Objectives: To describe variations in coronavirus disease 2019 (COVID-19) diagnosis by zip code race and ethnicity in Indiana. Methods: Cross-sectional evaluation of subjects with SARS-CoV-2 at Indiana University Health. We performed two separate analyses, first evaluating likelihood of COVID-19 diagnosis by race (Caucasian, African American, Asian, or other) and ethnicity (Hispanic vs. non-Hispanic) in the cohort encompassing the entire state of Indiana. Subsequently, patient data was geolocated with zip codes in Marion County and the immediate surrounding counties, and descriptive statistical analyses were used to calculate the number of COVID-19 cases per 10,000 persons for each of these zip codes. Results: Indiana had a total of 3,892 positive COVID-19 cases from January 1 to April 30, 2020. The odds of testing positive for COVID-19 were four-fold higher in African Americans than non-African Americans (OR 4.58, 95% CI 4.25-4.94, P < 0.0001). Increased COVID-19 cases per 10,000 persons were seen in zip codes with higher percentage of African American (median infection rate of 17.4 per 10,000 population in zip codes above median % African American compared to 6.7 per 10,000 population in zip codes below median % African American, with an overall median infection rate 9.9 per 10,000 population, P < 0.0001) or Hispanic residents (median infection rate of 15.9 per 10,000 population in zip codes above median % Hispanic compared to 7.0 per 10,000 population in zip codes below median % Hispanic, overall median infection rate 9.6 per 10,000 population, P < 0.0001). Conclusions: Individuals from zip codes with higher percentages of African American, Hispanic, foreign-born, and/or residents living in poverty are disproportionately affected by COVID-19. Urgent work is needed to understand and address the disproportionate burden of COVID-19 in minority communities and when economic disparities are present.
Objectives: To describe variations in coronavirus disease 2019 (COVID-19) diagnosis by zip code race and ethnicity in Indiana. Methods: Cross-sectional evaluation of subjects with SARS-CoV-2 at Indiana University Health. We performed two separate analyses, first evaluating likelihood of COVID-19 diagnosis by race (Caucasian, African American, Asian, or other) and ethnicity (Hispanic vs. non-Hispanic) in the cohort encompassing the entire state of Indiana. Subsequently, patient data was geolocated with zip codes in Marion County and the immediate surrounding counties, and descriptive statistical analyses were used to calculate the number of COVID-19 cases per 10,000 persons for each of these zip codes. Results: Indiana had a total of 3,892 positive COVID-19 cases from January 1 to April 30, 2020. The odds of testing positive for COVID-19 were four-fold higher in African Americans than non-African Americans (OR 4.58, 95% CI 4.25-4.94, P < 0.0001). Increased COVID-19 cases per 10,000 persons were seen in zip codes with higher percentage of African American (median infection rate of 17.4 per 10,000 population in zip codes above median % African American compared to 6.7 per 10,000 population in zip codes below median % African American, with an overall median infection rate 9.9 per 10,000 population, P < 0.0001) or Hispanic residents (median infection rate of 15.9 per 10,000 population in zip codes above median % Hispanic compared to 7.0 per 10,000 population in zip codes below median % Hispanic, overall median infection rate 9.6 per 10,000 population, P < 0.0001). Conclusions: Individuals from zip codes with higher percentages of African American, Hispanic, foreign-born, and/or residents living in poverty are disproportionately affected by COVID-19. Urgent work is needed to understand and address the disproportionate burden of COVID-19 in minority communities and when economic disparities are present.
Authors: Rishi K Wadhera; Priya Wadhera; Prakriti Gaba; Jose F Figueroa; Karen E Joynt Maddox; Robert W Yeh; Changyu Shen Journal: JAMA Date: 2020-06-02 Impact factor: 56.272
Authors: Claire L Niedzwiedz; Catherine A O'Donnell; Bhautesh Dinesh Jani; Evangelia Demou; Frederick K Ho; Carlos Celis-Morales; Barbara I Nicholl; Frances S Mair; Paul Welsh; Naveed Sattar; Jill P Pell; S Vittal Katikireddi Journal: BMC Med Date: 2020-05-29 Impact factor: 11.150
Authors: Mark L Wieland; Gladys B Asiedu; Jane W Njeru; Jennifer A Weis; Kiley Lantz; Adeline Abbenyi; Luz Molina; Yahye Ahmed; Ahmed Osman; Miriam Goodson; Gloria Torres-Herbeck; Omar Nur; Graciela Porraz Capetillo; Ahmed A Mohamed; Irene G Sia Journal: Public Health Rep Date: 2022-01-13 Impact factor: 2.792