ABSTRACT
Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the '20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of 'Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level.
ABSTRACT
Social vulnerability is related to the differential abilities of socio-economic groups to withstand and respond to the adverse impacts of hazards and stressors. COVID-19, as a human risk, is influenced by and contributes to social vulnerability. The purpose of this study was to examine the association between social vulnerability and the prevalence of COVID-19 infection in the counties of Khuzestan province, Iran. To determine the social vulnerability of the counties in the Khuzestan province, decision-making techniques and geographic information systems were employed. Also, the Pearson correlation was used to examine the relationship between the two variables. The findings indicate that Ahvaz county and the province's northeastern counties have the highest levels of social vulnerability. There was no significant link between the social vulnerability index of the counties and the rate of COVID-19 cases (per 1000 persons). We argue that all counties in the province should implement and pursue COVID-19 control programs and policies. This is particularly essential for counties with greater rates of social vulnerability and COVID-19 cases.
ABSTRACT
This study analyzes the compactness/sprawl index and its effects on the spread of COVID-19 in the neighborhoods of Ahvaz, Iran. Multiple Criteria Decision Making and GIS techniques were used to develop the index. Also, the effects of compactness/sprawl on COVID-19 were investigated using a regression model. It was found that when considering the number of COVID-19 cases per 1000 people, the compactness/sprawl index did not affect the spread of the disease. However, it had a low but significant effect if the raw number of cases was considered. Results also showed that the compactness index significantly affected the raw number of cases, with a coefficient of 0.291, indicating that more compact neighborhoods had more COVID-19 cases. This is unsurprising as more people live in compact areas and, therefore, the raw number of cases is also likely to be higher. In the absence of proper control measures, this could result in further contact between people, thereby, increasing the risk of virus spread. Overall, we found that compactness had a dual effect on the spread of COVID-19 in Ahvaz. We conclude that proper development and implementation of control measures in well-designed compact neighborhoods are essential for enhancing pandemic resilience.
ABSTRACT
This study analyzes the compactness/sprawl index and its effects on the spread of COVID-19 in the neighborhoods of Ahvaz, Iran. Multiple Criteria Decision Making and GIS techniques were used to develop the indices. Also, the effects of compactness/sprawl on COVID-19 were investigated using a regression model. It was found that when considering the number of COVID-19 cases per 1000 people, the compactness/sprawl index did not affect the spread of the disease. However, it had a low but significant effect if the raw number of cases was considered. Results also showed that the compactness index significantly affected the raw number of cases, with a coefficient of 0.291, indicating that more compact neighborhoods had more COVID-19 cases. This is unsurprising as more people live in compact areas and, therefore, the raw number of cases is also likely to be higher. In the absence of proper control measures, this could result in further contact between people, thereby, increasing the risk of virus spread. Overall, we found that compactness had a dual effect on the spread of COVID-19 in Ahvaz. We conclude that proper development and implementation of control measures in well-designed compact neighborhoods are essential for enhancing pandemic resilience.