Knowledge, risk perceptions and practices regarding rodents and their associated pathogens: environmental consultants in Chile

Table 3 Results of the best GLMs for response frequencies of known rodent-borne diseases in Chile. Models were built for the fourth more mentioned diseases. Binomial (analyses of deviance) use goodness of fit against null models (P < 0.05 is interpreted as fit). When the null model is a better fit, then it replaces the other models. *P values < 0.05. The question was: what rodent species of zoonotic importance do you know of in Chile?

	β	±SE	Z	P value	OR	CI low (2.5%)	CI high (97.5%
1. Hanta (binomial GLM: null model)
Intercept	3.92	0.50	7.77	< 0.001*
2. Leptospirosis (binomial GLM: χ2 = 82.8, df = 3, P = 0.000)^a
Intercept	1.90	0.36	5.31	< 0.001*
Environmental engineer	-3.10	0.49	-6.39	< 0.001*	0.05	0.02	0.17
Biologist	-3.27	0.47	-7.00	< 0.001*	0.04	0.02	0.10
Others	-2.41	0.63	-3.83	< 0.001*	0.09	0.03	0.31
3. Salmonelosis (binomial GLM: χ2 = 11.06, df = 3, P = 0.011)^b
Intercept	-2.80	0.60	-4.70	< 0.001*
Veterinarian	1.83	0.65	2.80	0.005*	6.21	1.73	22.32
Biologist	1.24	0.67	1.83	0.070*	-	-	-
Others	1.69	0.83	2.04	0.041*	5.44	1.07	27.64
4. Rabia (binomial GLM: χ2 = 9.26, df = 4, P = 0.054)^b
Intercept	-1.22	0.37	-3.29	0.001*
Veterinarian	-1.16	0.49	-2.37	0.018*	0.31	0.12	0.82
Biologist	-1.15	0.49	-2.36	0.018*	0.32	0.12	0.82
Others	-0.82	0.74	-1.10	0.270
Experience (years)	0.05	0.03	1.57	0.117

ISSN: 2524-4655