Multivariate visualization of the global COVID-19 pandemic: A comparison of 161 countries

Use of a risk assessment tool to determine the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

The origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is contentious. Most studies have focused on a zoonotic origin, but definitive evidence such as an intermediary animal host is lacking. We used an established risk analysis tool for differentiating natural and unnatural epidemics, the modified Grunow-Finke assessment tool (mGFT) to study the origin of SARS-COV-2. The mGFT scores 11 criteria to provide a likelihood of natural or unnatural origin. Using published literature and publicly available sources of information, we applied the mGFT to the origin of SARS-CoV-2. The mGFT scored 41/60 points (68%), with high inter-rater reliability (100%), indicating a greater likelihood of an unnatural than natural origin of SARS-CoV-2. This risk assessment cannot prove the origin of SARS-CoV-2 but shows that the possibility of a laboratory origin cannot be easily dismissed.

Enhanced EPIRISK tool for rapid epidemic risk analysis

OBJECTIVES

This study aims to create an enhanced EPIRISK tool in order to correctly predict COVID-19 severity in various countries. The original EPIRISK tool was developed in 2018 to predict the epidemic risk and prioritise response. The tool was validated against nine historical outbreaks prior to 2020. However, it rated many high-income countries that had poor performance during the COVID-19 pandemic as having lower epidemic risk.

STUDY DESIGN

This study was designed to modify EPIRISK by reparameterizing risk factors and validate the enhanced tool against different outbreaks, including COVID-19.

METHODS

We identified three factors that could be indicators of poor performance witnessed in some high-income countries: leadership, culture and universal health coverage. By adding these parameters to EPIRISK, we created a series of models for the calibration and validation. These were tested against non-COVID outbreaks in nine countries and COVID-19 outbreaks in seven countries to identify the best-fit model. The COVID-19 severity was determined by the global incidence and mortality, which were equally divided into four levels.

RESULTS

The enhanced EPIRISK tool has 17 parameters, including seven disease-related and 10 country-related factors, with an algorithm developed for risk level classification. It correctly predicted the risk levels of COVID-19 for all seven countries and all nine historical outbreaks.

CONCLUSIONS

The enhanced EPIRSIK is a multifactorial tool that can be widely used in global infectious disease outbreaks for rapid epidemic risk analysis, assisting first responders, government and public health professionals with early epidemic preparedness and prioritising response to infectious disease outbreaks.

Risk factors, clinical indicators, and pathological findings of abomasal ulcers in tropical dairy buffaloes

The current study aimed at identifying the risk factors and initial diagnostic aids for abomasal ulcers. The risk factor analysis confirmed a significant association (P < 0.05) of abomasal ulcers with concentrate-rich diets (OR, 4.795; CI, 1.212-15.974) and concurrent disorders (OR, 2.978; CI, 0.987-8.980), while the buffaloes in early lactation (OR, 2.777; CI, 0.703-10.972) showed a higher tendency (P = 0.078) for the disorder. The depressed demeanour, dark or black manure (melena), anemia, tachycardia, decreased milk production, anorexia, tachypnea, absence of rumination, abdominal guarding, kyphosis, and tachypnea were the most frequent clinical signs. Subjecting the abomasal fluid for cultural isolation, gram staining, and stormy clot fermentation test identified the presence of clostridium perfringes, while screening through uniplex PCR detected cpa toxin. The buffaloes affected with type-3 and 4 abomasal ulcers exhibited a higher peritoneal fluid to serum ratio of total protein, albumin, and glucose with a low (P < 0.01) serum-ascites albumin gradient (SAAG) concentration compared to reference values of healthy buffaloes. The first two principal components of PCA explained 54.50% of the total variances with lymphocytes, creatine kinase, and rumen chloride levels as the top contributors to dimension I, and albumin, total protein, sodium, and methylene blue reduction time (MBRT) for rumen liquor as the major contributors to dimension II. The vector plot revealed lymphocytopenia, decreased hemoglobin, hypoalbuminemia, hypokalemia, decreased rumen pH, neutrophilia, eosinophilia, leucocytosis, greater MBRT, and higher rumen chloride, serum creatine kinase, and blood urea nitrogen as the major indicators for abomasal ulcers. Histopathological studies revealed infiltration of inflammatory cells in the mucosa along with multifocal areas of necrosis, degeneration, and eroded muscle structure. The study projected a few high-scored clinical signs and extremely variable clinical indicators as initial diagnostic aids of abomasal ulcers, which can be confirmed by ultrasonography and peritoneal fluid examination.

Abomasal impaction in buffaloes: Risk factors, clinical indicators, necropsy findings, and histology studies

The present study aims to identify potential risk factors and most possible clinical indicators of abomasal impaction in buffaloes. Among the screened buffaloes (n = 636), the logistic model was fitted for 491 buffaloes because of the non-availability of parity-related data for 145 buffaloes. Third-trimester pregnancy, feeding paddy straw alone, and concurrent disorders were identified as the potential risk factors using multivariate regression analysis. The buffaloes reared by farmers devoid of land tended to have a higher incidence of abomasal impaction. Depressed demeanour, absence of rumination, abdominal guarding, scleral congestion, sunken eyeballs, anorexia, reduced dung output, abacus beads-like faeces, colic signs (straining to defecate, frequent lying down, and kicking at abdomen), tachypnea, and tachycardia were the most repeatedly noticed clinical signs in buffaloes diagnosed with abomasal impaction. Further, the principal component analysis revealed increased rumen fluid sedimentation time and chloride content, serum creatine phosphokinase, and blood neutrophil and eosinophil content along with decreased blood lymphocytes proportion, potassium, and chloride as the greatest indicators for abomasal impaction. Next to them, a higher rumen fluid methylene blue reduction time, serum urea nitrogen, and blood total leucocyte count, along with a lower serum albumin and blood haemoglobin were the best possible indicators for diagnosis. The necropsy findings of the buffaloes that died with abomasal disorders revealed an abomasum with increased dimensions and constant pitting on pressure. Furthermore, the histopathological studies showed degeneration and necrosis of the abomasal wall with infiltrated mononuclear cells. The results of the study help in designing a comprehensive evaluation mechanism for diagnosing abomasal impaction in buffaloes.

What have we learned about socioeconomic inequalities in the spread of COVID-19? A systematic review

This article aims to provide a better understanding of the associations between groups of socioeconomic variables and confirmed cases of COVID-19. The focus is on cross-continental differences of reported positive, negative, unclear, or no associations. A systematic review of the literature is conducted on the Web of Science and SCOPUS databases. Our search identifies 314 eligible studies published on or before 31 December 2021. We detect nine groups of frequently used socioeconomic variables and results are presented by region of the world (Africa, Asia, Europe, Middle East, North American and South America). The review expands to describe the most used statistical and modelling techniques as well as inclusion of additional dimensions such as demographic, healthcare weather and mobility. Meanwhile findings agree on the generalized positive impact of population density, per capita GDP and urban areas on transmission of infections, contradictory results have been found concerning to educational level and income.

Insights into Controlling the Spread of COVID-19: A Study Inspired by Seven of the Earliest Vaccinated Countries

Background

The aim of the study is to derive deeper insights into the control of the spread of COVID-19 during the second half of 2021, from seven countries that are among the earliest to have accelerated the deployment of COVID-19 vaccines. Methodology. This study used data from the Global COVID-19 Index and Google COVID-19 Community Mobility Reports. Data was extracted on the 5^th of each month from July to December 2021. Seven countries were selected—United Kingdom, United States of America, Israel, Canada, France, Italy, and Austria. The sample comprised number of new cases, hospitalisations, ICU admissions and deaths due to COVID-19, government stringency measures, partial and full vaccination coverage, and changes in human mobility. Principal component analysis was conducted, and the results were interpreted and visualized through 2-dimensional and 3-dimensional plots to reveal the systematic patterns of the data.

Results

The first three principal components captured around 77.3% of variance in the data. The first component was driven by the spread of COVID-19 (31.6%), the second by mobility activities (transit, retail, and recreational) (24.3%), whereas the third by vaccination coverage, workplace-related mobility, and government stringency measures (21.4%). Visualizations showed lower or moderate levels of severity in COVID-19 during this period for most countries. By contrast, the surge in the USA was more severe especially in September 2021. Human mobility activities peaked in September for most countries and then receded in the following months as more stringent government measures were imposed, and countries began to grapple with a surge in COVID-19 cases.

Conclusion

This study delineated the spread of COVID-19, human mobility patterns, widespread vaccination coverage, and government stringency measures on the overall control of COVID-19. While at least moderate levels of stringency measures are needed, high vaccine coverage is particularly important in curbing the spread of this disease.