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Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City.

ABSTRACT: As the COVID-19 pandemic continues, formulating targeted policy interventions that are informed by differential severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission dynamics will be of vital importance to national and regional governments. We develop an individual-level model for SARS-CoV-2 transmission that accounts for location-dependent distributions of age, household structure, and comorbidities. We use these distributions together with age-stratified contact matrices to instantiate specific models for Hubei, China; Lombardy, Italy; and New York City, United States. Using data on reported deaths to obtain a posterior distribution over unknown parameters, we infer differences in the progression of the epidemic in the three locations. We also examine the role of transmission due to particular age groups on total infections and deaths. The effect of limiting contacts by a particular age group varies by location, indicating that strategies to reduce transmission should be tailored based on population-specific demography and social structure. These findings highlight the role of between-population variation in formulating policy interventions. Across the three populations, though, we find that targeted "salutary sheltering" by 50% of a single age group may substantially curtail transmission when combined with the adoption of physical distancing measures by the rest of the population.

SUBMITTER: Wilder B

PROVIDER: S-EPMC7568285 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City.

Wilder Bryan B Charpignon Marie M Killian Jackson A JA Ou Han-Ching HC Mate Aditya A Jabbari Shahin S Perrault Andrew A Desai Angel N AN Tambe Milind M Majumder Maimuna S MS

Proceedings of the National Academy of Sciences of the United States of America 20200924 41

As the COVID-19 pandemic continues, formulating targeted policy interventions that are informed by differential severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission dynamics will be of vital importance to national and regional governments. We develop an individual-level model for SARS-CoV-2 transmission that accounts for location-dependent distributions of age, household structure, and comorbidities. We use these distributions together with age-stratified contact matrices to ...[more]

PMID: 32973089

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Project description:ObjectivesThere is limited evidence on how clinical outcomes differ by socioeconomic conditions among patients with coronavirus disease 2019 (COVID-19). Most studies focused on COVID-19 patients from a single hospital. Results based on patients from multiple health systems have not been reported. The objective of this study is to examine variation in patient characteristics, outcomes, and healthcare utilization by neighborhood social conditions among COVID-19 patients.MethodsWe extracted electronic health record data for 23,300 community dwelling COVID-19 patients in New York City between March 1st and June 11th, 2020 from all care settings, including hospitalized patients, patients who presented to the emergency department without hospitalization, and patients with ambulatory visits only. Zip Code Tabulation Area-level social conditions were measured by the Social Deprivation Index (SDI). Using logistic regressions and Cox proportional-hazards models, we examined the association between SDI quintiles and hospitalization and death, controlling for race, ethnicity, and other patient characteristics.ResultsAmong 23,300 community dwelling COVID-19 patients, 60.7% were from neighborhoods with disadvantaged social conditions (top SDI quintile), although these neighborhoods only account for 34% of overall population. Compared to socially advantaged patients (bottom SDI quintile), socially disadvantaged patients (top SDI quintile) were older (median age 55 vs. 53, P<0.001), more likely to be black (23.1% vs. 6.4%, P<0.001) or Hispanic (25.4% vs. 8.5%, P<0.001), and more likely to have chronic conditions (e.g., diabetes: 21.9% vs. 10.5%, P<0.001). Logistic and Cox regressions showed that patients with disadvantaged social conditions had higher risk for hospitalization (odds ratio: 1.68; 95% confidence interval [CI]: [1.46, 1.94]; P<0.001) and mortality (hazard ratio: 1.91; 95% CI: [1.35, 2.70]; P<0.001), adjusting for other patient characteristics.ConclusionSubstantial socioeconomic disparities in health outcomes exist among COVID-19 patients in NYC. Disadvantaged neighborhood social conditions were associated with higher risk for hospitalization, severity of disease, and death.

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.

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Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City.

Publications

Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City.

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