Previous COVID-19 infection and antibody levels after vaccination (preprint)

Background The emergence of new COVID-19 variants of concern coupled with a global inequity in vaccine access and distribution, prompted many public health authorities to circumvent the vaccine shortages by altering vaccination protocols and prioritizing high-risk individuals. Those with previous COVID-19 infection may have not been prioritized due to existing humoral immunity. Objective We aim to study the association between previous COVID-19 infection and antibody levels after COVID-19 vaccination. Methods A serological analysis to measure SARS-CoV-2 IgG, IgA and neutralizing antibodies was performed on individuals who received one or two doses of either BNT162b2 or ChAdOx1 vaccines in Kuwait. Generalized linear regression models adjusted for individual characteristics and comorbidities were fitted to study the average levels of IgG and neutralizing antibodies in vaccinated individuals based who had previous COVID-19 infection compared to those who had not. Results A total of 1025 individuals were recruited. The mean levels of IgG, IgA and neutralizing antibodies were higher in vaccinated subjects with previous COVID-19 infection when compared with those vaccinated without previous COVID-19 infection. Regression analysis showed a steeper slope of decline for IgG in vaccinated individuals without previous COVID-19 infection in comparison with vaccinated individuals with previous COVID-19 infection. Conclusion Previous COVID-19 infection appears to elicit robust and sustained levels of SARS-CoV-2 antibodies in vaccinated individuals. Given the inconsistent supply of COVID-19 vaccines in many countries due to the global inequity, our results point towards wider vaccination plans to especially cover individuals without previous COVID-19 infection.

Robust antibody levels in both diabetic and non-diabetic individuals after BNT162b2 mRNA COVID-19 vaccination (preprint)

The emergence of effective vaccines for COVID-19 has been welcomed by the world with great optimism. Given their increased susceptibility to COVID-19, the question arises whether individuals with type-2 diabetes mellitus (T2DM) and other metabolic conditions can respond effectively to the mRNA-based vaccine. We aimed to evaluate the levels of anti-SARS-CoV-2 IgG and neutralizing antibodies in people with T2DM and/or other metabolic risk factors (hypertension and obesity) compared to those without. This study included 262 people that took two doses of BNT162b2 (Pfizer-BioNTech) mRNA vaccine. Both T2DM and non-diabetic individuals had a robust response to vaccination as demonstrated by their high antibody titers. However, both SARS-CoV-2 IgG and neutralizing antibodies titers were lower in people with T2DM. Their levels were 154{+/-}49.1 vs. 138{+/-}59.4BAU/mL for IgG and 87.1{+/-}11.6 vs. 79.7{+/-}19.5% for neutralizing antibodies in individuals without diabetes compared to those with T2DM, respectively. In a multiple linear regression adjusted for individual characteristics, comorbidities, previous COVID-19 infection and duration since second vaccine dose, diabetics had 13.86 BAU/ml (95%CI: -27.08 to -0.64BAU/ml, p=0.041) less IgG antibodies and 4.42% (95%CI: -8.53 to -0.32%, p=0.036) less neutralizing antibodies than non-diabetics. Hypertension and obesity did not show significant changes in antibody titers. Taken together, both type-2 diabetic and non-diabetic individuals elicited strong immune responses to SARS-CoV-2 BNT162b2 mRNA vaccine; nonetheless, lower levels were seen in people with diabetes. Continuous monitoring of the antibody levels might be a good indicator to guide personalized needs for further booster shots to maintain adaptive immunity.

Probabilities of ICU Admission and Hospital Discharge According to Patient Characteristics in the Designated COVID-19 Hospital of Kuwait (preprint)

Background Subsequent epidemic waves have already emerged in some countries and in the absence of highly effective preventive and curative options, there is a need for detailed epidemiological examination of the role of patient characteristics on the development of outcomes. The objective of this study is to describe the probabilities of admission to the Intensive Care Unit (ICU) and the probabilities of hospital discharge among positive COVID-19 patients according to demographics and comorbidities recorded at hospital admission.  Methods A prospective cohort study of all patients with COVID-19 found in the Electronic Medical Records of Jaber Al-Ahmad Al-Sabah Hospital in Kuwait was conducted. The study included 3995 individuals (symptomatic and asymptomatic) of all ages who tested positive from February 24th to May 27th, 2020, out of which 315 were treated in the ICU and 3619 were discharged including those who were transferred to a different healthcare unit without previously entering the ICU. A competing risk analysis considering two events, namely, ICU admission and hospital discharge using flexible hazard models was performed to describe the association between event-specific probabilities and patient characteristics.Results Results showed that being male, increasing age and comorbidities such as chronic kidney disease (CKD), asthma or chronic obstructive pulmonary disease and weakened immune system increased the risk of ICU admission within 10 days of entering the hospital. CKD and weakened immune system decreased the probabilities of discharge in both females and males however, the age-related pattern differed by gender. Diabetes, which was the most prevalent comorbid condition, had only a moderate impact on both probabilities whilst CKD which had the largest effect, was only present in 2% of the study cohort.Conclusion This study provides useful insight in describing the probability of ICU admission and hospital discharge according to age, gender, and comorbidities among confirmed COVID-19 cases in Kuwait. A web-tool is also provided for free to allow the user to estimate these probabilities for any combination of these covariates. These probabilities enable the deeper understanding of the hospital demand according to patient characteristics which is essential to hospital management and useful for developing a vaccination strategy.

COVID-19 Clinical Outcomes and Nationality: Results from a Nationwide Registry in Kuwait (preprint)

Background: In light of the COVID-19 pandemic, many have flagged racial and ethnic differences in health outcomes in western countries as an urgent global public health priority. Kuwait has a unique demographic profile with two-thirds of the population consisting of non-nationals, most of which are migrant workers.Objective: We aimed to explore whether there is a significant difference in health outcomes between non-Kuwaiti and Kuwaiti patients diagnosed with COVID-19.Methods: We used a prospective COVID-19 registry of all patients (symptomatic and asymptomatic) in Kuwait who tested positive from February 24th to April 20th, 2020 , collected from Jaber Al-Ahmad Al-Sabah Hospital, the officially-designated COVID-19 healthcare facility in the country. We ran separate logistic regression models comparing non-Kuwaitis to Kuwaitis for death, intensive care unit (ICU) admission, acute respiratory distress syndrome (ARDS) and pneumonia.Results: The first 1,123 COVID-19 positive patients in Kuwait were all recruited in the study. About 26% were Kuwaitis and 73% were non-Kuwaiti. With adjustments made to age, gender, smoking and selected co-morbidities, non-Kuwaitis had two-fold increase in the odds of death or being admitted to the intensive care unit compared to Kuwaitis (OR: 2.14, 95% CI 1.12-4.32). Non-Kuwaitis had also higher odds of ARDS (OR:2.44, 95% CI 1.23-5.09) and pneumonia (OR: 2.24, 95% CI 1.27-4.12).Conclusion: This is the first study to report on COVID-19 outcomes between Kuwaiti and non-Kuwaiti patients. The current pandemic may have amplified the differences of health outcomes among marginalized subpopulations. A number of socioeconomic and environmental factors could explain this health disparity. More research is needed to advance the understanding of policymakers in Kuwait in order to make urgent public health interventions.

Clinical Characteristics, Risk Factors and Outcomes Among the First Consecutive 1,096 Patients Diagnosed with COVID-19: The Kuwait Experience (preprint)

Background In Kuwait, prior to the first case of COVID-19 being reported in the country, mass screening of incoming travelers from countries with known outbreaks was performed and resulted in the first identified cases in the country. All COVID-19 cases at the time and subsequently after, were transferred to a single center, Jaber Al-Ahmad Al-Sabah Hospital, where the patients received standardized investigations and treatments. The objective of this study was to characterize the demographics, clinical manifestations and outcomes in this unique patient population. Methods This retrospective cohort study was conducted between 24th February 2020 and 20th April 2020. All consecutive patients in the entire State of Kuwait diagnosed with COVID-19 according to WHO guidelines and admitted to Jaber Al-Ahmad Al-Sabah Hospital were recruited. Patients received standardized investigations and treatments. Multivariable analysis was used to determine the associations between risk factors and outcomes. Findings Of 1096 patients, the median age was 41 years and 81% of patients were male. Most patients were asymptomatic on admission (49.5%), 69.4% had no signs of infection and 94.6% were afebrile. Only 3.6% of patients required an ICU admission and 1.7% were dead at the study cutoff date. On multivariate analysis, the risk factors found to be significantly associated with admission to intensive care were age above 50 years old, a qSOFA score above 0, smoking, elevated CRP and elevated procalcitonin levels. Asthma, smoking and elevated procalcitonin levels correlated significantly with mortality in our cohort. Interpretation To our knowledge, this is the first large retrospective cohort study observing the characteristics of the initial consecutive COVID-19 patients of an entire country. Further, large proportion of asymptomatic patients provides novel insights into the clinical features of patients with milder disease.

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

Kuwait has been experiencing a COVID-19 outbreak since the first imported case on Feb 24, 2020. Analysis of data from the early stage of COVID-19 outbreak in Kuwait can provide important information about the potential epidemic and healthcare burdens as well as assist in evaluating the potential impact of various outbreak control measures. Such control measures are essentially implemented to achieve a sufficient reduction in the effective reproduction number during an outbreak. In this study, we use a mathematical modeling framework to simulate the outbreak dynamics of SARS-CoV-2 transmission in Kuwait and forecast the potential burden on the healthcare system. We calibrate the model against daily numbers of detected infection and death cases using a maximum likelihood framework and estimate both the basic and effective reproduction numbers. Our results indicate that the early control measures implemented in Kuwait had the effect of delaying the intensity of the outbreak but were unsuccessful in reducing Rt below 1. This highlights a need for a systematic investigation of the current public health interventions as well as a scientific surveillance tool that is sufficiently sensitive to outbreak temporal dynamics. Meanwhile, the developed model can serve as a public health tool to control the current outbreak and can be used to anticipate effective measures should a second wave re-emerge in Kuwait.