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Table 1 Bayesian Poisson regression models of Plasmodium vivax and P. falciparum malaria, Yunnan, China, 1991–2006.

From: Space-time variation of malaria incidence in Yunnan province, China

Variable Plasmodium vivax Plasmodium falciparum
Relative Risks   
Monthly rainfall (10 ml increase) 1.045 (1.044, 1.046) 1.037 (1.034, 1.040)
Monthly maximum temperature (°C increase) 1.047 (1.045, 1.050) 1.053 (1.047, 1.060)
Provincial average temporal trend (annual increase) 0.948 (0.944, 0.952) 0.957 (0.949, 0.965)
Regression of June–September on January–February (log incidence)
Regression slope (Jan–Feb → Jun–Sep) 0.77 (0.70, 0.84) 0.90 (0.75, 1.09)
Variance components (variances on a scale of log incidence)
Spatial random effect 8.74 (7.90, 9.89) 12.66 (10.50, 15.58)
Spatially-smoothed county-level temporal trend 0.08 (0.06, 0.10) 0.01 (0.00, 0.01)
Seasonal effect (January–February) 0.02 (0.01, 0.04) 0.02 (0.01, 0.06)
Overall Intercept -2.52 (-2.60, -2.45) -3.24 (-3.46, -3.04)
  1. Results show mean and 95% credible interval (CrI). Summaries of the posterior distributions for the relative risks for each season are presented in the additional materials and the means are plotted in Figure 3.