Spatial health inequalities
During the observation period, nearly all of the 1,206 dissemination areas in the region reported cases. The cumulative incidence per area averaged 4.4 reported cases per 100 residents (median = 4.1). Spread was more limited in municipalities outside the Quebec City metropolitan area and, within the metropolitan area, in less densely populated neighbourhoods (Table 1, Map 1, and Supplementary table 1). The cumulative incidence of the area at the 90th percentile of the distribution was three times higher than that of the 10th percentile (90/10 ratio = 3.37). The Gini index for all areas was equal to 0.265 (95% CI [0.251, 0.279]). The index varied little between strata, as did the 90/10 ratio. In other words, the spread differed significantly between territories, but the inequality between areas of equal population density was relatively constant. The second part of Table 1 focuses on the 119 areas at excess risk. The cumulative incidence was, on average, 0.093 (median = 0.083), i.e., a mean deviation (FGT1) from the threshold value of 35% (95% CI [26.0%, 43.5%]). These areas were located mainly, but not exclusively, in the most densely populated areas of downtown Quebec City (Map 1B). This group of areas was heterogeneous (Gini = 0.15; FGT2 = 33%), with cumulative incidence ranging from 0.069 to 0.24.
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Map 1. Spatial distribution of population and SARS-CoV-2 transmission. Quebec City agglomeration and Capitale-Nationale region
Social and spatial health inequalities
Table 2 provides a summary picture of the socioeconomic characteristics of the DAs by cumulative incidence. The areas were divided into four groups according to whether they fell between the 1st and 10th percentile of the distribution, the 10th percentile and the median, the median and the 90th percentile, or above the 90th percentile. The comparison revealed the significant concentration of spread in the most disadvantaged territories. The most exposed territories were those in which the indices of social and material deprivation were highest. Median income was lower in the most exposed areas and vice versa. The proportion of immigrants and the population density in the most affected DAs (90th percentile) exceeded that of the least exposed areas by almost 50%, and the median income of economic families was 20% lower.
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The curves presented in Figure 1 present the results of non-parametric regressions on the relationship between cumulative incidence and ecological indicators of deprivation. The analysis was repeated in each of the strata defined by the area locations and population density. In the three strata of the Quebec City agglomeration, the economic gradient in health persisted after stratification. Exposure to the pandemic was associated with median household income and material deprivation in the Quebec City agglomeration. In contrast, the relationship between spread and social deprivation was less tangible (Supplementary figure 2).
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In the following sections, median household income will be used as the reference indicator for calculating inequality indices. The concentration coefficients in the three zones were negative. They were ‑0.03 (95% CI [0.07, 0.00]) in the least densely populated areas, 0.07 (95% CI [0.10, 0.4]) in the intermediate stratum, and ‑0.09 (95% CI [0.12, 0.07]) in the most densely populated areas. These values thus indicated a concentration of the epidemic’s spread in economically disadvantaged areas, especially in densely populated areas.
Statistical modeling supplemented this picture of social inequalities in health. Based on the model, the probability that a more socioeconomically disadvantaged area (first income quintile) was in the group least exposed, or most exposed, to the epidemic was estimated. The process was then replicated for each income group. The results are shown in Figure 4 (see Supplementary table 2). An area with an economically disadvantaged population was three times more likely to be among the areas most exposed to the pandemic (RR = 3.55; 95% CI [2.02, 5.08]), whereas an area with a higher income population was two times less likely to be among the areas most exposed to the pandemic (RR = 0.52; 95% CI [0.32, 0.72]). Conversely, an area with a low-income population had less than a 10% likelihood of being in the most spared quintile (RR = 0.09; 95% CI [0.07, 0.12]). An area with the highest median income population had a less than 26% likelihood of being in the most spared quintile (RR = 0.26; 95% CI [0.21, 0.31]).
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Evolution of the economic gradient in health
Figure 3 suggests that socioeconomic inequality in health appeared from the beginning of the pandemic. It persisted and tended to increase thereafter, as the different waves were experienced. Over time, the areas with the lowest family incomes were demarcated from the other groups of areas, especially in the two strata that included the most densely populated areas.
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Economic deprivation and excess risk
Of the 119 areas at excess risk, 44% (N = 51) belonged to the group made up of the most socioeconomically disadvantaged territories (first income quintile), while only 10% (N = 12) belonged to the group consisting of the areas with the highest income (Table 3). In other words, an area with lower income was four times more likely to be in the excess risk group than an area with the highest family income. Among the areas with the lowest family income, more than one in five were in excess risk, even though they constituted only 10% of the areas (Table 6; FGT0 = 21.6%). Only one in 20 of the highest-income areas had excess risk.
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The mean excess risk in the economically disadvantaged areas was 38.1%, a value four times higher than that observed in the 12 areas with the highest family income (FGT1 = 9.9%). The cumulative incidence in the most economically advantaged areas was only slightly above the cut-off value (0.076 rather than 0.069). In other words, excess risk was modest in the more advantaged areas and greater in those with the lowest family income. The standard deviations and FGT2 indices also showed that disparities were more pronounced within the same group of economically more disadvantaged areas: FGT2 reached 40%, whereas at the opposite end of the spectrum, the group of areas at excess risk containing the population in the highest income bracket was extremely homogeneous (FGT2 = 2.1%).