Environmental correlation and epidemiologic analysis of COVID-19 pandemic in ten regions in five continents

COVID 19: Prevention and treatment through the Indian perspective

The most destructive period the world has experienced seems to be behind us. Not a single nation was spared by this disease, and many continue to struggle today. Even after recovering from COVID, patient may continue to experience some post-COVID effects, such as heart irregularities or a decline in lung vitality. In the past three years (2019-2022), the world has witnessed the power of a small entity, a single peculiar virus. Science initially appeared to be helpless in this regard, but due to the emergence of disease, pharmaceutics (the development of anti-covid drugs), immunology (the rapid antigen test), microbiology (the isolation of viruses from infected people), biotechnology (the development of recombinant vaccines), biochemistry (the blood profile, the D-dimer test), and biochemistry (blood profile, D-dimer test), biophysics (PCR, RT-PCR, CT Scan, MRI) had worked together to fight the disease. The results of these efforts are the development of new diagnostic techniques, possible treatment and finally the availability of vaccines against COVID-19. However, it is not proven that the treatment through the traditional medical system is directly active on SARS-CoV-2 but is instead indirectly acting on SARS-CoV-2 effects by improving symptoms derived from the viral disease. In India, the traditional system of medicine and tradition knowledge together worked in the pandemic and proved effective strategies in prevention and treatment of SARS-CoV-2. The use of effective masks, PPE kits, plasma therapy, yoga, lockdowns and social seclusion, use of modern antiviral drugs, monoclonal antibodies, herbal remedies, homoeopathy, hygienic practice, as well as the willpower of people, are all contributing to the fight against COVID. Which methods or practices will be effective against COVID nobody is aware since medical professionals who wear PPE kits do not live longer, and some people in India who remained unprotected and roamed freely were not susceptible to infection. The focus of this review is on the mode of transmission, diagnosis, preventive measures, vaccines currently under development, modern medicine developed against SARS-CoV-2, ayurvedic medicine used during pandemic, homoeopathic medicine used during pandemic, and specific yoga poses that can be used to lessen COVID-related symptoms.

Impact of continuous labor companion- who is the best: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Continuous labor support is widely acknowledged for potentially enhancing maternal and neonatal outcomes, the physiological labor process, and maternal satisfaction with the labor experience. However, the existing literature lacks a comprehensive analysis of the optimal characteristics of labor companions, particularly in comparing the effects of trained versus untrained and familiar versus unfamiliar labor companions across diverse geographical regions, both pre-and post-millennial. This meta-analysis addresses these research gaps by providing insights into the most influential aspects of continuous labor support.

METHODOLOGY

A thorough search of PubMed, Google Scholar, Science Direct, International Clinical Trials Registry Platform (ICTRP), ClinicalTrials.gov, Research4Life, and Cochrane Library was conducted from 25/06/2023 to 04/07/2023. Study selection utilized the semi-automated tool Rayyan. The original version of the Cochrane Risk of Bias tool was used to assess the quality of Randomized Controlled Trials (RCTs) while funnel plots gauged the publication bias. Statistical analysis employed RevMan 5.4, using Mantel-Haenszel statistics and random effects models to calculate risk ratios with 95% confidence intervals. Subgroup analyses were performed for different characteristics, including familiarity, training, temporal associations, and geographical locations. The study was registered in INPLASY (Registration number: INPLASY202410003).

RESULTS

Thirty-five RCTs were identified from 5,346 studies. The meta-analysis highlighted significant positive effects of continuous labor support across various outcomes. The highest overall effect without subgroup divisions was the improvement reported in the 5-minute Apgar score < 7, with an effect size of 1.52 (95% Confidence Interval (CI) 1.05, 2.20). Familiar labor companions were better at reducing tocophobia, with an effect size of 1.73 (95% CI 1.49, 2.42), compared to unfamiliar companions, with an effect size of 1.34 (95% CI 1.14, 1.58). Untrained labor companions were the better choice in reducing tocophobia and the cesarean section rate compared to trained companions. For the analysis of tocophobia, the pooled effect sizes were 1.34 (95% CI 1.14, 1.57) and 1.84(95% CI 1.60, 2.12) in trained versus untrained subgroup comparisons. For the cesarean rate, they were represented as 1.22 (95% CI 1.05, 1.42) and 2.16 (95% CI 1.37, 3.40), respectively. The pooled effect size for the duration of labor was 0.16 (95% CI 0.06, 0.26) for the subgroup of RCTs conducted before 2000 and 0.53 (95% CI 0.30, 0.77) for the subgroup of RCTs conducted after 2000. A significant subgroup difference (<0.1) was found in relation to the duration of labor, cesarean section rate, oxytocin for labor induction, analgesic usage, and tocophobia in the subgroup analysis of geographical regions.

DISCUSSION AND CONCLUSION

The beneficial effects of a labor companion are well-established in the literature. However, studies systematically assessing the characteristics of labor companions for optimal beneficial effects are lacking. The current study provides insights into the familiarity, training, temporal association, and geographical settings of labor companions, highlighting the differing impact of these characteristics on measured outcomes by evaluating the current randomized controlled trials on the topic. There is insufficient evidence to define the 'best labor companion' owing to the heterogeneity of labor companions and outcome assessment across different studies. We encourage well-designed further research to fill the research gap.

Influence of Environmental Factors and Genome Diversity on Cumulative COVID-19 Cases in the Highland Region of China: Comparative Correlational Study

BACKGROUND

The novel coronavirus SARS-CoV-2 caused the global COVID-19 pandemic. Emerging reports support lower mortality and reduced case numbers in highland areas; however, comparative studies on the cumulative impact of environmental factors and viral genetic diversity on COVID-19 infection rates have not been performed to date.

OBJECTIVE

The aims of this study were to determine the difference in COVID-19 infection rates between high and low altitudes, and to explore whether the difference in the pandemic trend in the high-altitude region of China compared to that of the lowlands is influenced by environmental factors, population density, and biological mechanisms.

METHODS

We examined the correlation between population density and COVID-19 cases through linear regression. A zero-shot model was applied to identify possible factors correlated to COVID-19 infection. We further analyzed the correlation of meteorological and air quality factors with infection cases using the Spearman correlation coefficient. Mixed-effects multiple linear regression was applied to evaluate the associations between selected factors and COVID-19 cases adjusting for covariates. Lastly, the relationship between environmental factors and mutation frequency was evaluated using the same correlation techniques mentioned above.

RESULTS

Among the 24,826 confirmed COVID-19 cases reported from 40 cities in China from January 23, 2020, to July 7, 2022, 98.4% (n=24,430) were found in the lowlands. Population density was positively correlated with COVID-19 cases in all regions (ρ=0.641, P=.003). In high-altitude areas, the number of COVID-19 cases was negatively associated with temperature, sunlight hours, and UV index (P=.003, P=.001, and P=.009, respectively) and was positively associated with wind speed (ρ=0.388, P<.001), whereas no correlation was found between meteorological factors and COVID-19 cases in the lowlands. After controlling for covariates, the mixed-effects model also showed positive associations of fine particulate matter (PM2.5) and carbon monoxide (CO) with COVID-19 cases (P=.002 and P<.001, respectively). Sequence variant analysis showed lower genetic diversity among nucleotides for each SARS-CoV-2 genome (P<.001) and three open reading frames (P<.001) in high altitudes compared to 300 sequences analyzed from low altitudes. Moreover, the frequencies of 44 nonsynonymous mutations and 32 synonymous mutations were significantly different between the high- and low-altitude groups (P<.001, mutation frequency>0.1). Key nonsynonymous mutations showed positive correlations with altitude, wind speed, and air pressure and showed negative correlations with temperature, UV index, and sunlight hours.

CONCLUSIONS

By comparison with the lowlands, the number of confirmed COVID-19 cases was substantially lower in high-altitude regions of China, and the population density, temperature, sunlight hours, UV index, wind speed, PM2.5, and CO influenced the cumulative pandemic trend in the highlands. The identified influence of environmental factors on SARS-CoV-2 sequence variants adds knowledge of the impact of altitude on COVID-19 infection, offering novel suggestions for preventive intervention.

Prevalence and impact of long COVID-19 among patients with diabetes and cardiovascular diseases in Bangladesh

Introduction

Co-prevalence of long-COVID-19, cardiovascular diseases and diabetes is one of the major health challenges of the pandemic worldwide. Studies on long-COVID-19 and associated health outcomes are absent in Bangladesh. The main aim of this study was to determine the prevalence and impact of long-COVID-19 on preexisting diabetes and cardiovascular diseases (CVD) on health outcomes among patients in Bangladesh.

Methods

We collected data from 3,250 participants in Bangladesh, retrospectively. Multivariable logistic regression model was used to determine the odds ratio between independent and dependent variables. Kaplan-Meier survival curve was used to determine the cumulative survival.

Results

COVID-19 was detected among 73.4% (2,385 of 3,250) participants. Acute long-COVID-19 was detected among 28.4% (678 of 2,385) and chronic long-COVID-19 among 71.6% (1,707 of 2,385) patients. CVD and diabetes were found among 32%, and 24% patients, respectively. Mortality rate was 18% (585 of 3,250) among the participants. Co-prevalence of CVD, diabetes and COVID-19 was involved in majority of fatality (95%). Fever (97%), dry cough (87%) and loss of taste and smell (85%) were the most prevalent symptoms. Patients with co-prevalence of CVD, diabetes and COVID-19 had higher risk of fatality (OR: 3.65, 95% CI, 2.79-4.24). Co-prevalence of CVD, diabetes and chronic long-COVID-19 were detected among 11.9% patients.

Discussion

Risk of hospitalization and fatality reduced significantly among the vaccinated. This is one of the early studies on long-COVID-19 in Bangladesh.

What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update

The climatological parameters can be different in various geographical locations. Moreover, they have possible impacts on COVID-19 incidence. Therefore, the purpose of this systematic review article was to describe the effects of climatic variables on COVID-19 pandemic in different countries. Systematic literature search was performed in Scopus, ISI Web of Science, and PubMed databases using ("Climate" OR "Climate Change" OR "Global Warming" OR "Global Climate Change" OR "Meteorological Parameters" OR "Temperature" OR "Precipitation" OR "Relative Humidity" OR "Wind Speed" OR "Sunshine" OR "Climate Extremes" OR "Weather Extremes") AND ("COVID" OR "Coronavirus disease 2019" OR "COVID-19" OR "SARS-CoV-2" OR "Novel Coronavirus") keywords. From 5229 articles, 424 were screened and 149 were selected for further analysis. The relationship between meteorological parameters is variable in different geographical locations. The results indicate that among the climatic indicators, the temperature is the most significant factor that influences on COVID-19 pandemic in most countries. Some studies were proved that warm and wet climates can decrease COVID-19 incidence; however, the other studies represented that warm location can be a high risk of COVID-19 incidence. It could be suggested that all climate variables such as temperature, humidity, rainfall, precipitation, solar radiation, ultraviolet index, and wind speed could cause spread of COVID-19. Thus, it is recommended that future studies will survey the role of all meteorological variables and interaction between them on COVID-19 spread in specific small areas such as cities of each country and comparison between them.

Impact of meteorological factors and population density on COVID-19 pandemic in Saudi Arabia

Transmission and increase in cases and fatalities of coronavirus disease-2019 (COVID-19) are significantly influenced by the parameters of weather, human activities and population factors. However, study gap on the seasonality of COVID-19 and impact of environmental factors on the pandemic in Saudi Arabia is present. The main aim of the study is to evaluate the impact of environment on the COVID-19 pandemic. Data were analyzed from January 2020 to July 2021. The generalized estimating equation (GEE) was used to determine the effect of environmental variables on longitudinal outcomes. Spearman's rank correlation coefficient (r_s ) was used to analyze the impact of different parameters on the outcome of the pandemic. Multiple sequence alignment was performed by using ClustalW. Vaccination and fatalities (r _s = -0.85) had the highest association followed by vaccination with cases (r _s = -0.81) and population density with the fatalities (r_s  = 0.71). The growth rate had the highest correlation with sun hours (r _s = -0.63). Isolates from variant of concern alpha and beta were detected. Most of the reference sequences in Saudi Arabia were closely related with B.1.427/429 variant. Clade GH (54%) was the most prevalent followed by O (27%), GR (9%), G (6%), and S (4%), respectively. Male to female patient ratio was 1.4:1. About 95% fatality and hospitalization were reported in patients aged >60 years. This study will create a comprehensive insight of the interaction of environmental factors and the pandemic and add knowledge on seasonality of COVID-19 in Saudi Arabia.

Climatic and Environmental Factors Influencing COVID-19 Transmission-An African Perspective

Since the outbreak of COVID-19 was decreed by the World Health Organization as a public health emergency of worldwide concern, the epidemic has drawn attention from all around the world. The disease has since spread globally in developed and developing countries. The African continent has not been spared from the pandemic; however, the low number of cases in Africa compared to developed countries has brought about more questions than answers. Africa is known to have a poor healthcare system that cannot sustain the emerging infectious disease pandemic. This study explored climatic and environmental elements influencing COVID-19 transmission in Africa. This study involved manuscripts and data that evaluated and investigated the climatic and environmental elements of COVID-19 in African countries. Only articles written in English were considered in the systematic review. Seventeen articles and one database were selected for manuscript write-ups after the review process. The findings indicated that there is evidence that suggests the influence of climatic and environmental elements on the spread of COVID-19 in the continent of Africa; however, the evidence needs more investigation in all six regions of Africa and at the country level to understand the role of weather patterns and environmental aspects in the transmission of COVID-19.

Impact of Zinc, Vitamins C and D on Disease Prognosis among Patients with COVID-19 in Bangladesh: A Cross-Sectional Study

Vitamin C, (ascorbic acid), vitamin D (cholecalciferol) and zinc (zinc sulfate monohydrate) supplements are important in immunity against coronavirus disease-2019 (COVID-19). However, a limited number of studies have been conducted on the association of vitamins and supplements with the reduced risks of COVID-19 infection. This study aims to evaluate the association of vitamins and supplements as treatment options to reduce the severity of COVID-19. Data were collected from 962 participants from 13 December 2020 to 4 February 2021. The presence of COVID-19 was confirmed by qRT-PCR. The Chi-square test and multivariate regression analyses were conducted. The ratio of uptake of vitamin C:vitamin D:zinc was 1:1:0.95. Uptake of vitamin C, vitamin D and zinc were significantly associated with the reduced risk of infection and severity of COVID-19 (OR: 0.006 (95% CI: 0.03-0.11) (p = 0.004)) and (OR: 0.03 (95% CI: 0.01-0.22) (p = 0.005)). The tendency of taking supplements was associated with the presence of infection of COVID-19 (p = 0.001), age (p = 0.02), sex (p = 0.05) and residence (p = 0.04). The duration of supplementation and medication was significantly associated with reduced hospitalization (p = 0.0001). Vitamins C, D and zinc were not significantly (p = 0.9) associated with a reduced risk of severity when taken through the diet. Hospitalization (p = 0.000001) and access to health facilities (p = 0.0097) were significantly associated with the survival period of the participants. Participants with better access to health facilities recovered early (OR: 6.21, 95% CI 1.56-24.7). This study will add knowledge in the field of treatment of COVID-19 by using vitamins and zinc supplements.

Genomic surveillance, evolution and global transmission of SARS-CoV-2 during 2019-2022

In spite of the availability of vaccine, the health burden associated with the COVID-19 pandemic continues to increase. An estimated 5 million people have died with SARS-CoV-2 infection. Analysis of evolution and genomic diversity can provide sufficient information to reduce the health burden of the pandemic. This study focused to conduct worldwide genomic surveillance. About 7.6 million genomic data were analyzed during 2019 to 2022. Multiple sequence alignment was conducted by using maximum likelihood method. Clade GK (52%) was the most predominant followed by GRY (12%), GRA (11%), GR (8%), GH (7%), G (6%), GV (3%), and O (1%), respectively. VOC Delta (66%) was the most prevalent variant followed by VOC Alpha (18%), VOC Omicron (13%), VOC Gamma (2%) and VOC Beta (1%), respectively. The frequency of point mutations including E484K, N501Y, N439K, and L452R at spike protein has increased 10%-92%. Evolutionary rate of the variants was 23.7 substitution per site per year. Substitution mutations E484K and N501Y had significant correlation with cases (r = .45, r = .23), fatalities (r = .15, r = .44) and growth rate R₀ (r = .28, r = .54). This study will help to understand the genomic diversity, evolution and the impact of the variants on the outcome of the COVID-19 pandemic.

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review

COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.

COVID-19 among staff and their family members of a healthcare research institution in Bangladesh between March 2020 and April 2021: a test-negative case-control study

OBJECTIVE

To identify factors associated with COVID-19 positivity among staff and their family members of icddr,b, a health research institute located in Bangladesh.

SETTING

Dhaka, Bangladesh.

PARTICIPANTS

A total of 4295 symptomatic people were tested for SARS-CoV-2 by reverse-transcription PCR between 19 March 2020 and 15 April 2021. Multivariable logistic regression was done to identify the factors associated with COVID-19 positivity by contrasting test positives with test negatives.

RESULT

Forty-three per cent of the participants were tested positive for SARS-CoV-2. The median age was high in positive cases (37 years vs 34 years). Among the positive cases, 97% were recovered, 2.1% had reinfections, 24 died and 41 were active cases as of 15 April 2021. Multivariable regression analysis showed that age more than 60 years (adjusted OR (aOR)=2.1, 95% CI 1.3 to 3.3; p<0.05), blood group AB (aOR=1.5, 95% CI 1.1 to 2; p<0.05), fever (aOR=3.1, 95% CI 2.6 to 3.7; p<0.05), cough (aOR=1.3, 95% CI 1.1 to 1.6; p<0.05) and anosmia (aOR=2.7, 95% CI 1.3 to 5.7; p<0.05) were significantly associated with higher odds of being COVID-19 positive when compared with participants who were tested negative.

CONCLUSIONS

The study findings suggest that older age, fever, cough and anosmia were associated with COVID-19 among the study participants.

Protective measures are associated with the reduction of transmission of COVID-19 in Bangladesh: A nationwide cross-sectional study

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.

Efficacy, Immunogenicity and Safety of COVID-19 Vaccines: A Systematic Review and Meta-Analysis

There is a significant research gap in meta-analysis on the efficacy and safety of coronavirus disease 2019 (COVID-19) vaccines. This study analyzed the efficacy of COVID-19 vaccines. Published phase I, phase II, and phase III trials analyzing safety and immunogenicity and phase III randomized clinical trials evaluating the efficacy of COVID-19 vaccines were included. We searched MEDLINE, Scopus, and The Lancet for published articles evaluating the relative reduction in COVID-19 risk after vaccination. Selected literatures were published between December 15, 2019 and May 15, 2021 on the safety, efficacy, and immunogenicity of COVID-19 vaccines. This meta-analysis included studies that confirmed cases of COVID-19 using reverse transcriptase polymerase chain reaction. This study detected 8,926 eligible research articles published on COVID-19 vaccines. Of these, 25 studies fulfilled the inclusion criteria. Among the selected articles, 19 randomized clinical trials, 2 non-randomized clinical trials, and 3 observational studies were analyzed. Seven (28%) studies were included in the meta-analysis. The efficacy of the adenovirus vector vaccine was 73% (95% CI = 69–77) and that of the messenger RNA (mRNA) vaccine was 85% (95% CI = 82–88) in participants aged ≥18 years. There are no reports of clinical trials in participants aged under 16 years. The production of neutralizing antibodies against receptor-binding domains (RBDs) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in >90% of the vaccinated samples was reported within 0–30 days of the first or the second dose of the vaccine. Pain at the injection site was the most common local symptom in people receiving mRNA vaccines (29%–85% of participants). Fever (0.2%–95%) was the most prevalent in people receiving adenovirus vector vaccines, and fatigue (8.4%–55%) was the most common side effect in people receiving the mRNA vaccines. Studies suggest that mRNA vaccines and adenovirus vector vaccines can provide moderate to high protection against COVID-19 infection in people over 18 years. Evidence of the long-term protection of the vaccines in people aged under 16 years against the multiple variants of COVID-19 are limited. This study will provide an integrated evaluation on the efficacy, safety, and immunogenicity of the COVID-19 vaccines.

The positive impact of social media on health behavior towards the COVID-19 pandemic in Bangladesh: A web-based cross-sectional study

BACKGROUND

Health information has a profound impact on developing awareness and ultimately preventing the burden of coronavirus disease-2019 (COVID-19) pandemic, but study in Bangladesh is lacking.

AIMS

Therefore, this study was conducted to investigate the impact of information from social media and television in developing health awareness among people amid the COVID-19 pandemic.

METHODS

Data was collected during December 10, 2020 to February 10, 2021 from 1808 people. Data was collected by using questionnaire about information source and their impact on COVID-19 related health measures. Pearson's correlation analyses was conducted.

RESULTS

Female (52%, 937 of 1808) was the most prevalent sex and the mean age was 24 ± 3.9 years. Most of the social media users were students (63%, 1131 of 1808). Social media (53%, 959 of 1808) and television (44%, 800 of 1808) were the most popular sources and Facebook (66.5%, 1203 of 1808) was the most common source of getting health information. About 87% people received health information on social media and television. Users of social media had about 3 times more likelihood to follow the health rules. About 80% participants who used social media followed the health measures after 0-28 days of getting the information. The strongest correlation was found between social distancing and the information on television (r = 0.943).

CONCLUSION

Strong correlation of health information was present among the participants in building awareness about taking preventive measures. This is the first study to describe the positive influence of information amid COVID-19 in Bangladesh.

Prevalence and impact of comorbidities on disease prognosis among patients with COVID-19 in Bangladesh: A nationwide study amid the second wave

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.

Prevalence and impact of diabetes and cardiovascular disease on clinical outcome among patients with COVID-19 in Bangladesh

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.

Impact of meteorological parameters and population density on variants of SARS-CoV-2 and outcome of COVID-19 pandemic in Japan

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.