Investigating the impact of socio-economic and environmental indicators on the rate of contracting the disease of COVID-19 in the neighborhoods of Urmia city

Extended Abstract
Introduction
In the past decades, the frequency of pandemics of global importance has increased significantly and created significant threats to human health and society. Covid-19 is a contagious infectious disease. This virus has a high reproduction rate, spreading faster than COVID-19. With widespread human-to-human transmission, it has deeply affected the world and has had a different impact on countries, cities, and societies. It has also significantly affected human society, including health care, economic structures, and social relations. This virus has spread in all continents of the world except Antarctica. Since January 2020, the virus has spread significantly in countries such as Italy, Iran, Brazil, and the United States of America and has rapidly spread to other countries. Moreover, it infected hundreds and killed thousands in the fastest unprecedented crisis ever. As of June 31, 2023, the number of cases of COVID-19 in the world is approximately 675,033,474, and the number of deaths has reached 6,761,290. Cities house most of the world's inhabitants. The high concentration of people and activities in cities makes people vulnerable to various stressors, such as natural and manufactured disasters. In the recent pandemic, cities are the places where the transmission started.  Cities are generally considered as a vulnerable area for infectious diseases. The origin of many infectious diseases is within the cities, fueled by the increase in urbanization, and these types of diseases spread rapidly within the urban texture. In many countries, COVID-19 has changed the face of cities, at least temporarily. However, this is not the first time in human history that epidemic diseases have affected cities. This impact will change the way we think about cities and health. Therefore, cities are a natural environment for spreading infectious diseases. This pandemic is happening right now, and this fundamental challenge in global health governance can also be considered an urban accident, which has created significant problems for urban management and planning. The current pandemic is crucial for managing urban planning in critical conditions. As many regions of the world struggle with the COVID-19 crisis, researchers are constantly trying to shed more light on the underlying patterns of the pandemic and its unanswered aspects. This topical aspect of this virus requires analysis that adopts an interdisciplinary approach. Furthermore, geography is one of the few disciplines that intends to perform this analysis according to environmental characteristics. In this research, urban geography examines environmental factors, social factors, economic factors, etc. A growing literature shows that residential, economic, and social living conditions and neighborhood conditions significantly affect the pandemic. There is evidence that socio-economic and demographic characteristics are factors influencing the transmission of COVID-19.
Person, place, and time are the essential elements of outbreak and epidemiology research. It is necessary to examine the interaction of the internal environment (residential space) and the external environment and its effects on the health of city dwellers. The influence of the neighborhood environment is a fundamental factor that cannot be neglected when studying the health of residents and the indoor environment. Considering that the neighborhood environment can affect the indoor environment, it is reasonable to assume that the indoor environment can mediate the relationship between the neighborhood environment and the residents' health. The built environment can be essential in minimizing crowding and facilitating social distancing and has historically played an essential role in controlling epidemics. The purpose of this research is to measure the impact of each socio-economic quantity and the built environment on the rate of contracting the disease of COVID-19 at the level of all localities of Urmia city in 2020. Socio-economic quantities include the population, the number of older people (over 65 years old), the number of literate people, and the number of workers in each neighborhood. The quantities of the built environment include building density, net population density, population density, commercial density, medical density, density of roads and streets, green space density, occupation level, street congestion, average height of buildings, and number of bus stops.
 
Methodology
The type of research is quantitative. The research is also practical from the point of view of the goal. In terms of approach, the research is descriptive. The required data for the research are the number of people infected with Covid-19 and social, economic and environmental indicators (number of population, number of elderly people (above 65 years old), number of literate people and number of employed people, building density, net population density, population density, commercial density, treatment density, density of roads and streets, density of green space, occupancy level, street congestion, average height of buildings, number of bus stops in each neighborhood). Moran's analysis and hot spot analysis have been exerted to find out whether the patients are sprawl or concentrated (clustered). And in the following, Pearson's correlation coefficient and multivariate regression were applied to analyze and determine the direction and intensity of the relationship between the variables.
 
Results and discussion
The results of the Moran's coefficient indicate the clustering of the number of patients at the neighborhood level. Also, the p-value confirms the cluster formation, and the results of the analysis of hot spots also led to the identification of six high-risk neighborhoods with different confidence levels. The presented correlation and regression analysis showed that among the fifteen variables mentioned in the research findings section, six had a positive relationship with the infection rate at the neighborhood level, and three had a negative relationship.
 
Conclusion
The results show that the number of employees, population density, number of older people, building density, commercial density, and road density affect the infection rate with Covid-19. What is fundamentally clear is that reflecting on past events and learning about what can be improved for future responses is essential for the built environment and related professionals, because life after the pandemic will never be the same. Planning, architecture and the built environment will change under the influence of values, life and habits. Increasing layers of immunity in modern built environments seem to help prevent the spread of infections and diseases.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the scientific consultants of this paper.