COVID-19 In Kuwait Research Articles

Knowledge, Attitude and Practice Assessment of Healthcare Workers Regarding COVID-19 in Kuwait

Knowledge, Attitude and Practice Assessment of Healthcare Workers Regarding COVID-19 in Kuwait

The Reality of Planning for Crisis Management Facing Education Departments during Covid-19 in Kuwait from Teachers’ Point of View

Objectives: the current study aims to identify the reality of planning for crisis management facing education departments during the COVID-19 pandemic in the State of Kuwait from the teachers' point of view.
 Methods: to achieve the objectives of the study, the descriptive and analytical approach was used, where the questionnaire was used as a tool to collect data that was distributed to a sample consisted of 150 male and female teachers in government secondary schools affiliated to the Ministry of Education in the State of Kuwait.
 The results: the results showed that the mean of crisis management planning in public schools in the State of Kuwait from the teachers’ point of view was of a high degree. The results also showed that there are statistically significant differences between the means of the study sample responses to the study tool due to the gender variable in favor of the females, and to the academic qualification variable in favor of PhD holders.
 Conclusions: the current study concluded that the reality of crisis management planning in public schools in the State of Kuwait from the teachers’ point of view was high, the study also recommended emphasizing the crisis management planning process, given its importance in avoiding crises and confronting emerging problems, and organizing awareness and educational programs on crisis management planning in the educational departments in the State of Kuwait.

Exploring the Degree of Awareness of Teachers Regarding the Use of Multimodality and Its Influence on Online Teaching: A Case Study of Online Teaching before and during COVID-19 in Kuwait

Teaching and learning took place differently before and during the COVID-19 pandemic. The pandemic changed the way people lead their lives – switching from traditional teaching (face-to-face) in a public setting to online teaching due to social distancing. The teaching system was forced to accommodate distance learning during COVID-19 to complete academic studies. As a result, some Gulf countries found it difficult to implement distance learning and blended learning due to a lack of infrastructure and other challenges and difficulties. In online teaching, to adequately meet the individual needs of students, effective communication and cooperation between the teacher and the student is required. Thus, this research seeks to determine the differences in teaching and learning during COVID-19. The major aim is to determine how teaching and learning occurred before COVID-19 and how effective they were during COVID-19. This paper studies teachers' use of multimodality in teaching and their perceptions, knowledge, and experiences before and during COVID-19. It also explores the implications and impact of using multimodality in teaching in line with technology before and during COVID-19. Additionally, it investigates the opinion of the teachers regarding their students' interpretation and interaction with multimodality.

Development of novel hybrid models for the prediction of COVID-19 in Kuwait

The first case of COVID-19 in Kuwait was reported on February 24, 2020. There is a need to develop a prediction model for estimating this epidemic size. In this study, we aimed to develop and compare several prediction models using real-time data of COVID-19 from February 24 to June 12, 2020. We modeled the uncertainty and non-stationary real-time data of COVID-19 cases using a multilayer model with different decomposition techniques. We applied our proposed hybrid methodology to predict COVID-19 cases in Kuwait. We further evaluated the performance of the novel hybrid model with others using mean relative error, mean absolute error, and mean square error. We found that our proposed hybrid approach performed better than others for predicting COVID-19 cases.

The Impact of Strict Public Health Measures on COVID-19 Transmission in Developing Countries: The Case of Kuwait.

Background: Many countries have succeeded in curbing the initial outbreak of COVID-19 by imposing 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.Methods: We use a SEIR mathematical model to simulate the first wave of the epidemic outbreak of COVID-19 in Kuwait with additional testing and hospitalization compartments. We calibrate our model by using a NBD observational framework for confirmed case and death counts. We simulate trajectories of model forecasts and assess the effectiveness of public health interventions by using maximum likelihood to estimate both the basic and effective reproduction numbers.Results: Our 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.Conclusion: Strict 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.

Sociodemographic variables and illness attitudes toward COVID-19 in Kuwait.

The COVID-19 pandemic has had a negative impact on the world However, the real consequences to the lives of individuals are still unclear, especially regarding mental health The present study aims to investigate whether there are any significant differences in illness attitudes (worry about illness, concern about pain, hypochondriacal beliefs, thanatophobia, and treatment experience) toward COVID-19 among Kuwaiti participants An online survey was distributed via WhatsApp to 1,413 residents of Kuwait The survey included the Illness Attitude Toward COVID-19 Scale (IATCS) and demographic data During any pandemic or crisis worldwide, individuals' mental health and illness attitude levels toward it differ depending on their sociodemographic characteristics This study detects that females, people aged 49 years old and younger, students, and people with bachelor's degrees reported higher scores of illness attitudes toward the COVID pandemic (PsycInfo Database Record (c) 2021 APA, all rights reserved) Abstract (French) La pandemie de COVID-19 a eu des repercussions negatives dans le monde entier Toutefois, les consequences reelles dans la vie des individus ne sont pas encore connues, en particulier en ce qui concerne la sante mentale La presente etude visait a examiner d'eventuelles differences importantes dans les attitudes a l'egard de la maladie (inquietudes au sujet de la maladie ou de la douleur, croyances hypocondriaques, thanatophobie et experience du traitement), en ce qui a trait a la COVID-19 parmi des participants au Kuwait Un sondage en ligne a ete distribue par l'entremise de WhatsApp a 1413 residents du Kuwait Le questionnaire incluait la llness Attitude Toward COVID-19 Scale (IATCS;Echelle des attitudes a l'egard de la COVID-19) et des donnees demographiques Durant toute pandemie ou crise internationale, les niveaux de sante mentale des individus et leurs attitudes envers la maladie varient selon leurs profils demographiques Cette etude a revele que les femmes, les personnes agees de 49 ans ou moins, les etudiants et les personnes detenant un baccalaureat ont rapporte de plus hauts scores pour les attitudes envers la maladie en ce qui a trait a la pandemie de COVID (PsycInfo Database Record (c) 2021 APA, all rights reserved) Impact Statement Public Significance Statement-Moreover, this study highlights that individuals developed different areas of illness attitudes toward COVID-19 than other studies, such as worrying about contracting the virus, concern about pain, hypochondriacal beliefs, fear of death from the virus, and treatment experience (PsycInfo Database Record (c) 2021 APA, all rights reserved)

A study on the efficiency of the estimation models of COVID-19

Today, the world is fighting against a dangerous epidemic caused by the novel coronavirus, also known as COVID-19. All have been impacted and countries are trying to recover from the social, economic, and health devastations of COVID-19. Recent epidemiology research has concentrated on using different prediction models to estimate the numbers of infected, recovered, and deceased cases around the world. This study is primarily focused on evaluating two common prediction models: Susceptible – Infected – Recovered (SIR) and Susceptible – Exposed – Infected – Recovered (SEIR). The SIR and SEIR models were compared in estimating the outbreak and identifying the better fitting model for forecasting future spread in Kuwait. Based on the results of the comparison, the SEIR model was selected for predicting COVID-19 infected, recovered, and cumulative cases. The data needed for estimation was collected from official sites of the Kuwait Government between 24 February and 1 December 2020. This study presents estimated values for peak dates and expected eradication of COVID-19 in Kuwait. The proposed estimation model is simulated using the Python Programming language on the collected data. The simulation was performed with various basic reproduction numbers (between 5.2 and 3), the initial exposed population, and the incubation rate. The results show that the SEIR model was better suited than the SIR model for predicting both infection and recovery cases with R0 values ranging from 3 to 4, E0=80 and α=0.2.

MO830COVID-19 INFECTION IN HEMODIALYSIS POPULATION

Background and AimsA third novel coronavirus leading to severe respiratory infection (coronavirus disease 2019, COVID-19) was first identified in Wuhan, China in December 2019; 1 as of January 2021, more than 90 million person infected and more than 2,000,000 died worldwide. 2 Hemodialysis (HD) patients are at risk of COVID-19 infection but reported infection rates are variable. 1 We report results of prospectively collected data on HD patients who contracted COVID-19 infection in Kuwait.MethodDemographics, comorbidities, and mortality data for HD patients who got infected with COVID-19 in Kuwait from 1/March/2020 to 31/July/2020 were collected and analyzed.ResultsKuwait population during that same period was 4,600,000 (63% Males and 37%Females). 3 Total number of HD patients was 2000 (representing only 0.04% of the total population with 52% Males and 48% Females). Total number of COVID-19 cases confirmed by PCR from nasopharyngeal swab was 66,957. Total number of infected HD patients was 141 (representing 7% of the total HD population and 0.2% of the total number of people infected with COVID-19 in Kuwait). All COVID-19 positive cases were treated for free in ministry of health hospitalsMean age for HD patients with COVID-19 was 57 (54 for males and 62 for males). DM was present in 70%, HTN in 95%, CV disease in 61%, respiratory illness in 20.5%, and ICU admission was required for 31 patients (22%), with 80% requiring intubation and assisted ventilation. Conventional HD was switched to CRRT in 61 patients (43%). Steroids were used for 23%, convalescent plasma in 1 patient, lopinavir/ritonavir in 7 patients, tocilizumab in 3 patients.Total number of mortality due to covid-19 infection in Kuwait was 447 (0.7% of the total cases). 4 Total mortality in HD population during that period for any reason was 100 (5% of the total HD population), however, total mortality due to COVID-19 infection was 30% of the total mortality in the HD population (and 7% of the total COVID-19 related mortality in the country). Patients who died were older with mean age of 63 vs 56 for survivors and had respiratory illness more frequently (27% vs 18%) and 60% were males. Of those who were switched to CRRT, 21 of 61 (34%) died. Of the 31 HD patients admitted to ICU, 19 (61%) died.ConclusionDespite the fact the HD population represents only a small fraction of the total population, they represent a sizable proportion of the total COVID-19 positive cases and a significant percentage of the total COVID-19 related mortality. This study highlights the increased susceptibility of HD population to COVID-19 infection, which is associated with high rate of mortality, although lower than mortality rates reported in Europe and the united states. 5,6

Maternal and perinatal characteristics and outcomes of pregnancies complicated with COVID-19 in Kuwait

BackgroundThe effect of SARS-CoV-2 infection in pregnant women and newborns is incompletely understood. Preliminary data shows a rather fluctuating course of the disease from asymptomatic or mild symptoms to maternal death. However, it is not clear whether the disease increases the risk of pregnancy-related complications. The aim of the study is to describe the maternal and neonatal clinical characteristics and outcome of pregnancies with SARS-CoV-2 infection.MethodsIn this retrospective national-based study, we analyzed the medical records of all pregnant women infected with SARS-CoV-2 and their neonates who were admitted to New-Jahra Hospital (NJH), Kuwait, between March 15th 2020 and May 31st 2020. During the study period and as part of the public health measures, a total of 185 pregnant women infected with SARS-CoV-2, regardless of symptoms, were hospitalized at NJH, and were included. Maternal and neonatal clinical manifestations, laboratory tests and treatments were collected. The outcomes of pregnancies included miscarriage, intrauterine fetal death (IUFD), preterm birth and live birth were assessed until the end date of the outcomes follow-up (November 10th 2020).ResultsA total of 185 pregnant women infected with SARS-CoV-2 were enrolled with a median age of 31 years (interquartile range, IQR: 27.5–34), and median gestational age at diagnosis of SARS-CoV2 infection was 29 weeks (IQR: 18–34). The majority (88%) of these women had mild symptoms, with fever (58%) being the most common presenting symptom followed by cough (50.6%). At the time of the analysis, out of the 185, 3 (1.6%) of the pregnant women had a miscarriage, 1 (0.54%) had IUFD which was not related to COVID-19, 16 (8.6%) had ongoing pregnancies and 165 (89%) had a live birth. Only 2 (1.1%) of these women developed severe pneumonia and required intensive care. A total of 167 neonates with two sets of twins were born with median gestational age at birth was 38 (IQR: 36–39) weeks. Most of the neonates were asymptomatic, and only 2 of them tested positive on day 5 by nasopharyngeal swab testing.ConclusionsIn this national-based study, most of the pregnant women infected with SARS-CoV-2 showed mild symptoms. Although mother-to-child vertical transmission of SARS-CoV-2 is possible, COVID-19 infection during pregnancy may not lead to unfavorable maternal and neonatal outcomes.

Prediction of COVID-19 Dynamics in Kuwait using SIRD Model

COVID-19 infectious started on 24 February 2020 with 5 patients returning to Kuwait. The ministry of health (MOH) has reported a total of 26,192 patients with 10,156 recovered, 15,831 under treatment, 205 deceased, 206 critical, and 23 quarantined in Kuwait on 30 May 2020. Accurate prediction of the number of expected infected patients, patients under treatment, patients in critical condition, and death will assist health authorities for better planning and the government policymakers a better approach to reduce the number of susceptible people to COVID-19. In this study, a modified SIR model is used to determine COVID-19 dynamics in Kuwait. COVID-19 data for 97 days consist of infectious, recovered, and deceased cases are used to study the SIRD model and to obtain the re-production number and the total susceptible (Sus) population. The accuracy of the fitted model is assessed using the coefficient of determination (R2). The re-production of the total susceptible (predicted) population of 123,102 is obtained to assess the dynamics of COVID-19 in Kuwait. It is predicted that the peak of COVID-19 infectious will be around 23 June 2020 with total infected cases of 56,533. However, a maximum of 26,039 people in the need of hospitals may be accelerated on 10 June 2020 and will quickly drop on 2 July 2020 to only 377 people. The total deceased cases will be 1,169 on this date; although, the death tolls may continue to the total value of 2,667 by the end of the pandemic.

Characteristics, risk factors and outcomes among the first consecutive 1096 patients diagnosed with COVID-19 in Kuwait.

BackgroundIn 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.MethodsThis 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 included. Patients received standardized investigations and treatments. Multivariable analysis was used to determine the associations between risk factors and outcomes (admission to intensive care and/or mortality).FindingsOf 1096 patients, the median age was 41 years and 81% of patients were male. Most patients were asymptomatic on admission (46.3%), of whom 35 later developed symptoms, and 59.7% had no signs of infection. Only 3.6% of patients required an ICU admission and 1.7% were dead at the study's cutoff date. On multivariable 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.

Spatiotemporal dynamics of the COVID-19 pandemic in the State of Kuwait

ObjectivesPrompt understanding of the temporal and spatial patterns of the COVID-19 pandemic on a national level is a critical step for the timely allocation of surveillance resources. Therefore, this study explored the temporal and spatiotemporal dynamics of the COVID-19 pandemic in Kuwait using daily confirmed case data collected between the 23 February and 07 May 2020. MethodsThe pandemic progression was quantified using the time-dependent reproductive number (R(t)). The spatiotemporal scan statistic model was used to identify local clustering events. Variability in transmission dynamics was accounted for within and between two socioeconomic classes: citizens-residents and migrant workers. ResultsThe pandemic size in Kuwait continues to grow (R(t)s ≥2), indicating significant ongoing spread. Significant spreading and clustering events were detected among migrant workers, due to their densely populated areas and poor living conditions. However, the government's aggressive intervention measures have substantially lowered pandemic growth in migrant worker areas. However, at a later stage of the study period, active spreading and clustering events among both socioeconomic classes were found. ConclusionsThis study provided deeper insights into the epidemiology of COVID-19 in Kuwait and provided an important platform for rapid guidance of decisions related to intervention activities.

Forecasting the Spread of COVID-19 in Kuwait Using Compartmental and Logistic Regression Models

The state of Kuwait is facing a substantial challenge in responding to the spread of the novel coronavirus 2019 (COVID-19). The government’s decision to repatriate stranded citizens back to Kuwait from various COVID-19 epicenters has generated a great concern. It has heightened the need for prediction models to estimate the epidemic size. Mathematical modeling plays a pivotal role in predicting the spread of infectious diseases to enable policymakers to implement various health and safety measures to contain the spread. This research presents a forecast of the COVID-19 epidemic size in Kuwait based on the confirmed data. Deterministic and stochastic modeling approaches were used to estimate the size of COVID-19 spread in Kuwait and determine its ending phase. In addition, various simulation scenarios were conducted to demonstrate the effectiveness of nonpharmaceutical intervention measures, particularly with time-varying infection rates and individual contact numbers. Results indicate that, with data until 19 April 2020 and before the repatriation plan, the estimated reproduction number in Kuwait is 2.2. It also confirms the efficiency of the containment measures of the state of Kuwait to control the spread even after the repatriation plan. The results show that a high contact rate among the population implies that the epidemic peak value is yet to be reached and that more strict intervention measures must be incorporated

Predicting COVID-19 (Coronavirus Disease) Outbreak Dynamics Using SIR-based Models: Comparative Analysis of SIRD and Weibull-SIRD

The SIR type models are built by a set of ordinary differential equations (ODE), which are strongly initial value dependent. To fit multiple biological data with SIR type equations requires fitting coefficients of these equations by an initial guess and applying optimization methods. These coefficients are also extremely initial value-dependent. In the vast publication of these types, we hardly see, among simple to highly complicated SIR type methods, that these methods presented more than a maximum of two biological data sets. We propose a novel method that integrates an analytical solution of the infectious population using Weibull distribution function into any SIR type models. The Weibull-SIRD method has easily fitted 4 set of COVID-19 biological data simultaneously. It is demonstrated that the Weibull-SIRD method predictions for susceptible, infected, recovered, and deceased populations from COVID-19 in Kuwait and UAE are superior compared with SIRD original ODE model. The proposed method here opens doors for new deeper studying of biological dynamic systems with realistic biological data trends than providing some complicated, cumbersome mathematical methods with little insight into biological data's real physics.