Table 1 |
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Bayesian Poisson regression models of Plasmodium vivax and P. falciparum malaria, Yunnan, China, 1991–2006. |
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Variable |
Plasmodium vivax |
Plasmodium falciparum |
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Relative Risks |
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Monthly rainfall (10 ml increase) |
1.045 (1.044, 1.046) |
1.037 (1.034, 1.040) |
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Monthly maximum temperature (°C increase) |
1.047 (1.045, 1.050) |
1.053 (1.047, 1.060) |
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Provincial average temporal trend (annual increase) |
0.948 (0.944, 0.952) |
0.957 (0.949, 0.965) |
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Regression of June–September on January–February (log incidence) |
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Regression slope (Jan–Feb → Jun–Sep) |
0.77 (0.70, 0.84) |
0.90 (0.75, 1.09) |
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Variance components (variances on a scale of log incidence) |
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Spatial random effect |
8.74 (7.90, 9.89) |
12.66 (10.50, 15.58) |
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Spatially-smoothed county-level temporal trend |
0.08 (0.06, 0.10) |
0.01 (0.00, 0.01) |
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Seasonal effect (January–February) |
0.02 (0.01, 0.04) |
0.02 (0.01, 0.06) |
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Overall Intercept |
-2.52 (-2.60, -2.45) |
-3.24 (-3.46, -3.04) |
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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. |
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Clements et al. Malaria Journal 2009 8:180 doi:10.1186/1475-2875-8-180 |
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