Table 4.
Poisson regression models predicting cumulative COVID‐19 infections among Toronto's neighbourhoods
| Peak of first wave | Peak of second wave | |||
|---|---|---|---|---|
| (Apr. 20, 2020) | (Jan 1th, 2021) | |||
| Standardized Covariates | β | β/se | β | β/se |
| Percent Black | 0.23*** | 10.87 | 0.11*** | 19.66 |
| Percent foreign‐born | 0.29*** | 12.82 | 0.47*** | 74.27 |
| Percent low‐income | −0.08*** | −3.50 | −0.17*** | −26.36 |
| Percent working in health | 0.08*** | 4.38 | 0.04*** | 7.96 |
| Percent w/bachelor's degree or more | 0.00 | 0.11 | −0.18*** | −23.18 |
| Percent 65+ years of age | −0.05** | −2.69 | −0.18*** | −35.72 |
| Population density | 0.08*** | 5.88 | −0.01** | −2.79 |
| Intercept | 3.59*** | 246.62 | 6.10*** | 1417.75 |
Notes: Data come from Toronto Public Health and Toronto's Open Data Catalogue. Covariates are standardized. Separate models are run for two time points: the cumulative count of COVID‐19 infections at the peak of the pandemic's first wave (April 10, 2020) and at the peak of the second wave (January 10th, 2021). Statistical significance is indicated by: * p < .05, ** p < .01, *** p < .001.
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