Mohadeseh Motamed- Jahromi; Kourosh Azizi; Mohammad Hossein Kaveh
Abstract
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Abdolhalim Rajabi; Mohammad Ebrahimi Kalan; Ali Shahryari; Maryam Ahmadi-Livani; Arezoo Foroughi; Teimoor Jorjani; Mehdi Fazlzadeh; Ziyad Ben Taleb; Abdurrahman Charkazi
Abstract
Background: In the early days of the pandemic, the rise in COVID-19 cases prompted many governments to lockdown the waterpipe-serving venues, which may affect the patterns of use among this centuries-old tobacco product. Here, we studied the pattern of WP smoking among Iranian adults during the COVID-19 ...
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Background: In the early days of the pandemic, the rise in COVID-19 cases prompted many governments to lockdown the waterpipe-serving venues, which may affect the patterns of use among this centuries-old tobacco product. Here, we studied the pattern of WP smoking among Iranian adults during the COVID-19 epidemic.Methods: In this cross-sectional study, we conducted an online survey among sample of 213 waterpipe(WP) smokers who were selected by convenience sampling method from the Golestan province, in Northern Iran using WP smoking patterns, Lebanese Waterpipe Dependence Scale, 11 (LWDS11), and selected demographic variables. Collected data comprises demographic and WP smoking patterns during COVID-19.Results: About 70% of participants reduced their WP use compared to the time before COVID-19, modestly due to pandemic effects. Around 38.5% of the subjects believed WP bars were covertly operating during the lockdown and continued serving their customers. Singles and less educated adults had lower mean attitude scores regarding the decrease in WP smoking during the COVID-19 pandemic (P<0.05). Structural equation analysis revealed that the immune system improvement with WP smoking had the strongest effect. (0.74). A strong inverse correlation exists between the WP dependence level and the negative belief toward WP smoking during the COVID-19 epidemic (r=-0.66, P<0.001).Conclusion: There is a clear need for appropriate interventions to change the belief of WP smokers regarding the dangers of this practice during the COVID-19 outbreak, particularly among single people and those with lower levels of education. Furthermore, regulatory authorities should exercise stricter controls to ensure the complete closure of WP bars.
Anwesha Mahanta
Abstract
Background: The COVID-19 pandemic has shattered the global health system and caused havoc worldwide. Since there is no proper medication, non-pharmaceutical intervention methods are followed to mitigate viral transmission. For its proper implementation, it is crucial to track the spatial pattern of transmission ...
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Background: The COVID-19 pandemic has shattered the global health system and caused havoc worldwide. Since there is no proper medication, non-pharmaceutical intervention methods are followed to mitigate viral transmission. For its proper implementation, it is crucial to track the spatial pattern of transmission and target those areas which require immediate action to control the spread of the pandemic. The geospatial technologies have established themselves as powerful tools that have substantial ability to track outbreak patterns in real-time, identify at-risk populations, and plan targeted intervention.
Methods: The study provides a robust methodological framework with three geospatial tools: Spatial Autocorrelation (Global Moran's I), Hot Spot Analysis (Getis-Ord Gi*), and Space-time scan statistic. The quantitative study was carried out exclusively for North-East India to track the COVID-19 outbreaks from April 2020 to December 2020.
Results: The results obtained indicate a gradual change of spatial distribution of the disease from cluster to random distribution at the global scale. But, eventually, the COVID-19 cases tend to form clusters again. Kamrup Metro, the district with the highest urban population, was reported constantly as a hotspot. Moreover, space-time clusters tend to expand in size over time.
Conclusion: The research study's findings provide an overview of the spatio-temporal pattern of COVID-19 in the study area and help the health officials and policy-makers in formulating effective management strategies and non-pharmaceutical intervention measures by targeting the high-risk areas. The study is a valuable guide towards implementing Geographic Information Science technologies in monitoring and tracking the pandemic.
Fernando Almeida
Abstract
Background: The estimation of the real number of COVID-19 infected people is one of the concerns of the governments around the world. In this sense, this study seeks to assess the incidence and fatality of COVID-19 in Europe considering the expected number of the infected cases.
Methods: A quantitative ...
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Background: The estimation of the real number of COVID-19 infected people is one of the concerns of the governments around the world. In this sense, this study seeks to assess the incidence and fatality of COVID-19 in Europe considering the expected number of the infected cases.
Methods: A quantitative exploratory study was performed on the top 10 countries most affected by COVID-19 by 9th June in Europe. Furthermore, this study presents three propagation estimation models of the COVID-19 that help us to understand the real incidence of the pandemic in each country. Each model is briefly explained and applied.
Results: The findings revealed a great heterogeneity of COVID-19 cases and deaths among the countries. The indicator of the number of deaths reveals the greatest disparity between other countries with the United Kingdom, recording about 6 or 7 times more deaths than Russia or Germany. Infection fatality rate (IFR) tends to be a more reliable indicator when analyzing data because it is less dependent on the number of tests performed.
Conclusion: Several estimation models can be used to determine the incidence of COVID-19. However, their results in European countries are still quite asymmetrical although they are more reliable than just looking at the perspective of the number of cases or deaths recorded. The infection fatality rate (IFR) emerges as a more accurate indicator by estimating the expected number of registered cases, which includes asymptomatic cases and patients with mild symptoms that are not known and reported by health authorities.