Latent Blowout of COVID-19 Globally: An Effort to Healthcare Alertness via Medical GIS Approach

Sharma, Laxmi Kant; Verma, Rajani Kant

doi:10.1101/2020.04.27.20082503

Cited by 2 publications

(2 citation statements)

References 24 publications

(28 reference statements)

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“…The first symptoms of COVID-19 in Iran (Qom Province that imported from Wuhan, China) were observed on February 19, 2020. Some research mentioned Iran as one of the most affected countries, globally, almost among the first fifth countries (e.g., Sharma and Verma 2020;Binti Hamzah et al 2020). As Shojaee et al (2020) reported that the countries with the highest number of confirmed cases and deaths after China are Italy, Iran, and South Korea.…”

Section: Case Studymentioning

confidence: 99%

Spatial and temporal analysis of the COVID-19 incidence pattern in Iran

Hazbavi

Mostfazadeh

Alaei

et al. 2020

Environ Sci Pollut Res

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In the present paper, province-level variations of novel coronavirus (COVID-19) disease incidence across Iran were investigated. To this end, a geo-database from infected cases, deaths, total population, death-to-population ratio, and infected case-to-death ratio for 31 provinces of Iran and during seven successive periods of February 18–March 19 (P1), March 20–April 8 (P2), April 9–April 28 (P3), April 29–May 20 (P4), May 21–June 20 (P5), June 21–September 21 (P6), and September 22–October 21 (P7) of 2020 was built. Based on the last reports of the population and housing census (2018), Iran is home to 81.8 million people. Nationwide case series of 536,181 and 29,403 infected cases and deaths respectively with COVID-19 were reported to Iran’s Minister of Health from February 18 to October 21, 2020. Of the infected cases, 5.48% have died. The spatiotemporal patterns of COVID-19 were different throughout the 31 study provinces. Firstly, the central, north, and northwest of Iran were the main hosts of this virus. Shortly after, other parts of Iran, most notably the west and southwest regions, experienced a momentous rise in the numeral of infected cases and deaths. In the first study period, Tehran, West Azerbaijan, Mazandaran, Qom, and Gilan had the most infected cases (> 1000). In the second to fourth periods, the number of provinces with higher than 1000 infected cases, respectively, reached 12, 10, and 17. For the last three periods (P5–P7), 31 provinces were assigned higher than 1000 infected cases. Tehran had the most deaths with an increasing trend for all study periods among other provinces. The areas around Kohgiluyeh and Boyer-Ahmad, Bushehr, Chaharmahal and Bakhtiari, South Khorasan, and Ilam had the least death cases. The numbers of infected (death) cases in Iran for the first to seventh periods (P1–P7) respectively were 16,730 (1208), 41,285 (1595), 28,530 (1876), 16,366 (1856), 80,694 (6588), 201,585 (6232), and 128,336 (6953). The location quotient (LQ) index showed that most provinces of Iran have the LQ > 1 indicating a high degree of COVID-19 concentration in most of the province’s area in comparison with the nation, especially in the last study period (P7).

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Section: Case Studymentioning

confidence: 99%

Spatial and temporal analysis of the COVID-19 incidence pattern in Iran

Hazbavi

Mostfazadeh

Alaei

et al. 2020

Environ Sci Pollut Res

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“…The present paper examines Iran as the second-largest country in the Middle East (Fig. 1 ), the area of this country is 1873959 and it has an arid and semi-arid climate [ 32 ]. Iran has 31 provinces due to its political characteristics according to several studies, Iran has suffered the most harm from the virus in the world and ranks fifth in terms of vulnerability [ 33 ].…”

Section: Methodsmentioning

confidence: 99%

Spatio-temporal analysis of the COVID-19 pandemic in Iran

2022

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Globally, the COVID-19 pandemic is a top-level public health concern. This paper is an attempt to identify and COVID-19 pandemic in Iran using spatial analysis approaches. This study was based on secondary data of confirmed cases, deaths, recoveries, number of hospitals, hospital beds and population from March 2, 2019 to the end of November 2021 in 31 provinces of Iran from hospitals and the website of the National Institute of Health. In this paper, three geographical models in ArcGIS10.3 were utilized to analyze and evaluate COVID-19, including Geographic Weight Regression (GWR), Getis-OrdGi* (G-i-star) statistics (hot and cold spot), and Moran autocorrelation spatial analysis. Moran statistics, based on the GWR model, demonstrated that deaths and recoveries followed a clustering pattern for the confirmed cases index during the study period. The Moran Z-score for all three indicators confirmed cases, deaths, and recoveries, which was greater than 2.5 (95% confidence level). The Getis-OrdGi* (G-I-Star) (hot and cold spot) data revealed a wide range of levels for six variables (confirmed cases, deaths, recoveries, population, hospital beds, and hospital) across Iran's provinces. The overall number of deaths exceeded the population and the number of hospitals in the central and southern regions, including the provinces of Qom, Alborz, Tehran, Markazi, Isfahan, Razavi Khorasan, East Azerbaijan, Fars, and Yazd, which had the largest number and The Z-score for the deaths Index is greater than 14.314. The results of this research can pave the way for future studies.

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Latent Blowout of COVID-19 Globally: An Effort to Healthcare Alertness via Medical GIS Approach

Cited by 2 publications

References 24 publications

Spatial and temporal analysis of the COVID-19 incidence pattern in Iran

Spatial and temporal analysis of the COVID-19 incidence pattern in Iran

Spatio-temporal analysis of the COVID-19 pandemic in Iran

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