Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level

PLoS Neglected Tropical Diseases
Ricardo Ramírez-AldanaOmar Yaxmehen Bello-Chavolla

Abstract

The Islamic Republic of Iran reported its first COVID-19 cases by 19th February 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths to this date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. Therefore, in the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how socioeconomic and climatic features of Iranian provinces might predict the number of cases. The analyses are applied to cumulative cases of the disease from February 19th to March 18th. They correspond to obtaining maps associated with quartiles for rates of COVID-19 cases smoothed through a Bayesian technique and relative risks, the calculation of global (Moran's I) and local indicators of spatial autocorrelation (LISA), both univariate and bivariate, to derive significant clustering, and the fit of a multivariate spatial lag model considering a set of variables potentially affecting the presence of the disease. We identified a cluster of provinces with significantly h...Continue Reading

References

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Citations

Apr 4, 2021·Viruses·Ilaria SpassianiGiorgio Palù
Mar 31, 2021·BMJ Open·Esayas Kebede GudinaTizta Tilahun Degfie
Apr 20, 2021·Journal of Transport & Health·Carlos Dornels Freire de SouzaRodrigo Feliciano do Carmo
Jul 20, 2021·Spatial Statistics·Vincenzina VitaleLivia De Giovanni
Nov 27, 2021·Environmental Science and Pollution Research International·Malihe MoazeniAfshin Ebrahimi

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Software Mentioned

GeoDa
LISA

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