Estimation of SARS-CoV-2 Seroprevalence in Central North Carolina: Accounting for Outcome Misclassification in Complex Sample Designs.

BACKGROUND: Population-based seroprevalence studies are crucial to understand community transmission of COVID-19 and guide responses to the pandemic. Seroprevalence is typically measured from diagnostic tests with imperfect sensitivity and specificity. Failing to account for measurement error can lead to biased estimates of seroprevalence. Methods to adjust seroprevalence estimates for the sensitivity and specificity of the diagnostic test have largely focused on estimation in the context of convenience sampling. Many existing methods are inappropriate when data are collected using a complex sample design. METHODS: We present methods for seroprevalence point estimation and confidence interval construction that account for imperfect test performance for use with complex sample data. We apply these methods to data from the Chatham County COVID-19 Cohort (C4), a longitudinal seroprevalence study conducted in central North Carolina. Using simulations, we evaluate bias and confidence interval coverage for the proposed estimator compared with a standard estimator under a stratified, three-stage cluster sample design. RESULTS: We obtained estimates of seroprevalence and corresponding confidence intervals for the C4 study. SARS-CoV-2 seroprevalence increased rapidly from 10.4% in January to 95.6% in July 2021 in Chatham County, North Carolina. In simulation, the proposed estimator demonstrates desirable confidence interval coverage and minimal bias under a wide range of scenarios. CONCLUSION: We propose a straightforward method for producing valid estimates and confidence intervals when data are based on a complex sample design. The method can be applied to estimate the prevalence of other infections when estimates of test sensitivity and specificity are available.

Interferon activated gene 204 protects against bone loss in experimental periodontitis.

BACKGROUND: Periodontal destruction can be the result of different known and yet-to-be-discovered biological pathways. Recent human genetic association studies have implicated interferon-gamma inducible protein 16 (IFI16) and absent in melanoma 2 (AIM2) with high periodontal interleukin (IL)-1ß levels and more destructive disease, but mechanistic evidence is lacking. Here, we sought to experimentally validate these observational associations and better understand IFI16 and AIM2's roles in periodontitis. METHODS: Periodontitis was induced in Ifi204-/- (IFI16 murine homolog) and Aim2-/- mice using the ligature model. Chimeric mice were created to identify the main source cells of Ifi204 in the periodontium. IFI16-silenced human endothelial cells were treated with periodontal pathogens in vitro. Periodontal tissues from Ifi204-/- mice were evaluated for alveolar bone (micro-CT), cell inflammatory infiltration (MPO+ staining), Il1b (qRT-PCR), and osteoclast numbers (cathepsin K+ staining). RESULTS: Ifi204-deficient mice> exhibited >20% higher alveolar bone loss than wild-type (WT) (P < 0.05), while no significant difference was found in Aim2-/- mice. Ifi204's effect on bone loss was primarily mediated by a nonbone marrow source and was independent of Aim2. Ifi204-deficient mice had greater neutrophil/macrophage trafficking into gingival tissues regardless of periodontitis development compared to WT. In human endothelial cells, IFI16 decreased the chemokine response to periodontal pathogens. In murine periodontitis, Ifi204 depletion elevated gingival Il1b and increased osteoclast numbers at diseased sites (P < 0.05). CONCLUSIONS: These findings support IFI16's role as a novel regulator of inflammatory cell trafficking to the periodontium that protects against bone loss and offers potential targets for the development of new periodontal disease biomarkers and therapeutics.