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Table 2 Regression models using GT-based RSVs for “Ebola” searched worldwide, and epidemiological data (the number of Ebola cases) and the HDI as predictor variables

From: Assessing Ebola-related web search behaviour: insights and implications from an analytical study of Google Trends-based query volumes

Parameter

Estimate

Std error

t

Sig.

95 % CI

Lower limit

Upper limit

FIRST MODEL

AIC 776.979

Intercept

4.083293

.381482

10.704

.000

3.328576

4.838010

Ebola cases

.008047

.000255

31.552

.000

.007542

.008551

SECOND MODEL

AIC 709.927

Intercept

7.771741

.596617

13.026

.000

6.590580

8.952901

Ebola cases

.006199

.000466

13.301

.000

.005277

.007122

HDI

-.078454

.010805

-7.261

.000

-.099846

-.057061

Ebola cases X HD

.000543

.000147

3.693

.000

.000252

.000834I