Background Patients with coronavirus disease-2019 (COVID-19) with preexisting diabetes and cardiovascular metabolic diseases have higher fatality rate. The circulation of new variants with emerging clinical characteristics requires more studies focusing the impact of preexisting health conditions on outcome of COVID-19 accurately. Aims Main aim of this study was to investigate the impact of diabetes and cardiovascular disease (CVD) on disease prognosis and severe health outcomes among patients with COVID-19. Methods A retrospective study was performed on 799 patients with COVID-19 during December 10, 2020, to February 10, 2020 in Bangladesh. Logistic regression analysis was performed for age, sex, diabetes, CVD and symptoms on fatality. Kaplan-Meier survival analysis was conducted to predict the survival rate. Results Fatality was detected in 40% (318 of 799) patients with COVID-19. Among 318 fatalities, 90.6% were detected in patients with CVD and 74.5% in patients with diabetes. Case fatality rate was highest in patients with COVID-19, CVD and diabetes (94, 184 of 195). Fever (91%) and dry cough (71%) were the most frequent symptoms. CVD (42.2%), diabetes (32.7%) and obesity (18%) were prevalent. The highest odds of risk was detected in patients with COVID-19, CVD and diabetes (OR: 6.98, 95% CI, 4.21 to 7.34). Female patients had the highest survival rate. Conclusions In this study, 318 fatality was seen in 799 patients with COVID-19. The highest odds of fatality risk was detected in patients with COVID-19, CVD and diabetes. The risk increased many folds when CVD and diabetes coexisted in patients.

Background Socio-demographics and comorbidities are involved in determining the severity and fatality in patients with COVID-19 suggested by studies in various countries, but study in Bangladesh is insufficient. Aims We designed the study to evaluate the association of sociodemographic and comorbidities with the prognosis of adverse health outcomes in patients with COVID-19 in Bangladesh. Methods A multivariate retrospective cohort study was conducted on data from 966 RT-PCR positive patients from eight divisions during December 13, 2020, to February 13, 2021. Variables included sociodemographic, comorbidities, symptoms, Charlson comorbidity index (CCI) and access to health facilities. Major outcome was fatality. Secondary outcomes included hospitalization, duration of hospital stay, requirement of mechanical ventilation and severity. Results Male (65.8%, 636 of 966) was predominant and mean age was 39.8 ± 12.6 years. Fever (79%), dry cough (55%), and loss of test/smell (51%) were frequent and 74% patients had >3 symptoms. Fatality was recorded in 10.5% patients. Comorbidities were found in 44% patients. Hypertension (21.5%) diabetes (14.6%), and cardiovascular diseases (11.3%) were most prevalent. Age >60 years (OR: 4.83, 95% CI: 2.45–6.49), and CCI >3 (OR: 5.48, 95% CI: 3.95–7.24) were predictors of hospitalizations. CCI >4 (aOR: 3.41, 95% CI: 2.57–6.09) was predictor of severity. Age >60 years (aOR: 3.77, 95% CI: 1.07–6.34), >3 symptoms (aOR: 2.14, 95% CI: 0.97–4.91) and CCI >3 vs. CCI <3 (aOR: 5.23, 95% CI: 3.77–8.09) were independently associated with fatality. Conclusions Increased age, >3 symptoms, increasing comorbidities, higher CCI were associated with increased hospitalization, severity and fatality in patients with COVID-19.

Coronavirus disease 2019 (COVID-19) pandemic has become a major public health issue globally. Preventive health measures against COVID-19 can reduce the health burden significantly by containing the transmission. A few research have been undertaken on the effectiveness of preventive strategies such as mask use, hand washing, and keeping social distance in preventing COVID-19 transmission. The main aim of this study was to determine the association of the preventive measures with the reduction of transmission of COVID-19 among people. Data was collected during January 06, 2021 to May 10, 2021 from 1690 participants in Bangladesh. A validated questionnaire was used to collect both the online and offline data. Chi-square test and logistic regression analyses were performed to determine the association among the variables. The prevalence of COVID-19 was 11.5% (195 of 1690) among the population. Age, gender, occupation and monthly income of the participants were significantly associated with the likelihood of following the preventive measures. The risk of infection and death reduced significantly among the participants following preventive measures (p = .001). The odds of incidence was lower among the participants using masks properly (OR: 0.02, 95% CI: 0.01–0.43), maintaining social distances (OR: 0.04, 95% CI: 0.01–0.33), avoiding crowded places (OR: 0.07, 95% CI: 0.02–0.19) and hand shaking (OR: 0.17, 95% CI: 0.09–0.41). This study suggests that preventive health measures are significantly associated with the reduction of the risk of infection of COVID-19. Findings from this study will help the policymakers to take appropriate steps to curb the health burden of COVID-19.

Although vaccines have become available, emergence and rapid transmission of new variants have added new paradigm in the coronavirus disease-2019 (COVID-19) pandemic. Weather, population and host immunity have been detected as the regulatory elements of COVID-19. This study aims to investigate the effects of weather, population and host factors on the outcome of COVID-19 and mutation frequency in Japan. Data were collected during January 2020 to February 2021. About 92% isolates were form GR clades. Variants 501Y.V1 (53%) and 452R.V1 (24%) were most prevalent in Japan. The strongest correlation was detected between fatalities and population density (rs = 0.81) followed by total population (rs = 0.72). Relative humidity had the highest correlation (rs = −0.71) with the case fatality rate. Cluster mutations namely N501Y (45%), E484K (30%), N439K (16%), K417N (6%) and T478I (3%) at spike protein have increased during January to February 2021. Above 90% fatality was detected in patients aged >60 years. The ratio of male to female patients of COVID-19 was 1.35:1. This study will help to understand the seasonality of COVID-19 and impact of weather on the outcome which will add knowledge to reduce the health burden of COVID-19 by the international organisations and policy makers.

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