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Vandelli V, Palandri L, Coratza P, Rizzi C, Ghinoi A, Righi E, Soldati M. Conditioning factors in the spreading of Covid-19 - Does geography matter? Heliyon 2024; 10:e25810. [PMID: 38356610 PMCID: PMC10865316 DOI: 10.1016/j.heliyon.2024.e25810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 01/23/2024] [Accepted: 02/02/2024] [Indexed: 02/16/2024] Open
Abstract
There is evidence in literature that the spread of COVID-19 can be influenced by various geographic factors, including territorial features, climate, population density, socioeconomic conditions, and mobility. The objective of the paper is to provide an updated literature review on geographical studies analysing the factors which influenced COVID-19 spreading. This literature review took into account not only the geographical aspects but also the COVID-19-related outcomes (infections and deaths) allowing to discern the potential influencing role of the geographic factors per type of outcome. A total of 112 scientific articles were selected, reviewed and categorized according to subject area, aim, country/region of study, considered geographic and COVID-19 variables, spatial and temporal units of analysis, methodologies, and main findings. Our literature review showed that territorial features may have played a role in determining the uneven geography of COVID-19; for instance, a certain agreement was found regarding the direct relationship between urbanization degree and COVID-19 infections. For what concerns climatic factors, temperature was the variable that correlated the best with COVID-19 infections. Together with climatic factors, socio-demographic ones were extensively taken into account. Most of the analysed studies agreed that population density and human mobility had a significant and direct relationship with COVID-19 infections and deaths. The analysis of the different approaches used to investigate the role of geographic factors in the spreading of the COVID-19 pandemic revealed that the significance/representativeness of the outputs is influenced by the scale considered due to the great spatial variability of geographic aspects. In fact, a more robust and significant association between geographic factors and COVID-19 was found by studies conducted at subnational or local scale rather than at country scale.
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Affiliation(s)
- Vittoria Vandelli
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
| | - Lucia Palandri
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
| | - Paola Coratza
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
| | - Cristiana Rizzi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
| | - Alessandro Ghinoi
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
| | - Elena Righi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
| | - Mauro Soldati
- Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, 41125, Modena, Italy
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Nelson JR, Lu A, Maestre JP, Palmer EJ, Jarma D, Kinney KA, Grubesic TH, Kirisits MJ. Space-time analysis of COVID-19 cases and SARS-CoV-2 wastewater loading: A geodemographic perspective. Spat Spatiotemporal Epidemiol 2022; 42:100521. [PMID: 35934330 PMCID: PMC9142176 DOI: 10.1016/j.sste.2022.100521] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 05/24/2022] [Accepted: 05/26/2022] [Indexed: 11/05/2022]
Abstract
Severe acute respiratory syndrome - coronavirus 2 (SARS-CoV-2) continues to effect communities across the world. One way to combat these effects is to enhance our collective ability to remotely monitor community spread. Monitoring SARS-CoV-2 in wastewater is one approach that enables researchers to estimate the total number of infected people in a region; however, estimates are often made at the sewershed level which may mask the geographic nuance required for targeted interdiction efforts. In this work, we utilize an apportioning method to compare the spatial and temporal trends of daily case count with the temporal pattern of viral load in the wastewater at smaller units of analysis within Austin, TX. We find different lag-times between wastewater loading and case reports. Daily case reports for some locations follow the temporal trend of viral load more closely than others. These findings are then compared to socio-demographic characteristics across the study area.
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Affiliation(s)
- J R Nelson
- Department of Geosciences, Auburn University, 2050 Beard Eaves Coliseum, Auburn, AL 36849, USA
| | - A Lu
- Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA
| | - J P Maestre
- Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA
| | - E J Palmer
- Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA
| | - D Jarma
- Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA
| | - K A Kinney
- Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA
| | - T H Grubesic
- Geoinformatics & Policy Analytics Laboratory, School of Information, University of Texas at Austin, USA
| | - M J Kirisits
- Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, 301 E. Dean Keeton St., Stop C1786, Austin, TX 78712, USA
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