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Table 4 ADL time-series regression coefficients of the temperature and HS associated with human brucellosis, 2004–2009

From: Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China

  Variablesa Model I Model II Model III
β(95% CI) for temperature β(95% CI) for HS β(95% CI) for temperature β(95% CI) for HS
Inner Lag0 −0.019 (−0.023 to −0.016) −0.028 (−0.043 to −0.013) −0.019 (−0.031 to −0.008) 0.033 (−0.011 to 0.076)
Mongoliab Lag1 −0.019 (−0.021 to −0.017) −0.044 (−0.055 to −0.033) −0.015 (−0.024 to −0.006) 0.009 (−0.024 to 0.043)
  Lag2 −0.018 (−0.020 to −0.017) −0.060 (−0.067 to −0.052) −0.011 (−0.018 to −0.004) −0.014 (−0.041 to 0.013)
  Lag3 −0.018 (−0.020 to −0.016) −0.076 (−0.082 to −0.069) −0.007 (−0.013 to −0.0003) −0.037 (−0.063 to −0.011)
  Lag4 −0.017(−0.020 to −0.015) −0.091 (−0.100 to −0.082) −0.002 (−0.005 to −0.010) −0.060 (−0.091 to −0.029)
  Lag5 −0.017(−0.021 to −0.013) −0.107 (−0.120 to −0.094) 0.002 (−0.008 to 0.012) −0.083 (−0.123 to −0.043)
  Constant term 1.152 (0.946 to 1.357) 10.738 (9.778 to 11.698) 4.706 (1.037 to 8.374)
  Incidence(−1) 0.846 (0.795 to 0.898) 0.822 (0.772 to 0.873) 0.832 (0.784 to 0.880)
  R-square 0.925 0.926 0.923
  AIC 2.088 2.066 2.219
  RMS error 1.300 1.230 1.180
Heilongjiangc Lag0 −0.005 (−0.006 to −0.005) −0.005 (−0.008 to −0.001) −0.005 (−0.007 to −0.004) 0.005 (−0.0003 to 0.010)
  Lag1 −0.005 (−0.005 to −0.004) −0.009 (−0.012 to −0.007) −0.005 (−0.006 to −0.004) 0.003 (−0.002 to 0.007)
  Lag2 −0.004 (−0.005 to −0.004) −0.014 (−0.016 to −0.012) −0.004 (−0.005 to −0.003) 0.001 (−0.004 to 0.005)
  Lag3 −0.004 (−0.004 to −0.003) −0.019 (−0.021 to −0.017) −0.003 (−0.004 to −0.002) −0.002 (−0.006 to 0.003)
  Lag4 −0.003 (−0.004 to −0.002) −0.024 (−0.027 to −0.020) −0.002 (−0.003 to −0.002) −0.004 (−0.009 to 0.001)
  Lag5 −0.002 (−0.003 to −0.001) - −0.002 (−0.003 to −0.001) -
  Lag6 −0.002 (−0.003 to −0.001) - −0.001 (−0.002 to −0.001) -
  Constant term 0.267 (0.196 to 0.339) 1.669 (1.494 to 1.844) 0.206 (−0.239 to 0.650)
  Incidence(−1) 0.741 (0.659 to 0.823) 0.776 (0.716 to 0.835) 0.745 (0.659 to 0.830)
  R-square 0.910 0.880 0.913
  AIC −0.969 −0.708 −0.938
  RMS error 0.213 0.258 0.216
Province Variables a Model I Model II Model III
β(95% CI) for temperature β(95% CI) for HS β(95% CI) for temperature β(95% CI) for HS
Shanxid Lag0 −0.007 (−0.008 to −0.005) −0.006 (−0.010 to −0.002) −0.003 (−0.005 to −0.0003) −0.007 (−0.013 to −0.0004)
  Lag1 −0.007 (−0.007 to −0.006) −0.001 (−0.013 to −0.006) −0.004 (−0.005 to −0.002) −0.007 (−0.012 to −0.002)
  Lag2 −0.006 (−0.007 to −0.005) −0.013 (−0.015 to −0.010) −0.005 (−0.005 to −0.004) −0.007 (−0.011 to −0.003)
  Lag3 −0.006 (−0.006 to −0.005) −0.016 (−0.019 to −0.014) −0.005 (−0.006 to −0.004) −0.007 (−0.010 to −0.003)
  Lag4 −0.005 (−0.006 to −0.004) −0.020 (−0.022 to −0.017) −0.006 (−0.008 to −0.004) −0.007 (−0.010 to −0.003)
  Lag5 −0.005 (−0.006 to −0.004) −0.023 (−0.026 to −0.020) −0.007 (−0.010 to −0.004) −0.007 (−0.010 to −0.003)
  Lag6 - −0.026 (−0.031 to −0.022) - −0.006 (−0.011 to −0.002)
  Lag7 - −0.030 (−0.035 to −0.025) - −0.006 (−0.012 to −0.001)
  Constant term 0.554 (0.468 to 0.640) 3.230 (2.818 to 3.642) 1.676 (1.16 to 2.19)
  Incidence(−1) 0.781 (0.716 to 0.846) 0.540 (0.457 to 0.622) 0.609 (0.519 to 0.698)
  R-square 0.893 0.860 0.903
  AIC −0.376 −0.104 −0.506
  RMS error 0.253 0.303 0.213
Jiline Lag0 −0.004 (−0.004 to −0.003)    
  Lag1 −0.003 (−0.004 to −0.003)    
  Lag2 −0.003 (−0.003 to −0.002)    
  Lag3 −0.002 (−0.002 to −0.002)    
  Lag4 −0.001 (−0.002 to −0.001)    
  Lag5 −0.001 (−0.002 to −0.0001)    
  Constant term 0.123 (0.090 to 0.157)    
  Incidence(−1) 0.914 (0.867 to 0.962)    
  R-square 0.894    
  AIC −0.800    
  RMS error 0.376    
  1. a. Lagx: the lagged months; HS: monthly hours of sunshine; Unit: temperature (degree centigrade), monthly hours of sunshine (10 hours).
  2. b. The model including average wind velocity had a lower R-square (0.882) and higher RMS error (1.66) and it was not shown in the table. The purely autoregressive model had a R-square 0.788.
  3. c. The model including rainfall had lower R-squares (0.874) and higher RMS errors (0.337) and it was not shown in the table. The purely autoregressive model had a R-square 0.714.
  4. d. The model including rainfall or wind velocity had lower R-squares (0.859, 0.827) and higher RMS errors (0.334, 0.339) and they were not shown in the table. The purely autoregressive model had a R-square 0.753.
  5. e. The model including rainfall had lower R-squares (0.892) and higher RMS errors (0.382) and it was not shown in the table. The purely autoregressive model had a R-square 0.818.