LOCAL-SCALE SPATIAL VARIABILITY in SARS-CoV-2 SEROPREVALENCE in AN INDIAN MEGACITY

ABSTRACT

Background: While the diversity in SARS-CoV-2 transmission across geographies and risk groups is well recognized, there has been limited investigation into spatial heterogeneity at a local scale, that is variability across a single city. Identifying patterns and factors associated with spatial variability requires population representative samples which are challenging to obtain but critical for mitigation strategies including vaccine distribution. Methods: From Jan to May 2021, we sampled 4,828 participants from 2,723 unique households across 100 spatial locations in Chennai, India using a probability proportional to population density sampling approach. All participants provided a blood sample and underwent a household and individual survey. 4,712 samples were tested for antibodies to the Spike protein (anti-Spike IgG) by the Abbott ARCHITECT. SARS-CoV-2 prevalence by spatial location was plotted using splines estimated by generalized additive models. Associations between seroprevalence and spatial attributes (zone, population density), study characteristics (date of sampling), household and individual-level covariates were estimated using Bayesian mixed effects logistic regression accounting for clustering within households and locations. Results: The median age was 38 and 49% self-identified as female. Overall, anti-S IgG prevalence was 61.9% (95% confidence interval [CI] 60.5-63.3%) but ranged from 41.5% to 73.1% across the 12 zones. Splines indicated statistically significant variation in seroprevalence across the city (Panel A). Mixed effects regression including location and household effects indicated 31% of variance was attributable to location. In adjusted analysis, seroprevalence was significantly associated with population density (OR=1.46 per 100 people/100 sq meter [95%CI 1.08-1.97];Panel B), age (OR=1.004 [95%CI 1.0002-1.005]), having an air conditioner (OR=0.65 [95%CI 0.43-0.98]) and sample timing but not with household crowding (OR=0.97 per person/room [95%CI 0.75-1.26];Panel C). Significant spatial variation across locations remained after adjustment for these variables, accounting for 28% of variance. Conclusion: We observed substantial spatial heterogeneity of SARS-CoV-2 burden in this high prevalence setting not fully explained by individual, household or population factors. Such local variability in prevalence has implications not only for transmission but for scale-up of vaccines which remain in limited supply in low-and middle-income countries.