Detecting the Seasonal and Spatial Patterns of COVID‑19 Hospitalization and Deaths in Iran: Insights from a Spatiotemporal and Hotspot Analysis

Leila Mounesan, Ebrahim Farhadi, Sana Eybpoosh, Ali Hosseini, Mahboubeh Parsaeian, Safoora Gharibzadeh, Mozhgan Ahmadinezhad, Farideh Bahari, Mohammad Mehdi Gouya, Aliakbar Haghdoost, Ehsan Mostafavi

Abstract


Background: Understanding the seasonal and spatial patterns of COVID‑19 hospitalization and deaths is crucial for effective hospital management, resource allocation, and public health interventions. The current study conducts a spatiotemporal hotspot analysis that explores the seasonal and geographical patterns of high‑risk areas of COVID‑19 hospitalizations and deaths in Iran. Methods: Provincial‑level data on laboratory‑confirmed COVID‑19 cases with acute respiratory symptoms in Iran (February 2019–March 30, 2022) were collected. Hotspot analyses mapped seasonal incidence risks, and Global Moran’s spatial autocorrelation analysis identified COVID‑19 clusters. Results: Over the 2 years, 26 hotspots and 11 cold spots were identified (P < 0.05). Western and central provinces showed the highest hospitalization hotspots, while the west and north had the most death hotspots. South and southeast provinces exhibited low incidence and the highest number of cold spots. High‑risk areas were prevalent in spring and autumn, mainly in the west, north, and central regions. Conclusions: This research unveils the clustering patterns of COVID‑19 hospitalizations and fatalities in Iran during the most severe pandemic. Spatial clusters and dynamic hotspots varied across regions and time. Prioritizing high‑risk areas during critical epidemic waves, devising seasonal care strategies, and implementing preventive measures can significantly improve health outcomes.

Keywords


Covid‑19; hospitalization; incidence; Iran; spatiotemporal analysis

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References


Mahase E. China coronavirus: WHO declares international

emergency as death toll exceeds 200. BMJ 2020;368:m408. doi:

1136/bmj.m408.

Wise J. Covid‑19: WHO declares end of global health emergency.

BMJ 2023;381:1041.

Kolahchi Z, De Domenico M, Uddin LQ, Cauda V, Grossmann I,

Lacasa L, et al. COVID‑19 and its global economic impact. In:

Coronavirus Disease‑COVID‑19. Springer; 2021. p. 825‑37.

Lison A, Banholzer N, Sharma M, Mindermann S, Unwin HJT,

Mishra S, et al. Effectiveness assessment of non‑pharmaceutical

interventions: Lessons learned from the COVID‑19

pandemic. Lancet Public Health 2023;8:e311‑7. doi: 10.1016/

S2468‑2667 (23) 00046‑4.

Bollyky TJ, Castro E, Aravkin AY, Bhangdia K, Dalos J,

Hulland EN, et al. Assessing COVID‑19 pandemic policies and

behaviours and their economic and educational trade‑offs across

US states from Jan 1, 2020, to July 31, 2022: An observational

analysis. Lancet 2023;401:1341‑60.

Mounesan L, Eybpoosh S, Haghdoost A, Moradi G, Mostafavi E.

Is reporting many cases of COVID‑19 in Iran due to strength or

weakness of Iran’s health system? Iran J Microbiol 2020;12:73‑6.

Ahmadi A, Fadaei Y, Shirani M, Rahmani F. Modeling and

forecasting trend of COVID‑19 epidemic in Iran until May 13,

Med J Islam Repub Iran 2020;34:27.

Doosti‑Irani A, Haji‑Maghsoudi S, Haghdoost A, Eybpoosh S,

Mostafavi E, Karami M, et al. The dynamic effective

reproductive number of COVID‑19 during the epidemic in Iran.

Iran J Public Health 2022;51:886‑94.

Ebrahimoghli R, Abbasi‑Ghahramanloo A, Moradi‑Asl E,

Adham D. The COVID‑19 pandemic’s true death toll in Iran

after two years: An interrupted time series analysis of weekly

all‑cause mortality data. BMC Public Health 2023;23:1‑9.

Sadeghi K, Zadheidar S, Zebardast A, Nejati A, Faraji M,

Ghavami N, et al. Genomic surveillance of SARS‑CoV‑2 strains

circulating in Iran during six waves of the pandemic. Influenza

Other Respir Viruses 2023;17:e13135. doi: 10.1111/irv. 13135.

Mostafavi E, Eybpoosh S, Karamouzian M, Khalili M,

Haji‑Maghsoudi S, Salehi‑Vaziri M, et al. Efficacy and safety

of a protein‑based SARS‑CoV‑2 vaccine: A randomized clinical

trial. JAMA Netw Open 2023;6:e2310302. doi: 10.1111/irv.

Hay SI, Battle KE, Pigott DM, Smith DL, Moyes CL, Bhatt S,

et al. Global mapping of infectious disease. Philos Trans R Soc

Lond B Biol Sci 2013;368:20120250.

Ramírez‑Aldana R, Gomez‑Verjan JC, Bello‑Chavolla OY.

Spatial analysis of COVID‑19 spread in Iran: Insights into

geographical and structural transmission determinants at a

province level. PLoS Negl Trop Dis 2020;14:e0008875. doi:

1371/journal.pntd. 0008875.

Samany NN, Toomanian A, Maher A, Hanani K, Zali AR.

The most places at risk surrounding the COVID‑19 treatment

hospitals in an urban environment‑case study: Tehran city. Land

Use Policy 2021;109:105725.

Franch‑Pardo I, Napoletano BM, Rosete‑Verges F, Billa L.

Spatial analysis and GIS in the study of COVID‑19. A review.

Sci Total Environ 2020;739:140033.

Getis A. A history of the concept of spatial autocorrelation:

A geographer’s perspective. Geogr Anal 2008;40:297‑309.

Cliff AD, Ord K. Spatial autocorrelation: A review of

existing and new measures with applications. Econ Geogr

;46(suppl 1):269‑92.

Lak A, Maher A, Zali A, Badr S, Mostafavi E, Baradaran HR,

et al. A description of spatial‑temporal patterns of the novel

COVID‑19 outbreak in the neighbourhoods’ scale in Tehran,

Iran. Med J Islam Repub Iran 2021;35:128.

Rahnama MR, Bazargan M. Analysis of spatio‑temporal patterns

of Covid‑19 virus pandemic and its hazards in Iran. Environ

Manage Hazards 2020;7:113‑27.

Jesri N, Saghafipour A, Koohpaei A, Farzinnia B, Jooshin MK,

Abolkheirian S, et al. Mapping and spatial pattern analysis of

COVID‑19 in central Iran using the Local Indicators of Spatial

Association (LISA). BMC Public Health 2021;21:1‑10.

Shariati M, Jahangiri‑rad M, Mahmud Muhammad F,

Shariati J. Spatial analysis of COVID‑19 and exploration of its

environmental and socio‑demographic risk factors using spatial

statistical methods: A case study of Iran. Health Emerg Disasters

Q 2020;5:145‑54.

Manepalli U, Bham GH, Kandada S. Evaluation of hotspots

identification using kernel density estimation (K) and

Getis‑Ord (Gi*) on I‑630. In: 3rd International Conference on

Road Safety and Simulation. United States: National Academy of

Sciences Indianapolis Indiana; 2011.

Calderón Peralvo F, Cazorla Vanegas P, Avila‑Ordóñez E.

A systematic review of COVID‑19 transport policies and

mitigation strategies around the globe. Transp Res Interdiscip

Perspect 2022;15:100653.

Pourghasemi HR, Pouyan S, Heidari B, Farajzadeh Z,

Shamsi SRF, Babaei S, et al. Spatial modeling, risk

mapping, change detection, and outbreak trend analysis of

coronavirus (COVID‑19) in Iran (days between February 19 and

June 14, 2020). Int J Infect Dis 2020;98:90‑108.

Zhang L, Yang H, Wang K, Zhan Y, Bian L. Measuring imported

case risk of COVID-19 from inbound international flights - A

case study on China. Journal of Air Transport Management

;89:101918.

Brockmann D, Helbing D. The hidden geometry of

complex, network‑driven contagion phenomena. Science

;342:1337‑42.

Hazbavi Z, Mostfazadeh R, Alaei N, Azizi E. Spatial and

temporal analysis of the COVID‑19 incidence pattern in Iran.

Environ Sci Pollut Res Int 2021;28:13605‑15.

Panahi MH, Parsaeian M, Mansournia MA, Khoshabi M,

Gouya MM, Hemati P, et al. A spatio‑temporal analysis of

influenza‑like illness in Iran from 2011 to 2016. Med J Islam

Repub Iran 2020;34:65.

Iran statistics centre, population statistics. Available from: https://

www.amar.org.ir/. [Last accessed on 2024 Oct 16].

Ashtarinezhad E, Ahmadi K, Mojiri A. Clustering and

ranking Iranian provinces based on some health indicators.

Payesh (Health Monitor) 2024;23:7‑17.

Janbabaei G, Kalantari B, Darrudi A, Dehnavi H. Equity in

distribution of hospital beds in Iran. Sci J Kurdistan Univ Med

Sci 2020;24:12‑36.