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Spatial analysis of COVID-19 clusters and contextual factors in New York City.

ABSTRACT: Identifying areas with low access to testing and high case burden is necessary to understand risk and allocate resources in the COVID-19 pandemic. Using zip code level data for New York City, we analyzed testing rates, positivity rates, and proportion positive. A spatial scan statistic identified clusters of high and low testing rates, high positivity rates, and high proportion positive. Boxplots and Pearson correlations determined associations between outcomes, clusters, and contextual factors. Clusters with less testing and low proportion positive tests had higher income, education, and white population, whereas clusters with high testing rates and high proportion positive tests were disproportionately black and without health insurance. Correlations showed inverse associations of white race, education, and income with proportion positive tests, and positive associations with black race, Hispanic ethnicity, and poverty. We recommend testing and health care resources be directed to eastern Brooklyn, which has low testing and high proportion positives.

SUBMITTER: Cordes J

PROVIDER: S-EPMC7306208 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Spatial analysis of COVID-19 clusters and contextual factors in New York City.

Cordes Jack J Castro Marcia C MC

Spatial and spatio-temporal epidemiology 20200621

Identifying areas with low access to testing and high case burden is necessary to understand risk and allocate resources in the COVID-19 pandemic. Using zip code level data for New York City, we analyzed testing rates, positivity rates, and proportion positive. A spatial scan statistic identified clusters of high and low testing rates, high positivity rates, and high proportion positive. Boxplots and Pearson correlations determined associations between outcomes, clusters, and contextual factors. ...[more]

PMID: 32807400

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Project description:BackgroundCOVID-19 has affected millions of people, and several chronic medical conditions appear to increase the risk of severe COVID-19. However, our understanding of COVID-19 outcomes in patients with CKD remains limited.MethodsThis was a retrospective cohort study of patients with and without CKD consecutively admitted with COVID-19 to three affiliated hospitals in New York City. Pre-COVID-19 CKD diagnoses were identified by billing codes and verified by manual chart review. In-hospital mortality was compared between patients with and without underlying CKD. Logistic regression was used to adjust this analysis for confounders and to identify patient characteristics associated with mortality.ResultsWe identified 280 patients with CKD, and 4098 patients without CKD hospitalized with COVID-19. The median age of the CKD group was 75 (65-84) years, and age of the non-CKD group 62 (48-75) years. Baseline (pre-COVID-19) serum creatinine in patients with CKD was 1.5 (1.2-2.2) mg/dl. In-hospital mortality was 30% in patients with CKD versus 20% in patients without CKD (P<0.001). The risk of in-hospital death in patients with CKD remained higher than in patients without CKD after adjustment for comorbidities (hypertension, diabetes mellitus, asthma, and chronic obstructive pulmonary disease), adjusted OR 1.4 (95% CI,1.1 to 1.9), P=0.01. When stratified by age, elderly patients with CKD (age >70 years) had higher mortality than their age-matched control patients without CKD. In patients with CKD, factors associated with in-hospital mortality were age (adjusted OR, 1.09 [95% CI, 1.06 to 1.12]), P<0.001, baseline and admission serum phosphorus (adjusted OR, 1.5 [95% CI, 1.03 to 2.1], P=0.03 and 1.4 [95% CI, 1.1 to 1.7], P=0.001), serum creatinine on admission >0.3 mg/dl above the baseline (adjusted OR 2.6 [95% CI, 1.2 to 5.4]P=0.01), and diagnosis of acute on chronic kidney injury during hospitalization (adjusted OR 4.6 [95% CI, 2.3 to 8.9], P<0.001).ConclusionsCKD is an independent risk factor for COVID-19-associated in-hospital mortality in elderly patients. Acute-on-chronic kidney injury increases the odds of in-hospital mortality in patients with CKD hospitalized with COVID-19.

Dataset Information

Spatial analysis of COVID-19 clusters and contextual factors in New York City.

Publications

Spatial analysis of COVID-19 clusters and contextual factors in New York City.

Similar Datasets

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