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COVID-19 among Minority Children in Detroit, Michigan during the Early National Surge of the Pandemic.

ABSTRACT: Background. The COVID-19 pandemic has shed light on communities of racial/ethnic minority groups in the US where long-standing health issues and structural inequities are now known to have resulted in increased risk for infection, severe illness, and death from the virus. The objective of our study was to describe demographic characteristics, clinical presentations, medical interventions and outcomes of pediatric patients with COVID-19 treated at Children's Hospital of Michigan (CHM), a tertiary care center in urban Detroit, an early hotspot during the initial surge of the SARS-CoV-2 pandemic. Methods. A retrospective chart review was performed of children ≤18 years of age who had polymerase chain reaction (RT-PCR) testing via NP swab or serum IgG antibody testing for SARS-CoV-2 during March 1, 2020-June 30, 2020. Results. Seventy-eight COVID-19 infected children were identified of whom 85.8% (67/78) were from minority populations (African American, Hispanic). Hospitalization rate was 82% (64/78). About 44% (34/78) had an associated comorbidity with asthma and obesity being most common. Although all ages were affected, infants <1 year of age had the highest hospitalization rate (19/64, 30%). In all disease severity categories, dichotomized non-whites had more severe disease by percentage within race/ethnicity than Whites, and also within percent disease severity (P-value = .197). Overall, 37% of hospitalized patients required intensive care. Conclusions. Extremely high rates of COVID-19 hospitalization and requirement of ICU care were identified in our patient population. Further studies are needed to better understand the contributing factors to this health disparity in disadvantaged communities.

SUBMITTER: Ang JY

PROVIDER: S-EPMC8170283 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Wastewater-based epidemiology (WBE) is useful in predicting temporal fluctuations of COVID-19 incidence in communities and providing early warnings of pending outbreaks. To investigate the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in communities, a 12-month study between September 1, 2020, and August 31, 2021, prior to the Omicron surge, was conducted. 407 untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) in southeastern Michigan. N1 and N2 genes of SARS-CoV-2 were quantified using RT-ddPCR. Daily confirmed COVID-19 cases for the City of Detroit, and Wayne, Macomb, Oakland counties between September 1, 2020, and October 4, 2021, were collected from a public data source. The total concentrations of N1 and N2 genes ranged from 714.85 to 7145.98 gc/L and 820.47 to 6219.05 gc/L, respectively, which were strongly correlated with the 7-day moving average of total daily COVID-19 cases in the associated areas, after 5 weeks of the viral measurement. The results indicate a potential 5-week lag time of wastewater surveillance preceding COVID-19 incidence for the Detroit metropolitan area. Four statistical models were established to analyze the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in the study areas. Under a 5-week lag time scenario with both N1 and N2 genes, the autoregression model with seasonal patterns and vector autoregression model were more effective in predicting COVID-19 cases during the study period. To investigate the impact of flow parameters on the correlation, the original N1 and N2 gene concentrations were normalized by wastewater flow parameters. The statistical results indicated the optimum models were consistent for both normalized and non-normalized data. In addition, we discussed parameters that explain the observed lag time. Furthermore, we evaluated the impact of the omicron surge that followed, and the impact of different sampling methods on the estimation of lag time.

Project description:BackgroundQuarantine and isolation measures during COVID-19 pandemic may have caused additional stress and challenged the mental health of the youth. Aim of the study is to investigate the COVID-19 pandemic impact on neuropsychological disorders (NPD) of Italian children and adolescents to provide general pediatric recommendations.Material and methodsA retrospective multicenter observational study was planned by the Italian Pediatric Society (SIP) to explore the impact of COVID-19 on the access of children to pediatric Emergency Departments (pED) for the evaluation of neuropsychological symptoms, collecting the classification codes of diagnoses between March 1, 2019 and March 2, 2021. The period study was split into two sub-periods: a pre COVID-19 period (from March 1 2019 to March 1, 2020) and a COVID-19 period (from March 2, 2020 to March 2, 2021). As additional information, data on NPD hospitalizations in any pediatric department of the involved centers were recorded.ResultsDuring the study period, a total of 533,318 children were admitted to the pED involved in the study. Despite a 48.2% decline of pED admissions, there was a significant increase (83.1%) in patient admissions for NPD. The most frequent NPD conditions which increased during the COVID-19 pandemic were suicidal ideation (+ 147%), depression (+ 115%), eating disorder (+ 78.4%), and psychosis (+ 17.2%). During the pandemic period, a 39.5% increase in NPD hospitalizations was observed as well. The NPD disorders that mostly required hospitalizations were suicidal ideation (+ 134%), depression (+ 41.4%), eating disorder (+ 31.4%), and drug abuse (+ 26.7%). COVID-19 pandemic had a major impact on children's health, mainly on their NPD development. Neuropsychological assessment should be required at the primary level, in the pediatrician's office, to facilitate early capture of the sign of impairment and provide an adequate treatment.ConclusionSIP underlines the psychological consequences of COVID 19 pandemic on the youngest and recommends an early identification of NPD in the pediatric population to avoid other serious consequences for children's physical and mental health.

Project description:Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.

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COVID-19 among Minority Children in Detroit, Michigan during the Early National Surge of the Pandemic.

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