Cross-sectional study for COVID-19-related mortality predictors in a Brazilian state-wide landscape: the role of demographic factors, symptoms and comorbidities.

OBJECTIVE: The Brazilian state of Paraná has suffered from COVID-19 effects, understanding predictors of increased mortality in health system interventions prevent hospitalisation of patients. We selected the best models to evaluate the association of death with demographic characteristics, symptoms and comorbidities based on three levels of clinical severity for COVID-19: non-hospitalised, hospitalised non-ICU ward and ICU ward. DESIGN: Cross-sectional survey using binomial mixed models. SETTING: COVID-19-positive cases diagnosed by reverse transcription-PCR of municipalities located in Paraná State. PATIENTS: Cases of anonymous datasets of electronic medical records from 1 April 2020 to 31 December 2020. PRIMARY AND SECONDARY OUTCOME MEASURES: The best prediction factors were chosen based on criteria after a stepwise analysis using multicollinearity measure, lower Akaike information criterion and goodness-of-fit χ2 tests from univariate to multivariate contexts. RESULTS: Male sex was associated with increased mortality among non-hospitalised patients (OR 1.76, 95% CI 1.47 to 2.11) and non-ICU patients (OR 1.22, 95% CI 1.05 to 1.43) for symptoms and for comorbidities (OR 1.89, 95% CI 1.59 to 2.25, and OR 1.30, 95% CI 1.11 to 1.52, respectively). Higher mortality occurred in patients older than 35 years in non-hospitalised (for symptoms: OR 4.05, 95% CI 1.55 to 10.54; and for comorbidities: OR 3.00, 95% CI 1.24 to 7.27) and in hospitalised over 40 years (for symptoms: OR 2.72, 95% CI 1.08 to 6.87; and for comorbidities: OR 2.66, 95% CI 1.22 to 5.79). Dyspnoea was associated with increased mortality in non-hospitalised (OR 4.14, 95% CI 3.45 to 4.96), non-ICU (OR 2.41, 95% CI 2.04 to 2.84) and ICU (OR 1.38, 95% CI 1.10 to 1.72) patients. Neurological disorders (OR 2.16, 95% CI 1.35 to 3.46), neoplastic (OR 3.22, 95% CI 1.75 to 5.93) and kidney diseases (OR 2.13, 95% CI 1.36 to 3.35) showed the majority of increased mortality for ICU as well in the three levels of severity jointly with heart disease, diabetes and CPOD. CONCLUSIONS: These findings highlight the importance of the predictor's assessment for the implementation of public healthcare policy in response to the COVID-19 pandemic, mainly to understand how non-pharmaceutical measures could mitigate the virus impact over the population.

COVID-19: The question of genetic diversity and therapeutic intervention approaches.

Coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), is the largest pandemic in modern history with very high infection rates and considerable mortality. The disease, which emerged in China's Wuhan province, had its first reported case on December 29, 2019, and spread rapidly worldwide. On March 11, 2020, the World Health Organization (WHO) declared the COVID-19 outbreak a pandemic and global health emergency. Since the outbreak, efforts to develop COVID-19 vaccines, engineer new drugs, and evaluate existing ones for drug repurposing have been intensively undertaken to find ways to control this pandemic. COVID-19 therapeutic strategies aim to impair molecular pathways involved in the virus entrance and replication or interfere in the patients' overreaction and immunopathology. Moreover, nanotechnology could be an approach to boost the activity of new drugs. Several COVID-19 vaccine candidates have received emergency-use or full authorization in one or more countries, and others are being developed and tested. This review assesses the different strategies currently proposed to control COVID-19 and the issues or limitations imposed on some approaches by the human and viral genetic variability.