Spatial analysis of respiratory diseases in Irana Scoping Review of Domestic scientific-research Articles 2011-2023
Ghasem Fathi
1
(
Department of Geography and Urban Planning, Mohaghegh Ardabili University, Ardabil, Iran
)
Alireza Mohammadi
2
(
Ardabil university
)
Ata Ghaffarigilandeh
3
(
a_ghafarigilandeh@uma.ac.ir
)
Keywords: ", Spatial Analysis", , ", Respiratory Disease", , ", Scoping Review", , ", Iran", .,
Abstract :
In recent years, research on spatial analysis of respiratory diseases has increased in the country, especially after the coronavirus period. However, to our knowledge, no previous study has provided a comprehensive review of this research area. Therefore, in this research, with a scoping review approach, we examined the circle of geographical epidemiological studies, spatial analysis, and spatiotemporal analysis from the perspective of a geographic information system to summarize these studies and also examine the gaps in these research and as a result, guidelines for research Present the future. In this research, the scoping review method of the investigated research has been done in 5 stages. The findings show that most studies have dealt with disease mapping at the basic level of spatial analysis, such as heat maps, etc., at the level of the geographical area under investigation. None of the studies have focused on the spatial analysis of health promotion and recovered patients in the geographical area of their study, and they often pay attention to the current state of the disease. The use of Bayesian methods as an efficient method in measuring the bias of spatial analysis results was not observed in previous studies. The spatial autocorrelation method is rarely used due to the often contagious nature of respiratory diseases and the need to investigate the effect of factors. New methods and approaches for modeling and predicting the spread of diseases have been used less. Classification of effective factors in the prevalence and spread of respiratory diseases at the range level, their randomization, and taking into account the limitations of access to data sources about the variables have been used in fewer studies.