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Pierri F, Scotti F, Bonaccorsi G, Flori A, Pammolli F. Predicting economic resilience of territories in Italy during the COVID-19 first lockdown. EXPERT SYSTEMS WITH APPLICATIONS 2023; 232:120803. [PMID: 37363270 PMCID: PMC10281035 DOI: 10.1016/j.eswa.2023.120803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/19/2023] [Accepted: 06/08/2023] [Indexed: 06/28/2023]
Abstract
This paper aims to predict the economic resilience to crises of territories based on local pre-existing socioeconomic characteristics. Specifically, we consider the case of Italian municipalities during the first wave of the COVID-19 pandemic, leveraging a large-scale dataset of cardholders performing transactions in Point-of-Sales. Based on a set of machine learning classifiers, we show that network-based measures and variables related to the social, economic, demographic and environmental dimensions are relevant predictors of the economic resilience of Italian municipalities to the crisis. In particular, we find accurate classification performance both in balanced and un-balanced scenarios, as well as in the case we restrict the analysis to specific geographical areas. Our analysis predicts that territories with larger income per capita, soil consumption, concentration of real estate activities and commuting network centrality in terms of closeness and Pagerank constitute the set of most affected areas, experiencing the strongest reduction of economic activities during the COVID-19 pandemic. Overall, we provide an application of an early-warning system able to provide timely evidence to policymakers about the detrimental effects generated by natural disasters and severe crisis episodes, thus contributing to optimize public decision support systems.
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Affiliation(s)
- Francesco Pierri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Francesco Scotti
- Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy
| | - Giovanni Bonaccorsi
- Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy
| | - Andrea Flori
- Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy
| | - Fabio Pammolli
- Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milano, Italy
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Koanda O, Yonaba R, Tazen F, Karoui H, Sidibé ML, Lèye B, Diop M, Andrianisa HA, Karambiri H. Climate and COVID-19 transmission: a cross-sectional study in Africa. Sci Rep 2023; 13:18702. [PMID: 37907735 PMCID: PMC10618194 DOI: 10.1038/s41598-023-46007-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 10/26/2023] [Indexed: 11/02/2023] Open
Abstract
The role of climate in the Coronavirus disease 2019 (COVID-19) transmission appears to be controversial, as reported in earlier studies. In Africa, the subject is poorly documented. In this study, over the period from January 1st, 2020 to September 31, 2022, the daily variations in cumulative confirmed cases of COVID-19 for each African country (54 countries) are modelled through time-series-based approaches and using meteorological factors as covariates. It is suggested from the findings that climate plays a role in COVID-19 transmission since at least one meteorological factor is found to be significant in 32 countries. In decreasing order, the most often occurring meteorological factors are dewpoint temperature, relative and absolute humidity, average temperature and solar radiation. Most of these factors show a lagged effect with confirmed cases (between 0 and 28 days). Also, some meteorological factors exhibit contrasting effects on COVID-19 transmission, resulting in both positive and negative association with cumulative cases, therefore highlighting the complex nature of the interplay between climate and COVID-19 transmission.
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Affiliation(s)
- Ousmane Koanda
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Roland Yonaba
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso.
| | - Fowé Tazen
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Héla Karoui
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Mohamed Lamine Sidibé
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Babacar Lèye
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Mamadou Diop
- Laboratoire Eco-Matériaux et Habitat Durable (LEMHaD), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Harinaivo Anderson Andrianisa
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
| | - Harouna Karambiri
- Laboratoire Eaux, Hydro-Systèmes et Agriculture (LEHSA), Institut International d'Ingénierie de l'Eau et de l'Environnement (2iE), Ouagadougou, Burkina Faso
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Mathys T, Souza FTD, Barcellos DDS, Molderez I. The relationship among air pollution, meteorological factors and COVID-19 in the Brussels Capital Region. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:158933. [PMID: 36179850 PMCID: PMC9514957 DOI: 10.1016/j.scitotenv.2022.158933] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/06/2022] [Accepted: 09/18/2022] [Indexed: 06/01/2023]
Abstract
In great metropoles, there is a need for a better understanding of the spread of COVID-19 in an outdoor context with environmental parameters. Many studies on this topic have been carried out worldwide. However, there is conflicting evidence regarding the influence of environmental variables on the transmission, hospitalizations and deaths from COVID-19, even though there are plausible scientific explanations that support this, especially air quality and meteorological factors. Different urban contexts, methodological approaches and even the limitations of ecological studies are some possible explanations for this issue. That is why methodological experimentations in different regions of the world are important so that scientific knowledge can advance in this aspect. This research analyses the relationship between air pollution, meteorological factors and COVID-19 in the Brussels Capital Region. We use a data mining approach that is capable of extracting patterns in large databases with diverse taxonomies. Data on air pollution, meteorological, and epidemiological variables were processed in time series for the multivariate analysis and the classification based on association. The environmental variables associated with COVID-19-related deaths, cases and hospitalization were PM2.5, O3, NO2, black carbon, radiation, air pressure, wind speed, dew point, temperature and precipitation. These environmental variables combined with epidemiological factors were able to predict intervals of hospitalization, cases and deaths from COVID-19. These findings confirm the influence of meteorological and air quality variables in the Brussels region on deaths and cases of COVID-19 and can guide public policies and provide useful insights for high-level governmental decision-making concerning COVID-19. However, it is necessary to consider intrinsic elements of this study that may have influenced our results, such as the use of air quality aggregated data, ecological fallacy, focus on acute effects in the time-series study, the underreporting of COVID-19, and the lack of behavioral factors.
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Affiliation(s)
- Timo Mathys
- Centre for Economics and Corporate Sustainability (CEDON), KU Leuven, Warmoesberg 26, Brussels, Belgium.
| | - Fábio Teodoro de Souza
- Centre for Economics and Corporate Sustainability (CEDON), KU Leuven, Warmoesberg 26, Brussels, Belgium; Graduate Program in Urban Management (PPGTU), Pontifical Catholic University of Paraná (PUCPR), 1155 Imaculada Conceição St, Curitiba, Parana, Brazil.
| | - Demian da Silveira Barcellos
- Graduate Program in Urban Management (PPGTU), Pontifical Catholic University of Paraná (PUCPR), 1155 Imaculada Conceição St, Curitiba, Parana, Brazil.
| | - Ingrid Molderez
- Centre for Economics and Corporate Sustainability (CEDON), KU Leuven, Warmoesberg 26, Brussels, Belgium.
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Chowdhury T, Chowdhury H, Bontempi E, Coccia M, Masrur H, Sait SM, Senjyu T. Are mega-events super spreaders of infectious diseases similar to COVID-19? A look into Tokyo 2020 Olympics and Paralympics to improve preparedness of next international events. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:10099-10109. [PMID: 36066799 PMCID: PMC9446650 DOI: 10.1007/s11356-022-22660-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 08/18/2022] [Indexed: 04/16/2023]
Abstract
Tokyo Summer Olympics and Paralympics have raised social issues regarding the potential rise in COVID-19 cases in Japan and risks associated with the safe organization of mega sporting events during the pandemic, such as the FIFA World Cup Qatar 2022. This study investigates the Tokyo Summer Olympics as a unique case study to clarify the drivers of infectivity and provide guidelines to host countries for the safe organization of subsequent international sporting events. The result here reveals that Tokyo and Japan did not experience a rise in confirmed cases of COVID-19 due to the hosting of the Summer Olympics. Still, transmission dynamics seems to be mainly driven by the high density of population (about 1.2%, p-value <0.001) like other larger cities in Japan (result confirmed with Mann-Whitney U test, significance at 0.05). Our study provided evidence that hosting mega sporting events during this COVID-19 pandemic is safe if strictly maintained the precautions with non-pharmaceutical (and pharmaceutical) measures of control of infections. The Tokyo Summer Olympics hosting will be exemplary for next international events due to the successful implementation of preventive measures during COVID-19 pandemic crisis.
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Affiliation(s)
- Tamal Chowdhury
- Department of Electrical and Electronic Engineering, Chittagong University of Engineering & Technology (CUET), Chattogram, 4349, Bangladesh
| | - Hemal Chowdhury
- Department of Mechanical Engineering, Chittagong University of Engineering & Technology (CUET), Chattogram, 4349, Bangladesh.
| | - Elza Bontempi
- INSTM and Chemistry for Technologies Laboratory, University of Brescia, Via Branze 38, Brescia, 25123, Italy
| | - Mario Coccia
- CNR -- National Research Council of Italy, Via Real Collegio, N. 30, (Collegio Carlo Alberto), 10024, Moncalieri, TO, Italy
| | - Hasan Masrur
- Graduate School of Science & Engineering, University of the Ryukyus, 1 Senbaru, Okinawa, 903-0213, Japan
| | - Sadiq M Sait
- King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia
| | - Tomonobu Senjyu
- Graduate School of Science & Engineering, University of the Ryukyus, 1 Senbaru, Okinawa, 903-0213, Japan
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Yang SD, Park HS. Analysis of the Rate of Confirmed COVID-19 Cases in Seoul and Factors Affecting It Using Big Data Analysis. Asia Pac J Public Health 2022; 34:824-831. [PMID: 36112980 PMCID: PMC9678748 DOI: 10.1177/10105395221124435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Coronavirus disease (COVID-19) is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and presents with mild to severe symptoms. Vaccines have been developed, but COVID-19 persists. Therefore, it is necessary to analyze big data at an early stage to establish an effective infection prevention strategy. To reduce SARS-CoV-2 infection, this study aimed to analyze the infection factors by region within Seoul, Korea and identify the major factors affecting the infection rate. For ease of data aggregation, the study was conducted after a data refinement operation that organized data in the same group into categories, and classified them in detail by specific keywords. Based on the results of this study, if preventive measures are established after identifying the representative infectious factors, periods, and routes of COVID-19 infection, the infection rate could be effectively reduced in the future.
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Affiliation(s)
- San-Duk Yang
- Department of Cyber Security & AI technology, The School of Integrated Software and Design, Kyung Hee Cyber University, Seoul, Republic of Korea,San-Duk Yang, Department of Cyber Security & AI technology, The School of Integrated Software and Design, Kyung Hee Cyber University, 26, Kung Heed ae-ro, Dongdaemoon-gu, Seoul 02447, Republic of Korea.
| | - Hyun-Seok Park
- Bioinformatics Laboratory, ELTEC College of Engineering, Ewha Womans University, Seoul, Republic of Korea,Center for Convergence Research of Advanced Technologies, Ewha Womans University, Seoul, Republic of Korea
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Aouissi HA, Kechebar MSA, Ababsa M, Roufayel R, Neji B, Petrisor AI, Hamimes A, Epelboin L, Ohmagari N. The Importance of Behavioral and Native Factors on COVID-19 Infection and Severity: Insights from a Preliminary Cross-Sectional Study. Healthcare (Basel) 2022; 10:healthcare10071341. [PMID: 35885867 PMCID: PMC9323463 DOI: 10.3390/healthcare10071341] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 12/12/2022] Open
Abstract
The COVID-19 pandemic has had a major impact on a global scale. Understanding the innate and lifestyle-related factors influencing the rate and severity of COVID-19 is important for making evidence-based recommendations. This cross-sectional study aims at establishing a potential relationship between human characteristics and vulnerability/resistance to SARS-CoV-2. We hypothesize that the impact of the virus is not the same due to cultural and ethnic differences. A cross-sectional study was performed using an online questionnaire. The methodology included the development of a multi-language survey, expert evaluation, and data analysis. Data were collected using a 13-item pre-tested questionnaire based on a literature review between 9 December 2020 and 21 July 2021. Data were statistically analyzed using logistic regression. For a total of 1125 respondents, 332 (29.5%) were COVID-19 positive; among them, 130 (11.5%) required home-based treatment, and 14 (1.2%) intensive care. The significant and most influential factors on infection included age, physical activity, and health status (p < 0.05), i.e., better physical activity and better health status significantly reduced the possibility of infection, while older age significantly increased it. The severity of infection was negatively associated with the acceptance (adherence and respect) of preventive measures and positively associated with tobacco (p < 0.05), i.e., smoking regularly significantly increases the severity of COVID-19 infection. This suggests the importance of behavioral factors compared to innate ones. Apparently, individual behavior is mainly responsible for the spread of the virus. Therefore, adopting a healthy lifestyle and scrupulously observing preventive measures, including vaccination, would greatly limit the probability of infection and prevent the development of severe COVID-19.
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Affiliation(s)
- Hani Amir Aouissi
- Scientific and Technical Research Center on Arid Regions (CRSTRA), Biskra 07000, Algeria; (M.S.A.K.); (M.A.)
- Laboratoire de Recherche et d’Etude en Aménagement et Urbanisme (LREAU), Université des Sciences et de la Technologie (USTHB), Algiers 16000, Algeria
- Environmental Research Center (CRE), Badji-Mokhtar Annaba University, Annaba 23000, Algeria
- Correspondence: (H.A.A.); (R.R.); Tel.: +21-3662387144 (H.A.A.)
| | - Mohamed Seif Allah Kechebar
- Scientific and Technical Research Center on Arid Regions (CRSTRA), Biskra 07000, Algeria; (M.S.A.K.); (M.A.)
| | - Mostefa Ababsa
- Scientific and Technical Research Center on Arid Regions (CRSTRA), Biskra 07000, Algeria; (M.S.A.K.); (M.A.)
| | - Rabih Roufayel
- College of Engineering and Technology, American University of the Middle East, Kuwait;
- Correspondence: (H.A.A.); (R.R.); Tel.: +21-3662387144 (H.A.A.)
| | - Bilel Neji
- College of Engineering and Technology, American University of the Middle East, Kuwait;
| | - Alexandru-Ionut Petrisor
- Doctoral School of Urban Planning, Ion Mincu University of Architecture and Urbanism, 010014 Bucharest, Romania;
- National Institute for Research and Development in Tourism, 50741 Bucharest, Romania
- National Institute for Research and Development in Constructions, Urbanism and Sustainable Spatial Development URBAN-INCERC, 021652 Bucharest, Romania
| | - Ahmed Hamimes
- Faculty of Medicine, University Salah Boubnider of Constantine 3, Constantine 25000, Algeria;
| | - Loïc Epelboin
- Infectious and Tropical Diseases Department, Centre Hospitalier de Cayenne Andrée Rosemon, 97306 Cayenne, France;
- Centre d’Investigation Clinique (CIC INSERM 1424), Centre Hospitalier de Cayenne Andrée Rosemon, 97306 Cayenne, France
| | - Norio Ohmagari
- Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan;
- AMR Clinical Reference Center, National Center for Global Health and Medicine, Tokyo 162-8655, Japan
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Impact of urbanisation and environmental factors on spatial distribution of COVID-19 cases during the early phase of epidemic in Singapore. Sci Rep 2022; 12:9758. [PMID: 35697756 PMCID: PMC9191550 DOI: 10.1038/s41598-022-12941-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 04/22/2022] [Indexed: 11/26/2022] Open
Abstract
Geographical weighted regression (GWR) can be used to explore the COVID-19 transmission pattern between cases. This study aimed to explore the influence from environmental and urbanisation factors, and the spatial relationship between epidemiologically-linked, unlinked and imported cases during the early phase of the epidemic in Singapore. Spatial relationships were evaluated with GWR modelling. Community COVID-19 cases with residential location reported from 21st January 2020 till 17th March 2020 were considered for analyses. Temperature, relative humidity, population density and urbanisation are the variables used as exploratory variables for analysis. ArcGIS was used to process the data and perform geospatial analyses. During the early phase of COVID-19 epidemic in Singapore, significant but weak correlation of temperature with COVID-19 incidence (significance 0.5–1.5) was observed in several sub-zones of Singapore. Correlations between humidity and incidence could not be established. Across sub-zones, high residential population density and high levels of urbanisation were associated with COVID-19 incidence. The incidence of COVID-19 case types (linked, unlinked and imported) within sub-zones varied differently, especially those in the western and north-eastern regions of Singapore. Areas with both high residential population density and high levels of urbanisation are potential risk factors for COVID-19 transmission. These findings provide further insights for directing appropriate resources to enhance infection prevention and control strategies to contain COVID-19 transmission.
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Asif Z, Chen Z, Stranges S, Zhao X, Sadiq R, Olea-Popelka F, Peng C, Haghighat F, Yu T. Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review. SUSTAINABLE CITIES AND SOCIETY 2022; 81:103840. [PMID: 35317188 PMCID: PMC8925199 DOI: 10.1016/j.scs.2022.103840] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 03/10/2022] [Accepted: 03/12/2022] [Indexed: 05/05/2023]
Abstract
COVID-19 is deemed as the most critical world health calamity of the 21st century, leading to dramatic life loss. There is a pressing need to understand the multi-stage dynamics, including transmission routes of the virus and environmental conditions due to the possibility of multiple waves of COVID-19 in the future. In this paper, a systematic examination of the literature is conducted associating the virus-laden-aerosol and transmission of these microparticles into the multimedia environment, including built environments. Particularly, this paper provides a critical review of state-of-the-art modelling tools apt for COVID-19 spread and transmission pathways. GIS-based, risk-based, and artificial intelligence-based tools are discussed for their application in the surveillance and forecasting of COVID-19. Primary environmental factors that act as simulators for the spread of the virus include meteorological variation, low air quality, pollen abundance, and spatial-temporal variation. However, the influence of these environmental factors on COVID-19 spread is still equivocal because of other non-pharmaceutical factors. The limitations of different modelling methods suggest the need for a multidisciplinary approach, including the 'One-Health' concept. Extended One-Health-based decision tools would assist policymakers in making informed decisions such as social gatherings, indoor environment improvement, and COVID-19 risk mitigation by adapting the control measurements.
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Affiliation(s)
- Zunaira Asif
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada
| | - Zhi Chen
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada
| | - Saverio Stranges
- Department of Epidemiology and Biostatistics, Western University, Ontario, Canada
- Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Xin Zhao
- Department of Animal Science, McGill University, Montreal, Canada
| | - Rehan Sadiq
- School of Engineering (Okanagan Campus), University of British Columbia, Kelowna, BC, Canada
| | | | - Changhui Peng
- Department of Biological Sciences, University of Quebec in Montreal, Canada
| | - Fariborz Haghighat
- Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Canada
| | - Tong Yu
- Department of Civil and Environmental Engineering, University of Alberta, Canada
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Ai H, Nie R, Wang X. Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model. J Transl Med 2022; 20:170. [PMID: 35410263 PMCID: PMC8995909 DOI: 10.1186/s12967-022-03371-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Accepted: 03/28/2022] [Indexed: 12/23/2022] Open
Abstract
Background Although numerous studies have explored the impact of meteorological factors on the epidemic of COVID-19, their relationship remains controversial and needs to be clarified. Methods We assessed the risk effect of various meteorological factors on COVID-19 infection using the distributed lag nonlinear model, based on related data from July 1, 2020, to June 30, 2021, in eight countries, including Portugal, Greece, Egypt, South Africa, Paraguay, Uruguay, South Korea, and Japan, which are in Europe, Africa, South America, and Asia, respectively. We also explored associations between COVID-19 prevalence and individual meteorological factors by the Spearman’s rank correlation test. Results There were significant non-linear relationships between both temperature and relative humidity and COVID-19 prevalence. In the countries located in the Northern Hemisphere with similar latitudes, the risk of COVID-19 infection was the highest at temperature below 5 ℃. In the countries located in the Southern Hemisphere with similar latitudes, their highest infection risk occurred at around 15 ℃. Nevertheless, in most countries, high temperature showed no significant association with reduced risk of COVID-19 infection. The effect pattern of relative humidity on COVID-19 depended on the range of its variation in countries. Overall, low relative humidity was correlated with increased risk of COVID-19 infection, while the high risk of infection at extremely high relative humidity could occur in some countries. In addition, relative humidity had a longer lag effect on COVID-19 than temperature. Conclusions The effects of meteorological factors on COVID-19 prevalence are nonlinear and hysteretic. Although low temperature and relative humidity may lower the risk of COVID-19, high temperature or relative humidity could also be associated with a high prevalence of COVID-19 in some regions.
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Using an Eigenvector Spatial Filtering-Based Spatially Varying Coefficient Model to Analyze the Spatial Heterogeneity of COVID-19 and Its Influencing Factors in Mainland China. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2022. [DOI: 10.3390/ijgi11010067] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
The COVID-19 pandemic has led to many deaths and economic disruptions across the world. Several studies have examined the effect of corresponding health risk factors in different places, but the problem of spatial heterogeneity has not been adequately addressed. The purpose of this paper was to explore how selected health risk factors are related to the pandemic infection rate within different study extents and to reveal the spatial varying characteristics of certain health risk factors. An eigenvector spatial filtering-based spatially varying coefficient model (ESF-SVC) was developed to find out how the influence of selected health risk factors varies across space and time. The ESF-SVC was able to take good control of over-fitting problems compared with ordinary least square (OLS), eigenvector spatial filtering (ESF) and geographically weighted regression (GWR) models, with a higher adjusted R2 and lower cross validation RMSE. The impact of health risk factors varied as the study extent changed: In Hubei province, only population density and wind speed showed significant spatially constant impact; while in mainland China, other factors including migration score, building density, temperature and altitude showed significant spatially varying impact. The influence of migration score was less contributive and less significant in cities around Wuhan than cities further away, while altitude showed a stronger contribution to the decrease of infection rates in high altitude cities. The temperature showed mixed correlation as time passed, with positive and negative coefficients at 2.42 °C and 8.17 °C, respectively. This study could provide a feasible path to improve the model fit by considering the problem of spatial autocorrelation and heterogeneity that exists in COVID-19 modeling. The yielding ESF-SVC coefficients could also provide an intuitive method for discovering the different impacts of influencing factors across space in large study areas. It is hoped that these findings improve public and governmental awareness of potential health risks and therefore influence epidemic control strategies.
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Marquès M, Domingo JL. Positive association between outdoor air pollution and the incidence and severity of COVID-19. A review of the recent scientific evidences. ENVIRONMENTAL RESEARCH 2022; 203:111930. [PMID: 34425111 PMCID: PMC8378989 DOI: 10.1016/j.envres.2021.111930] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 08/19/2021] [Indexed: 05/04/2023]
Abstract
In June 2020, we published a review focused on assessing the influence of various air pollutants on the transmission of SARS-CoV-2, and the severity of COVID-19 in patients infected by the coronavirus. The results of most of those reviewed studies suggested that chronic exposure to certain air pollutants might lead to more severe and lethal forms of COVID-19, as well as delays/complications in the recovery of the patients. Since then, a notable number of studies on this topic have been published, including also various reviews. Given the importance of this issue, we have updated the information published since our previous review. Taking together the previous results and those of most investigations now reviewed, we have concluded that there is a significant association between chronic exposure to various outdoor air pollutants: PM2.5, PM10, O3, NO2, SO2 and CO, and the incidence/risk of COVID-19 cases, as well as the severity/mortality of the disease. Unfortunately, studies on the potential influence of other important air pollutants such as VOCs, dioxins and furans, or metals, are not available in the scientific literature. In relation to the influence of outdoor air pollutants on the transmission of SARS-CoV-2, although the scientific evidence is much more limited, some studies point to PM2.5 and PM10 as potential airborne transmitters of the virus. Anyhow, it is clear that environmental air pollution plays an important negative role in COVID-19, increasing its incidence and mortality.
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Affiliation(s)
- Montse Marquès
- Laboratory of Toxicology and Environmental Health, Universitat Rovira i Virgili, School of Medicine, Sant Llorens 21, 43201, Reus, Catalonia, Spain.
| | - José L Domingo
- Laboratory of Toxicology and Environmental Health, Universitat Rovira i Virgili, School of Medicine, Sant Llorens 21, 43201, Reus, Catalonia, Spain
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Han Y, Lam JCK, Li VOK, Crowcroft J, Fu J, Downey J, Gozes I, Zhang Q, Wang S, Gilani Z. Outdoor PM 2.5 concentration and rate of change in COVID-19 infection in provincial capital cities in China. Sci Rep 2021; 11:23206. [PMID: 34853387 PMCID: PMC8636470 DOI: 10.1038/s41598-021-02523-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 11/08/2021] [Indexed: 01/13/2023] Open
Abstract
This study investigates thoroughly whether acute exposure to outdoor PM2.5 concentration, P, modifies the rate of change in the daily number of COVID-19 infections (R) across 18 high infection provincial capitals in China, including Wuhan. A best-fit multiple linear regression model was constructed to model the relationship between P and R, from 1 January to 20 March 2020, after accounting for meteorology, net move-in mobility (NM), time trend (T), co-morbidity (CM), and the time-lag effects. Regression analysis shows that P (β = 0.4309, p < 0.001) is the most significant determinant of R. In addition, T (β = -0.3870, p < 0.001), absolute humidity (AH) (β = 0.2476, p = 0.002), P × AH (β = -0.2237, p < 0.001), and NM (β = 0.1383, p = 0.003) are more significant determinants of R, as compared to GDP per capita (β = 0.1115, p = 0.015) and CM (Asthma) (β = 0.1273, p = 0.005). A matching technique was adopted to demonstrate a possible causal relationship between P and R across 18 provincial capital cities. A 10 µg/m3 increase in P gives a 1.5% increase in R (p < 0.001). Interaction analysis also reveals that P × AH and R are negatively correlated (β = -0.2237, p < 0.001). Given that P exacerbates R, we recommend the installation of air purifiers and improved air ventilation to reduce the effect of P on R. Given the increasing observation that COVID-19 is airborne, measures that reduce P, plus mandatory masking that reduces the risks of COVID-19 associated with viral-particulate transmission, are strongly recommended. Our study is distinguished by the focus on the rate of change instead of the individual cases of COVID-19 when modelling the statistical relationship between R and P in China; causal instead of correlation analysis via the matching analysis, while taking into account the key confounders, and the individual plus the interaction effects of P and AH on R.
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Affiliation(s)
- Yang Han
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Jacqueline C K Lam
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong.
| | - Victor O K Li
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong.
| | - Jon Crowcroft
- Department of Computer Science and Technology, The University of Cambridge, Cambridge, UK
| | - Jinqi Fu
- MRC Cancer Unit, Department of Oncology, The University of Cambridge, Cambridge, UK
| | - Jocelyn Downey
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Illana Gozes
- Department of Human Molecular Genetics and Biochemistry, Sackler Faculty of Medicine, Adams Super Center for Brain Studies and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Qi Zhang
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Shanshan Wang
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Zafar Gilani
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong
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13
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Xie Z, Zhao R, Ding M, Zhang Z. A Review of Influencing Factors on Spatial Spread of COVID-19 Based on Geographical Perspective. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:12182. [PMID: 34831938 PMCID: PMC8620996 DOI: 10.3390/ijerph182212182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 11/08/2021] [Accepted: 11/12/2021] [Indexed: 11/29/2022]
Abstract
The COVID-19 outbreak is a manifestation of the contradiction between man and land. Geography plays an important role in epidemic prevention and control with its cross-sectional characteristics and spatial perspective. Based on a systematic review of previous studies, this paper summarizes the research progress on factors influencing the spatial spread of COVID-19 from the research content and method and proposes the main development direction of geography in epidemic prevention and control research in the future. Overall, current studies have explored the factors influencing the epidemic spread on different scales, including global, national, regional and urban. Research methods are mainly composed of quantitative analysis. In addition to the traditional regression analysis and correlation analysis, the spatial lag model, the spatial error model, the geographically weighted regression model and the geographic detector have been widely used. The impact of natural environment and economic and social factors on the epidemic spread is mainly reflected in temperature, humidity, wind speed, air pollutants, population movement, economic development level and medical and health facilities. In the future, new technologies, new methods and new means should be used to reveal the driving mechanism of the epidemic spread in a specific geographical space, which is refined, multi-scale and systematic, with emphasis on exploring the factors influencing the epidemic spread from the perspective of spatial and behavioral interaction, and establish a spatial database platform that combines the information of residents' cases, the natural environment and economic society. This is of great significance to further play the role of geography in epidemic prevention and control.
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Affiliation(s)
- Zhixiang Xie
- College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China; (Z.X.); (M.D.); (Z.Z.)
- Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng 475001, China
| | - Rongqin Zhao
- College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China; (Z.X.); (M.D.); (Z.Z.)
| | - Minglei Ding
- College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China; (Z.X.); (M.D.); (Z.Z.)
| | - Zhiqiang Zhang
- College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China; (Z.X.); (M.D.); (Z.Z.)
- Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Henan University, Ministry of Education, Kaifeng 475004, China
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14
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Dutta A, Dutta G. Association of air pollution and meteorological variables with the two waves of COVID-19 pandemic in Delhi: A critical analysis. Heliyon 2021; 7:e08468. [PMID: 34841120 PMCID: PMC8610833 DOI: 10.1016/j.heliyon.2021.e08468] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 07/01/2021] [Accepted: 11/19/2021] [Indexed: 12/23/2022] Open
Abstract
Various countries across the globe have been affected by different COVID-19 waves at different points in time and with varying levels of virulence. With the backdrop of the two COVID-19 waves that broke out in Delhi, this study examines the variations in the concentrations of criteria pollutants, air quality, and meteorological variables across the waves and their influence on COVID-19 morbidity/mortality. Descriptive statistics, violin plots, and Spearman rank correlation tests were employed to assess the variations in environmental parameters and investigate their associations with COVID-19 incidence under the two waves. The susceptible-infected-recovered model and multiple linear regression were used to assess the wave-wise basic reproduction number (R0) and infection spreading trajectory of the virus. Our results show that the first wave in Delhi had three successive peaks and valleys, and the first peak of the second wave was the tallest, indicating the severity of per-day infection cases. During the analysed period (April 2020 and April 2021), concentrations of criteria pollutants varied across the waves, and air pollution was substantially higher during the second wave. In addition, the results revealed that during the second wave, NO2 maintained a significant negative relationship with COVID-19 (cases per day), while SO2 had a negative relationship with COVID-19 (cumulative cases) during the first wave. Our results also show a significant positive association of O3 with COVID-19 deaths during the first wave and cumulative cases and deaths during the second wave. The study indicates that a higher relative humidity in Delhi had a negative relation with COVID-19 cumulative cases and mortality during the first wave. The study confirms that the estimated R0 was marginally different during the two waves, and the spread of COVID-19 new cases followed a cubic growth trajectory. The findings of this study provide valuable information for policymakers in handling COVID-19 waves in various cities.
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Affiliation(s)
- Abhishek Dutta
- Department of Environmental Science, Faculty of Science, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok 10330, Thailand
| | - Gautam Dutta
- Department of Management Studies, Indian Institute of Foreign Trade, 1583, Madurdaha, Kolkata, West Bengal 700100, India
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15
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Ali G, Abbas S, Qamer FM, Irteza SM. Environmental spatial heterogeneity of the impacts of COVID-19 on the top-20 metropolitan cities of Asia-Pacific. Sci Rep 2021; 11:20339. [PMID: 34645879 PMCID: PMC8514535 DOI: 10.1038/s41598-021-99546-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/27/2021] [Indexed: 12/23/2022] Open
Abstract
This study investigated the environmental spatial heterogeneity of novel coronavirus (COVID-19) and spatial and temporal changes among the top-20 metropolitan cities of the Asia-Pacific. Remote sensing-based assessment is performed to analyze before and during the lockdown amid COVID-19 lockdown in the cities. Air pollution and mobility data of each city (Bangkok, Beijing, Busan, Dhaka, Delhi, Ho Chi Minh, Hong Kong, Karachi, Mumbai, Seoul, Shanghai, Singapore, Tokyo, Wuhan, and few others) have been collected and analyzed for 2019 and 2020. Results indicated that almost every city was impacted positively regarding environmental emissions and visible reduction were found in Aerosol Optical Depth (AOD), sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations before and during lockdown periods of 2020 as compared to those of 2019. The highest NO2 emission reduction (~ 50%) was recorded in Wuhan city during the lockdown of 2020. AOD was highest in Beijing and lowest in Colombo (< 10%). Overall, 90% movement was reduced till mid-April, 2020. A 98% reduction in mobility was recorded in Delhi, Seoul, and Wuhan. This analysis suggests that smart mobility and partial shutdown policies could be developed to reduce environmental pollutions in the region. Wuhan city is one of the benchmarks and can be replicated for the rest of the Asian cities wherever applicable.
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Affiliation(s)
- Ghaffar Ali
- College of Management, Shenzhen University, Shenzhen, 518060, Guangdong, China
| | - Sawaid Abbas
- Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
| | - Faisal Mueen Qamer
- International Center for Integrated Mountain Development (ICIMOD), Kathmandu, 44700, Nepal
| | - Syed Muhammad Irteza
- Remote Sensing, GIS and Climatic Research Lab (RSGCRL), National Center of GIS and Space Applications, University of the Punjab, Lahore, Pakistan
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16
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Naik PA, Zu J, Ghori MB, Naik MUD. Modeling the effects of the contaminated environments on COVID-19 transmission in India. RESULTS IN PHYSICS 2021; 29:104774. [PMID: 34493968 PMCID: PMC8413511 DOI: 10.1016/j.rinp.2021.104774] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 08/26/2021] [Accepted: 08/28/2021] [Indexed: 05/15/2023]
Abstract
COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that caused an outbreak of typical pneumonia first in Wuhan and then globally. Although researchers focus on the human-to-human transmission of this virus but not much research is done on the dynamics of the virus in the environment and the role humans play by releasing the virus into the environment. In this paper, a novel nonlinear mathematical model of the COVID-19 epidemic is proposed and analyzed under the effects of the environmental virus on the transmission patterns. The model consists of seven population compartments with the inclusion of contaminated environments means there is a chance to get infected by the virus in the environment. We also calculated the threshold quantity R 0 to know the disease status and provide conditions that guarantee the local and global asymptotic stability of the equilibria using Volterra-type Lyapunov functions, LaSalle's invariance principle, and the Routh-Hurwitz criterion. Furthermore, the sensitivity analysis is performed for the proposed model that determines the relative importance of the disease transmission parameters. Numerical experiments are performed to illustrate the effectiveness of the obtained theoretical results.
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Affiliation(s)
- Parvaiz Ahmad Naik
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Jian Zu
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Muhammad Bilal Ghori
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Mehraj-Ud-Din Naik
- Department of Chemical Engineering, College of Engineering, Jazan University, Jazan 45142, Saudi Arabia
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