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Mayo Clinic proceedings. Innovations, quality & outcomes ; 2022.
Article in English | EuropePMC | ID: covidwho-2073911


Objective To estimate rates and identify factors associated with asymptomatic COVID-19 in the population of Olmsted County during the pre-vaccination era. Patients and Methods We screened first responders (N=191) and Olmsted County employees (N=564) for antibodies to SARS-CoV-2 from November 2020 to February 2021 to estimate seroprevalence and asymptomatic infection. Second, we retrieved all PCR confirmed COVID-19 diagnoses in Olmsted County from March 2020 through January 2021, ed symptom information, estimated rates of asymptomatic infection and examined related factors. Results Twenty (10.5%;95%CI: 6.9%-15.6%) first responders and thirty-eight (6.7%;95% CI: 5.0%-9.1%) county employees had positive antibodies;an additional 5 (2.6%) and 10 (1.8%) had prior positive PCR tests per self-report or medical record, but no antibodies detected. Of persons with symptom information, 4/20, (20%, 95% CI: 3.0%-37.0%) of first responders and 10/39 (26%, 95% CI: 12.6%-40.0%) county employees, were asymptomatic. Of 6,020 positive PCR tests in Olmsted County with symptom information between March 1, 2020, and January 31, 2021, 6% (n=385;95% CI: 5.8%-7.1%) were asymptomatic. Factors associated with asymptomatic disease included age [0-18 years (OR=2.3, 95% CI: 1.7-3.1) and 65+ years (OR=1.40, 95% CI: 1.0-2.0) compared to ages 19-44 years], body-mass-index [overweight OR=0.58, 95% CI: 0.44-0.77) or obese (OR=0.48, 95% CI: 0.57-0.62) compared to normal or underweight] and tests after November 20, 2020 [(OR=1.35;95% CI: 1.13-1.71) compared to prior dates]. Conclusion Asymptomatic rates in Olmsted County prior to vaccine rollout ranged from 6-25%, and younger age, normal weight, and later tests dates were associated with asymptomatic infection.

Mayo Clin Proc ; 96(10): 2528-2539, 2021 10.
Article in English | MEDLINE | ID: covidwho-1294052


OBJECTIVE: To identify risk factors associated with severe COVID-19 infection in a defined Midwestern US population overall and within different age groups. PATIENTS AND METHODS: We used the Rochester Epidemiology Project research infrastructure to identify persons residing in a defined 27-county Midwestern region who had positive results on polymerase chain reaction tests for COVID-19 between March 1, 2020, and September 30, 2020 (N=9928). Age, sex, race, ethnicity, body mass index, smoking status, and 44 chronic disease categories were considered as possible risk factors for severe infection. Severe infection was defined as hospitalization or death caused by COVID-19. Associations between risk factors and severe infection were estimated using Cox proportional hazard models overall and within 3 age groups (0 to 44, 45 to 64, and 65+ years). RESULTS: Overall, 474 (4.8%) persons developed severe COVID-19 infection. Older age, male sex, non-White race, Hispanic ethnicity, obesity, and a higher number of chronic conditions were associated with increased risk of severe infection. After adjustment, 36 chronic disease categories were significantly associated with severe infection. The risk of severe infection varied significantly across age groups. In particular, persons 0 to 44 years of age with cancer, chronic neurologic disorders, hematologic disorders, ischemic heart disease, and other endocrine disorders had a greater than 3-fold increased risk of severe infection compared with persons of the same age without those conditions. Associations were attenuated in older age groups. CONCLUSION: Older persons are more likely to experience severe infections; however, severe cases occur in younger persons as well. Our data provide insight regarding younger persons at especially high risk of severe COVID-19 infection.

COVID-19/epidemiology , Health Status Disparities , Severity of Illness Index , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Child , Child, Preschool , Chronic Disease/epidemiology , Comorbidity , Humans , Infant , Male , Middle Aged , Midwestern United States , Risk Factors , Young Adult
Mayo Clin Proc ; 96(5): 1165-1174, 2021 05.
Article in English | MEDLINE | ID: covidwho-1157598


OBJECTIVE: To estimate the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in health care personnel. METHODS: The Mayo Clinic Serology Screening Program was created to provide a voluntary, two-stage testing program for SARS-CoV-2 antibodies to health care personnel. The first stage used a dried blood spot screening test initiated on June 15, 2020. Those participants identified as reactive were advised to have confirmatory testing via a venipuncture. Venipuncture results through August 8, 2020, were considered. Consent and authorization for testing was required to participate in the screening program. This report, which was conducted under an institutional review board-approved protocol, only includes employees who have further authorized their records for use in research. RESULTS: A total of 81,113 health care personnel were eligible for the program, and of these 29,606 participated in the screening program. A total of 4284 (14.5%) of the dried blood spot test results were "reactive" and warranted confirmatory testing. Confirmatory testing was completed on 4094 (95.6%) of the screen reactive with an overall seroprevalence rate of 0.60% (95% CI, 0.52% to 0.69%). Significant variation in seroprevalence was observed by region of the country and age group. CONCLUSION: The seroprevalence for SARS-CoV-2 antibodies through August 8, 2020, was found to be lower than previously reported in other health care organizations. There was an observation that seroprevalence may be associated with community disease burden.

Antibodies, Viral/blood , COVID-19 Serological Testing , COVID-19 , Disease Transmission, Infectious/statistics & numerical data , Health Personnel/statistics & numerical data , SARS-CoV-2 , Academic Medical Centers , Adult , COVID-19/blood , COVID-19/epidemiology , COVID-19/therapy , COVID-19 Serological Testing/methods , COVID-19 Serological Testing/statistics & numerical data , Female , Humans , Immunoglobulin G/blood , Male , Middle Aged , Public Health/methods , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Seroepidemiologic Studies , Spatio-Temporal Analysis , United States/epidemiology