Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)

Mansour, Shawky; Kindi, Abdullah Al; Al-Said, Alkhattab; Al-Said, Adham; Atkinson, Peter M.

doi:10.1016/j.scs.2020.102627

Cited by 175 publications

(124 citation statements)

References 51 publications

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“…Mollalo et al (2020) investigated county-level variations of disease incidence across the continental United States, compiling environmental, socioeconomic, topographic, and demographic variables that could explain the spatial variability of disease incidence, including the percentage of older adults. Similar studies were carried by Mansour, Al Kindi, Al-Said, Al-Said & Atkinson (2021) in Oman, where they also concluded that an increase in the number of the elderly is associated with an increased rate of disease incidence. Páez et al (2020) investigated the influence of environmental (meteorological) factors, coupled with economic and demographic control variables, on the progression of the incidence of COVID-19 in the coterminous provinces in Spain, demonstrating that population density and percentage of older adults displayed strong associations with incidence of COVID-19.…”

Section: Introductionsupporting

confidence: 71%

Explaining COVID-19 contagion in Portuguese municipalities using spatial autocorrelation models

Mourão

Bento

2021

RGE

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This paper investigates the pattern of COVID-19 contagion in Portuguese municipalities from March 23rd to April 5th (the exponential phase). We have recurred to spatial autocorrelation models to discuss how the conglomeration of highly infectious spaces has also contributed to infecting neighbouring municipalities. We have used several indicators for the contagion of COVID-19 from the number of infectious individuals to rates of infectious. As explicative variables, additionally to spatial proximity, we also considered population density, the share of the elderly population as well as the length of municipal perimeter/border. Our results show that highly dense municipalities tended to contaminate close areas. Lengthier perimeters also showed a positive effect on the contagious indicators for a given municipality.

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Section: Introductionsupporting

confidence: 71%

Explaining COVID-19 contagion in Portuguese municipalities using spatial autocorrelation models

Mourão

Bento

2021

RGE

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“…These findings are in line with other relevant studies. Positive associations were observed between percent of black population, older population, and COVID-19 mortality ( Hu, Roberts, Azevedo, & Milner, 2021 ) ( Mansour, Al Kindi, Al-Said, Al-Said, & Atkinson, 2021 ). Finally, compared to metropolitan counties, nonmetropolitan counties have significantly greater mortality rates ( Table 2 ).…”

Section: Discussion and Synthesismentioning

confidence: 99%

mentioning

confidence: 99%

“… 1 Only few papers to date examined spatial heterogeneity in COVID-19 spread and mortality ( Sannigrahi, Pilla, Basu, Basu, & Molter, 2020 ; Li, Ma, & Zhang, 2021 ; Mansour et al, 2021 ). Using spatial models, Li et al 2021 and Mansour et al, 2021 focused on the sociodemographic determinants of COVID-19 spread/infection in China and Oman, respectively. Likewise, Sannigrahi et al (2020) used spatial analysis methods to analyze socio-demographic composition and COVID-19 fatalities in the European region ( Sannigrahi et al, 2020 ).…”

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confidence: 99%

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Treating two pandemics for the price of one: Chronic and infectious disease impacts of the built and natural environment

Frank

Wali²

2021

Sustainable Cities and Society

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Compact walkable environments with greenspace support physical activity and reduce the risk for depression and several obesity-related chronic diseases, including diabetes and heart disease. Recent evidence confirms that these chronic diseases increase the severity of COVID-19 infection and mortality risk. Conversely, denser transit supportive environments may increase risk of exposure to COVID-19 suggesting the potential for contrasting chronic versus infectious disease impacts of community design. A handful of recent studies have examined links between density and COVID-19 mortality rates reporting conflicting results. Population density has been used as a surrogate of urban form to capture the degree of walkability and public transit versus private vehicle travel demand. The current study employs a broader range of built environment features (density, design, and destination accessibility) and assesses how chronic disease mediates the relationship between built and natural environment and COVID-19 mortality. Negative and significant relationships are observed between built and natural environment features and COVID-19 mortality when accounting for the mediating effect of chronic disease. Findings underscore the importance of chronic disease when assessing relationships between COVID-19 mortality and community design. Based on a rigorous simulation-assisted random parameter path analysis framework, we further find that the relationships between COVID-19 mortality, obesity, and key correlates exhibit significant heterogeneity. Ignoring this heterogeneity in highly aggregate spatial data can lead to incorrect conclusions with regards to the relationship between built environment and COVID-19 transmission. Results presented here suggest that creating walkable environments with greenspace is associated with reduced risk of chronic disease and/or COVID-19 infection and mortality.

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“…In this regard, models based on dynamic systems have been at the forefront in terms of variety and application ( Dimitrov & Meyers, 2014 ; Rainisch et al, 2020 ). However, in the last two decades, thanks to extensive advances in the computational power of computers and machine learning techniques, network-based approaches ( Sharkey, 2011 ; Feng et al, 2020 ; Castañeda et al, 2021 ; Mansour et al, 2021 ) and agent-based tracing ( Marini et al, 2020 ) have found a special place.…”

Section: Introductionmentioning

confidence: 99%

Seesaw scenarios of lockdown for COVID-19 pandemic: Simulation and failure analysis

Afshar-Nadjafi

Niaki

2021

Sustainable Cities and Society

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The ongoing COVOD-19(SARS-CoV-2) outbreak has had a devastating impact on the economy, education and businesses. In this paper, the behavior of an epidemic is simulated on different contact networks. Herein, it is assumed that the infection may be transmitted at each contact from an infected person to a susceptible individual with a given probability. The probability of transmitting the disease may change due to the individuals' social behavior or interventions prescribed by the authorities. We utilized simulation on the contact networks to demonstrate how seesaw scenarios of lockdown can curb infection and level the pandemic without maximum pressure on the poor societies. Soft scenarios consist of closing businesses 2, 3, and 4 days in between with four levels of lockdown respected by 25%, 50%, 75%, and 100% of the population. The findings reveal that the outbreak can be flattened under softer alternatives instead of a doomsday scenario of complete lockdown. More specifically, it is turned out that proposed soft lockdown strategies can flatten up to 120% of the pandemic course. It is also revealed that transmission probability has a crucial role in the course of the infection, growth rate of the infection, and the number of infected individuals.

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Sociodemographic determinants of COVID-19 incidence rates in Oman: Geospatial modelling using multiscale geographically weighted regression (MGWR)

Cited by 175 publications

References 51 publications

Explaining COVID-19 contagion in Portuguese municipalities using spatial autocorrelation models

Explaining COVID-19 contagion in Portuguese municipalities using spatial autocorrelation models

Treating two pandemics for the price of one: Chronic and infectious disease impacts of the built and natural environment

Seesaw scenarios of lockdown for COVID-19 pandemic: Simulation and failure analysis

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