SARS-CoV-2: Proof of recombination between strains and emergence of possibly more virulent ones

COVID-19 is challenging healthcare preparedness, world economies, and livelihoods. The infection and death rates associated with this pandemic are strikingly variable in different countries. To elucidate this discrepancy, we analyzed 2431 early spread SARS-CoV-2 sequences from GISAID. We estimated continental-wise admixture proportions, assessed haplotype block estimation, and tested for the presence or absence of strains recombination. Herein, we identified 1010 unique missense mutations and seven different SARS-CoV-2 clusters. In samples from Asia, a small haplotype block was identified; whereas, samples from Europe and North America harbored large and different haplotype blocks with nonsynonymous variants. Variant frequency and linkage disequilibrium varied among continents, especially in North America. Recombination between different strains was only observed in North American and European sequences. Additionally, we structurally modeled the two most common mutations D614G and P314L which suggested that these linked mutations may enhance viral entry and stability. Overall, we propose that COVID-19 virulence may be more severe in Europe and North America due to coinfection with different SARS-CoV-2 strains leading to genomic recombination which might be challenging for current treatment regimens and vaccine development. Furthermore, our study provides a possible explanation for the more severe second wave of COVID-19 that many countries are currently experiencing presented as higher rates of infection and death.

Outcomes of COVID-19: disparities by ethnicity

ObjectivesTo investigate the role of ethnicity in COVID-19 outcome disparities in a cohort in Kuwait. MethodsThis is a retrospective analysis of 405 individuals infected with SARS-CoV-2 in Kuwait. Outcomes such as symptoms severity and mortality were considered. Multivariate logistic regression models were used to report the odds ratios (OR) for ICU admission and dying from COVID-19. ResultsThe cohort included 290 Arabs and 115 South Asians. South Asians recorded significantly higher COVID-19 death rates compared to Arabs (33% vs. 7.6%, P value<0.001). When compared to Arabs, South Asians also had higher odds of being admitted to the ICU (OR = 6.28, 95% CI: 3.34 - 11.80, p < 0.001). South Asian patients showed 7.62 (95% CI: 3.62 - 16.02, p < 0.001) times the odds of dying from COVID-19. ConclusionCOVID-19 patients with South Asians ethnicity are more likely to have worse prognosis and outcome when compared to patients with Arab ethnicity. This suggest a possible role for ethnicity in COVID-19 outcome disparities and this role is likely to be multifactorial.

Clinical Characteristics and Outcomes of Diabetic COVID-19 patients in Kuwait

BackgroundCOVID-19 has a highly variable clinical presentation, ranging from asymptomatic to severe respiratory symptoms and death. Diabetes seems to be one of the main comorbidities contributing to a worse COVID-19 outcome. ObjectiveIn here we analyze the clinical characteristics and outcomes of diabetic COVID-19 patients Kuwait. MethodsIn this single-center, retrospective study of 417 consecutive COVID-19 patients, we analyze and compare disease severity, outcome, associated complications, and clinical laboratory findings between diabetic and non-diabetic COVID-19 patients. ResultsCOVID-19 patients with diabetes had more ICU admission than non-diabetic COVID-19 patients (20.1% vs. 16.8%, p<0.001). Diabetic COVID-19 patients also recorded higher mortality in comparison to non-diabetic COVID-19 patients (16.7% vs. 12.1%, p<0.001). Diabetic COVID-19 patients had significantly higher prevalence of comorbidities, such as hypertension. Laboratory investigations also highlighted notably higher levels of C-reactive protein in diabetic COVID019 patients and lower estimated glomerular filtration rate. They also showed a higher incidence of complications. logistic regression analysis showed that every 1 mmol/L increase in fasting blood glucose in COVID-19 patients is associated with 1.52 (95% CI: 1.34 - 1.72, p<0.001) times the odds of dying from COVID-19. ConclusionDiabetes is a major contributor to worsening outcomes in COVID-19 patients. Understanding the pathophysiology underlining these findings could provide insight into better management and improved outcome of such cases. Highlights of the StudyO_LIA significantly higher proportion of COVID-19 patients with diabetes mellitus required admission to the ICU. C_LIO_LIHigher fasting blood glucose was associated with higher risk of COVID-19 associated mortality. C_LIO_LICOVID-19 patients with diabetes mellitus had significantly higher incidence of complications including sepsis, ARDS, cardiac failure and renal failure. C_LI

Clinical characteristics of Coronavirus Disease 2019 (COVID-19) patients in Kuwait

This is a retrospective single-center study of 417 consecutive patients with coronavirus disease 2019 (COVID-19) admitted to Jaber Al-Ahmad Hospital in Kuwait between February 24, 2020 and May 24, 2020. In total, 39.3% of patients were asymptomatic, 41% were symptomatic with mild/moderate symptoms, 5.3% were admitted to the intensive care unit (ICU) and recovered, and 14.4% died. The mean age of death cases was 54.20 years ({+/-} 11.09). Comorbidities were more prevalent in patients who died compared with others. Key findings include abnormal levels of markers assicated with infection, inflammation, abnormal blood clotting, heart problems and kidney problems in patients with severe form of the disease and poor putcome. We report a rapidly deteriorating estimated glomerular filtration rate (eGFR) in deaths during ICU stay with kidney injury complications reported in 65% of deaths (p < 0.05). Our dynamic profiling of eGFR in ICU highlights the potential role of renal markers in forecasting disease outcome that could perhaps identify patients at risk of poor outcome.

Real-time tracking and forecasting of the of COVID-19 outbreak in Kuwait: a mathematical modeling study

BackgroundMany countries have succeeded in curbing the outbreak of COVID-19 by employing strict public health control measures. However, little is known about the effectiveness of such control measures in curbing the outbreak in developing countries. In this study, we seek to assess the impact of various outbreak control measures in Kuwait to gain more insight into the outbreak progression and the associated healthcare burden. MethodsWe use a SEIR mathematical model to simulate the epidemic outbreak of COVID-19 in Kuwait with additional testing and hospitalization compartments. We use a NBD observational framework for confirmed case and death counts. We forecast model trajectories and assess the effectiveness of public health interventions by using maximum likelihood to estimate both the basic and effective reproduction numbers. ResultsOur results indicate that the early strict control measures had the effect of delaying the intensity of the outbreak but were unsuccessful in reducing the effective reproduction number below 1. Forecasted model trajectories suggest a need to expand the healthcare system capacity to cope with the associated epidemic burden of such ineffectiveness. ConclusionStrict public health interventions may not always lead to the same desired outcomes, particularly when population and demographic factors are not accounted for as in the case in some developing countries. Real-time dynamic modeling can provide an early assessment of the impact of such control measures as well as a forecasting tool to support outbreak surveillance and the associated healthcare expansion planning. SUMMARY BOXO_ST_ABSWhat is already known on the subject?C_ST_ABSEvidence is accumulating about the positive impact of various strict public health interventions on the transmission of COVID-19 in the developed world. Currently, however, many developing countries are still struggling to control and suppress the initial wave of the outbreak. In particular, less attention is given to assessing the impact of taking similar strict control measures. What does this study add?Our modeling study provides the first evidence showing how the imposition of strict public health measures has not led to a reduction in COVID-19 transmission in Kuwait. It highlights the importance of performing systematic epidemiological and public health investigations of the population factors which may limit the effectiveness of standard public health interventions in developing countries. It also emphasizes the utility of adopting dynamic modeling approaches for intervention assessment and healthcare capacity re-adjustment at the earliest stages of the outbreak.