ABSTRACT
BACKGROUND: Diagnoses of HIV in the United States decreased by 17% in 2020 due to COVID-related disruptions. The extent to which this decrease is attributable to changes in HIV testing versus HIV transmission is unclear. We seek to better understand this issue by analyzing the discrepancy in expected versus observed HIV diagnoses in 2020 among persons who acquired HIV between 2010 and 2019 because changes in diagnosis patterns in this cohort cannot be attributed to changes in transmission. METHODS: We developed 3 methods based on the CD4-depletion model to estimate excess missed diagnoses in 2020 among persons with HIV (PWH) infected from 2010 to 2019. We stratified the results by transmission group, sex assigned at birth, race/ethnicity, and region to examine differences by group and confirm the reliability of our estimates. We performed similar analyses projecting diagnoses in 2019 among PWH infected from 2010 to 2018 to evaluate the accuracy of our methods against surveillance data. RESULTS: There were approximately 3100-3300 (approximately 18%) fewer diagnoses than expected in 2020 among PWH infected from 2010 to 2019. Females (at birth), heterosexuals, persons who inject drugs, and Hispanic/Latino PWH missed diagnoses at higher levels than the overall population. Validation and stratification analyses confirmed the accuracy and reliability of our estimates. CONCLUSIONS: The substantial drop in number of previously infected PWH diagnosed in 2020 suggests that changes in testing played a substantial role in the observed decrease. Levels of missed diagnoses differed substantially across population subgroups. Increasing testing efforts and innovative strategies to reach undiagnosed PWH are needed to offset this diagnosis gap. These analyses may be used to inform future estimates of HIV transmission during the COVID-19 pandemic.
Subject(s)
COVID-19 , Drug Users , HIV Infections , Substance Abuse, Intravenous , Female , Infant, Newborn , Humans , United States , HIV Infections/epidemiology , Pandemics , Reproducibility of Results , Substance Abuse, Intravenous/epidemiology , COVID-19/epidemiologyABSTRACT
PURPOSE: Acute phase reactants (APRs) play a critical role in inflammation. The difference in their physiological functions or the different dynamic ranges of these proteins in plasma makes it difficult to detect them simultaneously and to use several of these proteins as a tool in clinical practice. EXPERIMENTAL DESIGN: A novel multiplex assay has been designed and optimized to carry out a high-throughput and simultaneous screening of APRs, allowing the detection of each of them at the same time and in their corresponding dynamic range. RESULTS: Using Sars-CoV-2 infection as a model, it has been possible to profile different patterns of acute phase proteins that vary significantly between healthy and infected patients. In addition, severity profiles (acute respiratory distress syndrome and sepsis) have been established. CONCLUSIONS AND CLINICAL RELEVANCE: Differential profiles in acute phase proteins can serve as a diagnostic and prognostic tool, among patient stratification. The design of this new platform for their simultaneous detection paves the way for them to be more extensive use in clinical practice.
Subject(s)
Acute-Phase Proteins , Acute-Phase Reaction , COVID-19 , SARS-CoV-2 , Humans , Acute-Phase Proteins/analysis , COVID-19/blood , COVID-19/diagnosis , Proteomics , Acute-Phase Reaction/blood , Acute-Phase Reaction/diagnosis , Acute-Phase Reaction/virologyABSTRACT
Acute respiratory distress syndrome (ARDS) is a severe pulmonary disease, which is one of the major complications in COVID-19 patients. Dysregulation of the immune system and imbalances in cytokine release and immune cell activation are involved in SARS-CoV-2 infection. Here, the inflammatory, antigen, and auto-immune profile of patients presenting COVID-19-associated severe ARDS has been analyzed using functional proteomics approaches. Both, innate and humoral responses have been characterized through acute-phase protein network and auto-antibody signature. Severity and sepsis by SARS-CoV-2 emerged to be correlated with auto-immune profiles of patients and define their clinical progression, which could provide novel perspectives in therapeutics development and biomarkers of COVID-19 patients. Humoral response in COVID-19 patients' profile separates with significant differences patients with or without ARDS. Furthermore, we found that this profile can be correlated with COVID-19 severity and results more common in elderly patients.