However, the fundamental principles highlighted in these evaluations and the solutions developed should be of interest to any surveillance providers generating similar diagnostic data.

Linking human tick bite risk with tick abundance in the environment: A novel approach to quantify tick bite risk using orienteers in Scotland.

The rate that people are bitten by ticks is critical in determining the risk of tick-borne infections but is rarely quantified accurately. Often tick abundance in the environment is used as a proxy for tick bite risk, but the relationship with risk is poorly understood. We used a novel citizen science approach to measure tick bite rate in orienteers, to assess the relationship between tick abundance and tick bite risk and to identify risk factors for tick bites. Eleven orienteering events were attended in Scotland between August 2018 and September 2019. The number of tick bites in orienteers, and the time and distance of activity were collected using an online questionnaire. Tick abundance in the same areas used for the orienteering events was estimated by surveying ticks on ground vegetation using blanket drags. Among orienteers, mean incidence was 409 tick bites per 1,000 person-hours. Tick abundance and tick bite rate were strongly correlated, indicating that data from questing tick surveys is a useful proxy for the risk of human tick bites. Tick bite rate was better explained by the activity duration than distance covered and was higher in orienteers that ran earlier in the day, exposed to higher temperatures and in woodland habitats. This study highlights the value of the citizen science approach used, which crucially included submission of activity reports both with and without ticks, to generate robust data on tick bite rate. Accurately measuring tick bite rate and understanding environmental factors that influence it are essential in mitigating the risk of tick-borne diseases.

Modeling the Health and Economic Impact of Substandard and Falsified Medicines: A Review of Existing Models and Approaches.

Substandard and falsified medicines are harmful to patients, causing prolonged illness, side effects, and preventable deaths. Moreover, they have an impact on the health system and society more broadly by leading to additional care, higher disease burden, productivity losses and loss of trust in health care. Models that estimate the health and economic impacts of substandard and falsified medicines can be useful for regulators to contextualize the problem and to make an economic case for solutions. Yet these models have not been systematically catalogued to date. We reviewed existing models that estimate the health and economic impact of substandard and falsified medicines to describe the varying modeling approaches and gaps in knowledge. We compared model characteristics, data sources, assumptions, and limitations. Seven models were identified. The models assessed the impact of antimalarial (n = 5) or antibiotic (n = 2) quality at a national (n = 4), regional (n = 2), or global (n = 1) level. Most models conducted uncertainty analysis and provided ranges around potential outcomes. We found that models are lacking for other medicines, few countries' data have been analyzed, and capturing population heterogeneity remains a challenge. Providing the best estimates of the impact of substandard and falsified medicines on a level that is actionable for decision-makers is important. To enable this, research on the impact of substandard and falsified medicines should be expanded to more medicine types and classes and tailored to more countries that are affected, with greater specificity.

Field evaluation of diagnostic sensitivity (DSe) and specificity (DSp) of common tests for amoebic gill disease (AGD) and complex gill disease (CGD) in cultured Atlantic salmon (Salmo salar) in Scotland using Bayesian latent class models.

Amoebic gill disease (AGD) and complex gill disease (CGD) are the most significant marine gill diseases in salmon aquaculture in Scotland. Little is published about diagnostic performance of tests to detect these diseases, making it difficult to interpret test results. We estimated diagnostic sensitivity (DSe) and specificity (DSp) of common tests for AGD (gross AGD score, qPCR for Neoparamoeba perurans, histopathology) and CGD (gross proliferative gill disease (PGD) score, gross total gill score, histopathology). Because specifications in our sampling protocol implemented to encourage consistency across the farms might affect diagnostic performance of histopathology (historically the reference standard for gill diseases), we used Bayesian latent class models without reference standard. Cases and non-cases were based on less, medium, and severe stringent case definitions, representing different cut-off levels for the different tests. Gross gill scores for both diseases were excellent in designating non-diseased fish, DSps were generally around 1. To detect CGD, DSe of gross total gill score and gross PGD score were between respectively 0.81 (0.73 - 0.91 lower to upper 95% credible interval) and 0.53 (0.46 - 0.64) for medium stringent case definitions, and to detect AGD the DSe for the gross AGD score was between 0.53 (0.48-0.57) and 0.14 (0.07 - 0.22) for respectively the less and severe stringent case definition. Thus, gross gill scores were medium to good in designating truly diseased fish, implying some false negatives are expected. For CGD the DSe for gross total gill scores were the highest, for AGD it was the qPCR test at a DSe of 0.92 (0.86 - 0.99). For both diseases, DSe was lowest for histopathology, e.g. 0.23 (0.16 - 0.30) for AGD and 0.1 (0.07 - 0.14) for CGD under medium stringent case definitions, perhaps due to collecting the second gill arch on the right rather than the worst affected arch, whilst PCR sampling and gross gill scoring included multiple (PCR) or all (gross scoring) gill arches. The diagnostic goals of these tests differ; gross gill scoring provides a low-cost presumptive diagnosis, PCR a non-lethal confirmation of the presence of a specific pathogen and histopathology provides information on the underlying aetiology of gill damage as well as the extent, severity, and chronology of gill disease. An effective gill health surveillance strategy is likely to incorporate multiple diagnostic tools used in a complementary manner.

Paradoxical sleep deprivation induces oxidative stress in the submandibular glands of Wistar rats.

OBJECTIVES: Paradoxical sleep deprivation has been associated with impaired salivary secretion in rats. However, the mechanism that underlies this is not known. Therefore, this study assessed salivary and serum oxidative stress levels following paradoxical sleep deprivation in rats. METHODS: Twenty-one male Wistar rats randomly divided into three groups of seven rats each as; Control (C); partial sleep-deprived (PSD); and total sleep-deprived (TSD) were used. Malondialdehyde (MDA) concentration, Superoxide dismutase (SOD), and catalase activities were evaluated in saliva, serum, and submandibular glands after seven days of sleep deprivation. Data were expressed as mean ± standard error of the mean and analyzed using one-way ANOVA, Tukey HSD post hoc, and Pearson's correlation tests. RESULTS: Serum MDA levels were significantly higher in both the TSD and PSD groups compared to the control group whereas only the TSD group showed higher submandibular MDA levels compared to the PSD group and the control group. Submandibular SOD activity was significantly lower in both the TSD and PSD groups compared to the control group. Serum catalase activity was significantly lower in the TSD group only compared to the control group. CONCLUSIONS: These results have demonstrated for the first time that paradoxical sleep deprivation was associated with changes in the oxidant/antioxidant defense system in the submandibular salivary glands of male Wistar rats which may contribute to impairment in salivary secretion.

Prospects and Applications of Palladium Nanoparticles in the Cross-coupling of (hetero)aryl Halides and Related Analogues.

Discovering efficient methods for the formation of carbon-carbon bonds is a central ongoing theme in organic synthesis. Cross-coupling reactions catalysed by metal nanoparticles are attractive alternatives to the traditional use of metal counterparts due to the catalytic tunability, selectivity, recyclability and reusability of the nanoparticles. The ongoing search for sustainable processes demands that reusable and environmentally benign catalysts are used. While the advantages of nanoparticles catalysts over bulk catalysts cannot be overemphasised, the problem of sintering, agglomeration and leaching are drawbacks to their full industrial applications. Hence, efforts are being made towards advancing the efficiency of the catalytic nanoparticle systems over the years. This review presents the progress, the challenges and the prospects of palladium nanoparticle with focus on Heck, Suzuki, Hiyama and Sonogashira cross-coupling reactions involving (hetero) aryl halides and the analogues.

Prospects and Therapeutic Applications of Cardiac Glycosides in Cancer Remediation.

Active metabolites from natural sources are the predominant molecular targets in numerous biological studies owing to their appropriate compatibility with biological systems and desirable selective toxicities. Thus, their potential for therapeutic development could span a broad scope of disease areas, including pathological and neurological dysfunctions. Cardiac glycosides are a unique class of specialized metabolites that have been extensively applied as therapeutic agents for the treatment of numerous heart conditions, and more recently, they have also been explored as probable antitumor agents. They are a class of naturally derived compounds that bind to and inhibit Na+/K+-ATPase. This study presents cardiac glycosides and their analogues with highlights on their applications, challenges, and prospects as lead compounds for cancer treatment.

Importance of medicine quality in achieving universal health coverage.

OBJECTIVE: To assess the importance of ensuring medicine quality in order to achieve universal health coverage (UHC). METHODS: We developed a systems map connecting medicines quality assurance systems with UHC goals to illustrate the ensuing impact of quality-assured medicines in the implementation of UHC. The association between UHC and medicine quality was further examined in the context of essential medicines in low- and middle-income countries (LMICs) by analyzing data on reported prevalence of substandard and falsified essential medicines and established indicators for UHC. Finally, we examined the health and economic savings of improving antimalarial quality in four countries in sub-Saharan Africa: the Democratic Republic of the Congo (DRC), Nigeria, Uganda, and Zambia. FINDINGS: A systems perspective demonstrates how quality assurance of medicines supports dimensions of UHC. Across 63 LMICs, the reported prevalence of substandard and falsified essential medicines was found to be negatively associated with both an indicator for coverage of essential services (p = 0.05) and with an indicator for government effectiveness (p = 0.04). We estimated that investing in improving the quality of antimalarials by 10% would result in annual savings of $8.3 million in Zambia, $14 million in Uganda, $79 million in two DRC regions, and $598 million in Nigeria, and was more impactful compared to other potential investments we examined. Costs of substandard and falsified antimalarials per malaria case ranged from $7 to $86, while costs per death due to poor-quality antimalarials ranged from $14,000 to $72,000. CONCLUSION: Medicines quality assurance systems play a critical role in reaching UHC goals. By ensuring the quality of essential medicines, they help deliver effective treatments that lead to less illness and result in health care savings that can be reinvested towards UHC.

The Use of Sheep Movement Data to Inform Design and Interpretation of Slaughterhouse-Based Surveillance Activities.

The design of surveillance strategies is often a compromise between science, feasibility, and available resources, especially when sampling is based at fixed locations, such as slaughter-houses. Advances in animal identification, movement recording and traceability should provide data that can facilitate the development, design and interpretation of surveillance activities. Here, for the first time since the introduction of electronic identification of sheep, the utility of a statutory sheep movement database to inform the design and interpretation of slaughter-house based surveillance activities has been investigated. Scottish sheep movement records for 2015-2018 were analyzed in combination with several other data sources. Patterns of off-farm movements of Scottish sheep to slaughter were described and the spatial distribution of several distinct slaughter populations, throughputs and catchment areas for Scottish slaughterhouses were determined. These were used to evaluate the coverage of a convenience-sample slaughter-house based survey for antimicrobial resistance (AMR). In addition, non-slaughter sheep movements within and between Scottish regions were described and inter-and intra-regional movement matrices were produced. There is potential at a number of levels for bias in spatially-associated factors for ovine surveillance activities based at Scottish slaughterhouses. The first is intrinsic because the slaughtered in Scotland population differs from the overall Scottish sheep slaughter population. Other levels will be survey-dependent and occur when the catchment area differs from the slaughtered in Scotland population and when the sampled sheep differ from the catchment area. These are both observed in the AMR survey. Furthermore, the Scottish non-slaughter sheep population is dynamic. Inter-regional movements vary seasonally, driven by the sheep calendar year, structure of the Scottish sheep industry and management practices. These sheep movement data provide a valuable resource for surveillance purposes, despite a number of challenges and limitations that were encountered. They can be used to identify and characterize the spatial origin of relevant populations and so inform the interpretation of existing slaughterhouse-based surveillance activities. They can be used to improve future design by exploring the feasibility and cost:benefit of alternative sampling strategies. Further development could also contribute to other surveillance activities, such as situational awareness and resource allocation, for the benefit of stakeholders.

Using imperfect data in predictive mapping of vectors: a regional example of Ixodes ricinus distribution.

BACKGROUND: Knowledge of Ixodes ricinus tick distribution is critical for surveillance and risk management of transmissible tick-borne diseases such as Lyme borreliosis. However, as the ecology of I. ricinus is complex, and robust long-term geographically extensive distribution tick data are limited, mapping often relies on datasets collected for other purposes. We compared the modelled distributions derived from three datasets with information on I. ricinus distribution (quantitative I. ricinus count data from scientific surveys; I. ricinus presence-only data from public submissions; and a combined I. ricinus dataset from multiple sources) to assess which could be reliably used to inform Public Health strategy. The outputs also illustrate the strengths and limitations of these three types of data, which are commonly used in mapping tick distributions. METHODS: Using the Integrated Nested Laplace algorithm we predicted I. ricinus abundance and presence-absence in Scotland and tested the robustness of the predictions, accounting for errors and uncertainty. RESULTS: All models fitted the data well and the covariate predictors for I. ricinus distribution, i.e. deer presence, temperature, habitat, index of vegetation, were as expected. Differences in the spatial trend of I. ricinus distribution were evident between the three predictive maps. Uncertainties in the spatial models resulted from inherent characteristics of the datasets, particularly the number of data points, and coverage over the covariate range used in making the predictions. CONCLUSIONS: Quantitative I. ricinus data from scientific surveys are usually considered to be gold standard data and we recommend their use where high data coverage can be achieved. However in this study their value was limited by poor data coverage. Combined datasets with I. ricinus distribution data from multiple sources are valuable in addressing issues of low coverage and this dataset produced the most appropriate map for national scale decision-making in Scotland. When mapping vector distributions for public-health decision making, model uncertainties and limitations of extrapolation need to be considered; these are often not included in published vector distribution maps. Further development of tools to better assess uncertainties in the models and predictions are necessary to allow more informed interpretation of distribution maps.

Framework for Estimating Indirect Costs in Animal Health Using Time Series Analysis.

Traditionally, cost-benefit analyses (CBAs) focus on the direct costs of animal disease, including animal mortality, morbidity, and associated response costs. However, such approaches often fail to capture the wider, dynamic market impacts that could arise. The duration of these market dislocations could last well after an initial disease outbreak. More generally, current approaches also muddle definitions of indirect costs, confusing debate on the scope of the totalities of disease-induced economic impacts. The aim of this work was to clarify definitions of indirect costs in the context of animal diseases and to apply this definition to a time series methodological framework to estimate the indirect costs of animal disease control strategies, using a foot and mouth disease (FMD) outbreak in Scotland as a case study. Time series analysis is an econometric method for analyzing statistical relationships between data series over time, thus allowing insights into how market dynamics may change following a disease outbreak. First an epidemiological model simulated FMD disease dynamics based on alternative control strategies. Output from the epidemiological model was used to quantify direct costs and applied in a multivariate vector error correction model to quantify the indirect costs of alternative vaccine stock strategies as a result of FMD. Indirect costs were defined as the economic losses incurred in markets after disease freedom is declared. As such, our definition of indirect costs captures the knock-on price and quantity effects in six agricultural markets after a disease outbreak. Our results suggest that controlling a FMD epidemic with vaccination is less costly in direct and indirect costs relative to a no vaccination (i.e., "cull only") strategy, when considering large FMD outbreaks in Scotland. Our research clarifies and provides a framework for estimating indirect costs, which is applicable to both exotic and endemic diseases. Standard accounting CBAs only capture activities in isolation, ignore linkages across sectors, and do not consider price effects. However, our framework not only delineates when indirect costs start, but also captures the wider knock-on price effects between sectors, which are often omitted from CBAs but are necessary to support decision-making in animal disease prevention and control strategies.

Improving the Utility of Voluntary Ovine Fallen Stock Collection and Laboratory Diagnostic Submission Data for Animal Health Surveillance Purposes: A Development Cycle.

There are calls from policy-makers and industry to use existing data sources to contribute to livestock surveillance systems, especially for syndromic surveillance. However, the practical implications of attempting to use such data sources are challenging; development often requires incremental steps in an iterative cycle. In this study the utility of business operational data from a voluntary fallen stock collection service was investigated, to determine if they could be used as a proxy for the mortality experienced by the British sheep population. Retrospectively, Scottish ovine fallen stock collection data (2011-2014) were transformed into meaningful units for analysis, temporal and spatial patterns were described, time-series methods and a temporal aberration detection algorithm applied. Distinct annual and spatial trends plus seasonal patterns were observed in the three age groups investigated. The algorithm produced an alarm at the point of an historic known departure from normal (April 2013) for two age groups, across Scotland as a whole and in specific postcode areas. The analysis was then extended. Initially, to determine if similar methods could be applied to ovine fallen stock collections from England and Wales for the same time period. Additionally, Scottish contemporaneous laboratory diagnostic submission data were analyzed to see if they could provide further insight for interpretation of statistical alarms. Collaboration was required between the primary data holders, those with industry sector knowledge, plus veterinary, epidemiological and statistical expertise, in order to turn data and analytical outcomes into potentially useful information. A number of limitations were identified and recommendations were made as to how some could be addressed in order to facilitate use of these data as surveillance "intelligence." e.g., improvements to data collection and provision. A recent update of the fallen stock collections data has enabled a longer temporal period to be analyzed, with evidence of changes made in line with the recommendations. Further development will be required before a functional system can be implemented. However, there is potential for use of these data as: a proxy measure for mortality in the sheep population; complementary components in a future surveillance system, and to inform the design of additional surveillance system components.

Pig Abattoir Inspection Data: Can It Be Used for Surveillance Purposes?

Statutory recording of carcass lesions at the abattoir may have significant potential as a resource for surveillance of livestock populations. Food Standards Agency (FSA) data in Great Britain are not currently used for surveillance purposes. There are concerns that the sensitivity of detection, combined with other issues, may make the outputs unreliable. In this study we postulate that FSA data could be used for surveillance purposes. To test this we compared FSA data with BPHS (a targeted surveillance system of slaughtered pigs) and laboratory diagnostic scanning surveillance (FarmFile) data, from mid-2008 to mid-2012, for respiratory conditions and tail bite lesions in pigs at population level. We also evaluated the agreement/correlation at batch level between FSA and BPHS inspections in four field trials during 2013. Temporal trends and regional differences at population level were described and compared using logistic regression models. Population temporal analysis showed an increase in respiratory disease in all datasets but with regional differences. For tail bite, the temporal trend and monthly patterns were completely different between the datasets. The field trials were run in three abattoirs and included 322 batches. Pearson's correlation and Cohen's kappa tests were used to assess correlation/agreement between inspections systems. It was moderate to strong for high prevalence conditions but slight for low prevalence conditions. We conclude that there is potential to use FSA data as a component of a surveillance system to monitor temporal trends and regional differences of chosen indicators at population level. At producer level and for low prevalence conditions it needs further improvement. Overall a number of issues still need to be addressed in order to provide the pig industry with the confidence to base their decisions on these FSA inspection data. Similar conclusions, at national level, may apply to other livestock sectors but require further evaluation of the inspection and data collection processes.

Perfluoroalkyl substances in eggs and plasma of an avian top predator, great skua (Stercorarius skua), in the North Atlantic.

Temporal, biological, and environmental factors affecting accumulation of perfluoroalkyl substances (PFASs) are poorly understood in comparison with legacy lipid-soluble persistent organic pollutants. Temporal and biological comparisons of PFAS concentrations were made in great skuas (Stercorarius skua), a marine apex predator. Concentrations of 16 PFASs were quantified, including C4-C10 perfluorosulfonates (PFSAs), perfluorooctanesulfonamide (PFOSA), and C5-C14 perfluorocarboxylates (PFCAs). Concentrations of PFASs (ng/g wet wt) were significantly higher in eggs collected in Shetland in 2008 compared with 1980 for most compounds. However, the magnitude of the differences was small, with a mean increase of 3 ng/g. Levels of PFASs in great skuas were low compared with those of other seabirds in similar ecological niches; and in contrast to other contaminants measured in the same eggs, concentrations of PFASs did not correlate with trophic level. Concentrations of PFASs in adult plasma were significantly higher in males than in females for most PFASs. This suggests that maternal transfer through egg laying may be a significant mode of elimination of PFASs in female great skuas. The low concentrations of PFASs in eggs and plasma compared with other halogenated organic contaminants and other species suggest that great skuas do not bioaccumulate PFASs to the same extent as some other seabirds.