Prevalence and determinants of symptomatic COVID-19 infection among children and adolescents in Qatar: a cross-sectional analysis of 11 445 individuals.

There is a paucity of evidence about the prevalence and risk factors for symptomatic infection among children. This study aimed to describe the prevalence of symptomatic coronavirus disease 2019 (COVID-19) and its risk factors in children and adolescents aged 0-18 years in Qatar. We conducted a cross-sectional study of all children aged 0-18 years diagnosed with COVID-19 using polymerase chain reaction in Qatar during the period 1st March to 31st July 2020. A generalised linear model with a binomial family and identity link was used to assess the association between selected factors and the prevalence of symptomatic infection. A total of 11 445 children with a median age of 8 years (interquartile range (IQR) 3-13 years) were included in this study. The prevalence of symptomatic COVID-19 was 36.6% (95% confidence interval (CI) 35.7-37.5), and it was similar between children aged <5 years (37.8%), 5-9 years (34.3%) and 10 + years (37.3%). The most frequently reported symptoms among the symptomatic group were fever (73.5%), cough (34.8%), headache (23.2%) and sore throat (23.2%). Fever (82.8%) was more common in symptomatic children aged <5 years, while cough (38.7%) was more prevalent in those aged 10 years or older, compared to other age groups. Variables associated with an increased risk of symptomatic infection were; contact with confirmed cases (RD 0.21; 95% CI 0.20-0.23; P = 0.001), having visited a health care facility (RD 0.54; 95% CI 0.45-0.62; P = 0.001), and children aged under 5 years (RD 0.05; 95% CI 0.02-0.07; P = 0.001) or aged 10 years or older (RD 0.04; 95% CI 0.02-0.06; P = 0.001). A third of the children with COVID-19 were symptomatic with a higher proportion of fever in very young children and a higher proportion of cough in those between 10 and 18 years of age.

Epidemiological impact of public health interventions against diabetes in Qatar: mathematical modeling analyses.

Aims: To predict the epidemiological impact of specific, and primarily structural public health interventions that address lifestyle, dietary, and commuting behaviors of Qataris as well as subsidies and legislation to reduce type 2 diabetes mellitus (T2DM) burden among Qataris. Methods: A deterministic population-based mathematical model was used to investigate the impact of public health interventions on the epidemiology of T2DM among Qataris aged 20-79 years, which is the age range typically used by the International Diabetes Federation for adults. The study evaluated the impact of interventions up to 2050, a three-decade time horizon, to allow for the long-term effects of different types of interventions to materialize. The impact of each intervention was evaluated by comparing the predicted T2DM incidence and prevalence with the intervention to a counterfactual scenario without intervention. The model was parameterized using representative data and stratified by sex, age, T2DM risk factors, T2DM status, and intervention status. Results: All intervention scenarios had an appreciable impact on reducing T2DM incidence and prevalence. A lifestyle management intervention approach, specifically applied to those who are categorized as obese and ≥35 years old, averted 9.5% of new T2DM cases by 2050. An active commuting intervention approach, specifically increasing cycling and walking, averted 8.5% of new T2DM cases by 2050. Enhancing consumption of healthy diets including fruits and vegetables, specifically a workplace intervention involving dietary modifications and an educational intervention, averted 23.2% of new T2DM cases by 2050. A subsidy and legislative intervention approach, implementing subsidies on fruits and vegetables and taxation on sugar-sweetened beverages, averted 7.4% of new T2DM cases by 2050. A least to most optimistic combination of interventions averted 22.8-46.9% of new T2DM cases by 2050, respectively. Conclusions: Implementing a combination of individual-level and structural public health interventions is critical to prevent T2DM onset and to slow the growing T2DM epidemic in Qatar.

Association between pregnancy and severe COVID-19 symptoms in Qatar: A cross-sectional study.

There is inconclusive evidence whether pregnancy exacerbates COVID-19 symptoms or not, and scarce data from the Middle East and North Africa region. The aim of this study was to investigate the association between pregnancy and COVID-19 symptoms in Qatar. This cross-sectional study was carried out using data of all women with confirmed COVID-19, comparing women of child-bearing age (18-49 years). Data of all COVID-19 cases were collected by the Ministry of Public Health (MoPH) in Qatar, between March and September 2020. Symptoms were compared by pregnancy status and classified into moderate and severe. Multivariable logistic and Poisson regression was carried out to investigate the association between pregnancy and severity of COVID-19 symptoms. During the study period, 105 744 individuals were diagnosed with COVID-19, of which 16 908 were women of childbearing age. From that sample, 799 women were pregnant (mean age 29.9 years (SD 5.2)) and 16109 women were not pregnant (mean age 33.1 years (SD 7.8)). After multivariable logistic regression, pregnancy was associated with 1.4-fold higher odds of reporting any symptoms of COVID-19 (OR 1.41, 95% CI 1.18-1.68), and 1.3-fold higher odds of reporting shortness of breath (OR 1.29, 95% CI 1.02-1.63). In a multivariable Poisson regression, pregnancy was also associated with a higher count of symptoms (IRR 1.03, 95%CI 0.98-1.08), although with weak evidence against the null hypothesis. Our findings suggest that, in this setting, pregnant women are more likely to have symptomatic COVID-19, and shortness of breath, compared to women with no pregnancy.

Assessing the impact of climate conditions on the distribution of mosquito species in Qatar.

Qatar is a peninsular country with predominantly hot and humid weather, with 88% of the total population being immigrants. As such, it leaves the country liable to the introduction and dissemination of vector-borne diseases, in part due to the presence of native arthropod vectors. Qatar's weather is expected to become warmer with the changing climatic conditions across the globe. Environmental factors such as humidity and temperature contribute to the breeding and distribution of different types of mosquito species in a given region. If proper and timely precautions are not taken, a high rate of particular mosquito species can result in the transmission of various vector-borne diseases. In this study, we analyzed the environmental impact on the probability of occurrence of different mosquito species collected from several different sites in Qatar. The Naive Bayes model was used to calculate the posterior probability for various mosquito species. Further, the resulting Naive Bayes predictions were used to define the favorable environmental circumstances for identified mosquito species. The findings of this study will help in the planning and implementation of an active surveillance system and preventive measures to curb the spread of mosquitoes in Qatar.

Impact of Smoking on COVID-19 Symptoms in Non-Vaccinated Patients: A Matched Observational Study from Qatar.

Purpose: Predisposition to acute illness from COVID-19 is suggested to correlate with cigarette smoking as it augments the risk of developing cardiovascular and respiratory illnesses, including infections. However, the effects of smoking on COVID-19 symptoms are not well described and controversial. In this study, we aim to explore the associations between smoking and COVID-19 symptoms. Subjects and Methods: A cross-sectional study using the Ministry of Public Health (MoPH), Qatar database was administered to a Qatari population with confirmed COVID-19 disease who filled in pre-defined phone-call questionnaire between 27th February 2020 and 31st December 2020. We analyzed 11,701 non-vaccinated COVID-19 individuals (2952 smokers and 8749 non-smokers) with confirmed RT-PCR test results. The association of smoking and the presence of symptoms as well as patient characteristics was calculated using Pearson's Chi-square and Fisher's exact tests, adjusting for potential covariates. Results: Compared with the non-smokers, symptomatic COVID-19 infection is significantly higher in smokers. In addition, we found fever as the most common symptom developed in COVID-19 patients followed by cough, headache, muscle ache, and sore throat. As compared to other symptoms, association of smoking with chills and abdominal pain was less evident (P < 0.05 and P < 0.001, respectively). However, both groups showed similar rates of developing cough. Conclusion: In conclusion, smoking is associated with COVID-19 symptoms frequency in non-vaccinated patients; nevertheless, further investigations are necessary to understand the mechanism of this association which could generate new targets for the management of COVID-19 in smoker patients.