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Early Detection and Assessment of Covid-19.

ABSTRACT

Since the Covid-19 global pandemic emerged, developing countries have been facing multiple challenges over its diagnosis. We aimed to establish a relationship between the signs and symptoms of COVID-19 for early detection and assessment to reduce the transmission rate of SARS-Cov-2. We collected published data on the clinical features of Covid-19 retrospectively and categorized them into physical and blood biomarkers. Common features were assigned scores by the Borg scoring method with slight modifications and were incorporated into a newly-developed Hashmi-Asif Covid-19 assessment Chart. Correlations between signs and symptoms with the development of Covid-19 was assessed by Pearson correlation and Spearman Correlation coefficient (rho). Linear regression analysis was employed to assess the highest correlating features. The frequency of signs and symptoms in developing Covid-19 was assessed through Chi-square test two tailed with Cramer's V strength. Changes in signs and symptoms were incorporated into a chart that consisted of four tiers representing disease stages. Data from 10,172 Covid-19 laboratory confirmed cases showed a correlation with Fever in 43.9% ( = 0.000) cases, cough 54.08% and dry mucus 25.68% equally significant ( = 0.000), Hyperemic pharyngeal mucus membrane 17.92% ( = 0.005), leukopenia 28.11% ( = 0.000), lymphopenia 64.35% ( = 0.000), thrombopenia 35.49% ( = 0.000), elevated Alanine aminotransferase 50.02% ( = 0.000), and Aspartate aminotransferase 34.49% ( = 0.000). The chart exhibited a maximum scoring of 39. Normal tier scoring was ≤ 12/39, mild state scoring was 13-22/39, and star values scoring was ≥7/15; this latter category on the chart means Covid-19 is progressing and quarantine should be adopted. Moderate stage scored 23-33 and severe scored 34-39 in the chart. The Hashmi-Asif Covid-19 Chart is significant in assessing subclinical and clinical stages of Covid-19 to reduce the transmission rate. Copyright © 2020 Hashmi and Asif.