Diagnostic Delay in Pediatric Inflammatory Bowel Disease: A Systematic Review.

INTRODUCTION: Delays in diagnosing pediatric inflammatory bowel disease (IBD) are common, but the extent of this delay remains unclear due to variations in reported time-periods between studies. The objectives of this systematic review were to examine the extent of diagnostic delay in pediatric IBD and examine any association between specific characteristics and length of diagnostic delay. METHODS: We identified studies from several medical bibliographical databases (EMBASE, Medline and CINAHL) from their inception to April 2021. Studies examining pediatric cohorts (< 18 years old) defined as having a diagnosis of Crohn's Disease (CD), ulcerative colitis (UC), or by the more general definition of IBD, and reporting a median time-period between the onset of symptoms and a final diagnosis (diagnostic delay) were included. Two reviewers selected each study, extracted data, and assessed their quality using the Newcastle-Ottawa scale. Narrative synthesis was then used to examine the extent of overall diagnostic delay and delay associated with specific sample characteristics. RESULTS: Of the 10,119 studies initially identified, 24 were included in the review. The overall median diagnostic delay range was 2-10.4 months for IBD, 2.0-18.0 months for UC and 4.0-24.0 months for CD. However, for approximately two thirds of UC (68.8%) and CD (66.7%) studies, delay ranged from 2.0-3.0 and 4.0-6.3 months, respectively. A longer delay was significantly associated with several sample characteristics; however, these were too infrequently examined to draw robust conclusion on their role. CONCLUSION: Children continue to wait several months for a final diagnosis of IBD, and those with CD experience longer delay than those with UC. The role of specific characteristics on delay needs further exploration.

Modelling the evolution of the coronavirus disease (COVID-19) in Saudi Arabia.

INTRODUCTION: The ongoing COVID-19 pandemic has claimed hundreds of thousands of lives around the world. Health planners are seeking ways to forecast the evolution of the pandemic. In this study, a mathematical model was proposed for Saudi Arabia, the country with the highest reported number of COVID-19 cases in the Arab world. METHODOLOGY: The proposed model was adapted from the model used for the Middle East respiratory syndrome outbreak in South Korea. Using time-dependent parameters, the model incorporated the effects of both population-wide self-protective measures and government actions. Data before and after the government imposed control policies on 3 March 2020 were used to validate the model. Predictions for the disease's progression were provided together with the evaluation of the effectiveness of the mitigation measures implemented by the government and self-protective measures taken by the population. RESULTS: The model predicted that, if the government had continued to implement its strong control measures, then the scale of the pandemic would have decreased by 99% by the end of June 2020. Under the current relaxed policies, the model predicted that the scale of the pandemic will have decreased by 99% by 10 August 2020. The error between the model's predictions and actual data was less than 6.5%. CONCLUSIONS: Although the proposed model did not capture all of the effects of human behaviors and government actions, it was validated as a result of its time-dependent parameters. The model's accuracy indicates that it can be used by public health policymakers.

Using Google Trends to assess the impact of Global Public Health Days on online health information-seeking behaviour in Arabian Peninsula.

BACKGROUND: Global Public Health Days (GPHD) are public health interventions which serve to improve public awareness of specific health conditions. Google Trends is a publicly available tool that allows the user to view the popularity of a searched keyword during a specified time period and across a predetermined region. Our objective was to use Google Trends to assess the impact of four GPHD (World Heart Day, World Mental Health Day, World Diabetes Day and World Hypertension Day) on online health information-seeking behaviour (OHISB), 4 weeks before and a week after the GPHD, across six countries of the Arabian Peninsula (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates). METHODS: Relative Search Volume (RSV) was extracted for the aforementioned countries from 28 days before the GPHD and 7 days afterwards. Statistical analysis, undertaken using joinpoint regression software, showed that GPHD have significant changes for Saudi Arabia (Diabetes, Mental Health and Heart day) and UAE (Mental Health day) but were short-lived with a fall in RSV of up to 80% after peak interest. CONCLUSION: GPHD appears to be effective in some countries while further research is needed to investigate the reason of its limitations.