Baseline and early changes in laboratory parameters predict disease severity and fatal outcomes in COVID-19 patients.

Introduction: Coronavirus disease 2019 (COVID-19) has become the worst catastrophe of the twenty-first century and has led to the death of more than 6.9 million individuals across the globe. Despite the growing knowledge of the clinicopathological features of COVID-19, the correlation between baseline and early changes in the laboratory parameters and the clinical outcomes of patients is not entirely understood. Methods: Here, we conducted a time series cross-sectional study aimed at assessing different measured parameters and socio-demographic factors that are associated with disease severity and the outcome of the disease in 268 PCR-confirmed COVID-19 Patients. Results: We found COVID-19 patients who died had a median age of 61 years (IQR, 50 y - 70 y), which is significantly higher (p < 0.05) compared to those who survived and had a median age of 54 years (IQR, 42y - 65y). The median RBC count of COVID-19 survivors was 4.9 × 106/µL (IQR 4.3 × 106/µL - 5.2 × 106/µL) which is higher (p < 0.05) compared to those who died 4.4 × 106/µL (3.82 × 106/µL - 5.02 × 106/µL). Similarly, COVID-19 survivors had significantly (p < 0.05) higher lymphocyte and monocyte percentages compared to those who died. One important result we found was that COVID-19 patients who presented with severe/critical cases at the time of first admission but managed to survive had a lower percentage of neutrophil, neutrophil to lymphocyte ratio, higher lymphocyte and monocyte percentages, and RBC count compared to those who died. Conclusion: To conclude here, we showed that simple laboratory parameters can be used to predict severity and outcome in COVID-19 patients. As these parameters are simple, inexpensive, and radially available in most resource-limited countries, they can be extrapolated to future viral epidemics or pandemics to allocate resources to particular patients.

COVID-19 Preventive Practices among Bus Station Workers in Ethiopia.

As of May 19, 2021, Ethiopia was among the five African countries most affected by COVID-19. A cross-sectional design was used to assess the level of knowledge, perceptions, and practices of bus station workers about COVID-19 between August 25 and September 17, 2020. Face-to-face interviewer-administered questionnaires were used. To identify the factors associated with the dependent variables, simple and multiple binary logistic regression analyses were used. A P value < 0.05 was considered significant. Data were analyzed using SPSS version 20 software. In this study, 427 workers from three bus stations participated. Approximately 84.5%, 84.8%, and 81.3% of the workers had good knowledge, positive perceptions, and good practices, respectively. Multivariable logistic regression analysis showed that workers with a monthly income of 3,001 to 4,000 birr were about four times more likely to have poor knowledge compared with higher income workers. Those workers with poor knowledge were 2.4 times, and security workers were 3.7 times, more likely to have poor practices compared with workers with good knowledge and drivers, respectively. In conclusion, workers used in security and those who had poor knowledge regarding COVID-19 failed to exhibit effective preventative practices against the virus.