Abstract
Objective—To identify stakeholders who should be included in a Michigan-based avian influenza surveillance system (AISS) and to describe their avian influenza (AI) surveillance and reporting needs.
Design—Cross-sectional survey involving a convenience sample of respondents.
Sample—272 federal, state, and local governmental and regulatory agency professionals; veterinarians and laboratory professionals in academia; private practice veterinarians; and poultry industry members.
Procedures—A needs assessment survey that focused on stakeholder identification, current surveillance methods, information sharing, and desired AISS enhancements was administered by mail, and responses were summarized.
Results—Various AISS stakeholders were identified, among whom the requirements for surveillance information and methods of reporting (including via a World Wide Web-based database, e-mail, and a website) differed. Although 90% of all respondent types indicated that poultry industry representatives were key stakeholders, < 33% of poultry industry respondents indicated that private practice veterinarians and personnel in laboratories or public agencies should be considered stakeholders. The predominant concern (55.4% of respondents) regarding the current AISS was the effectiveness of communication among agencies, industry, and the public. The primary challenge identified by respondents was confidentiality (30.2% of respondents).
Conclusions and Clinical Relevance—In Michigan—and potentially in other regions of the United States—integration of Internet-related data systems and stakeholder communication is likely to promote earlier identification of AI, achieve more effective responses to outbreaks, reduce morbidity among humans and other animals, and decrease outbreak-associated financial losses. Stakeholder education and technological safeguard assurances will be essential in AISS enhancement.
Concern regarding the implications of AI outbreaks throughout the world is growing. This concern stems, in part, from the potential for a human influenza pandemic originating from HPAI virus infections.1–3 However, outbreaks of a specific strain of HPAI virus, known as H5N1, have spurred interest in this disease because of effects on the health of humans and other animals. Along with humans,1,2,4 birds (both domestic and wild),1,5–8 felids,9–11 and possibly other species12,13 are susceptible to infection with the HPAI H5N1 virus.
In 1997, the first case of bird-to-human transmission of the HPAI H5N1 virus was confirmed in Hong Kong. During this particular outbreak, 18 people became ill, of which 6 died.1,2 As of September 2009, the World Health Organization reported a total of 442 human cases and 262 deaths. Infections of humans with the HPAI H5N1 virus have occurred in Asia, Africa, Europe, the Pacific, and the Near East with most of the reports originating from Vietnam (111 cases and 56 deaths) and Indonesia (141 cases and 115 deaths).4
Reports of outbreaks of HPAI H5N1 virus infections in poultry and wild birds were first issued in 2003 in Southeast Asia. Poultry and wild bird cases have been identified across a geographic region similar to that in which human cases have been identified. Moreover, poultry and wild bird cases have been identified in areas in which human cases have yet to be reported, including Europe, Japan, and Russia.14 It has been estimated that > 150 million birds have died or been euthanized to date in an effort to contain the spread of the virus, and the disease is now considered to be endemic in bird populations in many parts of Asia.7
One scenario of a mild pandemic of HPAI virus infection estimated a loss of 1.4 million human lives and an economic cost of $330 billion (0.8% of global GDP) worldwide.15 Another, worst-case scenario proposed that 142.2 million people could lose their lives and the world could lose up to $4.4 trillion (12.5% of global GDP).15 In the United States, it has been estimated there could be an annual loss of $71.3 billion to $683 billion16,17 with economic losses of approximately 5.5% of the national GDP.17 Within the state of Michigan, the estimated loss from the state GDP if an influenza pandemic occurred was 5.39%, or $20.3 billion.17 This included a projected workforce loss of $9.6 billion, industry loss of $7.0 billion, and trade loss of $3.8 billion.
The PI in Michigan contributes substantially to the state's economic success. At the time of the 2007 census of agriculture in Michigan, there were 6,135 poultry farms and > 13 million birds.18 More specifically, in 2007, 9.1 million layer hens produced > 2.5 billion eggs that were valued at $155 million and the turkey industry raised 2 million turkeys that were valued at $84 million.18,19 During that year, poultry and egg sales accounted for 10.6% of the approximately $2.4 billion generated in Michigan livestock, poultry, and poultry product sales.20 Given this, the effects of HPAI H5N1 virus infection in Michigan would affect the productivity of the state's poultry and allied industries and would have a major impact on the state's economy.
To date, infection with HPAI H5N1 virus has not been detected in poultry, wild birds, or humans in North America. However, the potential for its entry into the United States exists because of factors such as human travel habits and migratory bird patterns.21–23 Early identification of cases and effective response should reduce the impact of a disease outbreak.24,25 Efforts are underway to develop surveillance systems that allow for ongoing data collection, collation, and analysis (ie, risk assessment).25–30 It is expected that these systems will contribute to accurate disease prevention and control strategies (ie, risk management) and risk communication for all stakeholders.31–35 With a One Health25,36,37 approach, effective surveillance and response must integrate the interests of multiple stakeholders, including public health and agricultural personnel and the community to save lives and ensure economic stability. To do this, it is imperative to include stakeholders in all stages of the development and deployment of a surveillance system.25,38
The purpose of the study reported here was to identify stakeholders who should be included in a Michigan-based AISS and to describe their AI surveillance and reporting needs by examining their perspective of surveillance methods, interagency and community information sharing, and surveillance system functions and their perceptions of the benefits and challenges associated with increased information sharing. It was anticipated that this information would provide a basis for continued enhancement of AI surveillance and reporting in Michigan, and indicate to other regional authorities in the United States that a comprehensive AISS can be created following identification of AISS stakeholders and their needs and consideration of input from all stakeholders.
Materials and Methods
Sample—In October 2007, a cross-sectional study was conducted with a convenience sample of persons from agencies known to be currently involved in the existing AISS in Michigan and individuals who were expected to have a role in avian disease reporting, diagnosis, and response and for whom contact information was readily available. The list frame developed included MAPI members; PPVs who were participating in the MSU College of Veterinary Medicine Large Animal Ambulatory Program; Michigan Veterinary Medical Association members who were working with livestock, poultry, or pet birds; public health and agricultural agency veterinarians; other professionals with regulatory and outbreak response assignments within the USDA-APHIS, MDA, MDNR, MDCH, MSU College of Veterinary Medicine, and MSU DCPAH; and all EXTs within the MSU Extension.
Needs assessment survey—An extensive, 8-page AISS needs assessment questionnairea was developed. For the purposes of future planning and system development, respondents were asked to identify which groups should be considered AISS stakeholders. The stakeholder groups for consideration were structured as follows: PI stakeholders included commercial producers, backyard poultry producers, and pet bird owners; community stakeholders included PPVs, private laboratory personnel, and the general public; and PAs included the USDA, MDA, MDNR, MDCH, MSU Extension, public laboratory personnel, and local health departments. An option was provided for respondents to identify other stakeholders in those groups or in addition to those groups.
Respondents were also asked to indicate what AI surveillance methods should be a part of the Michigan AISS and whether those systems should have mandatory or voluntary participation. The system types included a Michigan reportable disease list (eg, individual case reporting), flock sampling for poultry distributors and backyard poultry producers, bird sampling for county fair participants, US border testing, migratory bird testing, pet bird testing, fighting bird sampling, or none. An option was provided for respondents to identify other system types.
The agencies or organizations to which AI testing or disease reports should be provided were investigated. The agencies or organizations listed for consideration were the USDA, MDA, MAPI, MDNR, MDCH, MSU DCPAH, and National Poultry Improvement Plan. An option was provided for respondents to identify other agencies of organizations. With respect to AISS data collection, respondents were asked to indicate what means of reporting should be used and what general types of surveillance information should be collected. The means of communication for consideration were via telephone, fax, mail, e-mail, Web-based electronic report, and in person. An option was provided for respondents to identify other methods. The types of data for consideration included testing date, type or species of bird, clinical signs, bird identification method (eg, group or electronic identifier), vaccination status, location (eg, commercial premises or house), owner name, number of birds tested, number of birds affected, laboratory test results, information about other at-risk flocks, epidemiological data (eg, time and place or risk factor information), investigators assigned, regulatory procedures conducted, indemnity appropriated, and educational materials provided. An option was provided for respondents to identify other general types of data.
With respect to AISS data sharing, respondents were asked to identify the general types of AI surveillance information or reports that should be made accessible to 3 major stakeholder groups (ie, PI, community, and PA stakeholders); if respondents believed that other stakeholder groups should also have access to the information, those groups could be identified on the questionnaire. The types of data for consideration included no information, raw data (ie, with premises location and owner information), summary reports with aggregate counts (with no premises or owner information) of negative and positive test results and total number of birds tested, and maps displaying the aggregate counts (with no premises or owner information) of negative and positive results by county or region and total number of birds tested by county or region. An option was provided for respondents to identify other general AISS data sharing.
Enquiries were made regarding the best methods and optimal frequency of information sharing with 3 major stakeholder groups (ie, PI, community, and PA stakeholders); if respondents believed that other stakeholder groups should be included in data sharing, those groups could be identified on the questionnaire. Methods of data sharing for consideration included telephone, fax, mail, e-mail, immediate access via a Web-based database, website, newsletters, and meetings or presentations. Options were provided for respondents to indicate that information should not be shared and to identify other methods of AISS data sharing. Frequency of AI surveillance report sharing for consideration included immediately via access of a Web-based database, more than once a month, once a month, every 6 months, and annually. Options were provided for respondents to indicate that information should not be shared and to identify AISS data sharing at alternate frequencies.
Respondents were also asked how they would use AI surveillance reports or AI-related information. The questions included whether the respondent would use the information to make business decisions, determine which biosecurity practices to implement, assist in development of state animal health policies, assist in outbreak response processes, meet grant requirements, determine which educational materials to distribute, and conduct field research. Options were provided for respondents to indicate that they would not use such information and to identify other uses for reports and other information.
Respondents were asked to describe their perception of the effects of increased AISS information sharing on a variety of surveillance processes, including sample submission, AI reporting, and outbreak preparedness, identification, response, and recovery. An option was provided for respondents to identify other processes that might be affected. Respondents were invited to state whether they perceived that increased AISS information sharing would be greatly beneficial, somewhat beneficial, of no benefit, would hinder the process, or would eliminate the process.
Another question was designed to determine what barriers would keep respondents from entering surveillance information into a Web-based disease reporting system; the options provided were that the respondent never reports AI disease cases or related information, has insufficient time to enter or send reports or related information, has no staff support available to enter or send reports or related information, has inadequate computer facilities (eg, no Internet access), has concerns regarding data security and perception of confidentiality problems, and prefers to report cases personally. An option was provided for respondents to identify other barriers.
Another question asked respondents to specify AISS-related services that would be useful to them. Options provided for consideration included resources for disease identification, direct case reporting mechanism, case feedback information, case and outbreak management tools, disease or outbreak response information and fact sheets, disease surveillance information from surrounding areas, outbreak alert information, disease prevention and control guidelines, easy access to state regulatory requirements, and easy access to business and industry resources. An option was provided for respondents to identify other AISS-related services that would be useful to them. There was also an open question regarding what types of confidentiality issues might impede the AI reporting and surveillance process in Michigan, which required respondents to enter free text.
With respect to the status of the Michigan AISS, participants were asked to describe their perceptions of the national rank of the current Michigan AISS as among the best in the country, an average system, among the worst in the country, or do not know. Open questions invited respondents to identify 2 strengths and 2 weaknesses of the Michigan AISS, 2 major benefits of improving the sharing of AI surveillance information among stakeholders in Michigan, 2 challenges or hesitations regarding such information sharing, and recommendations or suggestions for strengthening the state's ability to conduct AI surveillance. To answer these questions, respondents were required to enter free text. A final section was provided for respondents to communicate any additional thoughts on the current AISS in Michigan.
The study design and confidentiality safeguards were reviewed and approved by the MSU Committee on Research Involving Human Subjects. All of the list frame subjects (272 individuals) were mailed the pre-coded needs assessment questionnaire. A cover letter describing the study and confidentiality safeguards accompanied the questionnaire. Those persons who did not respond after 6 weeks were sent a second mailing of the study materials. Participants were grouped by respondent type (PI, PPV, PA, or EXT) on the basis of their list frame classification. Data from coded (deidentified) questionnaires were summarized by use of statistical software.b The distribution of completed surveys received by respondent type versus the distribution of surveys was examined by use of a χ2 test; a value of P ≤ 0.05 was considered significant.
Results
Of the 272 questionnaires administered, 121 (44.5%) surveys were returned: 15 from PI participants, 42 from PPV participants, 22 from PA participants, and 42 from EXT participants. Although the response rates differed across participant types, the distribution of surveys returned by participant type was not significantly (P = 0.43) different than the distribution of surveys mailed (Table 1). For individual questions, the total number of completed responses is indicated.
Classification of 121 participants who returned an AISS needs assessment survey.
| Participant classification | No. of surveys sent (%) | No. of surveys returned (%) | Response rate (%) |
|---|---|---|---|
| PI | 42 (15.4) | 15 (12.4) | 35.7 |
| PPV | 107 (39.3) | 42 (34.7) | 39.3 |
| PA | 35 (12.9) | 22 (18.2) | 62.9 |
| EXT | 88 (32.4) | 42 (34.7) | 47.7 |
| Total | 272 (100) | 121 (100) | 44.5 |
Michigan AISS stakeholders—Respondents identified multiple stakeholders for inclusion in the Michigan AISS, although the importance of each differed by respondent type (Table 2). Approximately 90% of all respondent types indicated that PI representatives were key stakeholders; the proportion of each respondent type that indicated the need to include backyard poultry or pet bird owners in the process was less. Private practice veterinarians were, however, more inclined to consider pet bird owners as stakeholders (64.3% of PPV respondents) than were other respondent types. In contrast, < 33% of PI respondents indicated that PPVs or personnel in laboratories or any PA should be considered a stakeholder, whereas > 78% of all the remaining respondent types indicated that PPVs or personnel in laboratories or any PA should be considered a stakeholder. The general public was considered to be a stakeholder by < 50% of all respondents. Other PI stakeholders identified were game bird producers, avian conservation groups, poultry distributors and processors, and commercial livestock producers. Other PA stakeholders identified were state and local law enforcement and state and local elected officials. Other community stakeholders identified were private practice physicians, the bird hunting community, media personnel, and local emergency planning committees.
Avian influenza surveillance system stakeholders identified by respondents (described in Table 1) who returned an AISS needs assessment survey.
| Stakeholder | PI (No. of respondents [%]; n = 15) | PPV (No. of respondents [%]; n = 28) | PA (No. of respondents [%]; n = 16) | EXT (No. of respondents [%]; n = 26) | Total (No. of respondents [%]; n = 85) |
|---|---|---|---|---|---|
| PI | |||||
| Commercial | 15 (100.0) | 26 (92.9) | 14 (87.5) | 23 (88.5) | 78 (91.8) |
| Backyard | 5 (33.3) | 23 (82.1) | 12 (75.0) | 21 (80.8) | 61 (71.8) |
| Pet owners | 1 (6.7) | 18 (64.3) | 6 (37.5) | 7 (26.9) | 32 (37.6) |
| Community | |||||
| PPV | 5 (33.3) | 25 (89.3) | 13 (81.3) | 24 (92.3) | 67 (78.8) |
| Private diagnostic | 3 (20.0) | 22 (78.6) | 14 (87.5) | 21 (80.8) | 60 (70.6) |
| General public | 1 (6.7) | 14 (50.0) | 5 (31.3) | 7 (26.9) | 27 (31.8) |
| PA | |||||
| USDA | 5 (33.3) | 25 (89.3) | 13 (81.3) | 25 (96.2) | 68 (80.0) |
| MDA | 5 (33.3) | 26 (92.9) | 14 (87.5) | 26 (100.0) | 71 (83.5) |
| MDNR | 1 (6.7) | 17 (60.7) | 13 (81.3) | 22 (84.6) | 53 (62.4) |
| MDCH | 1 (6.7) | 25 (89.3) | 13 (81.3) | 25 (96.2) | 64 (75.3) |
| MSU Extension | 4 (26.7) | 21 (75.0) | 11 (68.8) | 26 (100.0) | 62 (72.9) |
| Public diagnostic laboratories | 0 (0.0) | 22 (78.6) | 13 (81.3) | 21 (80.8) | 56 (65.9) |
| Local health departments | 2 (13.3) | 23 (82.1) | 13 (81.3) | 25 (96.2) | 63 (74.1) |
AI surveillance methods—All of the listed types of surveillance methods were indicated as important to some degree by all types of respondents (Table 3). Specifically, > 50% of PI respondents chose each of the methods of surveillance, the most important of which were US border testing (80.0% of PI respondents) and individual case reporting (73.3% of PI respondents). Individual case reporting, commercial and distributor flock sampling, and US border testing were each indicated by > 50% of each of the remaining respondent types. Overall, in contrast to the PI respondents, the remaining 3 groups of respondents indicated that there was a lesser need for backyard flock sampling and for each of the remaining individual bird sampling systems. Additional surveillance systems suggested by respondents included wild and domestic bird die-offs and seized illegal poultry products.
Surveillance systems that should be included in the AISS identified by respondents who returned an AISS needs assessment survey.
| Mandatory surveillance systems | PI (No. of respondents [%]; n = 15) | PPV (No. of respondents [%]; n = 42) | PA (No. of respondents [%]; n = 22) | EXT (No. of respondents [%]; n = 41) | Total (No. of respondents [%]; n = 120) |
|---|---|---|---|---|---|
| Individual case reporting | 11 (73.3) | 39 (92.9) | 19 (86.4) | 27 (65.9) | 96 (80.0) |
| Flock sampling | |||||
| Commercial | 7 (46.7) | 32 (76.2) | 18 (81.8) | 20 (48.8) | 77 (64.2) |
| Distributor | 7 (46.7) | 32 (76.2) | 17 (77.3) | 23 (56.1) | 79 (65.8) |
| Backyard | 8 (53.3) | 10 (23.8) | 4 (18.2) | 11 (26.8) | 33 (27.5) |
| Bird sampling | |||||
| At county fair | 10 (66.7) | 16 (38.1) | 7 (31.8) | 17 (41.5) | 50 (41.7) |
| At US border | 12 (80.0) | 31 (73.8) | 18 (81.8) | 34 (82.9) | 95 (79.2) |
| Migratory bird | 9 (60.0) | 21 (50.0) | 8 (36.4) | 22 (53.7) | 60 (50.0) |
| Pet bird | 7 (46.7) | 4 (9.5) | 0 (0.0) | 10 (24.4) | 21 (17.5) |
| Fighting bird | 9 (60.0) | 20 (47.6) | 8 (36.4) | 17 (41.5) | 54 (45.0) |
Reporting of AISS results to agencies—Of 120 respondents, 113 (94.2%) indicated that results of AI testing or disease status reports should be shared with the MDA and 95 (79.2%) indicated that reports should be shared with the USDA APHIS Veterinary Services. Poultry industry respondents (n = 15) and EXT respondents (41) indicated that MAPI (73.3% and 70.7% of respondents, respectively) and MSU DCPAH (66.7% and 90.2% of respondents, respectively) were agencies that should also receive AI reports. Overall, only 83 of 120 (69.2%) respondents indicated that reporting AI results to the MDCH was necessary. A total of 6 of 15 (40.0%) PI respondents and 28 of 42 (66.7%) PPV respondents found it to be less important to report AI to MDCH, compared with 17 of 22 (77.3%) PA respondents and 32 of 41 (78.0%) EXT respondents. Other agencies suggested by respondents to receive status reports included MSU Extension, local health departments, the CDC, the World Health Organization, the National Wildlife Health Center, the AVMA, and the Michigan Agricultural Experiment Station.
AI reporting methods—Of 15 PI respondents, 12 (80.0%) indicated that the most preferred AI reporting method was via telephone followed by e-mail (n = 6) and fax (6). A total of 34 of 42 (81.0%) PPV respondents and 36 of 41 (87.8%) EXT respondents reported that e-mail was their most preferred reporting method; for 16 of 22 (72.7%) PA respondents, e-mail was the second most preferred method. Eighteen of 22 (81.8%) PA respondents indicated that a Web-based database was the most preferred method for disease status information sharing among agencies, whereas 34 of 41 (82.9%) EXT respondents indicated it was the second most preferred method. The least preferred reporting method among all respondent types (n = 120) was in person (18.3%).
AISS data collection—Among all respondent types (n = 121), testing date (95.0% of respondents), bird description (95.8% of respondents), bird location (92.5% of respondents), laboratory results (90.8% of respondents), total number of birds affected (89.2% of respondents), total number of birds tested (89.2% of respondents), and clinical signs (85.0% of respondents) were identified as the most important types of data to collect. Public agency respondents (n = 22) also reported that bird identification (90.9%) and owner name (86.4%) should be included, compared with only 66.7% and 40.0%, respectively, of PI respondents (n = 15) and 58.5% and 58.5%, respectively, of EXT respondents (n = 42). Among all 121 respondents, < 57% indicated that disease investigation information regarding investigators assigned, other flocks at risk, regulatory procedures conducted, indemnity appropriated, and educational materials provided was important to collect. Disposal method was another type of data to be collected, as suggested by 1 respondent.
Types of surveillance information that should be shared with stakeholders—Among all respondents (n = 121), < 11% reported that no information should be shared with representatives in 3 general stakeholder groups (PI, community, or PAs; Table 4). Within specific respondent types, 5 of 15 (33.3%) PI respondents indicated that no information should be shared with community stakeholder groups, compared with < 10% of respondents within each of the remaining 3 respondent types (42 PPV respondents, 22 PA respondents, and 42 EXT respondents). Only 4 of 15 (26.7%) PI respondents indicated that raw data should be shared with PA stakeholder groups, compared with 20 of 42 (47.6%) PPV respondents, 15 of 22 (68.2%) PA respondents, and 25 of 42 (59.5%) EXT respondents. Between 40% and 60% of PI respondents indicated that PI stakeholder groups should receive the aggregate count reports (ie, aggregate report of negative and positive test results, aggregate report of the total number of birds tested, maps of negative and positive test results by county or region, and maps of the total number of birds tested by county or region), compared with between 70% and 91% of each of the other 3 respondent types. Between 6% and 20% of PI respondents indicated that PA stakeholder groups should receive the aggregate types of reports listed, compared with 69% to 91% of each of the other 3 respondent types. Between 6% and 20% of PI respondents indicated that community stakeholder groups should receive the aggregate reports listed on the questionnaire, compared with 50% to 73% of each of the other 3 respondent types. As suggested by respondents, other types of surveillance data that should be made available to stakeholders were the quarantine procedures and type of treatment at sites with positive tests results.
Formats for AISS information sharing with 3 general stakeholder groups identified by all respondents who returned an AISS needs assessment survey.
| No. of respondents in favor of information sharing with stakeholder group (%; n = 121) | |||
|---|---|---|---|
| Format | PI | Community | PA |
| No information should be made available | 1 (0.8) | 13 (10.7) | 4 (3.3) |
| Raw data | 42 (34.7) | 3 (2.5) | 64 (52.9) |
| Summary report with aggregate count of negative and positive test results | 100 (82.6) | 68 (56.2) | 95 (78.5) |
| Summary report with aggregate count of total No. of birds tested | 84 (69.4) | 61 (50.4) | 78 (64.5) |
| Map displaying aggregate counts of negative and positive results by county or region | 99 (81.8) | 75 (62.0) | 91 (75.2) |
| Map displaying aggregate counts of total No. of birds tested by county or region | 91 (75.2) | 66 (54.5) | 83 (68.6) |
AI surveillance information sharing methods— Among all respondents (n = 121), the most preferred methods of sharing information with PI and PA stakeholder groups were via e-mail, a Web-based database, and a website (Table 5). Respondents most commonly indicated that no information should be shared with community stakeholder groups (11.6% of respondents); if information was shared, the most preferred method of providing information to community stakeholder groups was indicated as via a website (58.7% of respondents).
Methods for sharing AISS information with 3 general stakeholder groups identified by all respondents who returned an AISS needs assessment survey.
| No. of respondents in favor of information sharing with stockholder group (%; n = 121) | |||
|---|---|---|---|
| Method | PI | Community | PA |
| Provide no information | 2 (1.7) | 14 (11.6) | 7 (5.8) |
| 79 (65.3) | 26 (21.5) | 74 (61.2) | |
| Fax | 54 (44.6) | 15 (12.4) | 51 (42.1) |
| Telephone | 45 (37.2) | 12 (9.9) | 40 (33.1) |
| Web-based database | 72 (59.5) | 38 (31.4) | 77 (63.6) |
| Website | 71 (58.7) | 71 (58.7) | 71 (58.7) |
| Newsletter | 59 (48.8) | 42 (34.7) | 56 (46.3) |
| Meeting or presentation | 54 (44.6) | 56 (46.3) | 49 (40.5) |
Within specific respondent types, 6 of 15 (40.0%) PI respondents indicated that no information should be shared with community stakeholder groups and 3 (20.0%) of those respondents indicated that no information should be shared with PA groups. Poultry industry respondents (n = 15) indicated that the preferred methods of information sharing with PI stakeholder groups were via e-mail (60.0% of respondents), telephone (60.0% of respondents), and fax (53.3% of respondents). Private practice veterinarians (n = 42) indicated that preferred methods of information sharing with PI stakeholder groups were via e-mail (66.7% of respondents), Web-based database (64.3% of respondents), and a website (64.3% of respondents). Public agency respondents (n = 22) indicated that preferred methods of information sharing with PI stakeholder groups were via a website (81.8% of respondents), newsletter (68.2% of respondents), and e-mail (63.3% of respondents); EXT respondents (42) indicated that preferred methods of information sharing with PI stakeholder groups were via e-mail (66.7% of respondents), a Web-based database (66.7% of respondents), and a website (59.5% of respondents). Public agency respondents (n = 22) indicated that the preferred methods of information sharing with PA stakeholder groups were via a Web-based database (86.4% of respondents), e-mail (81.8% of respondents), and a website (72.7% of respondents). Private practice veterinarians (n = 42) indicated that preferred methods of information sharing with PAs were via a website (64.3% of respondents), e-mail (61.9% of respondents), fax (61.9% of respondents) and a Web-based database (59.5% of respondents), whereas EXT respondents (42) indicated that the preferred methods were via a Web-based database (71.4% of respondents), e-mail (64.3% of respondents), and a website (61.9% of respondents). Other methods for sharing information with community stakeholders, as suggested by respondents, included via radio and television public announcements, press releases, and newspapers and through the Michigan-Health Alert Network currently used by PAs.
Frequency of AI surveillance report sharing—Among the 121 respondents, immediate access to shared information via a Web-based database was identified as the best reporting frequency for PI stakeholders (58.7% of respondents), community stakeholders (27.3% of respondents), and PA stakeholders (62.0% of respondents). However, 10.7% of respondents specified that reports should be released to the public only on an as-needed basis or when public preparedness is required of community stakeholders.
Use of AI surveillance reports—Among the 121 respondents, 78 (64.5%) indicated that surveillance reports would be used to assist in outbreak response processes, followed by to determine which educational materials to distribute (73 [60.3%]) and to determine which biosecurity practices to implement (50 [41.3%]). Within respondent types, PI respondents (n = 15) indicated that their primary use of the reports would be to guide implementation of biosecurity practices (86.7% of PI respondents), to make business decisions (46.7% of PI respondents), and to assist in outbreak response processes (46.7% of PI respondents). Private practice veterinarians (n = 42) stated that they would use the reports to assist in outbreak response processes (59.5% of respondents), to determine which educational materials to distribute (52.4% of respondents), and to determine which biosecurity practices to implement (47.6% of respondents). Public agency respondents (n = 22) indicated that they would use the reports to assist in the outbreak response process (81.8% of PA respondents), to assist in development of state animal health policies (68.2% of PA respondents), and to determine which educational materials to distribute (63.6% of PA respondents). Extension specialist respondents (n = 42) indicated that the reports would be used to determine which educational materials to distribute (83.3% of EXT respondents) and to assist in the outbreak response process (66.7% of EXT respondents). Other uses of the system that were identified by respondents included use for human disease surveillance, in prioritizing and initiating vaccine distribution, to direct distribution of personal protective equipment, to provide food safety education for hunters, to respond to AI questions from clients, and for personal knowledge.
Effects of increased AISS information sharing—Among 116 respondents, 50 (43.1%) indicated that sample submission would be somewhat benefited and 24 (20.7%) indicated that it would be greatly benefited. Only 6 of 116 (5.2%) respondents indicated that sample submission would be hindered by increased information sharing. The 116 respondents indicated that the following processes would be greatly benefited: outbreak identification (74.4%), outbreak response (67.8%), outbreak preparedness (60.3%), outbreak recovery (52.1%), and AI reporting (42.2%).
Barriers to Web-based reporting of AI surveillance information—Among the 121 respondents, < 27% identified barriers to entering data into a Web-based database (Table 6). Within respondent types, the main deterrent to entering data into a Web-based database for both the PI and PA respondents was concerns regarding data security issues or confidentiality problems (53.3% and 31.8%, respectively). Private practice veterinarians (n = 42) preferred personal reporting (33.3%) or did not have enough staff for data entry (31.0%). Extension specialist respondents indicated that they did not have occasion to report AI disease cases or related information (59.5% of respondents). Other barriers identified by respondents included lack of computer knowledge, concerns regarding inaccurate reporting or mistakes when entering information, and not knowing what to report.
Barriers to entering AI surveillance information into a Web-based disease reporting system identified by respondents who returned an AISS needs assessment survey.
| Barriers | PI (No. of respondents [%]; n = 15) | PPV (No. of respondents [%]; n = 42) | PA (No. of respondents [%]; n = 22) | EXT (No. of respondents [%]; n = 42) | Total (No. of respondents [%];n = 121) |
|---|---|---|---|---|---|
| Never report AI cases or related information | 0 (0.0) | 2 (4.8) | 5 (22.7) | 25 (59.5) | 32 (26.4) |
| No time for data entry | 3 (20.0) | 10 (23.8) | 2 (9.1) | 4 (9.5) | 19 (15.7) |
| No staff for data entry | 2 (13.3) | 13 (31.0) | 4 (18.2) | 9 (21.4) | 28 (23.1) |
| Inadequate computer facilities | 2 (13.3) | 5 (11.9) | 3 (13.6) | 1 (2.4) | 11 (9.1) |
| Concerns regarding data security and confidentiality | 8 (53.3) | 6 (14.3) | 7 (31.8) | 6 (14.3) | 27 (22.3) |
| Prefer to report personally | 4 (26.7) | 14 (33.3) | 1 (4.5) | 2 (4.8) | 21 (17.4) |
Useful AISS Internet-related services—Among all 121 respondents, > 38% of the suggested AISS Internet-related services were considered to be important (Table 7). Within respondent type, along with outbreak alert information, the 15 PI and 22 PA respondents indicated that surveillance information from surrounding areas would be useful (53.3% and 90.9%, respectively). The 42 PPV respondents indicated a need for disease identification resources (90.5% of respondents), disease or outbreak response information and fact sheets (85.7% of respondents), and disease prevention and control guidelines (81.0% of respondents). Extension specialist respondents (n = 42) also indicated a need for disease or outbreak response information and fact sheets (83.3% of respondents) and disease identification resources (76.2% of respondents). Another service suggested by a respondent was to have telephone access to a professional consultant who could answer questions.
Useful AISS Internet-related services identified by respondents who returned an AISS needs assessment survey.
| Service | PI (No. of respondents [%]; n = 15) | PPV (No. of respondents [%]; n = 42) | PA (No. of respondents [%]; n = 22) | EXT (No. of respondents [%]; n = 42) | Total (No. of respondents [%];n = 121) |
|---|---|---|---|---|---|
| Outbreak alert information | 10 (66.7) | 35 (83.3) | 21 (95.4) | 37 (88.1) | 103 (85.1) |
| Disease identification resources | 7 (46.7) | 38 (90.5) | 14 (63.6) | 32 (76.2) | 91 (75.2) |
| Disease or outbreak response information and fact sheets | 4 (26.7) | 36 (85.7) | 16 (72.7) | 35 (83.3) | 91 (75.2) |
| Disease prevention and control guidelines | 5 (33.3) | 34 (81.0) | 18 (81.8) | 33 (78.6) | 90 (74.4) |
| Disease surveillance information from surrounding areas | 8 (53.3) | 30 (71.4) | 20 (90.9) | 31 (73.8) | 89 (73.6) |
| Easy access to state regulatory requirements | 5 (33.3) | 28 (66.7) | 16 (72.7) | 27 (64.3) | 76 (62.8) |
| Direct case reporting mechanism | 7 (46.7) | 32 (76.2) | 15 (68.2) | 18 (42.8) | 72 (59.5) |
| Case and outbreak managementtools | 5 (33.3) | 27 (64.3) | 17 (77.3) | 23 (54.8) | 72 (59.5) |
| Easy access to business and industry resources | 3 (20.0) | 18 (42.8) | 12 (54.5) | 19 (45.2) | 52 (43.0) |
| Case feedback information | 6 (40.0) | 22 (52.4) | 7 (31.8) | 11 (26.2) | 46 (38.0) |
Perceived ranking of the current Michigan AISS—Of 121 respondents, 70 (57.9%) indicated that they did not know how the current Michigan AISS ranked nationally, whereas 39 (32.2%) perceived it to be an average system and 11 (9.1%) perceived it to be one of the best in the nation. Within respondent type, 9 of 15 (60.0%) PI respondents and 19 of 22 (86.4%) PA respondents indicated it was an average system or among the best in the country, whereas 31 of 42 (73.8%) PPV respondents and 32 of 42 (76.2%) EXT respondents indicated that they did not know.
Confidentiality concerns—Only 34 of 121 (28.1%) respondents completed an open-ended question addressing confidentiality issues that might impede AI reporting and surveillance. When grouped by response type, the most important challenge proposed by 10 of 34 (29.4%) respondents was concern that specific farm information and location would be leaked to the public. Additionally, 7 of 34 (20.6%) respondents were concerned about the possibility for media overreaction that would cause public panic. The remaining concerns focused on issues such as financial loss (11.7% of respondents), fear of government (11.7% of respondents), reluctance of small flock owners to participate (8.8% of respondents), reluctance of industry to report positive test results (8.8% of respondents), targeting of farms by animal rights activists (5.9% of respondents), and confidentiality compliance among human and animal agencies (2.9% of respondents).
Strengths of the current MI AISS—Of 121 respondents, 61 (50.4%) completed an open-ended question addressing the strengths of the current Michigan AISS program. When the types of response were grouped, 27 (44.3%) respondents indicated that there was strong industry-agency cooperation and industry participation in Michigan, 20 (32.8%) indicated strength in commercial testing methods and availability of diagnostic staff, and 9 (14.8%) indicated strength in effective preplanning being conducted in Michigan.
Concerns regarding the current MI AISS—Of 121 respondents, 56 (46.3%) completed an open-ended question addressing their concerns with the current Michigan AISS program. When the types of response were grouped, 31 (55.4%) respondents were concerned with the effectiveness of communication among agencies, between agencies and industry, and with the public. This concern was followed by a concern about the lack of backyard flock monitoring (23.2% of respondents), issues with test sensitivity and surveillance programs (19.6% of respondents), and funding (12.5% of respondents).
Benefits of improving sharing of AI surveillance information in Michigan—Of 121 respondents, 105 (86.8%) completed an open-ended question addressing the perceived benefits of enhanced sharing of AI surveillance information in Michigan. When the types of response were grouped, 34 (32.4%) respondents indicated that the primary benefit would be faster outbreak response, followed by increased AI awareness (26 respondents [24.8%]) and improvements in communication and agency-industry cooperation (22 respondents [21.0%]). Preparedness efforts (12.4% of respondents) and outbreak recovery (9.5% of respondents) would also benefit.
Challenges associated with sharing of AI surveillance information in Michigan—Of 121 respondents, 86 (71.1%) completed an open-ended question addressing the perceived challenges associated with AI surveillance information sharing in Michigan. When the types of response were grouped, 26 (30.2%) respondents indicated that confidentiality would be an important issue; 23 (26.7%) indicated that media reaction and public overreaction may arise. Fifteen of the 86 (17.4%) respondents indicated that programmatic issues, including participation levels, program costs, and program inefficiencies, were concerning; 11 (12.8%) respondents indicated that business-related issues, including financial losses, competition, and market share, were important. Eleven (12.8%) respondents indicated that data quality issues were concerning.
Discussion
Results of the present study suggest that enhancing AI surveillance in Michigan was perceived as a means to promote faster outbreak response, increase AI awareness, and improve communications between the PI, PAs, and other AISS stakeholders. However, the perception of who should be involved and how an AISS should function was aligned primarily with the roles and responsibilities of the respondent. In general, PI representatives based their definition of the use of system functionality on business practices, PPV representatives based their definition on individual animal healthcare practices and client education, PA representatives based their definition on community-level health care, and EXT representatives based their definition on community education and response support. The perceived value of a surveillance system and the associated confidence of reported disease-free status can be related to multiple factors that have a direct economic, political, and social benefit to users as well as an indirect benefit by providing confidence to their trading partners that the animal sources will not acquire disease.39 Therefore, because these respondents have a variety of roles and responsibilities, it is anticipated that any enhancement of the Michigan AISS or any other AISS in the United States must include the requirements of multiple types of stakeholders to ensure participation.38,40
Identification of stakeholders to be included in a surveillance system is critical, and it must be ensured that each can make accurate risk assessments and informed decisions during response to an AI outbreak.27,33,35,38,40 In the present study, the stakeholders identified were part of diverse groups with diverse needs within the current AISS. It is interesting that PPV, PA, and EXT representatives viewed themselves as well as PI representatives to be important AISS stakeholders. Yet, in turn, PPVs, PAs, and EXTs, who serve the PI, were not viewed to be stakeholders by PI representatives. Additionally, even though AI is a zoonotic disease with health implications for humans and other animals,1,41 reporting to public health authorities was of lower priority to PI representatives and PPV representatives than it was for PA and EXT representatives. The concept of One Health36,37 should be considered when attempting to integrate health reporting issues for humans and other animals. Stressing the zoonotic potential of AI may facilitate cooperation among stakeholders. Increased understanding and acceptance of the roles and responsibilities of each of the stakeholder groups within the system should help to promote both the success of the PI and public health.28,41
Concerns with and challenges of an AISS that were mentioned may provide an indication of what could be driving the value placed by respondents on who should or should not be included as a stakeholder in the AISS. Although there were few concerns with the current AISS overall, respondent identification of programmatic issues, confidentiality, media and public overreaction, and the potential financial impact of the release of information indicated that there should be a great deal of importance placed on information security. Additionally, because the PI representatives did not believe that other potentially supporting groups were stakeholders, this may indicate an overall lack of trust or confidence with those involved in AI surveillance or response.
Although the needs assessment of the present study was based on a convenience sample of targeted individuals known to be involved in the current AISS or whose roles and responsibilities were expected to relate to AI outbreak identification and response, the response rate was relatively low.42,43 This may be attributable to the length (8 pages) and complexity of the survey; the lack of a third mailing or personal interview; the inclusion of individuals who do not routinely participate in AI-specific surveillance, reporting, or response; or the lack of engagement of essential stakeholders in the current surveillance process.40,42–44
With respect to stakeholder engagement, the lowest response rates were among PI and PPV representatives, compared with response rates among PA and EXT representatives. The low participation rate of PI representatives, even with assurances of confidentiality from their industry organization (MAPI), may be related to such issues as a lack of confidence in government programs, lack of desire to share information about their industry, lack of perceived need for enhanced AI surveillance, or lack of knowledge of the potential benefits of an enhanced AISS. The PPV representatives in the present study were primarily large animal veterinarians or veterinarians who indicated that they worked with pet birds. Their relatively low response rate may be related to a lack of direct involvement with the commercial PI (ie, small animal practitioners) or pet bird care (ie, large animal veterinarians), lack of confidence in government programs, or lack of a perceived need to enhance AI surveillance, among other factors. Small and large animal veterinarians are often considered to be zoonotic disease experts, and they are often the link between producers and PAs, so their engagement in AI disease surveillance is essential.41,45,46
In contrast, the response rates among PA and EXT representatives, who are likely those most involved in AI surveillance and response planning and have assigned roles and responsibilities that require disease information and population health data for decision-making and community-outreach purposes, were comparatively high. It is interesting that although all current EXT representatives were included in the sample and not all participated with animal-related health concerns, they had a relatively high response rate, which may reflect their comfort with government-related programs and their responsibilities to the health of populations of both humans and other animals.
A greater survey response rate could be expected in future studies if the survey was reduced considerably in length and complexity and included a follow-up personal interview.42,43 Additionally, as AISS enhancement continues, it will be crucial to identify factors that may be related to lack of engagement of stakeholders in an AISS and a perceived lack of need to include stakeholders who have assigned roles and responsibilities in the AI surveillance and response process. Identification of and contributions from potential AISS stakeholders will be necessary to ensure an effective system is developed that will benefit a diverse group of stakeholders.28,41,44,47
Despite the low response rate, results of the present study should be representative of individuals that have a strong interest in AI disease surveillance.43 Among these individuals, there was a sense of cooperation between AISS stakeholders in Michigan with respect to industry-agency cooperation, industry participation, and diagnostic capabilities. However, the effectiveness of communication among agencies, between agencies and industry, and between stakeholders and the public was one of the most common concerns regarding the current AISS. Lack of communication can reduce confidence and trust among stakeholders and lead to lack of engagement in surveillance system development.40,44
Communication through AISS information sharing was expected to provide benefits to outbreak identification, response, preparedness, and recovery. The main objective of infectious disease surveillance is to reduce the number of disease cases by enabling the administration of prophylaxis rapidly or to allow for social distancing to reduce the spread of disease.24 To achieve this, a disease outbreak must be recognized in the very early stages so that treatment and control efforts have high chances of a successful outcome.24,39,48 In the present study, it was concerning that although sample submission was not expected to be affected by increased information sharing, AI reporting was least likely to benefit from increased information sharing. A previous needs assessment of Michigan veterinarians identified low rates of case feedback after sample submission.49 Among stakeholders, clarification of the reasons why testing is required, the use of reported information, and the methods of information sharing may promote sample submission and disease reporting. Additionally, producers and veterinarians may be more inclined to submit samples for testing when they obtain some direct benefit from information that will help them solve their day-to-day animal health problems.39 The PI representatives placed importance on reporting to their industry alliance, the MAPI, and the state's veterinary diagnostic laboratory, the MSU DCPAH. These relationships may provide a foundation for development of more effective reporting systems in Michigan and similarly on a nationwide basis.
Poultry industry and PA representatives indicated that the Michigan AISS was average or among the best in the nation, whereas PPV and EXT representatives were identified as the stakeholders who knew the least about the system. Along with engagement, education related to AI surveillance in Michigan will be important for all stakeholders and should include information about what is being developed, where the stakeholders fit in, and how the system applies to the stakeholders' daily work.
Avian influenza and other emerging diseases are zoonotic,1,41,48 and because of this, the earliest cases may be identified in populations of either humans or other animals.39,41,48,49 Therefore, there has been a call for increased zoonotic disease surveillance on international,25,50 national,29,51,52 and local49,53 levels that includes surveillance of humans, domestic and wild animals, and other related environmental factors.
At the national level, several efforts are underway to enhance AI and other animal disease surveillance systems,28,54–57 diagnostic capacity,30 poultry health,58 and AI outbreak response.22,59 In Michigan, implementation of national programs at the state level, development of local surveillance and response systems, and building trust among AISS stakeholders are also ongoing. These efforts are being guided by the Avian Influenza Interagency Workgroup, which brings together representatives from a wide variety of AI stakeholders, including the Office of the Governor, MAPI, USDA APHIS Veterinary Services and Wildlife Services, MDA, MDCH, MDNR, Michigan Office of Public Health Preparedness, Michigan State Police, and the MSU DCPAH. The workgroup is charged with coordinating a state approach to risk management and communications relating to AI and other zoonotic diseases. Multiple stakeholder perspectives contribute to definition of legal authorities, risk communications, occupational safety protocols, surveillance, funding, research, response plans, and laboratory capacity relating to AI or other zoonotic diseases. In addition, a State Animal Response Team is being implemented in Michigan as an interagency animal emergency response team.60 By use of the Incident Command System, training exercises involving outbreak response simulations are conducted. A Veterinary Emergency Response Network (Vet Net) has been implemented by the MDA and is a program that provides information to Michigan veterinarians about bioterrorism and emerging animal diseases and outbreak response training to veterinarians across the state.61 Statewide health-related communications with health-care providers, public health agencies, and veterinarians, among others, are conducted through the Michigan Health Alert Network.62 It is anticipated that in the event of detection of an HPAI H5N1 virus—positive bird or flock or emergence of a pandemic, this preestablished trust among stakeholders will facilitate early disease identification and response efforts.
With the current emphasis on early recognition and management of health threats in humans and other animals, enhanced AISSs can be created on the basis of stakeholder engagement, technological advances, and uniform data standards.24,28,41,48,63–66 Development of uniform data standards within agriculture industries and between agriculture industries and public health authorities will promote the development of integrated early warning systems. The need for more efficient mechanisms of data collection and analysis and information dissemination that meet the requirements of stakeholders should drive system development.40,47 Implementation of Michigan's disease surveillance system for human disease reporting (Michigan Disease Surveillance System) and Canada's disease-specific enteric disease surveillance system (National Enteric Surveillance Program) provide examples of lessons learned through development of disease surveillance systems.40,67,68 These development processes identified stakeholders and common business practices (eg, electronic laboratory reporting, disease alerts, data management and analysis tools, and quality assurance processes) that led to development of systems with overwhelming buy-in and user ownership. Additionally, the interaction among different program areas allowed users to leverage tools developed for 1 specific program to be used across all program areas. Conducting a needs assessment of potential AISS users in Michigan is the first step toward enhancement of the current AISS system in that state.
In the present study, all of the suggested AI surveillance programs in Michigan were indicated to be important to include in an AISS and to be mandatory, especially individual case reporting and US border testing. Moreover, the PI representatives expressed that all of the additional bird sampling systems were necessary. However, whereas more than half of the PPV, PA, and EXT representatives viewed commercial and distributor flock sampling as important, fewer PI representatives indicated the need for these programs. In general, PI representatives may have indicated a greater interest in including surveillance of birds other than commercial or distributor flocks as these may be a potential source of AI transmission outside of their control, including wild birds,5 backyard flocks,69,70 pet birds,71 and fighting birds. It appears that there may be an opportunity for the PI to educate other stakeholders about the potential risk to their industry from other parts of the bird industry and wildlife. Conducting studies to provide a risk assessment of AI virus infection from birds other than those raised in the commercial bird industry will be important to improve trust and solicit buy-in from the PI as the AISS is developed.33
Within a surveillance system, most respondents understood that epidemiological data, such as test date, bird description, bird location, laboratory results, and total numbers of birds tested or affected, must be collected to conduct AI surveillance and response. Collection of this type of information can serve to improve confidence in and verification of a diagnostic test result and to improve the predictability of disease occurrence and response requirements.39 However, although the information was important to PA disease investigation and response, there was still a reluctance to require inclusion of bird identification and owner name among PI and EXT representatives. Education of public health stakeholders about the impact of response and release of information on business and the state's economy should help to assure the PI that their needs are included in any AI outbreak response.
Current HPAI reporting requirements include involvement of the MDA, USDA, MAPI, and MSU DCPAH.72 Consistent with findings of previous studies,41,49 these were the agencies receiving priority for reporting in the present study. At the time of this study, the Michigan AI response scheme did not detail methods used for reporting between human and animal health agencies when HPAI virus infection is suspected or confirmed in birds.
Making reports through personal communication via telephone was considered an important method for the PI representatives, whereas PPV and EXT representatives were most comfortable with e-mail reporting and PA representatives preferred to report directly into a database. Although electronic methods of disease reporting can increase the speed with which information is transmitted and decrease duplication of data entry, personal communication is important to allow for clarification of data findings, to receive immediate response recommendations, and to support collegial relationships.64
In the present study, respondents were receptive to information sharing in general and few indicated that no data should be shared. However, PI representatives were much less interested in sharing information with other stakeholder groups, especially with PA stakeholder groups, in contrast to PPV and EXT representatives. Sharing information with the community stakeholder groups received relatively low priority from all respondent types. To increase trust and program participation, all stakeholders should be included in the development of standard procedures for data access, analysis, summarization, and sharing.40,64
As would be expected, respondents wanted limited sharing of raw data and were more interested in the ability to view aggregated, deidentified data and summary maps. Creation of summaries or generalized mapping of positive and negative test results can obscure private data but allows for illustration of disease patterns to stakeholders. It is expected that each stakeholder should receive data only in an appropriate level of detail and that the use of surveillance information will differ.44,47 Public agency representatives indicated they would use the information to organize specific community response operations, whereas the PI representatives would use the information to enhance or create biosecurity practices. Providing producers with information that can be used to enhance on-farm biosecurity measures would greatly benefit risk assessment and disease containment in the case of an outbreak.27,35
E-mail and a Web-based database were considered to be the most important methods for sharing information with PI and PA stakeholder groups. E-mail is currently used for communication among most stakeholders for disease reporting, and so it was expected that this would also be an effective means of information sharing. The preferred use of a Web-based database for information sharing by PA and EXT representatives may be related to their increased comfort with these types of computer systems as they are already in use within their organizations. Additionally, because it was indicated that immediate access to the data was important for the PI and PA representatives, development of Web-based access methods for authorized stakeholders is desirable. People working in the field may not have access to a computer workstation. Availability of new, more portable methods of data sharing may increase their use of Web-based technologies.28 However, because of the importance of personal communication between stakeholders, the telephone remains an important method of information sharing.
Because there was little indication of a need to share information with community stakeholder groups and it was noted that the information should be provided to them on an as-needed basis only, a website was considered the best means with which to communicate with them. Releasing information with an appropriate level of detail to stakeholders is not unreasonable; however, how this will happen should be agreed upon by all stakeholders during system development.44,47,63 Stakeholder review and approval of information provided to the public can provide a means of conveying consistent and accurate situation updates and health promotion messages, thereby reducing the potential for media or public overreaction and maintaining stakeholder confidentiality.
To engage stakeholders, it is important to show them how a new way of doing things will benefit them directly.40,44 Because of this, a surveillance system should incorporate services that the stakeholders would find beneficial.28,40 Internet-related services were considered to be useful to all respondents, especially access to outbreak alert information and disease identification, fact sheets, and prevention and control guidelines. The ability to provide consistent, evidence-based information to formulate biosecurity recommendations for all stakeholders should translate into more effective risk assessments, business decisions, and public health promotion.27,73
In the present study, specific services desired and the use of these services were related to the roles respondents play in disease prevention and control. Poultry industry representatives valued area-wide surveillance information to ensure that biosecurity practices are implemented and to make business decisions. Public agency representatives were interested in tools that would assist in risk assessment during management of outbreak response and help to provide education to their constituents. As was found in a previous study,49 PPV representatives valued tools to assist in individual-animal disease identification and to provide prevention information and client education; EXT representatives stated they would use tools to provide education to producers and community members. Mechanisms of health promotion for human and animal populations are a part of the communications effort involved in prevention and control of emerging diseases74; thus, requests for these types of tools should not be overlooked when developing an Internet-related AISS.
Ensuring that the sequence of communications occurs in a timely manner with adequate stakeholder involvement requires excellent interstakeholder communication. Use of an Internet-based method of communication has the potential to increase the efficiency of reporting and information sharing. Overall, there were few reported barriers to entering data into a Web-based reporting system; problems that were mentioned included the preference of PI and PPV representatives to report in person. Additionally, although not all will be expected to participate in the AISS in a reporting role, there are a variety of stakeholders in AI prevention, control, and response who should be included in the development process. For example, most EXT representatives in the present study indicated that they did not have occasion to report AI cases (most reports would be made by the poultry producer or veterinarian), yet they may use information shared through the AISS to provide producer or community education and outbreak response support.
Increased AI information sharing may be challenging because of the sensitive nature of the information collected. Consistent with findings of another study,49 a relatively low-level but recurring concern throughout the survey involved confidentiality and data security, especially for the PI and PA representatives. Concerns regarding release of individual producer information, media overreaction, and public panic underlie some of the types of concerns related to data security. These concerns are not unfounded because unauthorized information release may profoundly affect the economic viability of individual poultry producers and the PI as well as the human health-care system and state economy.28
Unfortunately, a guarantee of secure communication does not always assure stakeholders that their individual privacy, business information, and sensitive data will be kept confidential. Confidentiality provides an example of the technical challenges associated with coordination and building trust within an AISS. Although electronic health data can provide stakeholders with faster and more in-depth access to health information, there is also a greater likelihood of unauthorized release of sensitive information and the potential for system unavailability.47 Therefore, for each data type, access and ongoing collection processes must be negotiated, established, and maintained among stakeholders.44,63 This may actually be one of the most challenging parts of a system development process because the factors that motivate data owners to provide information are diverse.44 Layering security measures (eg, provision of firewalls, user-authentication passwords, and encryption) throughout the system may greatly reduce the potential for system intrusion.47,63 Building trust through confidentiality will be a long-term investment for PAs. Judicious protection of stakeholder information will be essential for any AISS to be effective.
Although this needs assessment undertaken in the present study was based on a convenience sample, it has highlighted areas to focus on during the continued enhancement of AI surveillance in Michigan, including stakeholder identification and engagement, information reporting and sharing requirements, and AISS services that are useful to stakeholders. Such areas of focus could be applicable to other regional AISSs. In general, future development processes should include backyard flock owners, local health departments, physicians, and the general public. Additionally, consideration should be made to include indigenous agents—those causing endemic disease associated with current herd or flock health—into an AISS system as this may augment stakeholder participation and compliance.39
Serious efforts to safeguard personal information, including facility and bird location, and to ensure accurate disease reporting are essential to build trust among all stakeholders involved and to ensure the success of the AISS. Steps toward building trust and engagement of stakeholders, particularly within the PI, should continue to include educating system users on the roles, responsibilities, and expectations of stakeholders during an AI outbreak through activities such as stakeholder meetings and outbreak response drills. Additionally, the PI representatives in particular indicated that efforts to seek out backyard flocks and include them in the AISS process were important to them. Programs such as backyard flock registries have been implemented across the nation,75–77 the development of which may be a means to address surveillance of this potential source of AI transmission in Michigan and constitute another opportunity to build trust between PAs and commercial poultry producers.
Because AI is a threat to the health of humans and other animals and because animals can be sentinels for human disease, the inclusion of human public health agencies in the notification tree can provide an important dimension to an AISS or other zoonotic disease surveillance systems. Integration of data from currently operating AISSs and other human and animal disease surveillance systems may provide an opportunity to identify potential outbreak situations more rapidly with increased efficiency in data management.28,41,49 From lessons learned during implementation of other human and animal disease surveillance systems, business requirements and mutual agreements for data management and system interoperability standards within a comprehensive AISS can be created with input from all stakeholders.29,40,55,67,68
Because a goal of any surveillance system should be to capture and communicate specific information that will be used to make immediate disease control decisions,39 exploring options from a wide array of technologies and means of personal communication, including such processes as reporting via telephone or other handheld devices and desktop computers, can help to fully leverage the potential for early and accurate disease reporting and information sharing.28 Additionally, Web-based applications can provide users with interfaces to the data with mutually agreed upon security systems and enable construction of maps to provide a geographic context to the data.28,44 Although training of users will be necessary, systems such as these have the potential to provide stakeholders with customized Internet-related services.64
Identification of AISS stakeholder needs will provide a basis for development of an efficient mechanism for AI surveillance and communication among the diverse groups of AI stakeholders, thereby promoting earlier identification of HPAI virus outbreaks, more effective outbreak response, and reduction in morbidity, numbers of deaths, and financial losses. It is anticipated that the results of this needs assessment will provide a basis for continued enhancement of the AISS in Michigan, and perhaps encourage other regional authorities in the United States to similarly assess the needs of their AISS stakeholders for nationwide enhancement of AI surveillance.
ABBREVIATIONS
| AI | Avian influenza |
| AISS | Avian influenza surveillance system |
| DCPAH | Diagnostic Center for Population and Animal Health |
| EXT | Extension specialist |
| GDP | Gross domestic product |
| HPAI | Highly pathogenic avian influenza |
| MAPI | Michigan Allied Poultry Industries Incorporated |
| MDA | Michigan Department of Agriculture |
| MDCH | Michigan Department of Community Health |
| MDNR | Michigan Department of Natural Resources |
| MSU | Michigan State University |
| PA | Public agency |
| PI | Poultry industry |
| PPV | Private practice veterinarian |
Avian influenza surveillance—needs assessment survey (Michigan 2007). Available from the authors on request.
SAS, version 9.1, SAS Institute Inc, Cary, NC.
References
- 1.
Swayne DE, King DJ. Avian influenza and Newcastle disease. J Am Vet Med Assoc 2003;222:1534–1540.
- 2.
CDC. Avian influenza (flu): avian influenza A virus infections of humans. Available at: www.cdc.gov/flu/avian/gen-info/avianflu-humans.htm. Accessed Nov 30, 2009.
- 3.
CDC. Avian influenza (flu): interim guidance for protection of persons involved in US avian influenza outbreak disease control and eradication activities. Available at: www.cdc.gov/flu/avian/professional/protect-guid.htm. Accessed Nov 30, 2009.
- 4.↑
World Health Organization. Cumulative number of confirmed human cases of avian influenza A/(H5N1) reported to WHO. Available at: www.who.int/csr/disease/avian_influenza/country/cases_table_2009_11_27/en/index.html. Accessed Nov 30, 2009.
- 5.↑
Dierauf L, Karesh WB, Ip HS, et al. Avian influenza virus and free-ranging wild birds. J Am Vet Med Assoc 2006;12:1877–1882.
- 6.
CDC. Avian influenza (flu): spread of avian influenza virus among birds. Available at: www.cdc.gov/flu/avian/gen-info/spread.htm. Accessed Nov 30, 2009.
- 7.↑
World Health Organization. Global alert and response (GAR): avian influenza frequently asked questions. Available at: www.who.int/csr/disease/avian_influenza/avian_faqs/en/index.html#howdo. Accessed Nov 30, 2009.
- 8.
World Organisation for Animal Health (OIE). Update on highly pathogenic avian influenza in animals (type H5 and H7). Available at: www.oie.int/downld/AVIAN%20INFLUENZA/A_AI-Asia.htm. Accessed Nov 30, 2009.
- 9.
Keawcharoen J, Oraveerakul K, Kuiken T, et al. Avian influenza H5N1 in tigers and leopards. Emerg Infect Dis 2004;10:2189–2191.
- 10.
Kuiken T, Rimmelzwaan G, van Riel D, et al. Avian H5N1 influenza in cats. Science 2004;8:241.
- 11.
Marschall J, Hartmann K. Avian influenza A H5N1 infections in cats. J Feline Med Surg 2008;10:359–365.
- 12.
Cyranoski D. Bird flu spreads among Java's pigs. Nature 2005;435:390–391.
- 13.
Klopfleisch R, Wolf PU, Wolf C, et al. Encephalitis in a stone marten (Martesfoina) after natural infection with highly pathogenic avian influenza virus subtype H5N1. J Comp Pathol 2007;137:155–159.
- 14.↑
World Organisation for Animal Health (OIE). World Animal Health Information Database (WAHID) Interface: disease outbreak map. Available at www.oie.int/wahis/public.php?page=disease_outbreak_map&disease_type=Terrestrial&disease_id=15&empty=999999&newlang=1. Accessed Nov 30, 2009.
- 15.↑
McKibbin WJ, Sidorenko AA. Global macroeconomics consequences of pandemic influenza. Sydney, Australia: Lowy Institute for International Policy, 2006. Available at: www.lowyin-stitute.org/Publication.asp?pid=345. Accessed Nov 30, 2009.
- 16.
Meltzer MI, Cox NJ, Fukuda K. The economic impact of pandemic influenza in the United States: priorities for intervention. Emerg Infect Dis 1999;5:659–671.
- 17.↑
Levi J, Segal M, Segal LM, et al. Pandemic flu and the potential for economic recession: a state-by-state analysis. Washington, DC: Trust for America's Health, 2007. Available at: healthyamericans.org/reports/flurecession/FluRecession.pdf. Accessed Nov 30, 2009.
- 18.↑
USDA National Agricultural Statistics Service. 2007 Census of Agriculture, state data. Table 13. Poultry—inventory and sales: 2007 and 2002 Available at: www.agcensus.usda.gov/Publications/2007/Full_Report/Volume_1,_Chapter_2_US_State_Level/st99_2_013_013.pdf. Accessed Nov 30, 2009.
- 19.
USDA National Agricultural Statistics Service. Michigan Annual Statistical Bulletin 2007–2008: livestock, dairy, and poultry. Available at: www.nass.usda.gov/Statistics_by_State/Michigan/Publications/Annual_Statistical_Bulletin/stats08/livestock.txt. Accessed Nov 30, 2009.
- 20.↑
USDA National Agricultural Statistics Service. 2007 Census of Agriculture, state data. Table 2. Market value of agricultural products sold including direct Sales: 2007 and 2002. Available at: www.agcensus.usda.gov/Publications/2007/Full_Report/Volume_1,_Chapter_2_US_State_Level/st99_2_002_002.pdf. Accessed Nov 30, 2009.
- 21.
CDC. Outbreaks of avian influenza H5N1 in Asia and interim recommendations for evaluation and reporting of suspected cases—United States, 2004. MMWR Morb Mortal Wkly Rep 2004;53:97–100.
- 22.
USDA. Avian influenza (bird flu): USDA key messages for avian influenza. Available at: www.usda.gov/wps/portal/!ut/p/_s.7_0_A/7_0_1OB?contentidonly=true?contentid=AI_Spotlight_Documents.xml. Accessed Nov 30, 2009.
- 23.
USDA Agricultural Research Service. The Asian bird flu. Available at: www.ars.usda.gov/Research/docs.htm?docid=11425. Accessed Nov 30, 2009.
- 24.↑
Lombardo JS, Ross D. Disease surveillance, a public health priority. In: Lombardo JS, Buckeridge DL, eds. Disease surveillance: a public health informatics approach. Hoboken, NJ: John Wiley & Sons Inc, 2007:1–39.
- 25.
Institute of Medicine and National Research Council. Sustaining global surveillance and response to emerging zoonotic diseases. Washington, DC, The National Academics Press, 2009. Available at: www.nap.edu/catalog.php?record_id=12625#toc. Accessed Nov 30, 2009.
- 26.
Cowen P, Garland T, Hugh-Jones ME. Evaluation of ProMED-mail as an electronic early warning system for emerging animal diseases: 1996 to 2004. J Am Vet Med Assoc 2006;229:1090–1099.
- 27.
Stark KDC, Regula G, Hernandez J, et al. Concepts for risk-based surveillance in the field of veterinary medicine and veterinary public health: review of current approaches. BMC Health Serv Res 2006;6:20.
- 28.↑
Vourc'h G, Bridges VE, Gibbens J, et al. Detecting emerging diseases in farm animals through clinical observations (Erratum published in Emerg Infect Dis 2006;12:714). Emerg Infect Dis 2006;12:204–210.
- 29.
Tomlinson S. Building a comprehensive and integrated NAHSS: an update. NAHSS outlook 2008. Available at: www.aphis.usda.gov/vs/ceah/ncahs/nsu/outlook/issue18_jul08/outlook_jul_2008_comprehensive_surveillance_update.pdf. Accessed Dec 11, 2009.
- 30.↑
USDA APHIS. National Animal Health Laboratory Network. Available at: www.aphis.usda.gov/animal_health/nahln/. Accessed Dec 11, 2009.
- 31.
Ahl AS, Acree JA, Gipson PS, et al. Standardization of nomenclature for animal health risk analysis. Rev Sci Tech 1993;12:1045–1053.
- 32.
Toma B, Vaillancourt J, Dufour B, et al, eds. Dictionary of veterinary epidemiology. Ames, Iowa: Iowa State University Press, 1999:227.
- 33.↑
Fite RW. Animal health risk assessment in theory and practice. J Am Vet Med Assoc 2000;217:1837–1842.
- 34.
Last JM. A dictionary of epidemiology. 4th ed. New York: Oxford University Press, 2001;160.
- 35.
Wenzel JG, Nusbaum KE. Veterinary expertise in biosecurity and biological risk assessment. J Am Vet Med Assoc 2007;230:1476–2007.
- 36.
King LJ, Anderson LR, Blackmore CG, et al. Executive summary of the AVMA One Health Initiative task force report. J Am Vet Med Assoc 2008;233:259–261.
- 37.
One Health Initiative. Mission statement and vision statement. Available at: www.onehealthinitiative.com/mission.php. Accessed Nov 30, 2009.
- 38.
Public Health Informatics Institute. Guiding principles for effective health information systems. Available at: http://phii.org/resources/doc/PHII_Brochure.pdf. Accessed Mar 8, 2011.
- 39.↑
Thurmond, MC. Conceptual foundations for infectious disease surveillance. J Vet Diagn Invest 2003;15:501–514.
- 40.
Aramini, J, Shamir, NM. Canadian applications of modern surveillance informatics. In: Lombardo JS, Buckeridge DL, eds. Disease surveillance: a public health informatics approach. Hoboken, NJ: John Wiley & Sons Inc, 2007:303–333.
- 41.
Kahn LH. Confronting zoonoses, linking human and veterinary medicine. Emerg Infect Dis 2006;12:556–561.
- 42.
Dillman DA, Smyth JD, Christian, LM. Implementation procedures. In: Internet, mail, and mixed-mode surveys: the tailored design method. Hoboken, NJ: John Wiley & Sons Inc, 2009;234–299.
- 43.↑
Cummings SM, Savitz LA, Knorad T. Reported response rates to mailed physician questionnaires. Health Serv Res 2001;35:1347–1354.
- 44.↑
Wojcik, R, Hauenstein, L, Sniegoski, C. Obtaining the data. In: Lombardo JS, Buckeridge DL, eds. Disease surveillance: a public health informatics approach. Hoboken, NJ: John Wiley & Sons Inc, 2007:91–142.
- 45.
Pappaioanou M. Veterinary medicine protecting and promoting the public's health and well-being. Prev Vet Med 2004;62:153–163.
- 46.
Wohl JS, Nusbaum KE. Public health roles for small animal practitioners. J Am Vet Med Assoc 2007;230:494–500.
- 47.↑
Hauenstein, L, Wojcik, R, Loschen, W, et al. Putting it together: The biosurveillance information system. In: Lombardo JS, Buckeridge DL, eds. Disease surveillance: a public health informatics approach. Hoboken, NJ: John Wiley & Sons Inc, 2007:193–261.
- 48.
Murphy FA. Emerging zoonoses. Emerg Infect Dis 1998;4:429–435.
- 49.↑
Mauer WA, Kaneene JB. Integrated human-animal disease surveillance. Emerg Infect Dis 2005;11:1490–1491.
- 50.
Federation of American Scientists. Infectious Animal and Zoonotic Disease Surveillance, Animal Health/Emerging Animal Diseases project. Available at: www.fas.org/ahead/. Accessed Dec 11, 2009.
- 51.
CDC. National Center for Zoonotic, Enteric, and Vector-borne Diseases. Available at: www.cdc.gov/nczved/about.html. Accessed Dec 11, 2009.
- 52.
National Association of State Departments of Agriculture. Animal health safeguarding review: results and recommendations. Available at: www.aphis.usda.gov/vs/pdf_files/safeguarding.pdf. Accessed Dec 11, 2009.
- 53.
State of Michigan. Emerging disease issues. Available at: www.michigan.gov/emergingdiseases/0,1607,7-186-75792-,00.html. Accessed Dec 11, 2009.
- 54.
CDC, Division of Vector-borne Diseases. West Nile virus. Available at: www.cdc.gov/ncidod/dvbid/westnile/resources/wnv-guidelines-aug-2003.pdf. Accessed Dec 11, 2009.
- 55.
USDA APHIS. National Animal Health Surveillance System. Available at: www.aphis.usda.gov/vs/nahss/nahss.htm. Accessed Dec 11, 2009.
- 56.
National Biological Information Infrastructure, Wildlife Disease Information Node. Highly Pathogenic Avian Influenza Early Detection Data System. Available at: wildlifedisease.nbii.gov/ai/. Accessed Dec 11, 2009.
- 57.
USDA APHIS. National Avian Influenza Surveillance Plan. Available at: www.aphis.usda.gov/vs/nahss/poultry/ai/avian_influenza_surveillance_plan_062907.pdf. Accessed May 12, 2009.
- 58.↑
USDA APHIS. Poultry health. Available at: www.aphis.usda.gov/animal_health/animal_dis_spec/poultry/. Accessed Dec 11, 2009.
- 59.
Michigan Department of Natural Resources, Wildlife Division. Michigan Surveillance and Response Plan for Highly Pathogenic Avian Influenza in Free Ranging Wildlife, 2006. Available at: www.michigan.gov/documents/DNR_HPAI_PLAN_149202_7.pdf. Accessed Dec 11, 2009.
- 60.↑
Michigan State Animal Response Team. SART's mission. Available at: www.michigansart.org/mission.html. Accessed Dec 11, 2009.
- 61.↑
Michigan Department of Agriculture, Emergency Veterinary Network. Available at: www.michigan.gov/mda/0,1607,7-125-1566_22384_22389-193844-,00.html. Accessed Dec 11, 2009.
- 62.↑
Michigan Department of Public Health, Health Alert Network. Available at: www.michigan.gov/mdch/0,1607,7-132-2945_21919_25536-,00.html. Accessed Dec 11, 2009.
- 63.
Pinner RW. Public health surveillance and information technology. Emerg Infect Dis 1998;4:462–464.
- 64.↑
Happel Lewis S, Hurt-Mullen K, Martin C, et al. Modern disease surveillance systems in public health practice. In: Lombardo JS, Buckeridge DL, eds. Disease surveillance: a public health informatics approach. Hoboken, NJ: John Wiley & Sons Inc, 2007:265–302.
- 65.
CDC. Public Health Information Network. Available at: www.cdc.gov/phin/about.html. Accessed Dec 11, 2009.
- 66.
USDA APHIS. Animal health monitoring & surveillance, surveillance and data standards. Available at: www.aphis.usda.gov/vs/nahss/resources.htm#standards. Accessed Dec 11, 2009.
- 67.
Collins J, Carlson B. Rollout of the Michigan disease surveillance system. Michigan Department of Community Health, Bureau of Epidemiology. Epi Insight [serial online] 2003;11:1. Available at: www.michigan.gov/documents/EPI_insight_fall03_79492_7.pdf. Accessed Dec 11, 2009.
- 68.
Michigan Department of Community Health. Michigan Disease Surveillance System background. Available at: www.michigan.gov/mdch/0,1607,7-132-2945-96814-,00.html. Accessed Dec 11, 2009.
- 69.
Pelzel AM, McCluskey BJ, Scott AE. Review of the highly pathogenic avian influenza outbreak in Texas, 2004. J Am Vet Med Assoc 2006;228:1869–1875.
- 70.
Kelly AM, Marshak RR. Veterinary medicine, global health. J Am Vet Med Assoc 2007;231:1806–1808.
- 71.↑
Hawkins MG, Crossley BM, Osofsky A, et al. Avian influenza A virus subtype H5N2 in a red-lored Amazon parrot. J Am Vet Med Assoc 2006;228:236–241.
- 72.↑
State of Michigan. Michigan emergency avian disease manual. Available at: www.michigan.gov/documents/Avian_Disease_Plan_Revised_1-25-06_149332_7.doc. Accessed Dec 11, 2009.
- 73.
Moore DA, Merryman ML, Hartman M, et al. Comparison of published recommendations regarding biosecurity practices for various production animal species and classes. J Am Vet Med Assoc 2008;233:249–256.
- 74.↑
Folkers LF, Cerqueira MT, Quick RE, et al. Getting the handle of the proverbial pump: communication works. Emerg Infect Dis 1998;4:467–469.
- 75.
Division of Environmental Conservation, Division of Environmental Health. Alaska Poultry Disease Surveillance Program. Available at: www.dec.state.ak.us/eh/docs/vet/Alaska%20LPAI%20Disease%20Surveillance%20Program%205_07.pdf. Accessed Dec 11, 2009.
- 76.
Maryland Department of Agriculture. Maryland Domestic Poultry Registration Program. Available at: www.mda.state.md.us/animal_health/poultryreg/index.php. Accessed Dec 11, 2009.
- 77.
Zadina C. Poultry disease surveillance in Nebraska. NAHSS outlook 2005. Available at: www.aphis.usda.gov/vs/ceah/ncahs/nsu/outlook/issue8/ne_small_flock_surv.pdf Accessed Dec 11, 2009.
