Table 2.
Region | Ip1 | In1 | Ip2 | In2 | ||||
---|---|---|---|---|---|---|---|---|
R2 | P | R2 | P | R2 | P | R2 | P | |
Model A | ||||||||
Wuhan City | 0.882 | < 0.001 | 0.55 | < 0.001 | 0.49 | < 0.001 | 0.857 | < 0.001 |
Jilin Province | 0.939 | < 0.001 | 0.834 | < 0.001 | 0.781 | < 0.001 | 0.823 | < 0.001 |
Xiamen City | 0.105 | < 0.001 | 0.156 | < 0.001 | 0.202 | < 0.001 | 0.708 | < 0.001 |
Chuxiong Prefecture | 0.971 | < 0.001 | 0.971 | < 0.001 | 0.752 | < 0.001 | 0.619 | < 0.001 |
Model B | ||||||||
Wuhan City | 0.236 | < 0.001 | 0.083 | < 0.001 | 0.337 | < 0.001 | 0.761 | < 0.001 |
Jilin Province | 0.961 | < 0.001 | 0.615 | < 0.001 | 0.489 | < 0.001 | 0.559 | < 0.001 |
Xiamen City | 0.039 | 0.009 | 0.009 | 0.202 | 0.239 | < 0.001 | 0.399 | < 0.001 |
Chuxiong Prefecture | 0.978 | < 0.001 | 0.977 | < 0.001 | 0.952 | < 0.001 | 0.818 | < 0.001 |
Correlation between the simulated and observed data was tested using R2 and p values. We divided all the compartments representing active diseases (I) into four occupational compartments: pathogen positive students (Ip1 subscript), pathogen positive non-students (Ip2 subscript), pathogen negative students (In1 subscript) and pathogen negative non-students (In2 subscript)