The CHILD sample and data repository is a tremendous current and future resource and will provide a wealth of information not only informing studies of asthma and allergy, but also potentially in many other aspects of health relevant for Canadian infants and children.
Background: Black populations in the United States are being disproportionately affected by the COVID-19 pandemic, but the increased mortality burden after accounting for health and other demographic characteristics is not well understood. We examined characteristics of individuals who died from COVID-19 in Michigan by race stratified by their age, sex and comorbidity prevalence to illustrate and understand this disparity in mortality risk. Methods: We evaluate COVID-19 mortality in Michigan by demographic and health characteristics, using individual-level linked death certificate and surveillance data collected by the Michigan Department of Health and Human Services from March 16 to October 26, 2020. We identified differences in demographics and comorbidity prevalence across race among individuals who died from COVID-19 and calculated mortality rates by age, sex, race, and number of comorbidities. Findings: Among the 6,065 COVID-19 related deaths in Michigan, Black individuals are experiencing 3¢6 times the mortality rate of White individuals (p<0.001), with a mortality rate for Black individuals under 65 years without comorbidities that is 12¢6 times that of their White counterparts (p<0.001). After accounting for age, race, sex, and number of comorbidities, we find that Black individuals in all strata are at higher risk of COVID-19 mortality than their White counterparts. Interpretation: Our findings demonstrate that Black populations are disproportionately burdened by COVID-19 mortality, even after accounting for demographic and underlying health characteristics. We highlight how disparities across race, which result from systemic racism, are compounded in crises.
BackgroundDeath records are a rich source of data, which can be used to assist with public surveillance and/or decision support. However, to use this type of data for such purposes it has to be transformed into a coded format to make it computable. Because the cause of death in the certificates is reported as free text, encoding the data is currently the single largest barrier of using death certificates for surveillance. Therefore, the purpose of this study was to demonstrate the feasibility of using a pipeline, composed of a detection rule and a natural language processor, for the real time encoding of death certificates using the identification of pneumonia and influenza cases as an example and demonstrating that its accuracy is comparable to existing methods.ResultsA Death Certificates Pipeline (DCP) was developed to automatically code death certificates and identify pneumonia and influenza cases. The pipeline used MetaMap to code death certificates from the Utah Department of Health for the year 2008. The output of MetaMap was then accessed by detection rules which flagged pneumonia and influenza cases based on the Centers of Disease and Control and Prevention (CDC) case definition. The output from the DCP was compared with the current method used by the CDC and with a keyword search. Recall, precision, positive predictive value and F-measure with respect to the CDC method were calculated for the two other methods considered here. The two different techniques compared here with the CDC method showed the following recall/ precision results: DCP: 0.998/0.98 and keyword searching: 0.96/0.96. The F-measure were 0.99 and 0.96 respectively (DCP and keyword searching). Both the keyword and the DCP can run in interactive form with modest computer resources, but DCP showed superior performance.ConclusionThe pipeline proposed here for coding death certificates and the detection of cases is feasible and can be extended to other conditions. This method provides an alternative that allows for coding free-text death certificates in real time that may increase its utilization not only in the public health domain but also for biomedical researchers and developers.Trial RegistrationThis study did not involved any clinical trials.
Identities represented in birth certificates change over time. Specific events that cause changes to birth certificates also fluctuate over time. Understanding these changes can help in the development of automated strategies to improve identity resolution.
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