Parotitis-Like Symptoms Associated with COVID-19, France, March-April 2020.
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ABSTRACT:
SUBMITTER: Lechien JR
PROVIDER: S-EPMC7454100 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:COVID-19, although a respiratory illness, has been clinically associated with non-respiratory symptoms. We conducted a negative case-control study to identify the symptoms associated with SARS-CoV-2-positive results in Portugal. Twelve symptoms and signs included in the clinical notification of COVID-19 were selected as predictors, and the dependent variable was the RT-PCR test result. The χ2 tests were used to compare notified cases on sex, age group, health region and presence of comorbidities. The best-fit prediction model was selected using a backward stepwise method with an unconditional logistic regression. General and gastrointestinal symptoms were strongly associated with a positive test (P < 0.001). In this sense, the inclusion of general symptoms such as myalgia, headache and fatigue, as well as diarrhoea, together with actual clinical criteria for suspected cases, already updated and included in COVID-19 case definition, can lead to increased identification of cases and represent an effective strength for transmission control.
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Project description:The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged ?18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age ?65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.
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Project description:Pneumonia caused by severe acute respiratory syndrome coronavirus 2 emerged in China at the end of 2019. Because of the severe immunomodulation and lymphocyte depletion caused by this virus and the subsequent administration of drugs directed at the immune system, we anticipated that patients might experience fungal superinfection. We collected data from 186 patients who had coronavirus disease-associated pulmonary aspergillosis (CAPA) worldwide during March-August 2020. Overall, 182 patients were admitted to the intensive care unit (ICU), including 180 with acute respiratory distress syndrome and 175 who received mechanical ventilation. CAPA was diagnosed a median of 10 days after coronavirus disease diagnosis. Aspergillus fumigatus was identified in 80.3% of patient cultures, 4 of which were azole-resistant. Most (52.7%) patients received voriconazole. In total, 52.2% of patients died; of the deaths, 33.0% were attributed to CAPA. We found that the cumulative incidence of CAPA in the ICU ranged from 1.0% to 39.1%.
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Project description:IntroductionSARS-CoV-2, the virus that causes COVID-19, has spread rapidly worldwide. In January 2020, a surveillance system was implemented in France for early detection of cases and their contacts to help limit secondary transmissions.AimTo use contact-tracing data collected during the initial phase of the COVID-19 pandemic to better characterise SARS-CoV-2 transmission.MethodsWe analysed data collected during contact tracing and retrospective epidemiological investigations in France from 24 January to 30 March 2020. We assessed the secondary clinical attack rate and characterised the risk of a contact becoming a case. We described chains of transmission and estimated key parameters of spread.ResultsDuring the study period, 6,082 contacts of 735 confirmed cases were traced. The overall secondary clinical attack rate was 4.1% (95% confidence interval (CI): 3.6-4.6), increasing with age of index case and contact. Compared with co-workers/friends, family contacts were at higher risk of becoming cases (adjusted odds ratio (AOR): 2.1, 95% CI: 1.4-3.0) and nosocomial contacts were at lower risk (AOR: 0.3, 95% CI: 0.1-0.7). Of 328 infector/infectee pairs, 49% were family members. The distribution of secondary cases was highly over-dispersed: 80% of secondary cases were caused by 10% of cases. The mean serial interval was 5.1 days (interquartile range (IQR): 2-8 days) in contact tracing pairs, where late transmission events may be censored, and 6.8 (3-8) days in pairs investigated retrospectively.ConclusionThis study increases knowledge of SARS-CoV-2 transmission, including the importance of superspreading events during the onset of the pandemic.
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Project description:On March 24, 2020, the South Dakota Department of Health (SDDOH) was notified of a case of coronavirus disease 2019 (COVID-19) in an employee at a meat processing facility (facility A) and initiated an investigation to isolate the employee and identify and quarantine contacts. On April 2, when 19 cases had been confirmed among facility A employees, enhanced testing for SARS-CoV-2, the virus that causes COVID-19, was implemented, so that any employee with a COVID-19-compatible sign or symptom (e.g., fever, cough, or shortness of breath) could receive a test from a local health care facility. By April 11, 369 COVID-19 cases had been confirmed among facility A employees; on April 12, facility A began a phased closure* and did not reopen during the period of investigation (March 16-April 25, 2020). At the request of SDDOH, a CDC team arrived on April 15 to assist with the investigation. During March 16-April 25, a total of 929 (25.6%) laboratory-confirmed COVID-19 cases were diagnosed among 3,635 facility A employees. At the outbreak's peak, an average of 67 cases per day occurred. An additional 210 (8.7%) cases were identified among 2,403 contacts of employees with diagnosed COVID-19. Overall, 48 COVID-19 patients were hospitalized, including 39 employees and nine contacts. Two employees died; no contacts died. Attack rates were highest among department-groups where employees tended to work in proximity (i.e., <6 feet [2 meters]) to one another on the production line. Cases among employees and their contacts declined to approximately 10 per day within 7 days of facility closure. SARS-CoV-2 can spread rapidly in meat processing facilities because of the close proximity of workstations and prolonged contact between employees (1,2). Facilities can reduce this risk by implementing a robust mitigation program, including engineering and administrative controls, consistent with published guidelines (1).
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Project description:Infectious disease data can often involve complex spatial patterns intermixed with temporal trends. Archetypal Analysis is a method to mine complex spatio-temporal data, and can be used to discover the dynamics of spatial patterns. The application of Archetypal Analysis to epidemiological data is relatively new, and here we present one of the first applications on COVID-19 data from March 13, 2020 to April 26, 2022, for the counties of Montana, USA. We present three views of the data set decomposed with Archetypal Analysis. First, we evaluate the entire 56 county data set. Second, we use a mutual information calculation to remove counties whose dynamics are mainly independent from the other counties, reducing the set to 17 counties. Finally, we analyze the top ten counties in terms of population size to focus on the dynamics in the large cities in the state. For each data set, we analyze four significant disease outbreaks across Montana. Archetypal Analysis uncovers distinct spatial patterns for each outbreak and demonstrates that each has a unique trajectory across the state.
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Project description:ObjectivesSome studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates.MethodsUsing data from COVID-NET population-based surveillance reported during March 1-April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata.ResultsAmong 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1-156.1) in census tracts with >15.2%-83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9-78.1) in census tracts with 0%-4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3-128.2), 252.2 (95% CI: 241.4-263.0), and 341.1 (95% CI: 317.3-365.0), respectively, compared with 58.2 (95% CI: 55.4-61.1), 304.0 (95%: 282.4-325.6), and 540.3 (95% CI: 477.0-603.6), respectively, in low-poverty census tracts.ConclusionsOverall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.
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Project description:The coronavirus disease 2019 (COVID-19) pandemic has resulted in substantial morbidity and mortality since it was first described in December 2019 (1). Based on epidemiologic data showing spread in congregate settings (2-4), national, state, and local governments instituted significant restrictions on large gatherings to prevent transmission of disease in early March 2020. This and other nonpharmaceutical interventions (NPIs) have shown initial success in slowing the pandemic across the country (5). This report examines the first 7 weeks (March 1-April 18) of implementation of NPIs in Basic Military Training (BMT) at a U.S. Air Force base. In a population of 10,579 trainees, COVID-19 incidence was limited to five cases (47 per 100,000 persons), three of which were in persons who were contacts of the first patient. Transmission of symptomatic COVID-19 was successfully limited using strategies of quarantine, social distancing, early screening of trainees, rapid isolation of persons with suspected cases, and monitored reentry into training for trainees with positive test results after resolution of symptoms.
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Project description:The study compares empirical results on the coronavirus SARS-CoV-2 (causing COVID-19) fatality risk perception of US adult residents stratified for age, gender, and race in mid-March 2020 (N1 = 1,182) and mid-April 2020 (N2 = 953). While the fatality risk perception has increased from March 2020 to April 2020, our findings suggest that many US adult residents severely underestimated their absolute and relative fatality risk (i.e., differentiated for subgroups defined by pre-existing medical conditions and age) at both time points compared to current epidemiological figures. These results are worrying because risk perception, as our study indicates, relates to actual or intended health-protective behaviour that can reduce SARS-CoV-2 transmission rates.
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