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1.
Preprint in English | medRxiv | ID: ppmedrxiv-20163931

ABSTRACT

ObjectiveTo utilize publicly reported, state-level data to identify factors associated with the frequency of cases, tests, and mortality in the US. Materials & MethodsRetrospective study using publicly reported data collected included the number of COVID-19 cases, tests, and mortality from March 14th through April 30th, 2020. Publicly available state-level data was collected which included: demographics comorbidities, state characteristics and environmental factors. Univariate and multivariate regression analyses were performed to identify the significantly associated factors with percent mortality, case and testing frequency. All analyses were state-level analyses and not patient-level analyses. ResultsA total of 1,090,500 COVID-19 cases were reported during the study period. The calculated case and testing frequency were 3,332 and 19,193 per 1,000,000 patients. There were 63,642 deaths during this period which resulted in a mortality of 5.8%. Factors including to but not limited to population density (beta coefficient 7.5, p< 0.01), transportation volume (beta coefficient 0.1, p< 0.01), tourism index (beta coefficient -0.1, p=0.02) and older age (beta coefficient 0.2, p=0.01) are associated with case frequency and percent mortality. ConclusionsThere were wide variations in testing and case frequencies of COVID-19 among different states in the US. States with higher population density had a higher case and testing rate. States with larger population of elderly and higher tourism had a higher mortality. Key MessagesThere were wide variations in testing and case frequencies of COVID-19 among different states in the US. States with higher population density had a higher case and testing rate. States with larger population of elderly and higher tourism had a higher mortality.

2.
Preprint in English | medRxiv | ID: ppmedrxiv-20160226

ABSTRACT

IntroductionIntensive care has played a pivotal role during the COVID-19 pandemic as many patients developed severe pulmonary complications. The availability of information in pediatric intensive care (PICUs) remains limited. The purpose of this study is to characterize COVID-19 positive admissions (CPAs) in the United States and to determine factors that may impact those admissions. Materials and MethodsThis is a retrospective cohort study using data from the COVID-19 dashboard virtual pediatric system containing information regarding respiratory support and comorbidities for all CPAs between March and April 2020. The state level data contained 13 different factors from population density, comorbid conditions and social distancing score. The absolute CPAs count was converted to frequency using the states population. Univariate and multivariate regression analyses were performed to assess the association between CPAs frequency and endpoints. ResultsA total of 205 CPAs were reported by 167 PICUs across 48 states. The estimated CPAs frequency was 2.8 per million children. A total of 3,235 tests were conducted with 6.3% positive tests. Children above 11 years of age comprised 69.7% of the total cohort and 35.1% had moderated or severe comorbidities. The median duration of a CPA was 4.9 days [1.25-12.00 days]. Out of the 1,132 total CPA days, 592 [52.2%] were for mechanical ventilation. The inpatient mortalities were 3 [1.4%]. Multivariate analyses demonstrated an association between CPAs with greater population density [beta-coefficient 0.01, p<0.01] and increased percent of children receiving the influenza vaccination [beta-coefficient 0.17, p=0.01]. ConclusionsInpatient mortality during PICU CPAs is relatively low at 1.4%. CPA frequency seems to be impacted by population density while characteristics of illness severity appear to be associated with ultraviolet index, temperature, and comorbidities such as Type 1 diabetes. These factors should be included in future studies using patient-level data.

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