Estimating the all-cause excess mortalities due to COVID-19 UChicagoLaw COVID19 Pandemic SARSCoV2 mortalities
By Bhavana KunkalikarOct 12 2022Reviewed by Aimee Molineux In a recent study published in the Journal of Development Economics, researchers estimated all-cause excess death rates due to the coronavirus disease 2019 pandemic.
The main source of data for the study was the Consumer Pyramids Household Survey , which was a sizable and representative survey of Indian households conducted by the Center for Monitoring the Indian Economy. A collection of comparable districts inside a state is known as a homogenous region. Every round, which consists of four month periods, sample homes were visited. However, each month, a subsample of households typical of the entire country is sampled.
Results Related StoriesThe death rate appeared to have increased during the COVID-19 pandemic, according to CPHS raw data that was aggregated on the national level. Death rates increased significantly during the first wave, slightly less during the second wave, and barely during the third wave. However, the significant increase in wave one was partially attributable to homes that were left out of the poll during the lockdown reporting deaths afterward.
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Elevated vascular transformation blood biomarkers in Long-COVID indicate angiogenesis as a key pathophysiological mechanism - Molecular MedicineBackground Long-COVID is characterized by prolonged, diffuse symptoms months after acute COVID-19. Accurate diagnosis and targeted therapies for Long-COVID are lacking. We investigated vascular transformation biomarkers in Long-COVID patients. Methods A case–control study utilizing Long-COVID patients, one to six months (median 98.5 days) post-infection, with multiplex immunoassay measurement of sixteen blood biomarkers of vascular transformation, including ANG-1, P-SEL, MMP-1, VE-Cad, Syn-1, Endoglin, PECAM-1, VEGF-A, ICAM-1, VLA-4, E-SEL, thrombomodulin, VEGF-R2, VEGF-R3, VCAM-1 and VEGF-D. Results Fourteen vasculature transformation blood biomarkers were significantly elevated in Long-COVID outpatients, versus acutely ill COVID-19 inpatients and healthy controls subjects (P | 0.05). A unique two biomarker profile consisting of ANG-1/P-SEL was developed with machine learning, providing a classification accuracy for Long-COVID status of 96%. Individually, ANG-1 and P-SEL had excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, P | 0.0001; validated in a secondary cohort). Specific to Long-COVID, ANG-1 levels were associated with female sex and a lack of disease interventions at follow-up (P | 0.05). Conclusions Long-COVID patients suffer prolonged, diffuse symptoms and poorer health. Vascular transformation blood biomarkers were significantly elevated in Long-COVID, with angiogenesis markers (ANG-1/P-SEL) providing classification accuracy of 96%. Vascular transformation blood biomarkers hold potential for diagnostics, and modulators of angiogenesis may have therapeutic efficacy.
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