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Table 11 Logistic regression employing lagged [lag = 3 months] mr plus lagged [lag = 3 months] daa to predict monthly MVEV test site status in the Pilbara

From: Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

Variable Coefficient (SE) p Odds ratio (95%)
Intercept -3.411 (0.194) < 0.01 a  
Lagged mr (× 100 mm) 1.083 (0.167) < 0.01 a 2.95 (2.14-4.15) b
Lagged daa 0.096 (0.0350) < 0.01 a 1.10 (1.02-1.18) c
  1. AIC: 448.54
  2. ROC AUC: 0.80
  3. a Significance
  4. bInterpretation: after adjusting for the effect of lagged daa, 100 mm increases in lagged mr rainfall increased the odds of a site monthly testing positive to MVEV by a factor of 2.95 (95% CI 2.14 - 4.15)
  5. cInterpretation: after adjusting for the effect of lagged mr, single day increases in daa increased the odds of a site monthly testing positive to MVEV by a factor of 1.10 (95% CI 1.02 - 1.18)