Table 4.
Reported barriers to tick surveillance and control program development by jurisdiction
| Barrier category | Barriers to tick surveillance | Barriers to tick control | ||
|---|---|---|---|---|
|
|
|
|||
| Respondent jurisdictiona | Respondent jurisdictiona | |||
|
|
|
|||
| Sub-state (n = 73) | State (n = 67) | Sub-state (n = 73) | State (n = 67) | |
|
| ||||
| Funding Constraintsb | 39 (53.4%) | 52 (77.6%) | 32 (43.8%) | 33 (49.3%) |
| Lack of trained personnel | 28 (38.4%) | 22 (32.8%) | 19 (26.0%) | 20 (29.9%) |
| Competing priorities for limited program resources | 38 (52.1%) | 38 (56.7%) | 31 (42.5%) | 23 (34.3%) |
| Limitations in facilities/equipment | 22 (30.1%) | 19 (28.4%) | 19 (26.0%) | 17 (25.4%) |
| Lack of access to testing labs/resources | 23 (31.5%) | 20 (29.9%) | 11 (15.1%) | 10 (14.9%) |
| Coordination among agencies/units | 13 (17.8%) | 19 (28.4%) | 12 (16.4%) | 12 (17.9%) |
| Lack of guidelines for best practices | 22 (30.1%) | 15 (22.4%) | 24 (32.9%) | 15 (22.4%) |
| Lack of evidence-based, large-scale tick mgmt. practices | 18 (24.7%) | 8 (11.9%) | 24 (32.9%) | 25 (37.3%) |
a
Sub-state respondents include those working at either a local or county agency. State respondents include those working at either a state or federal agency.
b
Statistical testing for jurisdictional subgroups conducted through χ2 analysis. Statistically significant difference between jurisdictional subgroups detected only for funding constraints as a barrier to tick surveillance (χ2 = 8.984, P = 0.003).