Table 2.
Logistic Regression Models Predicting Different Infection of COVID-19.
Model 1 | Model 2 | Model 3 | |
---|---|---|---|
Respondent confirmed/suspected COVID-19 | Coresident family members confirmed COVID-19 | Respondent/Coresident family members confirmed COVID-19 | |
SES | −0.199* | −0.107* | −0.130** |
(0.080) | (0.043) | (0.042) | |
Age | −0.104† | 0.014 | 0.008 |
(0.056) | (0.035) | (0.034) | |
Age2 | 1.049† | −0.160 | −0.148 |
(0.570) | (0.374) | (0.368) | |
Female | −0.489† | −0.280† | −0.362** |
(0.267) | (0.146) | (0.140) | |
Married | 0.542 | 0.177 | 0.263 |
(0.456) | (0.251) | (0.243) | |
Household size | −0.487*** | −0.042 | −0.087 |
(0.133) | (0.060) | (0.059) | |
CCP membership | 0.110 | 0.051 | 0.046 |
(0.337) | (0.182) | (0.176) | |
Wuhan Hukou | 0.599 | 0.500† | 0.619* |
(0.530) | (0.286) | (0.286) | |
Neighborhood lockdown | 0.068 | 0.340 | 0.189 |
(0.438) | (0.267) | (0.241) | |
Constant | −0.169 | −3.282*** | −2.689*** |
(1.401) | (0.832) | (0.804) | |
Observations | 4234 | 4234 | 4234 |
Notes: Standard errors in parentheses; *** p < 0.001, ** p < 0.01, * p < 0.05, † p < 0.1.