A latent class analysis of biosecurity attitudes and decision-making strategies of swine producers in the United States.

The 2018 African swine fever (ASF) outbreak highlighted the importance of biosecurity in food production systems. Despite the significant economic impacts, the sociopsychological consequences on decision-making have been overlooked. Previous studies have focused on algebraic models and simulation-based models without considering the complex psychological and social factors that influence farmers' biosecurity behaviors and decision-making processes. This study aims to classify livestock producers into distinct subgroups based on their attitudes towards biosecurity. We conducted a survey presenting producers with three scenarios to assess their willingness to report suspected ASF cases, trust in government agencies, risk perception, biosecurity knowledge, willingness to purchase livestock insurance, motivation to invest in biosecurity, readiness to report suspected infections, and intention to contact a veterinarian. Using latent class analysis, we identified three distinct classes: Biosecurity Sceptics, Biosecurity Compliant, and Biosecurity Ultra-Compliant. Our results show that producer characteristics significantly influence biosecurity attitudes and class membership, with small-scale producers less likely to adopt ultra-compliant biosecurity practices. Attending at least one eradication program encouraged biosecurity compliance. This research informs the design of targeted food policy and risk communication strategies that account for attitudes of livestock producers to encourage biosecurity adoption and reduce the likelihood of Tier 1 disease incursion.

Biosecurity indemnification and attitudes of United States swine producers towards the prevention of an african swine fever outbreak.

Animal disease outbreaks, such as the recent outbreak of African Swine Fever in 2018, are a major concern for stakeholders across the food supply chain due to their potential to disrupt global food security, cause economic losses, and threaten animal welfare. As a result of their transboundary nature, discussions have shifted to preventive measures aimed at protecting livestock while ensuring food security and safety. Emergency assistance has been a critical response option during pandemics. However, this may not be sustainable in the long run because the expectation of government bailout may encourage risk taking behaviours. Our hypothesis is that an indemnity policy that is conditioned on showing biosecurity practices would increase compliance and reduce government expenditure during disease outbreaks. We developed and launched a survey from March to July 2022 targeted at swine producers across the US. From the survey, we examined livestock farmers' attitudes and intentions regarding biosecurity investment and assessed their attitudes towards the purchase of livestock insurance and reporting suspected infected livestock on their farm. We used a partial proportion odds model analysis to examine the model. Our analysis revealed that intention to call a veterinarian, trust in government agencies and risk perception of farmers were instrumental in the willingness to self-invest in biosecurity, purchase livestock insurance, and promptly report infected livestock on their farms. This provides evidence that biosecurity compliance would increase if indemnification was tied to a demonstration of effort to adopt biosecurity practices. We also show that individuals who have been in the industry for a longer period may become complacent and less likely to report outbreaks. Farmers with a higher share of income from their production operations bear a greater risk from their operational income and are more willing to report any suspected infections on their farms. The data suggest that motivating the willingness of farmers to invest in biosecurity while overcoming cost concerns is achievable.

Serologic Survey of Selected Arthropod-Borne Pathogens in Free-Ranging Snowshoe Hares (Lepus americanus) Captured in Northern Michigan, USA.

Snowshoe hares (Lepus americanus) in the Upper Peninsula (UP) of Michigan, USA, occupy the southern periphery of the species' range and are vulnerable to climate change. In the eastern UP, hares are isolated by the Great Lakes, potentially exacerbating exposure to climate-change-induced habitat alterations. Climate change is also measurably affecting distribution and prevalence of vector-borne pathogens in North America, and increases in disease occurrence and prevalence can be one signal of climate-stressed wildlife populations. We conducted a serosurvey for vector-borne pathogens in snowshoe hares that were captured in the Hiawatha National Forest in the eastern UP of Michigan, USA, 2016-2017. The most commonly detected antibody response was to the mosquito-borne California serogroup snowshoe hare virus (SSHV). Overall, 24 (51%) hares screened positive for SSHV antibodies and of these, 23 (96%) were confirmed positive by plaque reduction neutralization test. We found a positive association between seroprevalence of SSHV and live weight of snowshoe hares. Additionally, we detected a significant effect of ecological land type group on seroprevalence of SSHV, with strong positive support for a group representing areas that tend to support high numbers of hares (i.e., acidic mineral containing soils with cedar, mixed swamp conifers, tamarack and balsam fir as common overstory vegetation). We also detected and confirmed antibodies for Jamestown Canyon virus and Silverwater virus in a single hare each. We did not detect antibodies to other zoonotic vector-borne pathogens, including Lacrosse encephalitis virus, West Nile virus, Borrelia burgdorferi, Powassan virus, and Francisella tularensis. These results provide a baseline for future serological studies of vector-transmitted diseases that may increase climate vulnerability of snowshoe hares in the UP of Michigan, as well as pose a climate-related zoonotic risk.

Hashtags in Plastic Surgery: A Sentiment Analysis of over 1 Million Tweets.

BACKGROUND: Current literature has sparse recommendations that guide social networking practices in plastic surgery. To address this, we used natural language processing and sentiment analysis to investigate the differences in plastic surgery-related terms and hashtags on Twitter. METHODS: Over 1 million tweets containing keywords #plasticsurgery, #cosmeticsurgery, and their non-hashtagged versions plastic surgery and cosmetic surgery were collected from the Twitter Gardenhose feed spanning from 2012 to 2016. We extracted the average happiness/positivity (h-avg) using hedonometrics and created word-shift graphs to determine influential words. RESULTS: The most popular keywords were plastic and cosmetic surgery, comprising more than 90% of the sample. The positivity scores for plastic surgery, cosmetic surgery, #plasticsurgery, and #cosmeticsurgery were 5.72, 6.00, 6.17, and 6.18, respectively. Compared to plastic surgery, the term cosmetic surgery was more positive because it lacked antagonistic words, such as "fake," "ugly," "bad," "fails," and "wrong." For similar reasons, #plasticsurgery and #cosmeticsurgery were more positively associated than their non-hashtagged counterparts. CONCLUSION: Plastic surgery-related hashtags are more positively associated than their non-hashtagged versions. The language associated with such hashtags suggests a different user profile than the public and, given their underutilization, remain viable channels for professionals to achieve their diverse social media goals. LEVEL OF EVIDENCE V: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Effects of message delivery on cross-cultural biosecurity compliance: Insights from experimental simulations.

Background: Effective biosecurity communication of transmission risks and associated protective behaviors can reduce the impacts of infectious diseases in US animal agriculture. Yet, more than 1/5 of animal production workers speak a language other than English at home, and more than 40 percent are less than fluent in English. Communicating with these workers often involves translating into their primary languages. However, communication strategies targeting different cultural groups are not well-understood. Aims: To identify cross-linguistic risk communication strategies to facilitate compliance, we hypothesized that uncertainty avoidance cultures associated with the languages might affect biosecurity compliance contingent upon two additional covariates: (1) the risk of acquiring an infection and (2) the delivery method of the infection risk. Methods: We designed an experimental game simulating a line of separation (LOS) biosecurity tactic in a swine production facility, where participants were tasked with completing tasks inside and outside of the facility. Data were collected using games in the two most spoken languages in the US: English (EN) and Spanish (SP). Participants made binary decisions about whether to use the LOS biosecurity tactic based on the risk information provided. Mixed-effect logistic models were used to test the effects of covariates on using the LOS tactic by different language groups. Results: We found that biosecurity compliance rates of participants who took the experiments in the language associated with high and low uncertainty cultures showed no significant differences. However, there are substantial differences in how risk information is perceived between the two language groups under different infection risks. Specifically, and counterintuitively, SP participants were more risk-averse in gain scenarios but more risk-taking in loss scenarios. These differences are most pronounced in numeric risk messaging, indicating that numbers may not be the best way to communicate risk information regarding biosecurity cross-culturally. Conclusions: When confronted with situational biosecurity decisions, risk perception and preferences vary by language group. Effective biosecurity communication needs to account for these differences and not assume that direct translation of risk messages will result in comparable compliance.

Assessing strategic, tactical, and operational decision-making and risk in a livestock production chain through experimental simulation platforms.

This paper provides a research summary of a series of serious games and simulations that form the basis of an experimental platform for the study of human decision-making and behavior associated with biosecurity across complex livestock production chains. This platform is the first of its kind to address the challenges associated with scaling micro-behavior of biosecurity decision-making to macro-patterns of disease spread across strategic, tactical and operational levels, capturing the roles that facility managers and front-line workers play in making biosecurity decisions under risk and uncertainty. Informational and incentive treatments are tested within each game and simulation. Behavioral theories are used to explain these findings. Results from serious games in the form of behavioral probability distributions are then used to simulate disease incidence and spread across a complex production chain, demonstrating how micro-level behaviors contribute to larger macro-level patterns. In the case of this study, the propensity to adopt micro-level biosecurity practices are applied to a network percolation disease spread model. By presenting the suite of companion models of behavior and disease spread we are able to capture scaling dynamics of complex systems, and in the process, better understand how individual behaviors impact whole systems.

Comparing behavioral risk assessment strategies for quantifying biosecurity compliance to mitigate animal disease spread.

Understanding the impact of human behavior on the spread of disease is critical in mitigating outbreak severity. We designed an experimental game that emulated worker decision-making in a swine facility during an outbreak. In order to combat contamination, the simulation features a line-of-separation biosecurity protocol. Participants are provided disease severity information and can choose whether or not to comply with a shower protocol. Each simulated decision carried the potential for either an economic cost or an opportunity cost, both of which affected their potential real-world earnings. Participants must weigh the risk infection vs. an opportunity cost associated with compliance. Participants then completed a multiple price list (MPL) risk assessment survey. The survey uses a context-free, paired-lottery approach in which one of two options may be selected, with varying probabilities of a high and low risk payouts. We compared game response data to MPL risk assessment. Game risk was calculated using the normalized frequency of biosecurity compliance. Three predominant strategies were identified: risk averse participants who had the highest rate of compliance; risk tolerant participants who had the lowest compliance rate; and opportunists who adapted their strategy depending on disease risk. These findings were compared to the proportion of risk averse choices observed within the MPL and were classified into 3 categories: risk averse, risk tolerant and neutral. We found weak positive correlation between risk measured in our experimental game compared to the MPL. However, risk averse classified participants in the MPL tended to comply with the biosecurity protocol more often than those classified as risk tolerant. We also found that the behavioral risk clusters and categorization via the MPL were significantly, yet weakly associated. Overall, behavioral distributions were skewed toward more risk averse choices in both the MPL and game. However, the MPL risk assessment wasn't a strong predictor for observed game behavior. This may indicate that MPL risk aversion metrics might not be sufficient to capture these simulated, situational risk aversion behaviors. Experimental games have a large potential for expanding upon traditional survey instruments by immersing participants in a complex decision mechanism, and capturing dynamic and evolving behavioral signals.

Flow impacts of hot/cold zone infection control procedures during the COVID-19 pandemic in the emergency department.

BACKGROUND: The COVID-19 pandemic forced emergency departments (EDs) to change operations to minimize nosocomial infection risk. Many EDs cohort patients using provincial screening tools at triage. Despite cohorting, staff exposures occurred in the 'cold zone' due to lack of personal protective equipment (PPE) use with patients deemed low risk, resulting in staff quarantines. The cohorting strategy was perceived to lengthen time to physician initial assessment and ED length of stay times in our ED without protecting staff well enough due to varying PPE use. The objective of this study was to assess the impact of hot/cold zones for patient cohorting during a viral pandemic on ED length of stay. METHODS: We conducted an interrupted time series analysis 3 weeks before and after the removal of hot/cold zone care space cohorting in our ED. In the before period, staff did not routinely wear full PPE to see cold zone patients. After removal, staff wore full PPE to see almost all patients. We collected data on ED length of stay, physician initial assessment times, arrival-to-room times, patient volumes, Canadian Triage Acuity Score (CTAS), admissions, staff hours of coverage, as well as proportions of patients on droplet/contact precautions and COVD-19 positive patients. The primary outcome was median ED length of stay. RESULTS: After the removal of the hot/cold divisions, there was a decrease in the adjusted median ED length of stay by 24 min (95% CI 14; 33). PPE use increased in the after arm of the study. The interrupted time series analysis suggested a decrease in median ED length of stay after removal, although the change in slope and difference did not reach statistical significance. CONCLUSION: Cohorted waiting areas may provide a safety benefit without operational compromise, but cohorting staff and care spaces is likely to compromise efficiency and create delays.

RéSUMé: CONTEXTE: La pandémie de COVID-19 a contraint les services d'urgence (SU) à modifier leur fonctionnement afin de minimiser le risque d'infection nosocomiale. De nombreux SU regroupaient des patients à l'aide d'outils de dépistage provinciaux au triage. Malgré la constitution de cohortes, les expositions du personnel se sont produites dans la "zone froide" en raison du manque d'utilisation d'équipements de protection individuelle (EPI) avec des patients jugés à faible risque, ce qui a entraîné la mise en quarantaine du personnel. Dans notre service d'urgence, la stratégie de cohorte a été perçue comme prolongeant l'évaluation initiale des médecins et la durée du séjour dans le service sans pour autant protéger suffisamment le personnel en raison de l'utilisation variable des EPI. L'objectif de cette étude était d'évaluer l'impact des zones chaudes/froides pour le regroupement de patients lors d'une pandémie virale sur la durée du séjour à l'urgence. MéTHODES: Nous avons réalisé une analyse de séries chronologiques interrompues trois semaines avant et après la suppression de la cohorte d'espace de soins en zone chaude/froide dans nos urgences. Au cours de la période précédente, le personnel ne portait pas systématiquement un EPI complet pour voir les patients des zones froides. Après le retrait, le personnel a porté un EPI complet pour voir presque tous les patients. Nous avons recueilli des données sur la durée du séjour aux urgences, les délais d'évaluation initiale par les médecins, les délais d'arrivée en salle, le volume de patients, L'échelle canadienne de triage et de gravité (ÉTG), les admissions, les heures de couverture du personnel, ainsi que les proportions de patients ayant reçu des précautions contre les gouttelettes et les contacts et de patients positifs au COVD-19. Le critère de jugement principal était la durée médiane du séjour aux urgences. RéSULTATS: Après la suppression des divisions chaudes/froides, la durée médiane ajustée du séjour aux urgences a diminué de 24 minutes (IC à 95 % : 14 ; 33). L'utilisation des EPI a augmenté dans le groupe suivant de l'étude. L'analyse des séries chronologiques interrompues suggère une diminution de la durée médiane de séjour aux urgences après le retrait, bien que le changement de la pente et de la différence n'ait pas atteint la signification statistique. CONCLUSION: Les zones d'attente en cohorte peuvent offrir un avantage en matière de sécurité sans compromis sur le plan opérationnel, mais le regroupement du personnel et des espaces de soins est susceptible de compromettre l'efficacité et de créer des retards.

The Adverse Event Unit (AEU): A novel metric to measure the burden of treatment adverse events.

OBJECTIVE: To design a physician and patient derived tool, the Adverse Event Unit (AEU), akin to currency (e.g. U.S. Dollar), to improve AE burden measurement independent of any particular disease or medication class. PATIENTS/METHODS: A Research Electronic Data Capture (REDCap) online survey was administered to United States physicians with board certification or board eligibility in general neurology, subspecialty neurology, primary care internal medicine or family medicine, subspecialty internal medicine, general pediatrics, and subspecialty pediatrics. Physicians assigned value to 73 AE categories chosen from the Common Terminology Criteria of Adverse Events (CTCAE) relevant to neurologic disorder treatments. An online forced choice survey was administered to non-physician, potential patients, through Amazon Mechanical Turk (MTurK) to weight the severity of the same AE categories. Physician and non-physician data was combined to assign value to the AEU. Surveys completed between 1/2017 and 3/2019. RESULTS: 363 physicians rated the 73 AE categories derived from CTCAE. 660 non-physicians completed forced choice experiments comparing AEs. The AEU provides 0-10, weighted values for the AE categories studied that differ from the ordinal 1-4 CTCAE scale. For example, CTCAE severe diabetes (category 4) is assigned an AEU score of 9. Although non-physician input changed physician assigned AEU values, there was general agreement among physicians and non-physicians about severity of AEs. CONCLUSION: The AEU has promise to be a useful, practical tool to add precision to AE burden measurement in the clinic and in comparative efficacy research with neurology patients. AEU utility will be assessed in planned comparative efficacy clinical trials.

Connecting livestock disease dynamics to human learning and biosecurity decisions.

The acceleration of animal disease spread worldwide due to increased animal, feed, and human movement has driven a growing body of epidemiological research as well as a deeper interest in human behavioral studies aimed at understanding their interconnectedness. Biosecurity measures can reduce the risk of infection, but human risk tolerance can hinder biosecurity investments and compliance. Humans may learn from hardship and become more risk averse, but sometimes they instead become more risk tolerant because they forget negative experiences happened in the past or because they come to believe they are immune. We represent the complexity of the hog production system with disease threats, human decision making, and human risk attitude using an agent-based model. Our objective is to explore the role of risk tolerant behaviors and the consequences of delayed biosecurity investments. We set up experiment with Monte Carlo simulations of scenarios designed with different risk tolerance amongst the swine producers and we derive distributions and trends of biosecurity and porcine epidemic diarrhea virus (PEDv) incidence emerging in the system. The output data allowed us to examine interactions between modes of risk tolerance and timings of biosecurity response discussing consequences for disease protection in the production system. The results show that hasty and delayed biosecurity responses or slow shifts toward a biosecure culture do not guarantee control of contamination when the disease has already spread in the system. In an effort to support effective disease prevention, our model results can inform policy making to move toward more resilient and healthy production systems. The modeled dynamics of risk attitude have also the potential to improve communication strategies for nudging and establishing risk averse behaviors thereby equipping the production system in case of foreign disease incursions.