HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Interpretive Summary Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Buttars, N. K. Articles by Bailey, D. Search for Related Content PubMed PubMed Citation Articles by Buttars, N. K. Articles by Bailey, D.

Adoption of Security Systems By Dairy Farms to Address Bioterrorist Threats in the Intermountain United States¹

N. K. Buttars^*, A. J. Young^,2 and D. Bailey^*

^* Department of Economics, and
Department of Animal, Dairy, and Veterinary Sciences, Utah State University, Logan 84322

² Corresponding author: alleny{at}ext.usu.edu

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Data generated from a survey of western dairy farms was used to determine the characteristics of dairy farmers who have undertaken to improve security measures on their farms during the past 2 or 3 yr. The findings suggest that decisions to improve on-farm security are influenced by the producer’s awareness of how to develop a security policy, and by the size of the dairy operation. The results also support the notion that farms may be vulnerable to bioterrorist attacks because most farmers do not believe it is important to establish on-farm security policies.

Key Words: on-farm security • bioterrorism • dairy farm

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
After the terrorist attacks of September 11, 2001, the United States needed to consider in a profound way all its potential vulnerabilities (National Academy of Sciences, 2002). One area of potential vulnerability that quickly surfaced was the US food supply because, obviously, everyone consumes food and because of the importance of the food industry to the US and international economy.

The US Food Safety Inspection Service (FSIS) was organized to detect and eradicate food safety problems resulting from unintentional contaminations, especially related to pathogens (National Academy of Sciences, 2002; Bailey, 2004). The specter of bioterrorism (intentional contamination) presented an entirely new set of issues for the food industry and government food regulators to deal with regarding how to ensure the safety of the US food supply. For example, in an instance of bioterrorism, the food safety system needs to deal with the fact that the perpetrator chooses the time, place, and type of contamination that will occur rather than the seemingly random acts associated with unintentional contamination.

The National Academy of Sciences (2002) indicates that "Technical sophistication would not be necessary for attacks [on US agriculture]," and that "Although an attack ... is highly unlikely to result in famine or malnutrition, the possible damage includes major direct and indirect costs to the agricultural and national economy, adverse public health effects, loss of public confidence in the food system and in public officials, and widespread public concern and confusion." The US agriculture/food industry accounts for about $1 trillion annually in economic activity or 13% of the United States’ gross domestic product and about 18% of domestic employment (Smith, 2002; Dyckman, 2003). Consequently, a terrorist attack on the US food system has the potential to inflict a substantial level of human and economic damage.

In testimony to the US Senate, the United States General Accounting Office (GAO) suggests that a terrorist attack on the US food system intended to destroy human life would likely be directed at finished food products whereas an attempt to disrupt economic activity would probably take the form of an attack on crops or livestock (Dyckman, 2003). However, experts generally agree that a bioterrorist attack could occur at virtually any level of the food marketing chain (National Academy of Sciences, 2002; Dyckman, 2003).

Besides its importance as a basic industry, agriculture appears to be vulnerable to attack, especially at the farm level, for a number of other reasons. First, there are a relatively large number of farms providing a large pool of potential targets. Second, some production enterprises, especially livestock, are concentrated in large numbers in certain geographic locations making it potentially easy to infect a large number of livestock with relative ease. Third, agricultural products tend to move over significant geographical distances to intermediate production, processing, and consumption locations making the potential for spreading disease or other types of deadly material through natural day-to-day business activities an added threat. Finally, many experts suggest that biosecurity measures on farms in the United States are woefully inadequate. Smith (2002) refers to farming as "...an exceptionally porous industry from a security standpoint." Davis (2003) indicates that, "The poor level of biosecurity on the majority of farms today guarantees unchallenged and unhindered access to the determined, patient terrorist."

Much of the concern at the farm level about biosecurity is related to the intentional spreading of highly contagious animal diseases such as foot-and-mouth disease (National Academy of Sciences, 2002; Dyckman, 2003). But there are also concerns about other contaminants such as anthrax that can cause adverse health effects in humans. Threats with less deadly consequences, but still holding the potential for adverse effects in humans, include the intentional contamination of milk with antibiotics, as was suspected in a few cases in New York (Clinton, 2002).

The 2 components necessary for a successful terrorism act are vulnerability and capability (Siegrist, 1999); unfortunately, US agriculture appears to present both of these prerequisites to potential terrorists (National Academy of Sciences, 2002; Smith, 2002; Davis, 2003; Dyckman, 2003). Although bioterrorism could occur at any level of the marketing chain, one could argue that routine security measures at processing plants and other points in the chain are better, on average, than at the farm level, potentially rendering the farm level as the "weak link" in the food chain in relationship to bioterrorism.

A number of different crop and livestock enterprises could have been selected for this analysis. However, the dairy industry was selected 1) because it has been the target of suspected bioterrorist acts before (e.g., Clinton, 2002); 2) because of the close confinement and relatively large size of most dairy herds (compared with beef herds); and 3) the fact that milk is routinely commingled at the processing plant with milk from other farms, thus potentially providing terrorists with the means of spreading contamination broadly from a single point.

Virtually no published research is available about the economics of establishing security on farms against a possible bioterrorist attack. Much of the literature tends to focus on how agricultural products can function as a medium for the spread of animal and human diseases (e.g., National Academy of Sciences, 2002; Davis, 2003). In a related fashion, other literature has examined public health policy in relation to terrorist attacks and appropriate reactions to such attacks (e.g., McDade, 1999; Fidler, 2002; Avery, 2004). Brookmeyer and Blades (2003) discuss appropriate modeling procedures for the spread of disease resulting from a bioterrorist attacks using the 2001 US anthrax outbreak as a backdrop. Educational materials dealing with agroterrorism have been prepared by the US government and land-grant universities [Extension Disaster Education Network (EDEN); USDA, Food Safety Inspection Service, 2005], but we are unaware of scientific studies examining issues and concerns related to preparedness against a bioterrorist attack at the individual farm level.

The reason for this lack may be because of the perception of a low level of risk that exists for any particular farm. But we are aware of no scientific studies examining even basic actions taken by farmers as security measures against bioterrorism such as locking milk storage tanks when not in use or monitoring against unauthorized access to the farmer’s property. Consequently, this study offers an initial examination of whether very basic security measures are being undertaken on dairy farms, or if a security plan is even in place on these farms.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
A survey was developed and sent by mail to dairy farmers who receive the Utah Dairy Newsletter. Table 1 provides statistics for the number of surveys sent, response rate, and information about the representativeness of the sample compared with the population. The sample appeared to be quite representative of the population for all states except Idaho, where the average number of cows per herd for survey respondents was substantially and statistically lower than the population mean for herd size (Table 1). The survey data obtained from respondents in Idaho represents the lowest percentage of the total cow numbers with only about 1% being represented. The state with the highest percentage of cows represented in data from the survey was Nevada with 37% of the total population. The survey data represented 7% of the total population of dairy cows in the 5 states included in the survey.

In cases in which only action or inaction is observable, an index function model may be the best method to describe the probability of an action being carried out or not. In this case we observe whether the survey respondent has actually taken steps to improve security on his/her farm during the past 2 to 3 yr (SECURITY).

Greene (2003) suggests that survey participants will base their response, in this case on whether respondents have improved security on their farm, on "a marginal benefit–marginal cost calculation" of the perceived net benefit from improving on-farm security compared with not doing so (Greene, 2003). Greene (2003) demonstrates the difference between cost and benefit as an unobservable index variable, y*, in the following model:

[1]

where the error term, , is described as an "innocent normalization" because its actual variance is not known. However, if the actual variance were known, a normalization of the observed data (y and x) would not be changed (Greene, 2003). The explanatory variables and parameter estimates are represented in this model by x and ß, respectively. The model presented by Greene (2003) shows that because the survey measures only whether steps have been taken to improve on-farm security (SECURITY in Table 2), then the observed choice is demonstrated by

[2]

Greene (2003) states that a constant term must be included in the latent regression if the threshold for y* is zero. This is because the marginal cost and benefits are being evaluated indirectly through participants’ choice to undertake on-farm security improvement (SECURITY = 1) or not to do so (SECURITY = 0; Greene, 2003). Obviously, SECURITY is an imperfect measure of efforts to increase on-farm security measures because it does not provide detail regarding the level or the quality of measures that the farm operator has undertaken to improve security. However, considering that only about 24% of the farmers surveyed (30/125; Table 2) had undertaken measures to increase security on their farms in the last 2 or 3 yr, increased understanding of why only a small proportion of farmers have taken any steps to improve security may be important. The following equation shows a model for probability if the distribution of the error term is symmetric:

[3]

For normally distributed disturbances, either a logit or probit model may be used to estimate the probabilities according to Greene (2003). The explanatory variables describing the decision to improve on-farm security or not (y = SECURITY) are represented by the Xs in equation [3], which were the following:

[4]

where the variables are as defined in Table 2. If UNATTEND = 1, it indicates that the dairy is left unattended less than 12 h/d. The a priori expectation is that the fewer hours the dairy is left unattended, the less need there is to implement added security measures. Consequently, the expected sign for the estimated parameter for UNATTEND in a regression analysis is negative. If the dairy operator has a security policy in place, one would expect that efforts are more likely to have been made to improve security on the farm in the last few years. Consequently, the expected sign for POLICY’s estimated parameter is positive. If the farmer professes to believe that security measures against bioterrorism are important (IMPSECUR), then one would expect a higher likelihood that the farmer has taken measures to improve security on his/her farm and the expected sign of the parameter estimate for IMPSECUR is positive. The effect of experience (EXPER) on whether a dairy operator has increased security in the past few years is uncertain because the threat of bioterrorism is relatively new. Consequently, it is uncertain how the level of experience might affect the decision to increase on-farm security measures because probably all of the dairy farmers in the sample have had the same amount of experience with the specter of bioterrorism because it is so new.

If unauthorized persons are frequently found on the farm (UNAUTHP) one would expect that the farmer’s level of concern about intentional contamination would be heightened. Consequently, the a priori sign for UNAUTHP’s parameter estimate is positive. If the farmer has an idea of how much security improvements would cost (KNOWCOST), he or she must have at least thought about and probably made an effort to obtain these costs. Also, if he/she has been the victim of either intentional or unintentional contamination before (CONTAM), one would expect the farmer to be more sensitive to the potential threat of intentional contamination. For these reasons, the expected signs for the parameter estimates for KNOWCOST and CONTAM are both positive. Finally, the size of the milking herd (MILKING) likely increases the expected costs of a bioterrorist threat because a single act of intentional contamination potentially affects more animals or product. This suggests that the probability of a bioterrorist attack may be greater for larger dairies and that the cost of such an attack would be greater for larger dairies than for smaller dairies. Consequently, one would expect the sign for the parameter estimate for MILKING to be positive. The parameters for the binomial logit model described in equation [3] were estimated using LIMDEP (Greene, 1991).

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Survey participation response rates varied from 13 to 29% (Table 1). These rates may appear to be low; however, it is common to see response rates of 20 to 30% to mail surveys. Although it is difficult to determine if the results are representative of the population, the fact that the mean herd size for all states, with the exception of Idaho, was not statistically different suggests that the samples are representative of the population. One possible reason for the discrepancy in herd size for Idaho might be that the majority of farmers surveyed were from the eastern and southeastern part of Idaho, where a larger portion of smaller dairies exists. The 2 states with the lowest response rate were also those with the smallest number of total dairies. The failure of a dairy to respond would have a greater impact on the percentage for those states than a state with more dairies. Although we cannot determine reasons for nonresponse, it would be interesting to do a follow-up survey to determine if dairies that did not respond did so because of fear of being targeted by terrorists or increased government regulations that might result from the responses.

The frequencies and means of survey responses reported in Table 2 provided basic information on farmers’ characteristics, their attitudes about biosecurity issues, and whether they have recently improved security on their farms. Most of the farmers were experienced with at least 16 yr of experience as dairy farmers, and almost half having more than 25 yr of experience (EXPER in Table 2). Most of the dairies are left unattended fewer than 8 h/d (UNATTEND) and 62% (78 out of 126) are left unattended fewer than 5 h/d. This suggests a high level of direct observation of the operation by the farmer or employees and indicates that the window of opportunity for an external (nonemployee) bioterrorist to conduct operations undetected is limited to a few hours each day, probably at night. Only 22% of operations have a security policy in place (POLICY). This was a surprisingly low number, but may indicate that limited discussion and information about developing a plan has been provided to these farmers. Most of the farmers (almost 68%) either strongly agree or agree that it would be possible for an uninvited visitor to enter the farm unnoticed (UNNOTICE). This suggests that most of these farmers believe that an external bioterrorist could slip unnoticed onto their farms. The majority of respondents also believe that it would be possible to gain unauthorized access to the bulk tank (BULK) and feeding areas (FEED) on his/her farm. Obviously, an unauthorized person would need to enter the farm to gain access to the milk tank or the feeding areas. These questions, BULK and FEED were asked to ascertain if particular areas of the farm were more vulnerable than others. Also, the milk storage tank is left unlocked on almost all of the farms surveyed (LOCKLID).

About half of respondents (46.8%) indicate that they either strongly agree or agree that security measures would be important on their farm (IMPSECUR). But about 35% of the respondents (44 out of 126) are unsure whether the need for security measures on their farm is important. Only 18% of respondents (23 out of 126) are quite certain that security measures on their farm are unimportant (respondent either disagrees or strongly disagrees with IMPSECUR in Table 2). Only about 14% of respondents believed they knew how much it would cost to increase farm storage security for raw milk (KNOWCOST). Interestingly, over 22% of the respondents had experienced a problem with unintentional or intentional contamination (CONTAM). Although almost all of these cases were unintentional contamination, 2 respondents reported they had experienced intentional contamination. This suggests that even if security measures are not directed toward external bioterrorists, intentional contamination by employees or former employees is a potential threat that may need to be considered.

The survey results appear to confirm other assessments (e.g., National Academy of Sciences, 2002; Davis, 2003) that there may be relatively easy opportunities for bioterrorists to attack the food system at the farm level. The level of concern and level of preparedness appears to be mixed on these dairy farms, but leans toward unconcern and not being prepared. Obviously, this relates to the individual risk assessments each farmer makes about the threat of an attack on his/her individual farm. However, at minimum, the results suggest the need for additional information about potential threats and possible security measures that farmers could undertake that might counteract these threats. Costs of implementing security measures are likely a major consideration for these farmers and more information about specific security weaknesses and costs to develop systems to address those weaknesses needs to be researched.

The parameter estimates and marginal effects for the binomial logit analysis for respondent characteristics contributing to the decision to implement new or added security are reported in Table 3. The results suggest that the farmers most likely to have implemented improved security on their farms are those with a security policy in place (POLICY), know the costs for implementing improved security (KNOWCOST), and who have large dairies (MILKING). One might expect there to be a correlation between having recently completed security improvements and knowing the costs for doing so (KNOWCOST). The marginal effect for KNOWCOST indicates that a dairy operator that knew the costs for additional security was about 21% more likely to have implemented recent security improvements than an operator that did not know these costs. So, perhaps the 2 characteristics identified by the analysis (Table 3) that might offer new insights about the decision to improve security (or not) are POLICY and MILKING. The POLICY characteristic is probably affected by the level of information a producer has about security systems and protocols, and suggests that education about how to develop these policies would aid in the implementation of added security measures on dairy farms. However, the results also seem to suggest that the size of the operation is a very important determinant regarding recent decisions to improve security. This makes sense because there are probably economies of size associated with security improvements that would decrease the per-unit cost of improvements on large dairies compared with smaller dairies. For example, the marginal effect for MILKING suggests that a dairy with 1,100 cows would have a 40% greater probability of having recently completed security improvements compared with a dairy with just 100 cows.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

The results indicate that if the government believes that security education is important for farmers, different approaches to education about on-farm security will need to be taken with farmers with small and large operations. Educational efforts should probably focus on the potential risks from bioterrorists and disgruntled employees, and on developing a security policy for the farm.

	FOOTNOTES

 
¹ This research was supported by the Utah Agricultural Experiment Station, Utah State University, Logan. Approved as journal paper no. 7701.

Received for publication October 3, 2005. Accepted for publication November 30, 2005.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 


Avery, G. 2004. Bioterrorism, fear, and public health reform: Matching a policy solution to the wrong window. Public Health Rev. 64:275–288.

Bailey, D. 2004. Benefits and costs associated with an animal identification system for cattle in the United States. Western Extension Marketing Committee, WEMC FS#2-04, Fall 2004. Available: http://www.lmic.info/memberspublic/pubframes.html Accessed mon/day/year

Brookmeyer, R., and N. Blades. 2003. Statistical models and bioterrorism: Application to the U. S. anthrax outbreak. J. Am. Stat. Assoc. 98:781–788.

Clinton, H. R. 2002. Senator Clinton urges FBI to investigate possible bioterrorism on New York dairy farms. Available: http://Clinton.senate.gov/~clinton/news/2002/04/2002410A14.html Accessed Aug. 19, 2005.

Davis, R. G. 2003. Agroterrorism: Need for awareness. Pages 353–416 in Perspectives in World Food and Agriculture 2004. C. Scanes and J. Miranowski, ed. Blackwell Publishing, Malden, MA.

Dyckman, L. J. 2003. Bioterrorism: A threat to agriculture and the food supply. Testimony before the Committee on Governmental Affairs, US Senate. Released on November 19, 2003. Available: http://www.gao.gov/new.items/d04259t.pdf Accessed Aug. 22, 2005.

EDEN (Extension Disaster Education Network). Available: http://www.agctr.lsu.edu/eden/ Accessed March 17, 2005.

Fidler, D. P. 2002. Bioterrorism, public health, and international law. J. Int. Law 3:7–26.

Greene, W. H. 2003. Econometric Analysis. 5th ed. Prentice Hall, Upper Saddle River, NJ.

Greene, W. H. 1991. LIMDEP: User’s Manual and Reference Guide. Version 6.0. Econometric Software Inc., Bellport, NY.

Idaho Agricultural Statistics Service. 2004. Milk cows and production of milk and milkfat: Idaho 1994–03. Available: http://www.nass.usda.gov/id/publications/annualbulletin/2004/p55.pdf Accessed Aug. 22, 2005.

McDade, J. E. 1999. Addressing the potential threat of bioterrorism: Value added to an improved public health infrastructure. Emerg. Infect. Dis. 5:591–592.[Medline]

Montana Agricultural Statistics Service. 2004. Milk Cows: Number of farms, inventory, milk production, and milkfat. Montana. Available: http://www.nass.usda.gov/mt/Accessed Aug 22, 2005.

National Academy of Sciences. 2002. Countering agricultural bioterrorism. The National Academies Press, Washington, DC.

Nevada Agricultural Statistics Service. 2004. Milk cows and production of milk and milkfat: Nevada 1994–03. Available: http://www.nass.usda.gov/nv/Livestock.pdf Accessed Aug 22, 2005.

Siegrist, D. W. 1999. The threat of biological attack: Why concern now? Emerg. Infect. Dis. 5:505–508.[Medline]

Smith, S. 2002. U. S. farms called vulnerable to terrorism. The Boston Globe, November 22, 2002.

USDA Food Safety Inspection Service (FSIS). Protecting the Food Supply from Intentional Adulteration: An Introductory Training Session to Raise Awareness. Available: http://www.fsis.usda.gov/News_&_Events/Food_Security_Awareness_Training/index.asp Accessed March 17, 2005.

Utah Agricultural Statistics Service. 2004. Dairy: Farms, milk production and milkfat, Utah, 1996–2003, August 22, 2005. Available: http://www.nass.usda.gov/ut/Pdf/ab04/pg4904.pdf Accessed Aug 22, 2005.

Wyoming Agricultural Statistics Service. 2004. Milk cows on Wyoming farms and ranches that have calved by county, January 1, 1997–2004, August 22, 2005. Available: http://www.nass.usda.gov/wy/internet/cntydata/ce-milkcows.pdf Accessed Aug 22, 2005.

This article has been cited by other articles:

				D. A. Moore and M. Payne An Evaluation of Dairy Producer Emergency Preparedness and Farm Security Education J Dairy Sci, April 1, 2007; 90(4): 2052 - 2057. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Interpretive Summary Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Buttars, N. K. Articles by Bailey, D. Search for Related Content PubMed PubMed Citation Articles by Buttars, N. K. Articles by Bailey, D.