RESUMO
The transmission of the contagious COVID-19 is known to be highly dependent on individual viral dynamics. Since the cycle threshold (Ct) is the only semi-quantitative viral measurement that could reflect infectivity, we utilized Ct values to forecast COVID-19 incidences. Our COVID-19 cohort (n=9531), retrieved from a single representative cross-sectional virology test center in Lebanon, revealed that low daily mean Ct values are followed by an increase in the number of national positive COVID-19 cases. A subset of the data was used to develop a deep neural network model, tune its hyperparameters, and optimize the weights for minimal mean square error of prediction. The final models accuracy is reported by comparing its predictions with an unseen dataset. Our model was the first to capture the interaction of the previously reported Ct values with the upcoming number of COVID-19 cases and any temporal effects that arise from population dynamics. Our model was deployed as a publicly available and easy-to-use estimator to facilitate prospective validation. Our model has potential application in predicting COVID-19 incidences in other countries and in assessing post-vaccination policies. Aside from emphasizing patient responsibility in adopting early testing practices, this study proposed and validated viral load measurement as a rigid input that can enhance outcomes and precision of viral disease predicting models.
RESUMO
A sudden outbreak of pneumonia caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has rapidly spread all over the world facilitating the declaration of the resultant disease as a pandemic in March,2020. In Lebanon, the fast action of announcing a state of emergency with strict measures was among the factors that helped in achieving a successful containment of the disease in the country. Predisposing factors for acquiring COVID-19 and for developing a severe form of this disease were postulated to be related to epidemiological and clinical characteristics as well as the genomics signature of a given population or its environment. Biological markers such as the ABO blood group system was amongst those factors that were proposed to be linked to the variability in the disease course and/or the prevalence of this infection among different groups. We therefore conducted the first retrospective case-control study in the Middle-East and North Africa that tackles the association between the blood group types and the susceptibility as well as the severity of SARS-CoV2 infection. Opposing to the current acknowledged hypothesis, our results have challenged the association significance of this system with COVID-19. Herein, we highlighted the importance of studying larger cohorts using more rigorous approaches to diminish the potential confounding effect of some underlying comorbidities and genetic variants that are known to be associated with the ABO blood group system.
