Effects of Social Cues on Biosecurity Compliance in Livestock Facilities: Evidence From Experimental Simulations

Supporting Measures to Improve Biosecurity within Italian Poultry Production

This paper describes the selection and validation of supporting measures (SMs) aimed at enhancing biosecurity compliance within Italian poultry farms. A tailored methodology, based on a stakeholders' survey involving farmers and advisors, included a virtual farm tour, group discussion, and farmer coaching. Virtual farm tours and group discussions were delivered during two meetings targeting meat and egg production stakeholders, separately. Coaching was validated in 26 pilot farms (PFs) by assessing farmers' attitudes towards change (i.e., ADKAR®) and farms' biosecurity score (i.e., Biocheck.UgentTM) before and after a minimum six-month period. A total of 20 out of 26 farmers agreed to implement at least one action plan (AP). Full implementation of the agreed APs was observed in ten farms, while others only partially implemented (n = 7) or did not implement (n = 3) the improvement. Most APs focused on enhancing house hygiene locks (n = 7), followed by bacterial auto-control after cleaning and disinfection (n = 4). Scoring tools indicated minimal or no variations in farmers' attitudes towards change and farm biosecurity. Virtual farm tours and group discussions were found to be effective in fostering interaction and facilitating the exchange of experiences and knowledge among farmers and stakeholders of poultry production. Coaching indicated that farmers might prefer implementing minor changes possibly influenced by time and cost constraints associated with structural interventions. These limitations could have also impacted the scores of the farmer/farm. The findings of this study provide a foundation for further application of SMs to improve biosecurity in Italian poultry farms.

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.

The attitude-behaviour gap in biosecurity: Applying social theories to understand the relationships between commercial chicken farmers' attitudes and behaviours

Introduction

Traditionally, it is believed that people's behaviours align with their attitudes; however, during COVID-19 pandemic, an attitude-behaviour gap in relation to preventive measures has been observed in recent studies. As such, the mixed-methods research was used to examine the relationships between farmers' biosecurity attitudes and behaviours in Taiwan's chicken industry based on the cognitive consistency theory.

Methods

Content analysis of face-to-face interviews with 15 commercial chicken farmers identified their biosecurity responses to infectious disease threats.

Results

The results indicated the mismatch of farmers' attitudes and behaviours towards specific biosecurity measures, in that they act differently than they think. The findings of the qualitative research allowed the research team to conduct the subsequent quantitative, confirmatory assessment to investigate the mismatch of farmers' attitudes and behaviours in 303 commercial broiler farmers. Survey data were analyzed to discover the relationships between farmers' attitudes and behaviours in relation to 29 biosecurity measures. The results show a mixed picture. The percentage of the farmers who had the attitude-behaviour gap towards 29 biosecurity measures ranged from 13.9 to 58.7%. Additionally, at the 5% significant level, there is an association between farmers' attitudes and behaviours for 12 biosecurity measures. In contrast, a significant association does not exist for the other 17 biosecurity measures. Specifically, out of the 17 biosecurity measures, the disconnection of farmers' attitudes and behaviours was observed in three specific biosecurity measures such as using a carcass storage area.

Discussion

Based on a fairly large sample of farmers in Taiwan, this study confirms the existence of an attitude-behaviour gap in context and applies social theories to provide an in-depth understanding of how infectious diseases are managed in the animal health context. As the results demonstrate the necessity of tailoring biosecurity strategies to address the gap, it is time to reconsider the current approach by understanding farmers' real attitudes and behaviours in relation to biosecurity for the success of animal disease prevention and control at the farm level.

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.

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.

Evaluation of biosecurity measures on a swine operation using Glo Germ powder as a visible learning aid

Glo Germ powder was used to determine the efficacy of common biosecurity practices to prevent the powder from spreading to other areas within a farm. Pictures from 4 locations were taken before and after personnel movement to observe any differences in Glo Germ coverage. The percentage of Glo Germ coverage observed in the pictures was evaluated by 47 panelists and averaged. The area without biosecurity measures had more Glo Germ coverage than the 3 areas with biosecurity measures (P < .001). The use of Glo Germ can be used as a learning aid to demonstrate the efficacy of common biosecurity practices.

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.

Message Delivery Strategy Influences Willingness to Comply With Biosecurity

As the Covid-19 pandemic continues worldwide, it has become increasingly clear that effective communication of disease transmission risks associated with protective behaviors is essential, and that communication tactics are not ubiquitously and homogenously understood. Analogous to Covid-19, communicable diseases in the hog industry result in millions of animal deaths and in the United States costs hundreds of millions of dollars annually. Protective behaviors such as preventative biosecurity practices are implemented to reduce these costs. Yet even with the knowledge of the importance of biosecurity, these practices are not employed consistently. The efficacy of biosecurity practices relies on consistent implementation and is influenced by a variety of behavioral factors under the umbrella of human decision-making. Using an experimental game, we collected data to quantify how different messages that described the likelihood of a disease incursion would influence willingness to follow biosecurity practices. Here we show that graphical messages combined with linguistic phrases demarking infection risk levels are more effective for ensuring compliance with biosecurity practices, as contrasted with either simple linguistic phrases or graphical messages with numeric demarcation of risk levels. All three of these delivery methods appear to be more effective than using a simple numeric value to describe probability of infection. Situationally, we saw greater than a 3-fold increase in compliance by shifting message strategy without changing the infection risk, highlighting the importance of situational awareness and context when designing messages.

Emulating Agricultural Disease Management: Comparing Risk Preferences Between Industry Professionals and Online Participants Using Experimental Gaming Simulations and Paired Lottery Choice Surveys

Mitigating the spread of disease is crucial for the well-being of agricultural production systems. Implementing biosecurity disease prevention measures can be expensive, so producers must balance the costs of biosecurity investments with the expected benefits of reducing the risk of infections. To investigate the risk associated with this decision making process, we developed an online experimental game that simulates biosecurity investment allocation of a pork production facility during an outbreak. Participants are presented with several scenarios that vary the visibility of the disease status and biosecurity protection implemented at neighboring facilities. Certain rounds allowed participants to spend resources to reduce uncertainty and reveal neighboring biosecurity and/or disease status. We then test how this uncertainty affects the decisions to spend simulation dollars to increase biosecurity and reduce risk. We recruited 50 attendees from the 2018 World Pork Expo to participate in our simulation. We compared their performance to an opportunity sample of 50 online participants from the survey crowdsourcing tool, Amazon Mechanical Turk (MTurk). With respect to biosecurity investment, we did not find a significant difference between the risk behaviors of industry professionals and those of MTurk participants for each set of experimental scenarios. Notably, we found that our sample of industry professionals opted to pay to reveal disease and biosecurity information more often than MTurk participants. However, the biosecurity investment decisions were not significantly different during rounds in which additional information could be purchased. To further validate these findings, we compared the risk associated with each group's responses using a well-established risk assessment survey implementing paired lottery choices. Interestingly, we did not find a correlation in risk quantified with simulated biosecurity investment in comparison to the paired lottery choice survey. This may be evidence that general economic risk preferences may not always translate into simulated behavioral risk, perhaps due to the contextual immersion provided by experimental gaming simulations. Online recruitment tools can provide cost effective research quality data that can be rapidly assembled in comparison to industry professionals, who may be more challenging to sample at scale. Using a convenience sample of industry professionals for validation can also provide additional insights into the decision making process. These findings lend support to using online experimental simulations for interpreting risk associated with a complex decision mechanism.