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Table 3 Logistic regression models of demographic and hematological factors as individual predictors of DENV infection

From: Maintenance of demographic and hematological profiles in a long-lasting dengue fever outbreak: implications for management

   Dataset     
Factors Statistics All s1 s2 s3 s4
Sex βo 0.774 0.392 1.276 0.928 0.649
  β1 0.226 0.160 −0.288 0.325 0.660
  OR 1.254 1.173 0.750 1.384 1.934
  CL- 0.8352 0.5494 0.3175 0.5899 0.8172
  CL+ 1.8823 2.5068 1.7716 3.2458 4.5777
  P 0.2752 0.6794 0.5119 0.4553 0.1335
  AIC 551.1 155.9 130.7 132.7 138.9
Day βo 0.435 0.312 2.048 −7.409 −1.499
  β1 0.011 0.010 −0.027 0.178 0.036
  OR 1.011 1.010 0.973 1.194 1.037
  CL- 1.0009 0.9635 0.8820 1.0682 0.9876
  CL+ 1.0214 1.0593 1.0737 1.3350 1.0891
  P 0.0334 0.6728 0.5868 0.0018 0.1443
  AIC 547.7 155.9 130.8 122.2 138.9
Age βo 0.427 0.033 0.292 0.615 0.879
  β1 0.013 0.013 0.025 0.013 0.001
  OR 1.013 1.013 1.025 1.014 1.001
  CL- 1.0020 0.9934 0.9999 0.9896 0.9789
  CL+ 1.0242 1.0331 1.0503 1.0379 1.0226
  P 0.0210 0.1948 0.0510 0.2717 0.9628
  AIC 546.8 154.3 126.9 132.1 141.2
LEU βo 24.173 32.162 18.422 20.852 25.583
  β1 −6.3036 −8.4818 −4.6950 −5.3871 −6.7062
  OR 0.002 0.001 0.009 0.005 0.001
  CL- 0.0005 0.0000 0.0009 0.0004 0.0001
  CL+ 0.0069 0.0048 0.0972 0.0594 0.0206
  P <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
  AIC 440.6 99.9 111.3 110.7 107.4
PLA βo 31.916 43.426 34.360 30.579 19.594
  β1 −5.931 −8.143 −6.377 −5.646 −3.586
  OR 0.003 0.001 0.002 0.003 0.028
  CL- 0.0007 0.0001 0.0001 0.0002 0.0027
  CL+ 0.0108 0.0068 0.0359 0.0705 0.2855
  P <0.0001 <0.0001 <0.0001 0.0002 0.0026
  AIC 464.6 109.8 106.7 115.1 130.3
AL% βo 0.192 −0.287 0.547 0.672 −0.242
  β1 0.169 0.209 0.207 0.077 0.251
  OR 1.184 1.233 1.230 1.080 1.285
  CL- 1.1190 1.0950 1.0480 0.9891 1.1274
  CL+ 1.2538 1.3875 1.4439 1.1793 1.4654
  P <0.0001 0.0005 0.0113 0.0860 0.0002
  AIC 511.8 136.1 118.9 129.8 118.1
  1. Logistic regression models to evaluate the individual contribution of demographic and hematological factors to DENV incidence using different datasets (ALL = entire data; subsets s1 to s4 ordered by day of the first attendance at the Marilia Hemocenter; see text). βo = intercept, β1 = slope, OR odds ratio, and CL 95 % confidence limits. Figures lower than critical P were in bold. Considering six models (one for each factor) with each dataset, critical P = 0.05/6 = 0.0083. AIC indicate model fit (comparable both between subsets and factors for subsets s1 to s4; comparable between factors for ALL). Variable codes as in Table 1