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Gharaibeh A, Gharaibeh MA, Bataineh S, Kecerová AM. Exploring the Spatial and Temporal Patterns of Children and Adolescents with COVID-19 Infections in Slovakia during March 2020 to July 2022. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:931. [PMID: 38929548 PMCID: PMC11205471 DOI: 10.3390/medicina60060931] [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: 04/16/2024] [Revised: 05/11/2024] [Accepted: 05/30/2024] [Indexed: 06/28/2024]
Abstract
Background and Objectives: The COVID-19 pandemic has had a significant global impact, necessitating a comprehensive understanding of its spatiotemporal patterns. The objective of this study is to explore the spatial and temporal patterns of COVID-19 infections among five age groups (<1, 1-4, 5-9, 10-14, and 15-19 years) in 72 districts of Slovakia on a quarterly basis from March 2020 to July 2022. Material and Methods: During the study period, a total of 393,429 confirmed PCR cases of COVID-19 or positive antigen tests were recorded across all studied age groups. The analysis examined the spatiotemporal spread of COVID infections per quarter, from September 2021 to May 2022. Additionally, data on hospitalizations, intensive care unit (ICU) admissions, pulmonary ventilation (PV), and death cases were analyzed. Results: The highest number of COVID-19 infections occurred between September 2021 and May 2022, particularly in the 10-14-year-old group (68,695 cases), followed by the 15-19-year-old group (62,232 cases), while the lowest incidence was observed in the <1-year-old group (1235 cases). Out of the total confirmed PCR cases, 18,886 individuals required hospitalization, 456 needed ICU admission, 402 received pulmonary ventilation, and only 16 died. The analysis of total daily confirmed PCR cases for all regions showed two major peaks on 12 December 2021 (6114 cases) and 1 February 2022 (3889 cases). Spatial mapping revealed that during December 2021 to February 2022, the highest number of infections in all age groups were concentrated mainly in Bratislava. Moreover, temporal trends of infections within each age group, considering monthly and yearly variations, exhibited distinct spatial patterns, indicating localized outbreaks in specific regions. Conclusions: The spatial and temporal patterns of COVID-19 infections among different age groups in Slovakia showed a higher number of infections in the 10-14-year-old age group, mainly occurring in urban districts. The temporal pattern of the spread of the virus to neighboring urban and rural districts reflected the movement of infected individuals. Hospitalizations, ICU and PV admissions, and deaths were relatively low. The study highlights the need for more proactive measures to contain outbreaks promptly and ensure the resilience of healthcare systems against future pandemics.
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Affiliation(s)
- Ahmad Gharaibeh
- Teaching Department of Orthopaedics Musculoskeletal Trauma, Faculty of Medicine, University Hospital of Louise Pasteur, Pavel Jozef Safarik University, 040 11 Košice, Slovakia
| | - Mamoun A. Gharaibeh
- Department of Natural Resources and the Environment, Faculty of Agriculture, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan
| | - Siham Bataineh
- Department of Civil Engineering, Faculty of Engineering, Jordan University of Science and Technology, P.O. Box 3030, Irbid 22110, Jordan;
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Auliya AA, Syafarina I, Latifah AL, Wiharto. Significance of weather condition, human mobility, and vaccination on global COVID-19 transmission. Spat Spatiotemporal Epidemiol 2024; 48:100635. [PMID: 38355259 DOI: 10.1016/j.sste.2024.100635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 01/03/2024] [Accepted: 01/15/2024] [Indexed: 02/16/2024]
Abstract
The transmission growth rate of infectious diseases, particularly COVID-19, has forced governments to take immediate control decisions. Previous studies have shown that human mobility, weather condition, and vaccination are potential factors influencing virus transmission. This study investigates the contribution of weather conditions, namely temperature and precipitation, human mobility, and vaccination to coronavirus transmission. Three machine learning models: random forest (RF), XGBoost, and neural networks, are applied to predict the confirmed cases based on three aforementioned variables. All models' prediction are evaluated via spatial and temporal analysis. The spatial analysis observes the model performance over countries on certain times. The temporal analysis looks at the model prediction of each country during the specified period. The models' prediction results effectively indicate the transmission trend. The RF model performs best with a coefficient of determination of up to 89%. Meanwhile, all models confirm that vaccination is most significantly associated with COVID-19 cases.
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Affiliation(s)
- Amandha Affa Auliya
- Research Center for Computing, National Research and Innovation Agency, Jl. Raya Jakarta Bogor KM 46, Cibinong, 16911, Indonesia; Sebelas Maret University, Jl. Ir Sutami No. 36, Surakarta, 57126, Indonesia
| | - Inna Syafarina
- Research Center for Computing, National Research and Innovation Agency, Jl. Raya Jakarta Bogor KM 46, Cibinong, 16911, Indonesia
| | - Arnida L Latifah
- Research Center for Computing, National Research and Innovation Agency, Jl. Raya Jakarta Bogor KM 46, Cibinong, 16911, Indonesia; School of Computing, Telkom University, Jl. Telekomunikasi No. 1, Bandung, 40257, Indonesia.
| | - Wiharto
- Sebelas Maret University, Jl. Ir Sutami No. 36, Surakarta, 57126, Indonesia
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3
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Wan X, Cheng C, Zhang Z. Transmission rate and control efficiency of COVID-19 was lower in warm and wet climate. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:575-586. [PMID: 36571851 DOI: 10.1080/09603123.2022.2160433] [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: 10/21/2022] [Accepted: 12/14/2022] [Indexed: 01/23/2024]
Abstract
COVID-19 has caused huge damage to public health around the world, revealing the influencing factors are essential to take effective control. By using a global dataset covering 617 time series over the world, we estimated the transmission parameters and modeled human and climate effects on COVID-19 transmission. We found that the average transmission rate was lower in warm climate over the world and in wet climate (more precipitation) in Europe. The maximum transmission rate was lower in warm climate in the world, China and USA, and in wet climate in China. The control efficiency in the world, China, and USA was lower in warm and wet condition. In general, our results indicate that warm and wet climate do not favor transmission and human intervention of COVID-19, and COVID-19 transmission rate would be lower in warm and wet seasons or regions than in dry and cold ones.
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Affiliation(s)
- Xinru Wan
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
| | - Chaoyuan Cheng
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zhibin Zhang
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
- CAS Center for Excellence in Biotic Interactions, University of Chinese Academy of Sciences, Beijing, China
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4
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Townsend JP, Hassler HB, Lamb AD, Sah P, Alvarez Nishio A, Nguyen C, Tew AD, Galvani AP, Dornburg A. Seasonality of endemic COVID-19. mBio 2023; 14:e0142623. [PMID: 37937979 PMCID: PMC10746271 DOI: 10.1128/mbio.01426-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/04/2023] [Indexed: 11/09/2023] Open
Abstract
Successive waves of infection by SARS-CoV-2 have left little doubt that this virus will transition to an endemic disease. Foreknowledge of when to expect seasonal surges is crucial for healthcare and public health decision-making. However, the future seasonality of COVID-19 remains uncertain. Evaluating its seasonality is complicated due to the limited years of SARS-CoV-2 circulation, pandemic dynamics, and varied interventions. In this study, we project the expected endemic seasonality by employing a phylogenetic ancestral and descendant state approach that leverages long-term data on the incidence of circulating HCoV coronaviruses. Our projections indicate asynchronous surges of SARS-CoV-2 across different locations in the northern hemisphere, occurring between October and January in New York and between January and March in Yamagata, Japan. This knowledge of spatiotemporal surges leads to medical preparedness and enables the implementation of targeted public health interventions to mitigate COVID-19 transmission.IMPORTANCEThe seasonality of COVID-19 is important for effective healthcare and public health decision-making. Previous waves of SARS-CoV-2 infections have indicated that the virus will likely persist as an endemic pathogen with distinct surges. However, the timing and patterns of potentially seasonal surges remain uncertain, rendering effective public health policies uninformed and in danger of poorly anticipating opportunities for intervention, such as well-timed booster vaccination drives. Applying an evolutionary approach to long-term data on closely related circulating coronaviruses, our research provides projections of seasonal surges that should be expected at major temperate population centers. These projections enable local public health efforts that are tailored to expected surges at specific locales or regions. This knowledge is crucial for enhancing medical preparedness and facilitating the implementation of targeted public health interventions.
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Affiliation(s)
- Jeffrey P. Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, USA
- Program in Microbiology, Yale University, New Haven, USA
| | - Hayley B. Hassler
- Department of Biostatistics, Yale School of Public Health, New Haven, USA
| | - April D. Lamb
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, USA
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis, Yale University, New Haven, USA
| | | | - Cameron Nguyen
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, USA
| | - Alexandra D. Tew
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, USA
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis, Yale University, New Haven, USA
| | - Alex Dornburg
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, USA
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5
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Xiong R, Li X. Geospatial analysis in the United States reveals the changing roles of temperature on COVID-19 transmission. GEOSPATIAL HEALTH 2023; 18. [PMID: 37470265 DOI: 10.4081/gh.2023.1213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/30/2023] [Indexed: 07/21/2023]
Abstract
Environmental factors are known to affect outbreak patterns of infectious disease, but their impacts on the spread of COVID-19 along with the evolution of this relationship over time intervals and in different regions are unclear. This study utilized 3 years of data on COVID-19 cases in the continental United States from 2020 to 2022 and the corresponding weather data. We used regression analysis to investigate weather impacts on COVID-19 spread in the mainland United States and estimate the changes of these impacts over space and time. Temperature exhibited a significant and moderately strong negative correlation for most of the US while relative humidity and precipitation experienced mixed relationships. By regressing temperature factors with the spreading rate of waves, we found temperature change can explain over 20% of the spatial-temporal variation in the COVID-19 spreading, with a significant and negative response between temperature change and spreading rate. The pandemic in the continental United States during 2020-2022 was characterized by seven waves, with different transmission rates and wave peaks concentrated in seven time periods. When repeating the analysis for waves in the seven periods and nine climate zones, we found temperature impacts evolve over time and space, possibly due to virus mutation, changes in population susceptibility, social behavior, and control measures. Temperature impacts became weaker in 6 of 9 climate zones from the beginning of the epidemic to the end of 2022, suggesting that COVID-19 has increasingly adapted to wider weather conditions.
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Affiliation(s)
| | - Xiaolong Li
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL.
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6
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Mantilla Caicedo GC, Rusticucci M, Suli S, Dankiewicz V, Ayala S, Caiman Peñarete A, Díaz M, Fontán S, Chesini F, Jiménez-Buitrago D, Barreto Pedraza LR, Barrera F. Spatio-temporal multidisciplinary analysis of socio-environmental conditions to explore the COVID-19 early evolution in urban sites in South America. Heliyon 2023; 9:e16056. [PMID: 37200576 PMCID: PMC10162854 DOI: 10.1016/j.heliyon.2023.e16056] [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] [Received: 12/01/2021] [Revised: 04/24/2023] [Accepted: 05/03/2023] [Indexed: 05/20/2023] Open
Abstract
This study aimed to analyse how socio-environmental conditions affected the early evolution of COVID-19 in 14 urban sites in South America based on a spatio-temporal multidisciplinary approach. The daily incidence rate of new COVID-19 cases with symptoms as the dependent variable and meteorological-climatic data (mean, maximum, and minimum temperature, precipitation, and relative humidity) as the independent variables were analysed. The study period was from March to November of 2020. We inquired associations of these variables with COVID-19 data using Spearman's non-parametric correlation test, and a principal component analysis considering socio economic and demographic variables, new cases, and rates of COVID-19 new cases. Finally, an analysis using non-metric multidimensional scale ordering by the Bray-Curtis similarity matrix of meteorological data, socio economic and demographic variables, and COVID-19 was performed. Our findings revealed that the average, maximum, and minimum temperatures and relative humidity were significantly associated with rates of COVID-19 new cases in most of the sites, while precipitation was significantly associated only in four sites. Additionally, demographic variables such as the number of inhabitants, the percentage of the population aged 60 years and above, the masculinity index, and the GINI index showed a significant correlation with COVID-19 cases. Due to the rapid evolution of the COVID-19 pandemic, these findings provide strong evidence that biomedical, social, and physical sciences should join forces in truly multidisciplinary research that is critically needed in the current state of our region.
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Affiliation(s)
| | - Matilde Rusticucci
- Universidad de Buenos Aires, Departamento de Ciencias de la Atmósfera y los Océanos, CONICET, Argentina
| | - Solange Suli
- Universidad de Buenos Aires, Departamento de Ciencias de la Atmósfera y los Océanos, CONICET, Argentina
| | - Verónica Dankiewicz
- Universidad de Buenos Aires, Departamento de Ciencias de la Atmósfera y los Océanos, CONICET, Argentina
| | - Salvador Ayala
- Universidad de Chile, Programa de Doctorado en Salud Pública, Instituto de Salud Pública de Chile, Chile
| | - Alexandra Caiman Peñarete
- Subred Integrada de Servicios Hospitalarios Centro Oriente ESE, Red Hospitalaria Bogotá Distrito Capital, Colombia
| | - Martín Díaz
- Universidad Nacional de La Matanza, Departamento de Ciencias de la Salud, Argentina
| | - Silvia Fontán
- Universidad Nacional de La Matanza, Departamento de Ciencias de la Salud, Argentina
| | | | - Diana Jiménez-Buitrago
- Ministerio de Salud y Protección Social, Mesa de Variabilidad y Cambio Climático de la CONASA, Colombia
| | - Luis R. Barreto Pedraza
- Instituto de Hidrología, Meteorología y Estudios Ambientales - IDEAM, Subdirección de Meteorología, Mesa de Variabilidad y Cambio Climático de la CONASA, Miembro del grupo QuASAR UPN, Colombia
| | - Facundo Barrera
- Centro Austral de Investigaciones Científicas (CADIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Ushuaia, Argentina
- Centro i∼mar, Universidad de Los Lagos, Chile and Centre for Climate and Resilience Research (CR)2, Casilla 557, Puerto Montt Chile
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7
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Bhaskar A, Chandra J, Hashemi H, Butler K, Bennett L, Cellini J, Braun D, Dominici F. A Literature Review of the Effects of Air Pollution on COVID-19 Health Outcomes Worldwide: Statistical Challenges and Data Visualization. Annu Rev Public Health 2023; 44:1-20. [PMID: 36542771 DOI: 10.1146/annurev-publhealth-071521-120424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Several peer-reviewed papers and reviews have examined the relationship between exposure to air pollution and COVID-19 spread and severity. However, many of the existing reviews on this topic do not extensively present the statistical challenges associated with this field, do not provide comprehensive guidelines for future researchers, and review only the results of a relatively small number of papers. We reviewed 139 papers, 127 of which reported a statistically significant positive association between air pollution and adverse COVID-19 health outcomes. Here, we summarize the evidence, describe the statistical challenges, and make recommendations for future research. To summarize the 139 papers with data from geographical locations around the world, we also present anopen-source data visualization tool that summarizes these studies and allows the research community to contribute evidence as new research papers are published.
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Affiliation(s)
- A Bhaskar
- Department of Government, Harvard University, Cambridge, Massachusetts, USA
| | - J Chandra
- Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - H Hashemi
- Environmental Systems Research Institute, Redlands, California, USA
| | - K Butler
- Environmental Systems Research Institute, Redlands, California, USA
| | - L Bennett
- Environmental Systems Research Institute, Redlands, California, USA
| | - Jacqueline Cellini
- Countway Library of Medicine, Harvard Medical School, Harvard University, Boston, Massachusetts, USA
| | - Danielle Braun
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA;
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Francesca Dominici
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA;
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8
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Hu Z, Zhu S. Impact of the COVID-19 outbreak on China's tourism economy and green finance efficiency. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:49963-49979. [PMID: 36787070 PMCID: PMC9926458 DOI: 10.1007/s11356-023-25406-w] [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: 11/17/2022] [Accepted: 01/15/2023] [Indexed: 04/16/2023]
Abstract
As a result of the COVID-19 pandemic, production costs have grown, while human and economic resources have been reduced. COVID-19 epidemic costs can be reduced by implementing green financial policies, including carbon pricing, transferable green certificates, and green credit. In addition, China's tourist industry is a significant source of revenue for the government. Coronavirus has been found in 30 Chinese regions, and a study is being conducted to determine its influence on the tourism business and green financial efficiency. Econometric strategies that are capable of dealing with the most complex issues are employed in this study. According to the GMM system, the breakout of Covid-19 had a negative effect on the tourism business and the efficiency of green financing. Aside from that, the effects of gross capital creation, infrastructural expansion, and renewable energy consumption are all good. The influence of per capita income on the tourism industry is beneficial but detrimental to the efficiency of green finance. Due to the current pandemic condition, this report presents a number of critical recommendations for boosting tourism and green financial efficiency.
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Affiliation(s)
- Zhaolin Hu
- Henan Polytechnic, Zhengzhou, 450000 China
| | - Suting Zhu
- Henan Polytechnic, Zhengzhou, 450000 China
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9
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Chang L, Mohsin M, Iqbal W. Assessing the nexus between COVID-19 pandemic-driven economic crisis and economic policy: lesson learned and challenges. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:22145-22158. [PMID: 36282386 PMCID: PMC9593987 DOI: 10.1007/s11356-022-23650-0] [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: 03/31/2022] [Accepted: 08/05/2022] [Indexed: 05/04/2023]
Abstract
This study examines China's budgetary policy during the COVID-19 pandemic as a result of China's insufficient ability to deal with a new crisis when the epidemic struck in March 2020 and as a result of the economic crisis that began in China in March 2020. In order to better comprehend China's economic status during COVID-19, the study relies on secondary data. The fiscal response of emerging market economies like India is less than in advanced economies. However, it is generally considered to be in line with the average for emerging market economies. As a result of the Disaster Management authority imposing a rigorous lockdown, unemployment rose, the trade cycle was interrupted, and manufacturing and service activities were affected. According to the study's findings, China's economic policies, namely its fiscal policy, responded in the years leading up to 2019 by increasing health expenditure, income transfer, welfare payments, subsidies, and reducing short-term unemployment. As a result of the COVID-19 pandemic, China's government has adopted a number of measures to minimize the damage to the economy. This article also focuses on China's numerous budgetary actions with COVID-19.
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Affiliation(s)
- Lei Chang
- School of Economics, PEKING University, Beijing, 100871 China
| | - Muhammad Mohsin
- School of Finance and Economics, Jiangsu University, Zhenjiang, 212013 China
| | - Wasim Iqbal
- Department of Business Administration, ILMA University, Karachi, 75190 Pakistan
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Moazeni M, Rahimi M, Ebrahimi A. What are the Effects of Climate Variables on COVID-19 Pandemic? A Systematic Review and Current Update. Adv Biomed Res 2023; 12:33. [PMID: 37057247 PMCID: PMC10086649 DOI: 10.4103/abr.abr_145_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Revised: 01/05/2022] [Accepted: 01/19/2022] [Indexed: 04/15/2023] Open
Abstract
The climatological parameters can be different in various geographical locations. Moreover, they have possible impacts on COVID-19 incidence. Therefore, the purpose of this systematic review article was to describe the effects of climatic variables on COVID-19 pandemic in different countries. Systematic literature search was performed in Scopus, ISI Web of Science, and PubMed databases using ("Climate" OR "Climate Change" OR "Global Warming" OR "Global Climate Change" OR "Meteorological Parameters" OR "Temperature" OR "Precipitation" OR "Relative Humidity" OR "Wind Speed" OR "Sunshine" OR "Climate Extremes" OR "Weather Extremes") AND ("COVID" OR "Coronavirus disease 2019" OR "COVID-19" OR "SARS-CoV-2" OR "Novel Coronavirus") keywords. From 5229 articles, 424 were screened and 149 were selected for further analysis. The relationship between meteorological parameters is variable in different geographical locations. The results indicate that among the climatic indicators, the temperature is the most significant factor that influences on COVID-19 pandemic in most countries. Some studies were proved that warm and wet climates can decrease COVID-19 incidence; however, the other studies represented that warm location can be a high risk of COVID-19 incidence. It could be suggested that all climate variables such as temperature, humidity, rainfall, precipitation, solar radiation, ultraviolet index, and wind speed could cause spread of COVID-19. Thus, it is recommended that future studies will survey the role of all meteorological variables and interaction between them on COVID-19 spread in specific small areas such as cities of each country and comparison between them.
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Affiliation(s)
- Malihe Moazeni
- Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
- Student Research Committee, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad Rahimi
- Department of Combat Desertification, Faculty of Desert Studies, Semnan University, Semnan, Iran
| | - Afshin Ebrahimi
- Department of Environmental Health Engineering, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
- Environment Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
- Address for correspondence: Dr. Afshin Ebrahimi, Department of Environmental Health Engineering, School of Health, Hezar-Jerib Ave., Isfahan University of Medical Sciences, Isfahan, 81676 − 36954, Iran. E-mail:
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Zhang L, Han X, Wu J, Wang L. Mechanisms influencing the factors of urban built environments and coronavirus disease 2019 at macroscopic and microscopic scales: The role of cities. Front Public Health 2023; 11:1137489. [PMID: 36935684 PMCID: PMC10016229 DOI: 10.3389/fpubh.2023.1137489] [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: 01/04/2023] [Accepted: 02/02/2023] [Indexed: 03/05/2023] Open
Abstract
In late 2019, the coronavirus disease 2019 (COVID-19) pandemic soundlessly slinked in and swept the world, exerting a tremendous impact on lifestyles. This study investigated changes in the infection rates of COVID-19 and the urban built environment in 45 areas in Manhattan, New York, and the relationship between the factors of the urban built environment and COVID-19. COVID-19 was used as the outcome variable, which represents the situation under normal conditions vs. non-pharmacological intervention (NPI), to analyze the macroscopic (macro) and microscopic (micro) factors of the urban built environment. Computer vision was introduced to quantify the material space of urban places from street-level panoramic images of the urban streetscape. The study then extracted the microscopic factors of the urban built environment. The micro factors were composed of two parts. The first was the urban level, which was composed of urban buildings, Panoramic View Green View Index, roads, the sky, and buildings (walls). The second was the streets' green structure, which consisted of macrophanerophyte, bush, and grass. The macro factors comprised population density, traffic, and points of interest. This study analyzed correlations from multiple levels using linear regression models. It also effectively explored the relationship between the urban built environment and COVID-19 transmission and the mechanism of its influence from multiple perspectives.
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Affiliation(s)
- Longhao Zhang
- School of Architecture, Tianjin Chengjian University, Tianjin, China
| | - Xin Han
- Department of Landscape Architecture, Kyungpook National University, Daegu, Republic of Korea
| | - Jun Wu
- School of Architecture, Tianjin Chengjian University, Tianjin, China
- *Correspondence: Jun Wu
| | - Lei Wang
- School of Architecture, Tianjin University, Tianjin, China
- Lei Wang
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12
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Mwiinde AM, Siankwilimba E, Sakala M, Banda F, Michelo C. Climatic and Environmental Factors Influencing COVID-19 Transmission-An African Perspective. Trop Med Infect Dis 2022; 7:tropicalmed7120433. [PMID: 36548688 PMCID: PMC9785776 DOI: 10.3390/tropicalmed7120433] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/01/2022] [Accepted: 12/03/2022] [Indexed: 12/14/2022] Open
Abstract
Since the outbreak of COVID-19 was decreed by the World Health Organization as a public health emergency of worldwide concern, the epidemic has drawn attention from all around the world. The disease has since spread globally in developed and developing countries. The African continent has not been spared from the pandemic; however, the low number of cases in Africa compared to developed countries has brought about more questions than answers. Africa is known to have a poor healthcare system that cannot sustain the emerging infectious disease pandemic. This study explored climatic and environmental elements influencing COVID-19 transmission in Africa. This study involved manuscripts and data that evaluated and investigated the climatic and environmental elements of COVID-19 in African countries. Only articles written in English were considered in the systematic review. Seventeen articles and one database were selected for manuscript write-ups after the review process. The findings indicated that there is evidence that suggests the influence of climatic and environmental elements on the spread of COVID-19 in the continent of Africa; however, the evidence needs more investigation in all six regions of Africa and at the country level to understand the role of weather patterns and environmental aspects in the transmission of COVID-19.
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Affiliation(s)
- Allan Mayaba Mwiinde
- Graduate School of Public Health, Department of Epidemiology Ridgeway Campus, University of Zambia, Lusaka P.O. Box 50516, Zambia
- Department of Public Health, Mazabuka Municipal Council, Mazabuka P.O. Box 670022, Zambia
- Correspondence:
| | - Enock Siankwilimba
- Graduate School of Business, University of Zambia, Lusaka P.O. Box 50516, Zambia
| | - Masauso Sakala
- School of Engineering, Department of Geomatic Engineering, University of Zambia, Lusaka P.O. Box 50516, Zambia
| | - Faustin Banda
- School of Engineering, Department of Geomatic Engineering, University of Zambia, Lusaka P.O. Box 50516, Zambia
- The National Remote Sensing Centre, Plot Number 15302 Airport Road, Lusaka P.O. Box 310303, Zambia
| | - Charles Michelo
- Department of Public Health, Mazabuka Municipal Council, Mazabuka P.O. Box 670022, Zambia
- Harvest Research Institute, Lusaka P.O. Box 51176, Zambia
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Khojasteh D, Davani E, Shamsipour A, Haghani M, Glamore W. Climate change and COVID-19: Interdisciplinary perspectives from two global crises. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 844:157142. [PMID: 35798107 PMCID: PMC9252874 DOI: 10.1016/j.scitotenv.2022.157142] [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: 05/02/2022] [Revised: 06/29/2022] [Accepted: 06/29/2022] [Indexed: 05/12/2023]
Abstract
The repercussions of the COVID-19 pandemic and climate change - two major current global crises - are far-reaching, the parallels between the two are striking, and their influence on one another are significant. Based on the wealth of evidence that has emerged from the scientific literature during the first two years of the pandemic, this study argues that these two global crises require holistic multisectoral mitigation strategies. Despite being different in nature, neither crisis can be effectively mitigated without considering their interdependencies. Herein, significant interactions between these two crises are highlighted and discussed. Major implications related to the economy, energy, technology, environment, food systems and agriculture sector, health systems, policy, management, and communities are detailed via a review of existing joint literature. Based on these outcomes, practical recommendations for future research and management are provided. While the joint timing of these crises has created a global conundrum, the COVID-19 pandemic has demonstrated opportunities and lessons for devising sustainable recovery plans in relation to the climate crisis. The findings indicated that governments should work collaboratively to develop durable and adjustable strategies in line with long-term, global decarbonisation targets, promote renewable energy resources, integrate climate change into environmental policies, prioritise climate-smart agriculture and local food systems, and ensure public and ecosystem health. Further, differences in geographic distributions of climate change and COVID-19 related death cases revealed that these crises pose different threats to different parts of the world. These learnings provide insights to address the climate emergency - and potential future global problems with similar characteristics - if international countries act urgently and collectively.
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Affiliation(s)
- Danial Khojasteh
- Water Research Laboratory, School of Civil and Environmental Engineering, UNSW, Sydney, NSW, Australia.
| | - Ehsan Davani
- School of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | - Abbas Shamsipour
- School of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | - Milad Haghani
- Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, The University of New South Wales, UNSW, Sydney, Australia.
| | - William Glamore
- Water Research Laboratory, School of Civil and Environmental Engineering, UNSW, Sydney, NSW, Australia.
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Pu S, Ali Turi J, Bo W, Zheng C, Tang D, Iqbal W. Sustainable impact of COVID-19 on education projects: aspects of naturalism. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:69555-69572. [PMID: 35567688 PMCID: PMC9107217 DOI: 10.1007/s11356-022-20387-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 04/18/2022] [Indexed: 05/06/2023]
Abstract
History records show that pandemics and threats have always given new directions to the thinking, working, and learning styles. This article attempts to thoroughly document the positive core of coronavirus 2019 (COVID-19) and its impact on global social psychology, ecological stability, and development. Structural equation modeling (SEM) is used to test the hypotheses and comprehend the objectives of the study. The findings of the study reveals that the path coefficients for the variables health consciousness, naturalism, financial impact and self-development, sustainability, compassion, gregariousness, sympathy, and cooperation demonstrate that the factors have a positive and significant effect on COVID-19 prevention. Moreover, the content analysis was conducted on recently published reports, blog content, newspapers, and social media. The pieces of evidence from history have been cited to justify the perspective. Furthermore, to appraise the opinions of professionals of different walks of life, an online survey was conducted, and results were discussed with expert medical professionals. Outcomes establish that the pandemics give birth to creativity, instigate innovations, prompt inventions, establish human ties, and foster altruistic elements of compassion and emotionalism.
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Affiliation(s)
- Song Pu
- Guiyang Preschool Education College, Guiyang, China
| | - Jamshid Ali Turi
- Bahria Business School, Bahria University, Islamabad Campus, Islamabad, Pakistan
| | - Wang Bo
- University of Malaya, Kuala Lumpur, 50603 Malaysia
- Guiyang Preschool Education Normal College, Gui Yang, China
| | - Chen Zheng
- Weinan Vocational & Technical College, Shaanxi, China
| | - Dandan Tang
- University of Malaya, Kuala Lumpur, 50603 Malaysia
| | - Wasim Iqbal
- Department of Management Science, College of Management, Shenzhen University, Shenzhen, China
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Wang J, Zeng F, Tang H, Wang J, Xing L. Correlations between the urban built environmental factors and the spatial distribution at the community level in the reported COVID-19 samples: A case study of Wuhan. CITIES (LONDON, ENGLAND) 2022; 129:103932. [PMID: 35975194 PMCID: PMC9372090 DOI: 10.1016/j.cities.2022.103932] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Revised: 07/13/2022] [Accepted: 08/06/2022] [Indexed: 06/15/2023]
Abstract
COVID-19 has dramatically changed the lifestyle of people, especially in urban environments. This paper investigated the variations of built environments that were measurably associated with the spread of COVID-19 in 150 Wuhan communities. The incidence rate in each community before and after the lockdown (January 23, 2020), as respective dependent variables, represented the situation under normal circumstances and non-pharmaceutical interventions (NPI). After controlling the population density, floor area ratio (FAR), property age and sociodemographic factors, the built environmental factors in two spatial dimensions, the 15-minute walking life circle and the 10-minute cycling life circle, were brought into the Hierarchical Linear Regression Model and the Ridge Regression Model. The results indicated that before lockdown, the number of markets and schools were positively associated with the incidence rate, while community population density and FAR were negatively associated with COVID-19 transmission. After lockdown, FAR, GDP, the number of hospitals (in the 15-minute walking life circle) and the bus stations (in the 10-minute cycling life circle) became negatively correlated with the incidence rate, while markets remained positive. This study effectively extends the discussions on the association between the urban built environment and the spread of COVID-19. Meanwhile, given the limitations of sociodemographic data sources, the conclusions of this study should be interpreted and applied with caution.
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Affiliation(s)
- Jingwei Wang
- School of Architecture, Southeast University, Nanjing 210096, China
| | - Fanbo Zeng
- Faculty of Innovation and Design, City University of Macau, Macau 999078, China
| | - Haida Tang
- School of Architecture & Urban Planning/BenYuan Design and Research Center, Shenzhen University, Shenzhen 518000, China
- Shenzhen Key Laboratory of Architecture for Health & Well-being (in preparation), Shenzhen, China
| | - Junjie Wang
- School of Architecture & Urban Planning/BenYuan Design and Research Center, Shenzhen University, Shenzhen 518000, China
- Shenzhen Key Laboratory of Architecture for Health & Well-being (in preparation), Shenzhen, China
| | - Lihua Xing
- Shenzhen General Institute of Architectural Design and Research CO., LTD, Shenzhen 518000, China
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Li HL, Yang BY, Wang LJ, Liao K, Sun N, Liu YC, Ma RF, Yang XD. A meta-analysis result: Uneven influences of season, geo-spatial scale and latitude on relationship between meteorological factors and the COVID-19 transmission. ENVIRONMENTAL RESEARCH 2022; 212:113297. [PMID: 35436453 PMCID: PMC9011904 DOI: 10.1016/j.envres.2022.113297] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 04/08/2022] [Accepted: 04/09/2022] [Indexed: 05/15/2023]
Abstract
Meteorological factors have been confirmed to affect the COVID-19 transmission, but current studied conclusions varied greatly. The underlying causes of the variance remain unclear. Here, we proposed two scientific questions: (1) whether meteorological factors have a consistent influence on virus transmission after combining all the data from the studies; (2) whether the impact of meteorological factors on the COVID-19 transmission can be influenced by season, geospatial scale and latitude. We employed a meta-analysis to address these two questions using results from 2813 published articles. Our results showed that, the influence of meteorological factors on the newly-confirmed COVID-19 cases varied greatly among existing studies, and no consistent conclusion can be drawn. After grouping outbreak time into cold and warm seasons, we found daily maximum and daily minimum temperatures have significant positive influences on the newly-confirmed COVID-19 cases in cold season, while significant negative influences in warm season. After dividing the scope of the outbreak into national and urban scales, relative humidity significantly inhibited the COVID-19 transmission at the national scale, but no effect on the urban scale. The negative impact of relative humidity, and the positive impacts of maximum temperatures and wind speed on the newly-confirmed COVID-19 cases increased with latitude. The relationship of maximum and minimum temperatures with the newly-confirmed COVID-19 cases were more susceptible to season, while relative humidity's relationship was more affected by latitude and geospatial scale. Our results suggested that relationship between meteorological factors and the COVID-19 transmission can be affected by season, geospatial scale and latitude. A rise in temperature would promote virus transmission in cold seasons. We suggested that the formulation and implementation of epidemic prevention and control should mainly refer to studies at the urban scale. The control measures should be developed according to local meteorological properties for individual city.
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Affiliation(s)
- Hong-Li Li
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China
| | - Bai-Yu Yang
- College of Ecological and Environmental Sciences, East China Normal University, Shanghai, 200241, China
| | - Li-Jing Wang
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China
| | - Ke Liao
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China
| | - Nan Sun
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China
| | - Yong-Chao Liu
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China; Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, 315211, China; Donghai Academy, Ningbo University, Ningbo, 315211, China
| | - Ren-Feng Ma
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China; Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, 315211, China; Donghai Academy, Ningbo University, Ningbo, 315211, China
| | - Xiao-Dong Yang
- College of Geography and Tourism Culture, Ningbo University, Ningbo, 315211, China; Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, 315211, China; Donghai Academy, Ningbo University, Ningbo, 315211, China.
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Di Biagio K, Baldini M, Dolcini J, Serafini P, Sarti D, Dorillo I, Ranzi A, Settimo G, Bartolacci S, Simeoni TV, Prospero E. Atmospheric particulate matter effects on SARS-CoV-2 infection and spreading dynamics: A spatio-temporal point process model. ENVIRONMENTAL RESEARCH 2022; 212:113617. [PMID: 35667404 PMCID: PMC9164771 DOI: 10.1016/j.envres.2022.113617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 05/27/2022] [Accepted: 06/02/2022] [Indexed: 05/31/2023]
Abstract
Particulate matter (PM) may play a role in differential distribution and transmission rates of SARS-CoV-2. For public health surveillance, identification of factors affecting the transmission dynamics concerning the endemic (persistent sporadic) and epidemic (rapidly clustered) component of infection can help to implement intervention strategies to reduce the disease burden. The aim of this study is to assess the effect of long-term residential exposure to outdoor PM ≤ 10 μm (PM10) concentrations on SARS-CoV-2 incidence and on its spreading dynamics in Marche region (Central Italy) during the first wave of the COVID-19 pandemic (February to May 2020), using the endemic-epidemic spatio-temporal regression model for individual-level data. Environmental and climatic factors were estimated at 10 km2 grid cells. 10-years average exposure to PM10 was associated with an increased risk of new endemic (Rate Ratio for 10 μg/m3 increase 1.14, 95%CI 1.04-1.24) and epidemic (Rate Ratio 1.15, 95%CI 1.08-1.22) infection. Male gender, older age, living in Nursing Homes and Long-Term Care Facilities residence and socio-economic deprivation index increased Rate Ratio (RR) in epidemic component. Lockdown increased the risk of becoming positive to SARS-CoV-2 as concerning endemic component while it reduced virus spreading in epidemic one. Increased temperature was associated with a reduction of endemic and epidemic infection. Results showed an increment of RR for exposure to increased levels of PM10 both in endemic and epidemic components. Targeted interventions are necessary to improve air quality in most polluted areas, where deprived populations are more likely to live, to minimize the burden of endemic and epidemic COVID-19 disease and to reduce unequal distribution of health risk.
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Affiliation(s)
- Katiuscia Di Biagio
- Environmental Epidemiology Unit - Regional Environmental Protection Agency of Marche, Ancona, Italy.
| | - Marco Baldini
- Environmental Epidemiology Unit - Regional Environmental Protection Agency of Marche, Ancona, Italy
| | - Jacopo Dolcini
- Department of Biomedical Sciences and Public Health, Section of Hygiene - Polytechnic University, Ancona, Italy
| | - Pietro Serafini
- Medical Direction Department, Local Health Authority of Marche, Ancona, Italy
| | - Donatella Sarti
- Department of Biomedical Sciences and Public Health, Section of Hygiene - Polytechnic University, Ancona, Italy
| | - Irene Dorillo
- Air Quality Unit, Regional Environmental Protection Agency of Marche, Ancona, Italy
| | - Andrea Ranzi
- Centre for Environmental Health and Prevention, Regional Agency for Prevention, Environment and Energy of Emilia-Romagna, Modena, Italy
| | | | - Silvia Bartolacci
- Environmental Epidemiology Unit - Regional Environmental Protection Agency of Marche, Ancona, Italy
| | - Thomas Valerio Simeoni
- Environmental Epidemiology Unit - Regional Environmental Protection Agency of Marche, Ancona, Italy
| | - Emilia Prospero
- Department of Biomedical Sciences and Public Health, Section of Hygiene - Polytechnic University, Ancona, Italy
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Nanni V, Mammola S, Macías-Hernández N, Castrogiovanni A, Salgado AL, Lunghi E, Ficetola GF, Modica C, Alba R, Spiriti MM, Holtze S, de Mello ÉM, De Mori B, Biasetti P, Chamberlain D, Manenti R. Global response of conservationists across mass media likely constrained bat persecution due to COVID-19. BIOLOGICAL CONSERVATION 2022; 272:109591. [PMID: 35603331 PMCID: PMC9110911 DOI: 10.1016/j.biocon.2022.109591] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 05/01/2022] [Accepted: 05/09/2022] [Indexed: 05/30/2023]
Abstract
Most people lack direct experience with wildlife and form their risk perception primarily on information provided by the media. The way the media frames news may substantially shape public risk perception, promoting or discouraging public tolerance towards wildlife. At the onset of the COVID-19 pandemic, bats were suggested as the most plausible reservoir of the virus, and this became a recurrent topic in media reports, potentially strengthening a negative view of this ecologically important group. We investigated how media framed bats and bat-associated diseases before and during the COVID-19 pandemic by assessing the content of 2651 online reports published across 26 countries, to understand how and how quickly worldwide media may have affected the perception of bats. We show that the overabundance of poorly contextualized reports on bat-associated diseases likely increased the persecution towards bats immediately after the COVID-19 outbreak. However, the subsequent interventions of different conservation communication initiatives allowed pro-conservation messages to resonate across the global media, likely stemming an increase in bat persecution. Our results highlight the modus operandi of the global media regarding topical biodiversity issues, which has broad implications for species conservation. Knowing how the media acts is pivotal for anticipating the propagation of (mis)information and negative feelings towards wildlife. Working together with journalists by engaging in dialogue and exchanging experiences should be central in future conservation management.
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Affiliation(s)
- Veronica Nanni
- School for Advanced Studies IUSS, Science, Technology and Society Department, 25100 Pavia, Italy
| | - Stefano Mammola
- Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History (LUOMUS), University of Helsinki, Helsinki, Finland
- Molecular Ecology Group (MEG), Water Research Institute, National Research Council of Italy (CNR-IRSA), Largo Tonolli 50, 28922 Verbania Pallanza, Italy
| | - Nuria Macías-Hernández
- Laboratory for Integrative Biodiversity Research (LIBRe), Finnish Museum of Natural History (LUOMUS), University of Helsinki, Helsinki, Finland
- Department of Animal Biology, Edaphology and Geology, University of Laguna, La Laguna, Tenerife 38206, Canary Islands, Spain
| | - Alessia Castrogiovanni
- Department of Environmental Science and Policy, Università degli Studi di Milano, Via Cleoria, 10, 20133 Milano, Italy
| | - Ana L Salgado
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Enrico Lunghi
- Division of Molecular Biology, Ruđer Bošković Institute, Bijenicka cesta 54, 10000 Zagreb, Croatia
| | - Gentile Francesco Ficetola
- Department of Environmental Science and Policy, Università degli Studi di Milano, Via Cleoria, 10, 20133 Milano, Italy
| | - Corrado Modica
- Faunico office of species protection, Leanderstraße 16, 54295 Trier, Germany
| | - Riccardo Alba
- Dept. of Life Science and Systems Biology, University of Torino, Via Accademia Albertina, 13, 10123 Torino, Italy
| | - Maria Michela Spiriti
- Department of Comparative Biomedicine and Food Science, University of Padua, 35020 Padua, Italy
- Ethics Laboratory for Veterinary Medicine, Conservation and Animal Welfare, University of Padua, 35020 Padua, Italy
| | - Susanne Holtze
- Department of Reproduction Management, Leibniz Institute for Zoo and Wildlife Research, 10315 Berlin, Germany
| | - Érica Munhoz de Mello
- Urban Bats Laboratory, Zoonoses Control Center of Belo Horizonte, Belo Horizonte, Brazil
| | - Barbara De Mori
- Department of Comparative Biomedicine and Food Science, University of Padua, 35020 Padua, Italy
| | - Pierfrancesco Biasetti
- Department of Reproduction Management, Leibniz Institute for Zoo and Wildlife Research, 10315 Berlin, Germany
| | - Dan Chamberlain
- Dept. of Life Science and Systems Biology, University of Torino, Via Accademia Albertina, 13, 10123 Torino, Italy
| | - Raoul Manenti
- Department of Environmental Science and Policy, Università degli Studi di Milano, Via Cleoria, 10, 20133 Milano, Italy
- Laboratory of Subterranean Biology "Enrico Pezzoli", Parco Regionale del Monte Barro, 23851 Galbiate, Italy
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Sciannameo V, Goffi A, Maffeis G, Gianfreda R, Jahier Pagliari D, Filippini T, Mancuso P, Giorgi-Rossi P, Alberto Dal Zovo L, Corbari A, Vinceti M, Berchialla P. A deep learning approach for Spatio-Temporal forecasting of new cases and new hospital admissions of COVID-19 spread in Reggio Emilia, Northern Italy. J Biomed Inform 2022; 132:104132. [PMID: 35835438 PMCID: PMC9271423 DOI: 10.1016/j.jbi.2022.104132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/24/2022] [Accepted: 07/03/2022] [Indexed: 12/23/2022]
Abstract
Background Since February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM10, PM2.5, NO2, temperature, relative humidity, wind speed, solar radiation and mobility with the spread of the epidemic. In this work, we aimed to predict via Deep Learning the real-time transmission of SARS-CoV-2 in the province of Reggio Emilia, Northern Italy, in a grid with a small resolution (12 km × 12 km), including satellite information. Methods We focused on the Province of Reggio Emilia, which was severely hit by the first wave of the epidemic. The outcomes included new SARS-CoV-2 infections and COVID-19 hospital admissions. Pollution, meteorological and mobility data were analyzed. The spatial simulation domain included the Province of Reggio Emilia in a grid of 40 cells of (12 km)2. We implemented a ConvLSTM, which is a spatio-temporal deep learning approach, to perform a 7-day moving average to forecast the 7th day after. We used as training and validation set the new daily infections and hospital admissions from August 2020 to March 2021. Finally, we assessed the models in terms of Mean Absolute Error (MAE) compared with Mean Observed Value (MOV) and Root Mean Squared Error (RMSE) on data from April to September 2021. We tested the performance of different combinations of input variables to find the best forecast model. Findings Daily new cases of infection, mobility and wind speed resulted in being strongly predictive of new COVID-19 hospital admissions (MAE = 2.72 in the Province of Reggio Emilia; MAE = 0.62 in Reggio Emilia city), whereas daily new cases, mobility, solar radiation and PM2.5 turned out to be the best predictors to forecast new infections, with appropriate time lags. Interpretation ConvLSTM achieved good performances in forecasting new SARS-CoV-2 infections and new COVID-19 hospital admissions. The spatio-temporal representation allows borrowing strength from data neighboring to forecast at the level of the square cell (12 km)2, getting accurate predictions also at the county level, which is paramount to help optimise the real-time allocation of health care resources during an epidemic emergency.
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Affiliation(s)
- Veronica Sciannameo
- University of Padova, Unit of Biostatistics, Epidemiology and Public Health, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, Italy
| | - Alessia Goffi
- TerrAria s.r.l, Via Melchiorre Gioia, 132, 20125 Milan, Italy
| | | | | | | | - Tommaso Filippini
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Section of Public Health, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy
| | - Pamela Mancuso
- Epidemiology Unit, Azienda Unità Sanitaria Locale-Istituto di Ricovero e Cura a Carattere Scientifico di Reggio Emilia, 42123 Reggio Emilia, Italy
| | - Paolo Giorgi-Rossi
- Epidemiology Unit, Azienda Unità Sanitaria Locale-Istituto di Ricovero e Cura a Carattere Scientifico di Reggio Emilia, 42123 Reggio Emilia, Italy
| | | | - Angela Corbari
- Studiomapp s.r.l., Via Pietro Alighieri, 43, 48121 Ravenna, Italy
| | - Marco Vinceti
- Environmental, Genetic and Nutritional Epidemiology Research Center (CREAGEN), Section of Public Health, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via Campi 287, 41125 Modena, Italy; Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Paola Berchialla
- University of Torino, Department of Clinical and Biological Sciences, Italy.
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Karimi B, Moradzadeh R, Samadi S. Air pollution and COVID-19 mortality and hospitalization: An ecological study in Iran. ATMOSPHERIC POLLUTION RESEARCH 2022; 13:101463. [PMID: 35664828 PMCID: PMC9154086 DOI: 10.1016/j.apr.2022.101463] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/21/2022] [Accepted: 05/22/2022] [Indexed: 05/07/2023]
Abstract
Exposure to air pollution can exacerbate the severe COVID-19 conditions, subsequently causing an increase in the death rate. In this study, we investigated the association between long-term exposure to air pollution and risks of COVID-19 hospitalization and mortality in Arak, Iran. Air pollution data was obtained from air quality monitoring stations located in Arak, including particulate matter (PM), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3) and carbon monoxide (CO). Daily numbers of Covid-19 cases including hospital admissions (hospitalization) and deaths (mortality) were obtained from a national data registry recorded by Arak University of Medical Sciences. A Poisson regression model with natural spline functions was applied to set the effects of air pollution on COVID-19 hospitalization and mortality. The percent change of COVID-19 hospitalization per 10 μg/m3 increase in PM2.5 and PM10 were 8.5% (95% CI 7.6 to 11.5) and 4.8% (95% CI 3 to 6.5), respectively. An increase of 10 μg/m3 in PM2.5 resulting in 5.6% (95% CI: 3.1-8.3%) increase in COVID-19 mortality. The percent change of hospitalization (7.7%, 95% CI 2.2 to 13.3) and mortality (4.5%, 95% CI 0.3 to 9.5) were positively significant per one ppb increment in SO2, while NO2, O3 and CO were inversely associated with hospitalization and mortality. Our findings strongly suggesting that a small increase in long-term exposure to PM2.5, PM10 and SO2 elevating risks of hospitalization and mortality related to COVID-19.
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Affiliation(s)
- Behrooz Karimi
- Department of Environmental Health Engineering, Health Faculty, Arak University of Medical Sciences, Arak, Iran
| | - Rahmatollah Moradzadeh
- Department of Epidemiology, Health Faculty, Arak University of Medical Sciences, Arak, Iran
| | - Sadegh Samadi
- Department of Occupational Health and Safety Engineering, Health Faculty, Arak University of Medical Sciences, Arak, Iran
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21
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Lin S, Rui J, Xie F, Zhan M, Chen Q, Zhao B, Zhu Y, Li Z, Deng B, Yu S, Li A, Ke Y, Zeng W, Su Y, Chiang YC, Chen T. Assessing the Impacts of Meteorological Factors on COVID-19 Pandemic Using Generalized Estimating Equations. Front Public Health 2022; 10:920312. [PMID: 35844849 PMCID: PMC9284004 DOI: 10.3389/fpubh.2022.920312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 06/01/2022] [Indexed: 11/13/2022] Open
Abstract
Background Meteorological factors have been proven to affect pathogens; both the transmission routes and other intermediate. Many studies have worked on assessing how those meteorological factors would influence the transmissibility of COVID-19. In this study, we used generalized estimating equations to evaluate the impact of meteorological factors on Coronavirus disease 2019 (COVID-19) by using three outcome variables, which are transmissibility, incidence rate, and the number of reported cases. Methods In this study, the data on the daily number of new cases and deaths of COVID-19 in 30 provinces and cities nationwide were obtained from the provincial and municipal health committees, while the data from 682 conventional weather stations in the selected provinces and cities were obtained from the website of the China Meteorological Administration. We built a Susceptible-Exposed-Symptomatic-Asymptomatic-Recovered/Removed (SEIAR) model to fit the data, then we calculated the transmissibility of COVID-19 using an indicator of the effective reproduction number (Reff ). To quantify the different impacts of meteorological factors on several outcome variables including transmissibility, incidence rate, and the number of reported cases of COVID-19, we collected panel data and used generalized estimating equations. We also explored whether there is a lag effect and the different times of meteorological factors on the three outcome variables. Results Precipitation and wind speed had a negative effect on transmissibility, incidence rate, and the number of reported cases, while humidity had a positive effect on them. The higher the temperature, the lower the transmissibility. The temperature had a lag effect on the incidence rate, while the remaining five meteorological factors had immediate and lag effects on the incidence rate and the number of reported cases. Conclusion Meteorological factors had similar effects on incidence rate and number of reported cases, but different effects on transmissibility. Temperature, relative humidity, precipitation, sunshine hours, and wind speed had immediate and lag effects on transmissibility, but with different lag times. An increase in temperature may first cause a decrease in virus transmissibility and then lead to a decrease in incidence rate. Also, the mechanism of the role of meteorological factors in the process of transmissibility to incidence rate needs to be further explored.
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Affiliation(s)
- Shengnan Lin
- School of Public Health, Xiamen University, Xiamen, China
| | - Jia Rui
- School of Public Health, Xiamen University, Xiamen, China
- Cirad, UMR 17, Intertryp, Université de Montpellier, Montpellier, France
| | - Fang Xie
- School of Public Health, Xiamen University, Xiamen, China
| | - Meirong Zhan
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Qiuping Chen
- School of Public Health, Xiamen University, Xiamen, China
- Cirad, UMR 17, Intertryp, Université de Montpellier, Montpellier, France
| | - Bin Zhao
- Clinical Medical Laboratory, Xiang'an Hospital of Xiamen University, Xiamen, China
| | - Yuanzhao Zhu
- School of Public Health, Xiamen University, Xiamen, China
| | - Zhuoyang Li
- School of Public Health, Xiamen University, Xiamen, China
| | - Bin Deng
- School of Public Health, Xiamen University, Xiamen, China
| | - Shanshan Yu
- School of Public Health, Xiamen University, Xiamen, China
| | - An Li
- School of Public Health, Xiamen University, Xiamen, China
| | - Yanshu Ke
- School of Public Health, Xiamen University, Xiamen, China
| | - Wenwen Zeng
- School of Public Health, Xiamen University, Xiamen, China
| | - Yanhua Su
- School of Public Health, Xiamen University, Xiamen, China
| | - Yi-Chen Chiang
- School of Public Health, Xiamen University, Xiamen, China
| | - Tianmu Chen
- School of Public Health, Xiamen University, Xiamen, China
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22
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Wang D, Wu X, Li C, Han J, Yin J. The impact of geo-environmental factors on global COVID-19 transmission: A review of evidence and methodology. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 826:154182. [PMID: 35231530 PMCID: PMC8882033 DOI: 10.1016/j.scitotenv.2022.154182] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/22/2022] [Accepted: 02/23/2022] [Indexed: 06/14/2023]
Abstract
Studies on Coronavirus Disease 2019 (COVID-19) transmission indicate that geo-environmental factors have played a significant role in the global pandemic. However, there has not been a systematic review on the impact of geo-environmental factors on global COVID-19 transmission in the context of geography. As such, we reviewed 49 well-chosen studies to reveal the impact of geo-environmental factors (including the natural environment and human activity) on global COVID-19 transmission, and to inform critical intervention strategies that could mitigate the worldwide effects of the pandemic. Existing studies frequently mention the impact of climate factors (e.g., temperature and humidity); in contrast, a more decisive influence can be achieved by human activity, including human mobility, health factors, and non-pharmaceutical interventions (NPIs). The above results exhibit distinct spatiotemporal heterogeneity. The related analytical methodology consists of sensitivity analysis, mathematical modeling, and risk analysis. For future studies, we recommend highlighting geo-environmental interactions, developing geographically statistical models for multiple waves of the pandemic, and investigating NPIs and care patterns. We also propose four implications for practice to combat global COVID-19 transmission.
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Affiliation(s)
- Danyang Wang
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Xiaoxu Wu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
| | - Chenlu Li
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; School of Ecology and Environment, Northwestern Polytechnical University, Xi'an 710072, China
| | - Jiatong Han
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
| | - Jie Yin
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
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23
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Wei Y, Dong Z, Fan W, Xu K, Tang S, Wang Y, Wu F. A narrative review on the role of temperature and humidity in COVID-19: Transmission, persistence, and epidemiological evidence. ECO-ENVIRONMENT & HEALTH (ONLINE) 2022; 1:73-85. [PMID: 38013745 PMCID: PMC9181277 DOI: 10.1016/j.eehl.2022.04.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 03/30/2022] [Accepted: 04/28/2022] [Indexed: 12/11/2022]
Abstract
Since December 2019, the 2019 coronavirus disease (COVID-19) outbreak has become a global pandemic. Understanding the role of environmental conditions is important in impeding the spread of COVID-19. Given that airborne spread and contact transmission are considered the main pathways for the spread of COVID-19, this narrative review first summarized the role of temperature and humidity in the airborne trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Meanwhile, we reviewed the persistence of the virus in aerosols and on inert surfaces and summarized how the persistence of SARS-CoV-2 is affected by temperature and humidity. We also examined the existing epidemiological evidence and addressed the limitations of these epidemiological studies. Although uncertainty remains, more evidence may support the idea that high temperature is slightly and negatively associated with COVID-19 growth, while the conclusion for humidity is still conflicting. Nonetheless, the spread of COVID-19 appears to have been controlled primarily by government interventions rather than environmental factors.
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Affiliation(s)
- Yuan Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zhaomin Dong
- School of Space and Environment, Beihang University, Beijing 102206, China
| | - Wenhong Fan
- School of Space and Environment, Beihang University, Beijing 102206, China
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, China
| | - Kaiqiang Xu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ying Wang
- School of Space and Environment, Beihang University, Beijing 102206, China
| | - Fengchang Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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24
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Sun C, Chao L, Li H, Hu Z, Zheng H, Li Q. Modeling and Preliminary Analysis of the Impact of Meteorological Conditions on the COVID-19 Epidemic. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:6125. [PMID: 35627661 PMCID: PMC9140896 DOI: 10.3390/ijerph19106125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 05/15/2022] [Accepted: 05/16/2022] [Indexed: 01/27/2023]
Abstract
Since the COVID-19 epidemic outbreak at the end of 2019, many studies regarding the impact of meteorological factors on the attack have been carried out, and inconsistent conclusions have been reached, indicating the issue's complexity. To more accurately identify the effects and patterns of meteorological factors on the epidemic, we used a combination of logistic regression (LgR) and partial least squares regression (PLSR) modeling to investigate the possible effects of common meteorological factors, including air temperature, relative humidity, wind speed, and surface pressure, on the transmission of the COVID-19 epidemic. Our analysis shows that: (1) Different countries and regions show spatial heterogeneity in the number of diagnosed patients of the epidemic, but this can be roughly classified into three types: "continuous growth", "staged shock", and "finished"; (2) Air temperature is the most significant meteorological factor influencing the transmission of the COVID-19 epidemic. Except for a few areas, regional air temperature changes and the transmission of the epidemic show a significant positive correlation, i.e., an increase in air temperature is conducive to the spread of the epidemic; (3) In different countries and regions studied, wind speed, relative humidity, and surface pressure show inconsistent correlation (and significance) with the number of diagnosed cases but show some regularity.
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Affiliation(s)
- Chenglong Sun
- School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Sun Yat-Sen University, Zhuhai 519082, China; (C.S.); (L.C.); (H.L.)
| | - Liya Chao
- School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Sun Yat-Sen University, Zhuhai 519082, China; (C.S.); (L.C.); (H.L.)
| | - Haiyan Li
- School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Sun Yat-Sen University, Zhuhai 519082, China; (C.S.); (L.C.); (H.L.)
| | - Zengyun Hu
- Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;
| | - Hehui Zheng
- National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qingxiang Li
- School of Atmospheric Sciences and Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Sun Yat-Sen University, Zhuhai 519082, China; (C.S.); (L.C.); (H.L.)
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25
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Aboura S. The influence of climate factors and government interventions on the Covid-19 pandemic: Evidence from 134 countries. ENVIRONMENTAL RESEARCH 2022; 208:112484. [PMID: 35033549 PMCID: PMC8757650 DOI: 10.1016/j.envres.2021.112484] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/23/2021] [Accepted: 11/30/2021] [Indexed: 05/05/2023]
Abstract
This paper investigates at the world level the influence of climate on the transmission of the SARS-CoV-2 virus. For that purpose, panel regressions of the number of cases and deaths from 134 countries are run on a set of explanatory variables (air temperature, relative humidity, precipitation, and wind) along with control variables (government interventions and population size and density). The analysis is completed with a panel threshold regression to check for potential non-linearities of the weather variables on virus transmission. The main findings support the role of climate in the circulation of the virus across countries. The detailed analysis reveals that relative humidity reduces the number of cases and deaths in both low and high regimes, while temperature and wind reduce the number of deaths.
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Affiliation(s)
- Sofiane Aboura
- Université de Paris XIII, Sorbonne Paris Cité, 93 430, Villetaneuse, France.
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26
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Erdem S, Ipek F, Bars A, Genç V, Erpek E, Mohammadi S, Altınata A, Akar S. Investigating the effect of macro-scale estimators on worldwide COVID-19 occurrence and mortality through regression analysis using online country-based data sources. BMJ Open 2022; 12:e055562. [PMID: 35165110 PMCID: PMC8844970 DOI: 10.1136/bmjopen-2021-055562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVE To investigate macro-scale estimators of the variations in COVID-19 cases and deaths among countries. DESIGN Epidemiological study. SETTING Country-based data from publicly available online databases of international organisations. PARTICIPANTS The study involved 170 countries/territories, each of which had complete COVID-19 and tuberculosis data, as well as specific health-related estimators (obesity, hypertension, diabetes and hypercholesterolaemia). PRIMARY AND SECONDARY OUTCOME MEASURES The worldwide heterogeneity of the total number of COVID-19 cases and deaths per million on 31 December 2020 was analysed by 17 macro-scale estimators around the health-related, socioeconomic, climatic and political factors. In 139 of 170 nations, the best subsets regression was used to investigate all potential models of COVID-19 variations among countries. A multiple linear regression analysis was conducted to explore the predictive capacity of these variables. The same analysis was applied to the number of deaths per hundred thousand due to tuberculosis, a quite different infectious disease, to validate and control the differences with the proposed models for COVID-19. RESULTS In the model for the COVID-19 cases (R2=0.45), obesity (β=0.460), hypertension (β=0.214), sunshine (β=-0.157) and transparency (β=0.147); whereas in the model for COVID-19 deaths (R2=0.41), obesity (β=0.279), hypertension (β=0.285), alcohol consumption (β=0.173) and urbanisation (β=0.204) were significant factors (p<0.05). Unlike COVID-19, the tuberculosis model contained significant indicators like obesity, undernourishment, air pollution, age, schooling, democracy and Gini Inequality Index. CONCLUSIONS This study recommends the new predictors explaining the global variability of COVID-19. Thus, it might assist policymakers in developing health policies and social strategies to deal with COVID-19. TRIAL REGISTRATION NUMBER ClinicalTrials.gov Registry (NCT04486508).
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Affiliation(s)
- Sabri Erdem
- Department of Business Administration, Dokuz Eylül University, Izmir, Turkey
| | - Fulya Ipek
- Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Turkey
| | - Aybars Bars
- Social Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Volkan Genç
- Social Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Esra Erpek
- Department of Internal Medicine, Division of Rheumatology Atatürk Education and Research Hospital, Izmir Katip Celebi University, Izmir, Turkey
| | | | - Anıl Altınata
- Social Sciences Institute, Dokuz Eylül University, Izmir, Turkey
| | - Servet Akar
- Department of Internal Medicine, Division of Rheumatology Atatürk Education and Research Hospital, Izmir Katip Celebi University, Izmir, Turkey
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27
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Xiu Z, Feng P, Yin J, Zhu Y. Are Stringent Containment and Closure Policies Associated with a Lower COVID-19 Spread Rate? Global Evidence. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031725. [PMID: 35162748 PMCID: PMC8835598 DOI: 10.3390/ijerph19031725] [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: 12/13/2021] [Revised: 01/24/2022] [Accepted: 01/30/2022] [Indexed: 11/16/2022]
Abstract
Stringent government policies, in general, and strict containment and closure policies in particular including workplace closing, restrictions on gatherings, close of public transport, stay-at-home order, restrictions on internal movement, and international travel control are associated with a lower spread rate of COVID-19 cases. On the other hand, school closures and public event cancellations have not been found to be associated with lower COVID-19 spread. Restrictions on international travel and the closing of public transport are two policies that stand out and have a consistent and slowing effect on the spread of COVID-19. The slowing effect of the containment and closure policies on the spread of COVID-19 becomes stronger one week after the policies have been implemented, consistent with the SARS-CoV-2 transmission pattern and the incubation period evolution. Furthermore, the slowing effect becomes stronger for culturally tight countries and countries with a higher population density. Our findings have important policy implications, implying that governments need to carefully implement containment and closure policies in their own countries’ social and cultural contexts, with an emphasis on the ideas of the common interest, personal responsibility, and the sense of community.
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Affiliation(s)
- Zongfeng Xiu
- Business School, Central South University, Changsha 410083, China; (Z.X.); (P.F.)
| | - Pengshuo Feng
- Business School, Central South University, Changsha 410083, China; (Z.X.); (P.F.)
| | - Jingwei Yin
- Business School, Central South University, Changsha 410083, China; (Z.X.); (P.F.)
- Correspondence: (J.Y.); (Y.Z.)
| | - Yingjun Zhu
- School of Accounting, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China
- Correspondence: (J.Y.); (Y.Z.)
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28
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Shao L, Cao Y, Jones T, Santosh M, Silva LFO, Ge S, da Boit K, Feng X, Zhang M, BéruBé K. COVID-19 mortality and exposure to airborne PM 2.5: A lag time correlation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:151286. [PMID: 34743816 PMCID: PMC8553633 DOI: 10.1016/j.scitotenv.2021.151286] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 10/07/2021] [Accepted: 10/23/2021] [Indexed: 05/05/2023]
Abstract
COVID-19 has escalated into one of the most serious crises in the 21st Century. Given the rapid spread of SARS-CoV-2 and its high mortality rate, here we investigate the impact and relationship of airborne PM2.5 to COVID-19 mortality. Previous studies have indicated that PM2.5 has a positive relationship with the spread of COVID-19. To gain insights into the delayed effect of PM2.5 concentration (μgm-3) on mortality, we focused on the role of PM2.5 in Wuhan City in China and COVID-19 during the period December 27, 2019 to April 7, 2020. We also considered the possible impact of various meteorological factors such as temperature, precipitation, wind speed, atmospheric pressure and precipitation on pollutant levels. The results from the Pearson's correlation coefficient analyses reveal that the population exposed to higher levels of PM2.5 pollution are susceptible to COVID-19 mortality with a lag time of >18 days. By establishing a generalized additive model, the delayed effect of PM2.5 on the death toll of COVID-19 was verified. A negative correction was identified between temperature and number of COVID-19 deaths, whereas atmospheric pressure exhibits a positive correlation with deaths, both with a significant lag effect. The results from our study suggest that these epidemiological relationships may contribute to the understanding of the COVID-19 pandemic and provide insights for public health strategies.
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Affiliation(s)
- Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.
| | - Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Tim Jones
- School of Earth and Environmental Sciences, Cardiff University, Park Place, Cardiff CF10 3AT, UK
| | - M Santosh
- School of Earth Sciences and Resources, China University of Geoscience Beijing, Beijing 100083, China; Department of Earth Science, University of Adelaide, Adelaide, SA 5005, Australia
| | - Luis F O Silva
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
| | - Shuoyi Ge
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Kátia da Boit
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
| | - Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Mengyuan Zhang
- State Key Laboratory of Coal Resources and Safe Mining, College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, Wales, UK
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29
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Modeling the differences in the time-series profiles of new COVID-19 daily confirmed cases in 3,108 contiguous U.S. counties: A retrospective analysis. PLoS One 2021; 16:e0242896. [PMID: 34731173 PMCID: PMC8565782 DOI: 10.1371/journal.pone.0242896] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 08/06/2021] [Indexed: 02/07/2023] Open
Abstract
Objective The COVID-19 pandemic in the U.S. has exhibited a distinct multiwave pattern beginning in March 2020. Paradoxically, most counties do not exhibit this same multiwave pattern. We aim to answer three research questions: (1) How many distinct clusters of counties exhibit similar COVID-19 patterns in the time-series of daily confirmed cases? (2) What is the geographic distribution of the counties within each cluster? and (3) Are county-level demographic, socioeconomic and political variables associated with the COVID-19 case patterns? Materials and methods We analyzed data from counties in the U.S. from March 1, 2020 to January 2, 2021. Time series clustering identified clusters in the daily confirmed cases of COVID-19. An explanatory model was used to identify demographic, socioeconomic and political variables associated with the outbreak patterns. Results Three patterns were identified from the cluster solution including counties in which cases are still increasing, those that peaked in the late fall, and those with low case counts to date. Several county-level demographic, socioeconomic, and political variables showed significant associations with the identified clusters. Discussion The pattern of the outbreak is related both to the geographic location within the U.S. and several variables including population density and government response. Conclusion The reported pattern of cases in the U.S. is observed through aggregation of the daily confirmed COVID-19 cases, suggesting that local trends may be more informative. The pattern of the outbreak varies by county, and is associated with important demographic, socioeconomic, political and geographic factors.
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30
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Pan J, Tang J, Caniza M, Heraud JM, Koay E, Lee HK, Lee CK, Li Y, Nava Ruiz A, Santillan-Salas CF, Marr LC. Correlating indoor and outdoor temperature and humidity in a sample of buildings in tropical climates. INDOOR AIR 2021; 31:2281-2295. [PMID: 34138487 DOI: 10.1111/ina.12876] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 06/12/2023]
Abstract
The incidence of several respiratory viral infections has been shown to be related to climate. Because humans spend most of their time indoors, measures of indoor climate, rather than outdoor climate, may be better predictors of disease incidence and transmission. Therefore, understanding the relationship between indoor and outdoor climate will help illuminate their influence on the seasonality of diseases caused by respiratory viruses. Indoor-outdoor relationships between temperature and humidity have been documented in temperate regions, but little information is available for tropical regions, where seasonal patterns of respiratory viral diseases differ. We have examined indoor-outdoor correlations of temperature, relative humidity (RH), and absolute humidity (AH) over a 1-year period in each of seven tropical cities. Across all cities, the average monthly indoor temperature was 25 ± 3°C (mean ± standard deviation) with a range of 20-30°C. The average monthly indoor RH was 66 ± 9% with a range of 50-78%, and the average monthly indoor AH was 15 ± 3 g/m3 with a range of 10-23 g/m3 . Indoor AH and RH were linearly correlated with outdoor AH when the air conditioning (AC) was off, suggesting that outdoor AH may be a good proxy of indoor humidity in the absence of AC. All indoor measurements were more strongly correlated with outdoor measurements as distance from the equator increased. Such correlations were weaker during the wet season, especially when AC was in operation. These correlations will provide insight for assessing the seasonality of respiratory viral infections using outdoor climate data, which is more widely available than indoor data, even though transmission of these diseases mainly occurs indoors.
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Affiliation(s)
- Jin Pan
- Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA
| | - Julian Tang
- Infection, Immunity and Inflammation, University of Leicester, Leicester, UK
| | - Miguela Caniza
- Global Infectious Diseases Program, Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN, USA
| | | | - Evelyn Koay
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore City, Singapore
| | - Hong Kai Lee
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore City, Singapore
| | - Chun Kiat Lee
- Department of Laboratory Medicine, National University Health System, Singapore City, Singapore
| | - Yuguo Li
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
| | | | | | - Linsey C Marr
- Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA, USA
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31
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Quilodrán CS, Currat M, Montoya-Burgos JI. Air temperature influences early Covid-19 outbreak as indicated by worldwide mortality. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 792:148312. [PMID: 34144236 PMCID: PMC8178938 DOI: 10.1016/j.scitotenv.2021.148312] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 04/30/2021] [Accepted: 06/02/2021] [Indexed: 06/12/2023]
Abstract
The Covid-19 outbreak has triggered a global crisis that is challenging governments, health systems and the scientific community worldwide. A central question in the Covid-19 pandemic is whether climatic factors have influenced its progression. To address this question, we used mortality rates during the first three weeks of recorded mortality in 144 countries, during the first wave of the pandemic. We examined the effect of climatic variables, along with the proportion of the population older than 64 years old, the number of beds in hospitals, and the timing and strength of the governmental travel measures to control the spread of the disease. Our first model focuses on air temperature as the central climatic factor and explains 67% of the variation in mortality rate, with 37% explained by the fixed variables considered and 31% explained by country-specific variations. We show that mortality rate is negatively influenced by warmer air temperature. Each additional Celsius degree decreases mortality rate by ~5%. Our second model is centred on the UV Index and follows the same trend as air temperature, explaining 69% of the variation in mortality rate. These results are robust to the exclusion of countries with low incomes, as well as to the exclusion of low- and medium-income countries. We also show that the proportion of vulnerable age classes and access to healthcare are critical factors impacting the mortality rate of this disease. The effects of air temperature at an early stage of the Covid-19 outbreak is a key factor to understand the primary spread of this pandemic, and should be considered in projecting subsequent waves.
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Affiliation(s)
- Claudio S Quilodrán
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, United Kingdom; Laboratory of Anthropology, Genetics and Peopling History, Department of Genetics and Evolution - Anthropology Unit, University of Geneva, Geneva, Switzerland.
| | - Mathias Currat
- Laboratory of Anthropology, Genetics and Peopling History, Department of Genetics and Evolution - Anthropology Unit, University of Geneva, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva (IGE3), Switzerland
| | - Juan I Montoya-Burgos
- Laboratory of Vertebrate Evolution, Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva (IGE3), Switzerland
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32
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Yap TF, Decker CJ, Preston DJ. Effect of daily temperature fluctuations on virus lifetime. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 789:148004. [PMID: 34323833 PMCID: PMC8570935 DOI: 10.1016/j.scitotenv.2021.148004] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 05/17/2021] [Accepted: 05/20/2021] [Indexed: 05/25/2023]
Abstract
Epidemiological studies based on statistical methods indicate inverse correlations between virus lifetime and both (i) daily mean temperature and (ii) diurnal temperature range (DTR). While thermodynamic models have been used to predict the effect of constant-temperature surroundings on virus inactivation rate, the relationship between virus lifetime and DTR has not been explained using first principles. Here, we model the inactivation of viruses based on temperature-dependent chemical kinetics with a time-varying temperature profile to account for the daily mean temperature and DTR simultaneously. The exponential Arrhenius relationship governing the rate of virus inactivation causes fluctuations above the daily mean temperature during daytime to increase the instantaneous rate of inactivation by a much greater magnitude than the corresponding decrease in inactivation rate during nighttime. This asymmetric behavior results in shorter predicted virus lifetimes when considering DTR and consequently reveals a potential physical mechanism for the inverse correlation observed between the number of cases and DTR reported in statistical epidemiological studies. In light of the ongoing COVID-19 pandemic, a case study on the effect of daily mean temperature and DTR on the lifetime of SARS-CoV-2 was performed for the five most populous cities in the United States. In Los Angeles, where mean monthly temperature fluctuations are low (DTR ≈ 7 °C), accounting for DTR decreases predicted SARS-CoV-2 lifetimes by only 10%; conversely, accounting for DTR for a similar mean temperature but larger mean monthly temperature fluctuations in Phoenix (DTR ≈ 15 °C) decreases predicted lifetimes by 50%. The modeling framework presented here provides insight into the independent effects of mean temperature and DTR on virus lifetime, and a significant impact on transmission rate is expected, especially for viruses that pose a high risk of fomite-mediated transmission.
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Affiliation(s)
- Te Faye Yap
- Department of Mechanical Engineering, Rice University, 6100 Main St., Houston, TX 77005, United States of America
| | - Colter J Decker
- Department of Mechanical Engineering, Rice University, 6100 Main St., Houston, TX 77005, United States of America
| | - Daniel J Preston
- Department of Mechanical Engineering, Rice University, 6100 Main St., Houston, TX 77005, United States of America.
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Xu R, Rahmandad H, Gupta M, DiGennaro C, Ghaffarzadegan N, Amini H, Jalali MS. Weather, air pollution, and SARS-CoV-2 transmission: a global analysis. Lancet Planet Health 2021; 5:e671-e680. [PMID: 34627471 PMCID: PMC8497024 DOI: 10.1016/s2542-5196(21)00202-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 06/12/2021] [Accepted: 07/19/2021] [Indexed: 05/21/2023]
Abstract
BACKGROUND Understanding how environmental factors affect SARS-CoV-2 transmission could inform global containment efforts. Despite high scientific and public interest and multiple research reports, there is currently no consensus on the association of environmental factors and SARS-CoV-2 transmission. To address this research gap, we aimed to assess the relative risk of transmission associated with weather conditions and ambient air pollution. METHODS In this global analysis, we adjusted for the delay between infection and detection, estimated the daily reproduction number at 3739 global locations during the COVID-19 pandemic up until late April, 2020, and investigated its associations with daily local weather conditions (ie, temperature, humidity, precipitation, snowfall, moon illumination, sunlight hours, ultraviolet index, cloud cover, wind speed and direction, and pressure data) and ambient air pollution (ie, PM2·5, nitrogen dioxide, ozone, and sulphur dioxide). To account for other confounding factors, we included both location-specific fixed effects and trends, controlling for between-location differences and heterogeneities in locations' responses over time. We built confidence in our estimations through synthetic data, robustness, and sensitivity analyses, and provided year-round global projections for weather-related risk of global SARS-CoV-2 transmission. FINDINGS Our dataset included data collected between Dec 12, 2019, and April 22, 2020. Several weather variables and ambient air pollution were associated with the spread of SARS-CoV-2 across 3739 global locations. We found a moderate, negative relationship between the estimated reproduction number and temperatures warmer than 25°C (a decrease of 3·7% [95% CI 1·9-5·4] per additional degree), a U-shaped relationship with outdoor ultraviolet exposure, and weaker positive associations with air pressure, wind speed, precipitation, diurnal temperature, sulphur dioxide, and ozone. Results were robust to multiple assumptions. Independent research building on our estimates provides strong support for the resulting projections across nations. INTERPRETATION Warmer temperature and moderate outdoor ultraviolet exposure result in a slight reduction in the transmission of SARS-CoV-2; however, changes in weather or air pollution alone are not enough to contain the spread of SARS-CoV-2 with other factors having greater effects. FUNDING None.
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Affiliation(s)
- Ran Xu
- Department of Allied Health Sciences, University of Connecticut, Storrs, CT, USA
| | - Hazhir Rahmandad
- Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Marichi Gupta
- Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA
| | - Catherine DiGennaro
- Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA
| | - Navid Ghaffarzadegan
- Department of Industrial and Systems Engineering, Virginia Tech, Falls Church, VA, USA
| | - Heresh Amini
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark; Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Mohammad S Jalali
- Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA, USA; MGH Institute for Technology Assessment, Harvard Medical School, Harvard University, Boston, MA, USA.
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Kumar N, Susan S. Particle swarm optimization of partitions and fuzzy order for fuzzy time series forecasting of COVID-19. Appl Soft Comput 2021; 110:107611. [PMID: 34518764 PMCID: PMC8425580 DOI: 10.1016/j.asoc.2021.107611] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 06/03/2021] [Accepted: 06/07/2021] [Indexed: 12/16/2022]
Abstract
Major hyperparameters which affect fuzzy time series (FTS) forecasting are the number of partitions, length of partition intervals in the universe of discourse, and the fuzzy order. There are very few studies which have considered an integrated solution to optimize all the hyperparameters. In this paper, we strive to achieve optimum values of all three hyperparameters for fuzzy time series forecasting of the COVID-19 pandemic using the Particle Swarm Optimization (PSO) algorithm. We specifically propose two techniques, namely nested FTS-PSO and exhaustive search FTS-PSO for determining the optimal interval length, as an augmentation to the FTS-PSO model that optimizes the interval length and the fuzzy order. Nested PSO has two PSO loops: (i) the inner PSO optimizes the combination of fuzzy order and boundaries of intervals for a given number of partitions defined by the outer loop, and the resultant cost is fed back to the outer PSO; (ii) the outer PSO optimizes the number of partitions to reduce the cost while meeting the defined constraint. Exhaustive search FTS-PSO also has two loops where the inner loop is similar to nested FTS-PSO while the outer loop iterates over a pre-defined search space of number of partitions. We analyze the effectiveness of the two approaches by comparing with ARIMA, FbProphet, and the state-of-the-art FTS and FTS-PSO models. We adopt COVID-19 highly affected 10 countries worldwide to perform forecasting of coronavirus confirmed cases. We consider two phases of COVID-19 spread, one from the year 2020 and another from 2021. Our study provides an analytical aspect of the COVID-19 pandemic, and aims to achieve optimal number and length of intervals along with fuzzy order for FTS forecasting of COVID-19. The results prove that the exhaustive search FTS-PSO outperformed all the methods whereas nested FTS-PSO performed moderately well.
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Affiliation(s)
- Naresh Kumar
- Department of Information Technology, Delhi Technological University, Delhi, India
| | - Seba Susan
- Department of Information Technology, Delhi Technological University, Delhi, India
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Raiteux J, Eschlimann M, Marangon A, Rogée S, Dadvisard M, Taysse L, Larigauderie G. Inactivation of SARS-CoV-2 by Simulated Sunlight on Contaminated Surfaces. Microbiol Spectr 2021; 9:e0033321. [PMID: 34287031 PMCID: PMC8552605 DOI: 10.1128/spectrum.00333-21] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 06/30/2021] [Indexed: 12/21/2022] Open
Abstract
We studied the stability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) under different simulated outdoor conditions by changing the temperature (20°C and 35°C), the illuminance (darkness, 10 klx, and 56 klx), and/or the cleanness of the surfaces at 50% relative humidity (RH). In darkness, the loss of viability of the virus on stainless steel is temperature dependent, but this is hidden by the effect of the sunlight from the first minutes of exposure. The virus shows a sensitivity to sunlight proportional to the illuminance intensity of the sunlight. The presence of interfering substances has a moderate effect on virus viability even with an elevated illuminance. Thus, SARS-CoV-2 is rapidly inactivated by simulated sunlight in the presence or absence of high levels of interfering substances at 20°C or 35°C and 50% relative humidity. IMPORTANCE Clinical matrix contains high levels of interfering substances. This study is the first to reveal that the presence of high levels of interfering substances had little impact on the persistence of SARS-CoV-2 on stainless steel following exposure to simulated sunlight. Thus, SARS-CoV-2 should be rapidly inactivated in outdoor environments in the presence or absence of interfering substances. Our results indicate that transmission of SARS-CoV-2 is unlikely to occur through outdoor surfaces, dependent on illuminance intensity. Moreover, most studies are interested in lineage S of SARS-CoV-2. In our experiments, we studied the stability of L-type strains, which comprise the majority of strains isolated from worldwide patients. Nevertheless, the effect of sunlight seems to be similar regardless of the strain studied, suggesting that the greater spread of certain variants is not correlated with better survival in outdoor conditions.
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36
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Ning J, Chu Y, Liu X, Zhang D, Zhang J, Li W, Zhang H. Spatio-temporal characteristics and control strategies in the early period of COVID-19 spread: a case study of the mainland China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:48298-48311. [PMID: 33904137 PMCID: PMC8075720 DOI: 10.1007/s11356-021-14092-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 04/20/2021] [Indexed: 04/12/2023]
Abstract
COVID-19 has caused huge impacts on human health and the economic operation of the world. Analyzing and summarizing the early propagation law can help reduce the losses caused by public health emergencies in the future. Early data on the spread of COVID-19 in 30 provinces (autonomous regions and municipalities) of mainland China except for Hubei, Hong Kong, Macao, and Taiwan were selected in this study. Spatio-temporal analysis, inflection point analysis, and correlation analysis are used to explore the spatio-temporal characteristics in the early COVID-19 spread. The results suggested that (1) the total confirmed cases have risen in an "S"-shaped curve over time, and the daily new cases have first increased and finally decreased; (2) the spatial distributions of both total and daily new cases show a trend of more in the east and less in the west, with a "multi-center agglomeration distribution" around Hubei Province and some major cities; (3) the spatial agglomeration of total confirmed cases has been increasing over time, while that of the daily new cases shows much more obvious in the mid-stage; and (4) timely release of the first-level public health emergency response can accelerate the emergence of the epidemic inflection point. The above analysis results have a specific reference value for the government's policy-making and measures to face public health emergencies.
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Affiliation(s)
- Jiachen Ning
- College of Economics and Management, Northwest A&F University, Yangling, 712100, China
| | - Yuhan Chu
- College of Economics and Management, Northwest A&F University, Yangling, 712100, China
| | - Xixi Liu
- College of Economics and Management, Northwest A&F University, Yangling, 712100, China
| | - Daojun Zhang
- College of Economics and Management, Northwest A&F University, Yangling, 712100, China.
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, 712100, China.
| | - Jinting Zhang
- School of Resources and Environmental Sciences, Wuhan University, Wuhan, 430079, China
| | - Wangjun Li
- The school of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou, 215009, China
| | - Hui Zhang
- College of Economics and Management, Northwest A&F University, Yangling, 712100, China
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Early Spread of COVID-19 in the Air-Polluted Regions of Eight Severely Affected Countries. ATMOSPHERE 2021. [DOI: 10.3390/atmos12060795] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
COVID-19 escalated into a pandemic posing several humanitarian as well as scientific challenges. We here investigated the geographical character of the early spread of the infection and correlated it with several annual satellite and ground indexes of air quality in China, the United States, Italy, Iran, France, Spain, Germany, and the United Kingdom. The time of the analysis corresponded with the end of the first wave infection in China, namely June 2020. We found more viral infections in those areas afflicted by high PM 2.5 and nitrogen dioxide values. Higher mortality was also correlated with relatively poor air quality. In Italy, the correspondence between the Po Valley pollution and SARS-CoV-2 infections and induced mortality was the starkest, originating right in the most polluted European area. Spain and Germany did not present a noticeable gradient of pollution levels causing non-significant correlations. Densely populated areas were often hotspots of lower air quality levels but were not always correlated with a higher viral incidence. Air pollution has long been recognised as a high risk factor for several respiratory-related diseases and conditions, and it now appears to be a risk factor for COVID-19 as well. As such, air pollution should always be included as a factor for the study of airborne epidemics and further included in public health policies.
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Metelmann S, Pattni K, Brierley L, Cavalerie L, Caminade C, Blagrove MS, Turner J, Sharkey KJ, Baylis M. Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide. One Health 2021; 12:100221. [PMID: 33558848 PMCID: PMC7857042 DOI: 10.1016/j.onehlt.2021.100221] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Revised: 12/31/2020] [Accepted: 01/27/2021] [Indexed: 12/15/2022] Open
Abstract
Approximately a year into the COVID-19 pandemic caused by the SARS-CoV-2 virus, many countries have seen additional "waves" of infections, especially in the temperate northern hemisphere. Other vulnerable regions, such as South Africa and several parts of South America have also seen cases rise, further impacting local economies and livelihoods. Despite substantial research efforts to date, it remains unresolved as to whether COVID-19 transmission has the same sensitivity to climate observed for other common respiratory viruses such as seasonal influenza. Here, we look for empirical evidence of seasonality using a robust estimation framework. For 359 large cities across the world, we estimated the basic reproduction number (R0) using logistic growth curves fitted to cumulative case data. We then assess evidence for association with climatic variables through ordinary least squares (OLS) regression. We find evidence of seasonality, with lower R0 within cities experiencing greater surface radiation (coefficient = -0.005, p < 0.001), after adjusting for city-level variation in demographic and disease control factors. Additionally, we find association between R0 and temperature during the early phase of the epidemic in China. However, climatic variables had much weaker explanatory power compared to socioeconomic and disease control factors. Rates of transmission and health burden of the continuing pandemic will be ultimately determined by population factors and disease control policies.
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Affiliation(s)
- Soeren Metelmann
- Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Brownlow Hill, Liverpool L3 5RF, UK
- Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, UK
| | - Karan Pattni
- Department of Mathematical Sciences, University of Liverpool, Peach Street, Liverpool L69 7ZL, UK
| | - Liam Brierley
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Brownlow Street, Liverpool, L69 3GL, UK
| | - Lisa Cavalerie
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Brownlow Hill, Liverpool L3 5RF, UK
- International Livestock Research Institute, Addis Ababa, Ethiopia
| | - Cyril Caminade
- Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, UK
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Brownlow Hill, Liverpool L3 5RF, UK
| | - Marcus S.C. Blagrove
- Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Brownlow Hill, Liverpool L3 5RF, UK
| | - Joanne Turner
- Department of Mathematical Sciences, University of Liverpool, Peach Street, Liverpool L69 7ZL, UK
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Brownlow Hill, Liverpool L3 5RF, UK
| | - Kieran J. Sharkey
- Department of Mathematical Sciences, University of Liverpool, Peach Street, Liverpool L69 7ZL, UK
| | - Matthew Baylis
- Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, UK
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Brownlow Hill, Liverpool L3 5RF, UK
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39
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Karimi SM, Majbouri M, DuPré N, White KB, Little BB, McKinney WP. Weather and COVID-19 Deaths During the Stay-at-Home Order in the United States. J Occup Environ Med 2021; 63:462-468. [PMID: 34048380 PMCID: PMC8168671 DOI: 10.1097/jom.0000000000002160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE To estimate the association between weather and COVID-19 fatality rates during US stay-at-home orders. METHODS With a county-level longitudinal design, this study analyzed COVID-19 deaths from public health departments' daily reports and considered exposure as the 18 to 22 day-period before death. Models included state-level social distancing measures, Census Bureau demographics, daily weather information, and daily air pollution. The primary measures included minimum and maximum daily temperature, precipitation, ozone concentration, PM2.5 concentrations, and U.V. light index. RESULTS A 1 °F increase in the minimum temperature was associated with 1.9% (95% CI, 0.2% to 3.6%) increase in deaths 20 days later. An ozone concentration increase of 1 ppb (part per billion) decreased daily deaths by 2.0% (95% CI, 0.1% to 3.6%); ozone levels below 38 ppb negatively correlated with deaths. CONCLUSIONS Increased mobility may drive the observed association of minimum daily temperature on COVID-19 deaths.
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40
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Attia YA, El-Saadony MT, Swelum AA, Qattan SYA, Al-Qurashi AD, Asiry KA, Shafi ME, Elbestawy AR, Gado AR, Khafaga AF, Hussein EOS, Ba-Awadh H, Tiwari R, Dhama K, Alhussaini B, Alyileili SR, El-Tarabily KA, Abd El-Hack ME. COVID-19: pathogenesis, advances in treatment and vaccine development and environmental impact-an updated review. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:22241-22264. [PMID: 33733422 PMCID: PMC7969349 DOI: 10.1007/s11356-021-13018-1] [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: 12/26/2020] [Accepted: 02/15/2021] [Indexed: 05/08/2023]
Abstract
Diseases negatively impact the environment, causing many health risks and the spread of pollution and hazards. A novel coronavirus, severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) has led to a recent respiratory syndrome epidemic in humans. In December 2019, the sudden emergence of this new coronavirus and the subsequent severe disease it causes created a serious global health threat and hazards. This is in contrast to the two aforementioned coronaviruses, SARS-CoV-2 (in 2002) and middle east respiratory syndrome coronavirus MERS-CoV (in 2012), which were much more easily contained. The World Health Organization (WHO) dubbed this contagious respiratory disease an "epidemic outbreak" in March 2020. More than 80 companies and research institutions worldwide are working together, in cooperation with many governmental agencies, to develop an effective vaccine. To date, six authorized vaccines have been registered. Up till now, no approved drugs and drug scientists are racing from development to clinical trials to find new drugs for COVID-19. Wild animals, such as snakes, bats, and pangolins are the main sources of coronaviruses, as determined by the sequence homology between MERS-CoV and viruses in these animals. Human infection is caused by inhalation of respiratory droplets. To date, the only available treatment protocol for COVID-19 is based on the prevalent clinical signs. This review aims to summarize the current information regarding the origin, evolution, genomic organization, epidemiology, and molecular and cellular characteristics of SARS-CoV-2 as well as the diagnostic and treatment approaches for COVID-19 and its impact on global health, environment, and economy.
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Affiliation(s)
- Youssef A Attia
- Agriculture Department, Faculty of Environmental Sciences, King Abdulaziz University, P.O. Box 80208, Jeddah, 21589, Saudi Arabia.
- The Strategic Center to Kingdom Vision Realization, King Abdulaziz University, Jeddah, Saudi Arabia.
- Animal and Poultry Production Department, Faculty of Agriculture, Damanhour University, Damanhour, Egypt.
| | - Mohamed T El-Saadony
- Department of Agricultural Microbiology, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt
| | - Ayman A Swelum
- Department of Animal Production, College of Food and Agriculture Sciences, King Saud University, Riyadh, 11451, Saudi Arabia.
- Department of Theriogenology, Faculty of Veterinary Medicine, Zagazig University, Sharkia, Zagazig, 44519, Egypt.
| | - Shaza Y A Qattan
- Department of Biological Sciences, Microbiology, King Abdulaziz University, P.O. Box 80203, Jeddah, 21589, Saudi Arabia
| | - Adel D Al-Qurashi
- Agriculture Department, Faculty of Environmental Sciences, King Abdulaziz University, P.O. Box 80208, Jeddah, 21589, Saudi Arabia
| | - Khalid A Asiry
- Agriculture Department, Faculty of Environmental Sciences, King Abdulaziz University, P.O. Box 80208, Jeddah, 21589, Saudi Arabia
| | - Manal E Shafi
- Department of Biological Sciences, Zoology, King Abdulaziz University, P.O. Box 80203, Jeddah, 21589, Saudi Arabia
| | - Ahmed R Elbestawy
- Poultry and Fish Diseases Department, Faculty of Veterinary Medicine, Damanhour University, Damanhur, 22511, Egypt
| | - Ahmed R Gado
- Poultry and Fish Diseases Department, Faculty of Veterinary Medicine, Damanhour University, Damanhur, 22511, Egypt
| | - Asmaa F Khafaga
- Department of Pathology, Faculty of Veterinary Medicine, Alexandria University, Edfina, Alexandria, 22758, Egypt
| | - Elsayed O S Hussein
- Department of Animal Production, College of Food and Agriculture Sciences, King Saud University, Riyadh, 11451, Saudi Arabia
| | - Hani Ba-Awadh
- Department of Animal Production, College of Food and Agriculture Sciences, King Saud University, Riyadh, 11451, Saudi Arabia
| | - Ruchi Tiwari
- Department of Veterinary Microbiology and Immunology, College of Veterinary Sciences, Uttar Pradesh Pandit Deen Dayal Upadhyaya Pashu Chikitsa Vigyan Vishwavidyalaya Evam Go Anusandhan Sansthan (DUVASU), Mathura, 281001, India
| | - Kuldeep Dhama
- Division of Pathology, Indian Veterinary Research Institute (IVRI), Izatnagar-243, Bareilly, Uttar Pradesh, 122, India
| | - Bakr Alhussaini
- Department of Pediatric, Faculty of Medicine, King Abdualziz University, Jeddah, Saudi Arabia
| | - Salem R Alyileili
- Department of Integrative Agriculture, College of Food and Agriculture, United Arab Emirates University, 15551, Al-Ain, United Arab Emirates
| | - Khaled A El-Tarabily
- Department of Biology, College of Science, United Arab Emirates University, 15551, Al-Ain, United Arab Emirates.
- Harry Butler Institute, Murdoch University, Murdoch, Western Australia, 6150, Australia.
| | - Mohamed E Abd El-Hack
- Department of Poultry, Faculty of Agriculture, Zagazig University, Zagazig, 44511, Egypt
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Barlas SB, Adalier N, Dasdag O, Dasdag S. Evaluation of SARS-CoV-2 with a biophysical perspective. BIOTECHNOL BIOTEC EQ 2021. [DOI: 10.1080/13102818.2021.1885997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Affiliation(s)
- Sait Berk Barlas
- Pre-Graduate Internship Department, Medical School, Koc University, Istanbul, Turkey
| | - Nur Adalier
- Pre-Graduate Internship Department, Medical School, Koc University, Istanbul, Turkey
| | - Omer Dasdag
- Pre-Graduate Internship Department, Medical School, Biruni University, Istanbul, Turkey
| | - Suleyman Dasdag
- Biophysics Department, Medical School, Istanbul Medeniyet University, Istanbul, Turkey
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Abstract
Background: The outbreak of COVID-19 in China in early 2020 provides a rich data source for exploring the ecological determinants of this new infection, which may be of relevance as the pandemic develops. Objectives: Assessing the spread of the COVID-19 across China, in relation to associations between cases and ecological factors including population density, temperature, solar radiation and precipitation. Methods: Open-access COVID-19 case data include 18,069 geo-located cases in China during January and February 2020, which were mapped onto a 0.25° latitude/longitude grid together with population and weather data (temperature, solar radiation and precipitation). Of 15,539 grid cells, 559 (3.6%) contained at least one case, and these were used to construct a Poisson regression model of cell-weeks. Weather parameters were taken for the preceding week given the established 5–7 day incubation period for COVID-19. The dependent variable in the Poisson model was incident cases per cell-week and exposure was cell population, allowing for clustering of cells over weeks, to give incidence rate ratios. Results: The overall COVID-19 incidence rate in cells with confirmed cases was 0.12 per 1,000. There was a single confirmed case in 113/559 (20.2%) of cells, while two grid cells recorded over 1,000 confirmed cases. Weekly means of maximum daily temperature varied from −28.0°C to 30.1°C, minimum daily temperature from −42.4°C to 23.0°C, maximum solar radiation from 0.04 to 2.74 MJm−2 and total precipitation from 0 to 72.6 mm. Adjusted incidence rate ratios suggested brighter, warmer and drier conditions were associated with lower incidence. Conclusion: Though not demonstrating cause and effect, there were appreciable associations between weather and COVID-19 incidence during the epidemic in China. This does not mean the pandemic will go away with summer weather but demonstrates the importance of using weather conditions in understanding and forecasting the spread of COVID-19.
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Affiliation(s)
- Peter Byass
- Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden.,Aberdeen Centre for Health Data Science (ACHDS), Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, Scotland.,MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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