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Dales R, Lukina AO, Romero-Meza R, Blanco-Vidal C, Cakmak S. Ambient air pollution exposure and COVID-19 related hospitalizations in Santiago, Chile. Sci Rep 2024; 14:14186. [PMID: 38902344 PMCID: PMC11190141 DOI: 10.1038/s41598-024-64668-3] [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: 01/09/2024] [Accepted: 06/11/2024] [Indexed: 06/22/2024] Open
Abstract
Morbidity and mortality from several diseases are increased on days of higher ambient air pollution. We carried out a daily time-series analysis with distributive lags to study the influence of short-term air pollution exposure on COVID-19 related hospitalization in Santiago, Chile between March 16 and August 31, 2020. Analyses were adjusted for temporal trends, ambient temperature, and relative humidity, and stratified by age and sex. 26,579 COVID-19 hospitalizations were recorded of which 24,501 were laboratory confirmed. The cumulative percent change in hospitalizations (95% confidence intervals) for an interquartile range increase in air pollutants were: 1.1 (0.2, 2.0) for carbon monoxide (CO), 0.30 (0.0, 0.50) for nitrogen dioxide (NO2), and 2.7 (1.9, 3.0) for particulate matter of diameter ≤ 2.5 microns (PM2.5). Associations with ozone (O3), particulate matter of diameter ≤ 10 microns (PM10) and sulfur dioxide (SO2) were not significant. The observed effect of PM2.5 was significantly greater for females and for those individuals ≥ 65 years old. This study provides evidence that daily increases in air pollution, especially PM2.5, result in a higher observed risk of hospitalization from COVID-19. Females and the elderly may be disproportionately affected.
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Affiliation(s)
- Robert Dales
- Environmental Health Science and Research Bureau, Health Canada, 251 Sir Frederic Banting Driveway, Ottawa, ON, K1A 0K9, Canada
- University of Ottawa and Ottawa Hospital Research Institute, Ottawa, Canada
| | - Anna O Lukina
- Environmental Health Science and Research Bureau, Health Canada, 251 Sir Frederic Banting Driveway, Ottawa, ON, K1A 0K9, Canada
| | - Rafael Romero-Meza
- School of Economics and Business, Universidad Alberto Hurtado, Santiago, Chile
| | | | - Sabit Cakmak
- Environmental Health Science and Research Bureau, Health Canada, 251 Sir Frederic Banting Driveway, Ottawa, ON, K1A 0K9, Canada.
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2
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Rigolon A, Németh J, Anderson-Gregson B, Miller AR, deSouza P, Montague B, Hussain C, Erlandson KM, Rowan SE. The neighborhood built environment and COVID-19 hospitalizations. PLoS One 2023; 18:e0286119. [PMID: 37314984 DOI: 10.1371/journal.pone.0286119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 05/09/2023] [Indexed: 06/16/2023] Open
Abstract
Research on the associations between the built environment and COVID-19 outcomes has mostly focused on incidence and mortality. Also, few studies on the built environment and COVID-19 have controlled for individual-level characteristics across large samples. In this study, we examine whether neighborhood built environment characteristics are associated with hospitalization in a cohort of 18,042 individuals who tested positive for SARS-CoV-2 between May and December 2020 in the Denver metropolitan area, USA. We use Poisson models with robust standard errors that control for spatial dependence and several individual-level demographic characteristics and comorbidity conditions. In multivariate models, we find that among individuals with SARS-CoV-2 infection, those living in multi-family housing units and/or in places with higher particulate matter (PM2.5) have a higher incident rate ratio (IRR) of hospitalization. We also find that higher walkability, higher bikeability, and lower public transit access are linked to a lower IRR of hospitalization. In multivariate models, we did not find associations between green space measures and the IRR of hospitalization. Results for non-Hispanic white and Latinx individuals highlight substantial differences: higher PM2.5 levels have stronger positive associations with the IRR of hospitalization for Latinx individuals, and density and overcrowding show stronger associations for non-Hispanic white individuals. Our results show that the neighborhood built environment might pose an independent risk for COVID-19 hospitalization. Our results may inform public health and urban planning initiatives to lower the risk of hospitalization linked to COVID-19 and other respiratory pathogens.
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Affiliation(s)
- Alessandro Rigolon
- Department of City and Metropolitan Planning, The University of Utah, Salt Lake City, Utah, United States of America
| | - Jeremy Németh
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado, United States of America
| | - Brenn Anderson-Gregson
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado, United States of America
| | - Ana Rae Miller
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado, United States of America
| | - Priyanka deSouza
- Department of Urban and Regional Planning, University of Colorado Denver, Denver, Colorado, United States of America
| | - Brian Montague
- Department of Medicine, Division of Infectious Diseases, University of Colorado Anschutz Medical Campus, Denver, Colorado, United States of America
| | - Cory Hussain
- Department of Medicine, Division of Infectious Diseases, University of Colorado Anschutz Medical Campus, Denver, Colorado, United States of America
- Division of Infectious Diseases, Denver Health and Hospital Authority, Denver, Colorado, United States of America
| | - Kristine M Erlandson
- Department of Medicine, Division of Infectious Diseases, University of Colorado Anschutz Medical Campus, Denver, Colorado, United States of America
| | - Sarah E Rowan
- Department of Medicine, Division of Infectious Diseases, University of Colorado Anschutz Medical Campus, Denver, Colorado, United States of America
- Division of Infectious Diseases, Denver Health and Hospital Authority, Denver, Colorado, United States of America
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Grillenzoni C. Robust time-series analysis of the effects of environmental factors on the CoViD-19 pandemic in the area of Milan (Italy) in the years 2020-21. HYGIENE AND ENVIRONMENTAL HEALTH ADVANCES 2022; 4:100026. [PMID: 37520076 PMCID: PMC9458756 DOI: 10.1016/j.heha.2022.100026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 09/03/2022] [Accepted: 09/08/2022] [Indexed: 08/01/2023]
Abstract
The effects of environmental factors on the spread of the CoViD-19 pandemic have been widely debated in the scientific literature. The results are important for understanding the outbreak dynamics and for defining health measures of prevention and containment. Using multivariate autoregressive (AR) models and robust statistics of causality, this paper analyzes the effect of 19 time series (10 physical and 9 social) on 3 daily CoViD-19 series (infected, hospitalized, deaths) in the Milan area for about 16 months. Robust M-estimation shows the weak effect of climatic and pollution factors, while authority restrictions, people mobility, smart working and vaccination rate have a significant impact. In particular, the vaccination campaign is important for reducing hospitalizations and deaths.
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Rahman M, Petersen H, Irshad H, Liu C, McDonald J, Sood A, Meek PM, Tesfaigzi Y. Cleaning the Flue in Wood-Burning Stoves Is a Key Factor in Reducing Household Air Pollution. TOXICS 2022; 10:615. [PMID: 36287895 PMCID: PMC9609584 DOI: 10.3390/toxics10100615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/09/2022] [Accepted: 10/10/2022] [Indexed: 06/16/2023]
Abstract
In experimental settings, replacing old wood stoves with new wood stoves results in reduced personal exposure to household air pollution. We tested this assumption by measuring PM2.5 and levoglucosan concentrations inside homes and correlated them with wood stove age. Methods: Thirty homes in the Albuquerque, NM area were monitored over a seven-day period using in-home particulate monitors placed in a common living area during the winter months. Real-time aerosol monitoring was performed, and filter samples were analyzed gravimetrically to calculate PM2.5 concentrations and chemically to determine concentrations of levoglucosan. A linear regression model with backward stepwise elimination was performed to determine the factors that would predict household air pollution measures. Results: In this sample, 73.3% of the households used wood as their primary source of heating, and 60% burned daily or almost daily. The mean burn time over the test week was 50 ± 38 h, and only one household burned wood 24/day (168 h). The average PM2.5 concentration (standard deviation) for the 30 homes during the seven-day period was 34.6 µg/m3 (41.3 µg/m3), and median (min, max) values were 15.5 µg/m3 (7.3 µg/m3, 193 µg/m3). Average PM2.5 concentrations in 30 homes ranged from 0−15 μg/m3 to >100 μg/m3. Maximum PM2.5 concentrations ranged from 100−200 μg/m3 to >3000 μg/m3. The levoglucosan levels showed a linear correlation with the total PM2.5 collected by the filters (R2 = 0.92). However, neither mean nor peak PM2.5 nor levoglucosan levels were correlated with the age (10.85 ± 8.54 years) of the wood stove (R2 ≤ 0.07, p > 0.23). The final adjusted linear regression model showed that average PM2.5 was associated with reports of cleaning the flue with a beta estimate of 35.56 (3.47−67.65) and R2 = 0.16 (p = 0.04). Discussion: Cleaning the flue and not the wood stove age was associated with household air pollution indices. Education on wood stove maintenance and safe burning practices may be more important in reducing household air pollution than the purchase of new stoves.
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Affiliation(s)
- Mizanur Rahman
- Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Hans Petersen
- Chronic Obstructive Pulmonary Disease Program, Lovelace Biomedical Research Institute, Albuquerque, NM 87108, USA
| | - Hammad Irshad
- Applied Sciences, Lovelace Biomedical Research Institute, Albuquerque, NM 87108, USA
| | - Congjian Liu
- Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jacob McDonald
- Applied Sciences, Lovelace Biomedical Research Institute, Albuquerque, NM 87108, USA
| | - Akshay Sood
- Department of Internal Medicine, University of New Mexico School of Medicine and Miners Colfax Medical Center, Raton, NM 87740, USA
| | - Paula M. Meek
- Department of Internal Medicine, University of New Mexico School of Medicine and Miners Colfax Medical Center, Raton, NM 87740, USA
- College of Nursing, University of Utah, Salt Lake City, UT 84102, USA
| | - Yohannes Tesfaigzi
- Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
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Naimoli A. Modelling the persistence of Covid-19 positivity rate in Italy. SOCIO-ECONOMIC PLANNING SCIENCES 2022; 82:101225. [PMID: 35017746 PMCID: PMC8739816 DOI: 10.1016/j.seps.2022.101225] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 12/20/2021] [Accepted: 01/04/2022] [Indexed: 05/24/2023]
Abstract
The current Covid-19 pandemic is severely affecting public health and global economies. In this context, accurately predicting its evolution is essential for planning and providing resources effectively. This paper aims at capturing the dynamics of the positivity rate (PPR) of the novel coronavirus using the Heterogeneous Autoregressive (HAR) model. The use of this model is motivated by two main empirical features arising from the analysis of PPR time series: the changing long-run level and the persistent autocorrelation structure. Compared to the most frequently used Autoregressive Integrated Moving Average (ARIMA) models, the HAR is able to reproduce the strong persistence of the data by using components aggregated at different interval sizes, remaining parsimonious and easy to estimate. The relative merits of the proposed approach are assessed by performing a forecasting study on the Italian dataset. As a robustness check, the analysis of the positivity rate is also conducted by considering the case of the United States. The ability of the HAR-type models to predict the PPR at different horizons is evaluated through several loss functions, comparing the results with those generated by ARIMA models. The Model Confidence Set is used to test the significance of differences in the predictive performances of the models under analysis. Our findings suggest that HAR-type models significantly outperform ARIMA specifications in terms of forecasting accuracy. We also find that the PPR could represent an important metric for monitoring the evolution of hospitalizations, as the peak of patients in intensive care units occurs within 12-16 days after the peak in the positivity rate. This can help governments in planning socio-economic and health policies in advance.
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Affiliation(s)
- Antonio Naimoli
- Università di Salerno, Dipartimento di Scienze Economiche e Statistiche (DISES), Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy
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Goldstein ND, Webster JL, Robinson LF, Welles SL. Disparities of COVID-19 and HIV Occurrence Based on Neighborhood Infection Incidence in Philadelphia, Pennsylvania. Am J Public Health 2022; 112:408-416. [PMID: 35196028 PMCID: PMC8887150 DOI: 10.2105/ajph.2021.306538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Objectives. To evaluate the occurrence of HIV and COVID-19 infections in Philadelphia, Pennsylvania, through July 2020 and identify ecological correlates driving racial disparities in infection incidence. Methods. For each zip code tabulation area, we created citywide comparison Z-score measures of COVID-19 cases, new cases of HIV, and the difference between the scores. Choropleth maps were used to identify areas that were similar or dissimilar in terms of disease patterning, and weighted linear regression models helped identify independent ecological predictors of these patterns. Results. Relative to COVID-19, HIV represented a greater burden in Center City Philadelphia, whereas COVID-19 was more apparent in Northeast Philadelphia. Areas with a greater proportion of Black or African American residents were overrepresented in terms of both diseases. Conclusions. Although race is a shared nominal upstream factor that conveys increased risk for both infections, an understanding of separate structural, demographic, and economic risk factors that drive the overrepresentation of COVID-19 cases in racial/ethnic communities across Philadelphia is critical. Public Health Implications. Difference-based measures are useful in identifying areas that are underrepresented or overrepresented with respect to disease occurrence and may be able to elucidate effective or ineffective mitigation strategies. (Am J Public Health. 2022;112(3):408-416. https://doi.org/10.2105/AJPH.2021.306538).
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Affiliation(s)
- Neal D. Goldstein
- All of the authors are with the Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA
| | - Jessica L. Webster
- All of the authors are with the Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA
| | - Lucy F. Robinson
- All of the authors are with the Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA
| | - Seth L. Welles
- All of the authors are with the Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA
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Han Y, Zhao W, Pereira P. Global COVID-19 pandemic trends and their relationship with meteorological variables, air pollutants and socioeconomic aspects. ENVIRONMENTAL RESEARCH 2022; 204:112249. [PMID: 34740619 PMCID: PMC8563087 DOI: 10.1016/j.envres.2021.112249] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 10/18/2021] [Accepted: 10/18/2021] [Indexed: 05/04/2023]
Abstract
Meteorological variables, air pollutants, and socioeconomic factors are associated with COVID-19 transmission. However, it is unclear what impact their interactions have on COVID-19 transmission, whether their impact on COVID-19 transmission is linear or non-linear, and where the inflexion points are. This study examined 1) the spatial and temporal trends in COVID-19 monthly infection rate of new confirmed cases per 100,000 people (Rn) in 188 countries/regions worldwide from March to November 2020; 2) the linear correlation between meteorological variables (temperature (T), rainfall (R), wind speed (WS), relative humidity (RH), air pressure (AP)), air pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3)) and socioeconomic aspects (population density (PD), gross domestic product per capita (GDP), domestic general government health expenditure per capita (GHE)) and Rn, and 3) the interaction and non-linear effects of the different variables on Rn, based on GeoDetector and Boosted regression tree. The results showed that the global Rn had was spatially clustered, and the average Rn increased From March to November 2020. Global Rn was negatively correlated with meteorological variables (T, R, WS, AP) and positively correlated with air pollutants (NO2, SO2, O3) and socioeconomic aspects (GDP, GHE). The interaction of SO2 and O3, SO2 and RH, and O3 and T strongly affected Rn. The variables effect on COVID-19 transmission was non-linear, with one or more inflexion points. The findings of this work can provide a basis for developing a global response to COVID-19 for global sustainable development.
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Affiliation(s)
- Yi Han
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| | - Wenwu Zhao
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Institute of Land Surface System and Sustainable Development, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
| | - Paulo Pereira
- Environmental Management Center, Mykolas Romeris University, Ateities g. 20, LT-08303, Vilnius, Lithuania.
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Mondal S, Chaipitakporn C, Kumar V, Wangler B, Gurajala S, Dhaniyala S, Sur S. COVID-19 in New York state: Effects of demographics and air quality on infection and fatality. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 807:150536. [PMID: 34628294 PMCID: PMC8461036 DOI: 10.1016/j.scitotenv.2021.150536] [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: 03/10/2021] [Revised: 07/28/2021] [Accepted: 09/19/2021] [Indexed: 05/07/2023]
Abstract
The coronavirus disease 2019 (COVID-19) has had a global impact that has been unevenly distributed among and even within countries. Multiple demographic and environmental factors have been associated with the risk of COVID-19 spread and fatality, including age, gender, ethnicity, poverty, and air quality among others. However, specific contributions of these factors are yet to be understood. Here, we attempted to explain the variability in infection, death, and fatality rates by understanding the contributions of a few selected factors. We compared the incidence of COVID-19 in New York State (NYS) counties during the first wave of infection and analyzed how different demographic and environmental variables associate with the variation observed across the counties. We observed that infection and death rates, two important COVID-19 metrics, to be highly correlated with both being highest in counties located near New York City, considered as one of the epicenters of the infection in the US. In contrast, disease fatality was found to be highest in a different set of counties despite registering a low infection rate. To investigate this apparent discrepancy, we divided the counties into three clusters based on COVID-19 infection, death, or fatality, and compared the differences in the demographic and environmental variables such as ethnicity, age, population density, poverty, temperature, and air quality in each of these clusters. Furthermore, a regression model built on this data reveals PM2.5 and distance from the epicenter are significant risk factors for infection, while disease fatality has a strong association with age and PM2.5. Our results demonstrate that for the NYS, demographic components distinctly associate with specific aspects of COVID-19 burden and also highlight the detrimental impact of poor air quality. These results could help design and direct location-specific control and mitigation strategies.
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Affiliation(s)
- Sumona Mondal
- Department of Mathematics, Clarkson University, Potsdam, NY, USA
| | | | - Vijay Kumar
- Department of Mathematics, Clarkson University, Potsdam, NY, USA
| | - Bridget Wangler
- David D. Reh School of Business, Clarkson University, Potsdam, NY, USA
| | | | - Suresh Dhaniyala
- Department of Mechanical and Aeronautical Engineering, Clarkson University, Potsdam, NY, USA
| | - Shantanu Sur
- Department of Biology, Clarkson University, Potsdam, NY, USA.
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Prediction of highly vulnerable areas to COVID-19 outbreaks using spatial model: Case study of Cairo Governorate, Egypt. THE EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES 2022; 25:233-247. [PMCID: PMC8352670 DOI: 10.1016/j.ejrs.2021.08.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 08/02/2021] [Accepted: 08/02/2021] [Indexed: 06/02/2023]
Abstract
COVID-19 has affected over 170 countries around the world. Alarming rate has increased with the increase of infected cases and death rates. Whereas, the World Health Organization (WHO) had declared the COVID-19 virus as a pandemic on 11th March 2020. Preparations were made to face the spread of COVID-19, as predicting the most probable risk areas by using spatial models. Prediction spatial models of COVID-19 risk areas can help the governmental authorities to generate sustainable strategies and set up suitable protocols to control the pandemic. This research presents an attempt of a potential spatial prediction modeling of COVID-19 risk areas in Cairo governorate-Egypt. Four indicator models (demographic, residential, environmental and topographic) were developed using geomatics technology based on the guidelines of the UN-habitat sustainable development goals (SDGs) target (11 & 3). Five predicted scenarios were generated for the most pandemic probability areas by the integration of the four indicator models. The results showed that there are common areas in all scenarios for highly COVID-19 pandemic risk areas. These common risk areas were found in (El Marag, El Salam, Ain Shams, El Mataria, El Gammaleya, Manshiat Nasser, El Mosky, Bolak, Hadaak El Koba, and El Sharbeya) districts. The hotspots zones are characterized by overcrowding, high population density and economic activities, large family size, poor infrastructure service and low rate of education. Moreover, it was noticed that crowding points resulted in traffic density and air pollution, which may affect the pandemic spread. The accuracy assessment results displayed that, the environmental predicted scenario was more consistent with the official data of the Egyptian Ministry of Health and Population) MOHP), while the residential one was less convenient. The result of this study supports the health sector by predicting the hot spots areas. The present study is aimed to develop a proactive plan to confront the pandemic before spreading in the Cairo governorate-Egypt. Also, the proposed prediction model can be an effective aid for decision-makers across the world working on containment strategies to minimize the spread of Coronavirus.
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Liang Z, Deng C, Li D, Lo WLA, Yu Q, Chen Z. The effects of the home-based exercise during COVID-19 school closure on the physical fitness of preschool children in China. Front Pediatr 2022; 10:932734. [PMID: 36110116 PMCID: PMC9469900 DOI: 10.3389/fped.2022.932734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Social distancing and school closures during the COVID-19 pandemic reduced the physical activities of the preschool children living in China. However, the effects of home-based exercise on the physical fitness of Chinese preschool children during COVID-19 school closures are still unknown. This study aimed to investigate the effects of home-based exercise on the physical fitness of Chinese preschool children during COVID-19 school closure. METHODS In this retrospective analysis, data from 1,608 Chinese preschool children (aged 3-5.5 years) in a second-tier city of Guangdong Province of China (Zhongshan city) were extracted from three successive National Physical Fitness Measurement (NPFM) from 2019 to 2021. NPFM consists of weight, height, and six subtests of physical fitness including 10-m shuttle run test (SRT), standing long jump (SLJ), balance beam walking (BBW), sit-and-reach (SR), tennis throwing (TT), and double-leg timed hop (DTH) tests. The change differences or change ratios of all the items in NPFM between any two successive years from 2019 to 2021 were compared. The exercise profiles about home-based and outdoor exercise before, during, and after COVID-19 school closure were obtained from 185 preschool children via retrospective telephone survey. RESULTS Between 2019 and 2021, 1,608 preschool children were included in this study. We observed larger changes in SLJ, SR, TT, and DTH tests during school closure than after school closure. But the children showed lower reduction rates in the completion time of SRT and BBW. During school closure, higher change ratios in SLJ and TT were observed in the children primarily participating in home-based exercise than those primarily participating in outdoor exercise. However, no statistical differences were observed in the changes in SRT and BBW between home-based and outdoor training groups. CONCLUSION The home-based exercise program might be an alternative approach to improve the physical fitness of preschool children during COVID-19 school closure, but could not be beneficial to speed-agility and balance functions. A specific guideline geared toward a home-based exercise program during the COVID-19 outbreak is highly needed.
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Affiliation(s)
- Zhenwen Liang
- Department of Rehabilitation, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Cheng Deng
- Department of Children's Health Care, Zhongshan Torch Development Zone People's Hospital, Zhongshan, China
| | - Dan Li
- Department of Rehabilitation, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Wai Leung Ambrose Lo
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qiuhua Yu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhuoming Chen
- Department of Rehabilitation, The First Affiliated Hospital of Jinan University, Guangzhou, China
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11
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Salvacion AR. COVID-19 susceptibility mapping: a case study for Marinduque Island, Philippines. SPATIAL INFORMATION RESEARCH 2022; 30:563-570. [PMCID: PMC9136557 DOI: 10.1007/s41324-022-00444-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 03/02/2022] [Accepted: 03/06/2022] [Indexed: 06/16/2023]
Abstract
Small islands are highly susceptible to infectious disease outbreak and other health emergencies because of their remoteness, small physical size, and poorly developed infrastructure. These are true in the case of Marinduque, an island province around 200 km south of the National Capital Region (NCR), which is the “epidemiological epicenter” of the COVID-19 pandemic in the Philippines. This study utilized GIS and Principal Component Analysis (PCA) using demographic, socio-economic, and geographic indicators to map susceptibility of different villages in the island province of Marinduque, the Philippines. Based on the results, the northwestern and northeastern portion of Marinduque has a higher susceptibility score. Also, villages in the town centers have relatively high susceptibility scores compared to other villages in each municipality.
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Affiliation(s)
- Arnold R. Salvacion
- Department of Community and Environmental Resource Planning, College of Human Ecology, University of the Philippines Los Baños, 4031 College, Laguna, Philippines
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12
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Bontempi E, Coccia M. International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors. ENVIRONMENTAL RESEARCH 2021; 201:111514. [PMID: 34139222 PMCID: PMC8204848 DOI: 10.1016/j.envres.2021.111514] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 05/15/2021] [Accepted: 06/05/2021] [Indexed: 05/19/2023]
Abstract
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the Coronavirus Disease 2019 (COVID-19), generating high numbers of COVID-19 related infected individuals and deaths, is still circulating in 2021 with new variants of the coronavirus, such that the state of emergency remains in manifold countries. Currently, there is still a lack of a full understanding of the factors determining the COVID-19 diffusion that clarify the causes of the variability of infections across different provinces and regions within countries. The main goal of this study is to explain new and main determinants underlying the diffusion of COVID-19 in society. This study focuses on international trade because this factor, in a globalized world, can synthetize different drivers of virus spread, such as mobility patterns, economic potentialities, and social interactions of an investigated areas. A case study research is performed on 107 provinces of Italy, one of the first countries to experience a rapid increase in confirmed cases and deaths. Statistical analyses from March 2020 to February 2021 suggest that total import and export of provinces has a high association with confirmed cases over time (average r > 0.78, p-value <.001). Overall, then, this study suggests total import and export as complex indicator of COVID-19 transmission dynamics that outclasses other common parameters used to justify the COVID-19 spread, given by economic, demographic, environmental, and climate factors. In addition, this study proposes, for the first time, a time-dependent correlation analysis between trade data and COVID-19 infection cases to explain the relation between confirmed cases and social interactions that are a main source of the diffusion of SARS-CoV-2 and subsequent negative impact in society. These novel findings have main theoretical and practical implications directed to include a new parameter in modelling of the diffusion of COVID-19 pandemic to support effective policy responses of crisis management directed to constrain the impact of COVID-19 pandemic and similar infectious diseases in society.
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Affiliation(s)
- E Bontempi
- INSTM and Chemistry for Technologies Laboratory, University of Brescia, Via Branze 38, 25123, Brescia, Italy.
| | - M Coccia
- CNR -- National Research Council of Italy, Via Real Collegio, N. 30, (Collegio Carlo Alberto), 10024, Moncalieri, TO, Italy.
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Shao L, Ge S, Jones T, Santosh M, Silva LFO, Cao Y, Oliveira MLS, Zhang M, BéruBé K. The role of airborne particles and environmental considerations in the transmission of SARS-CoV-2. GEOSCIENCE FRONTIERS 2021; 12:101189. [PMID: 38620834 PMCID: PMC8020609 DOI: 10.1016/j.gsf.2021.101189] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 03/15/2021] [Accepted: 03/17/2021] [Indexed: 05/06/2023]
Abstract
Corona Virus Disease 2019 (COVID-19) caused by the novel coronavirus, results in an acute respiratory condition coronavirus 2 (SARS-CoV-2) and is highly infectious. The recent spread of this virus has caused a global pandemic. Currently, the transmission routes of SARS-CoV-2 are being established, especially the role of environmental transmission. Here we review the environmental transmission routes and persistence of SARS-CoV-2. Recent studies have established that the transmission of this virus may occur, amongst others, in the air, water, soil, cold-chain, biota, and surface contact. It has also been found that the survival potential of the SARS-CoV-2 virus is dependent on different environmental conditions and pollution. Potentially important pathways include aerosol and fecal matter. Particulate matter may also be a carrier for SARS-CoV-2. Since microscopic particles can be easily absorbed by humans, more attention must be focused on the dissemination of these particles. These considerations are required to evolve a theoretical platform for epidemic control and to minimize the global threat from future epidemics.
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Affiliation(s)
- Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Shuoyi Ge
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- 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, Museum Avenue, Cardiff, CF10 3YE, UK
| | - M Santosh
- School of Earth Sciences and Resources, China University of Geosciences 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
| | - Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Marcos L S Oliveira
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
- Departamento de Ingeniería Civil y Arquitectura, Universidad de Lima, Avenida Javier Prado Este 4600 - Santiago de, Surco 1503, Peru
| | - Mengyuan Zhang
- State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology (Beijing), Beijing 100083, China
- 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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Poyraz BM, Engin ED, Engin AB, Engin A. The effect of environmental diesel exhaust pollution on SARS-CoV-2 infection: The mechanism of pulmonary ground glass opacity. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2021; 86:103657. [PMID: 33838330 PMCID: PMC8025547 DOI: 10.1016/j.etap.2021.103657] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 03/30/2021] [Accepted: 04/02/2021] [Indexed: 05/19/2023]
Abstract
Diesel exhaust particles (DEP) are the major components of atmospheric particulate matter (PM) and chronic exposure is recognized to enhance respiratory system complications. Although the spread of SARS-CoV-2 was found to be associated with the PMs, the mechanism by which exposure to DEP increases the risk of SARS-CoV-2 infection is still under discussion. However, diesel fine PM (dPM) elevate the probability of SARS-CoV-2 infection, as it coincides with the increase in the number of ACE2 receptors. Expression of ACE2 and its colocalized activator, transmembrane protease serine 2 (TMPRSS2) facilitate the entry of SARS-CoV-2 into the alveolar epithelial cells exposed to dPM. Thus, the coexistence of PM and SARS-CoV-2 in the environment augments inflammation and exacerbates lung damage. Increased TGF-β1 expression due to DEP accompanies the proliferation of the extracellular matrix. In this case, "multifocal ground-glass opacity" (GGO) in a CT scan is an indication of a cytokine storm and severe pneumonia in COVID-19.
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Affiliation(s)
| | - Evren Doruk Engin
- Ankara University, Biotechnology Institute, Gumusdere Campus, Kecioren, Ankara, Turkey
| | - Ayse Basak Engin
- Gazi University, Faculty of Pharmacy, Department of Toxicology, Ankara, Turkey.
| | - Atilla Engin
- Gazi University, Faculty of Medicine, Department of General Surgery, Ankara, Turkey
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15
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Zhang S, Yang Z, Wang M, Zhang B. "Distance-Driven" Versus "Density-Driven": Understanding the Role of "Source-Case" Distance and Gathering Places in the Localized Spatial Clustering of COVID-19-A Case Study of the Xinfadi Market, Beijing (China). GEOHEALTH 2021; 5:e2021GH000458. [PMID: 34466764 PMCID: PMC8381857 DOI: 10.1029/2021gh000458] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 07/20/2021] [Accepted: 07/24/2021] [Indexed: 05/09/2023]
Abstract
The frequent occurrence of local COVID-19 today gives a strong necessity to better understand the effects of "source-case" distance and gathering places, which are often considered to be the key factors of the localized spatial clustering of an epidemic. In this study, the localized spatial clustering of COVID-19 cases, which originated in the Xinfadi market in Beijing from June-July 2020, was investigated by exploring the spatiotemporal characteristics of the clustering using descriptive statistics, point pattern analysis, and spatial autocorrelation calculation approaches. Spatial lag zero-inflated negative binomial regression model and geographically weighted Poisson regression with spatial effects were also introduced to explore the factors which influenced the clustering of COVID-19 cases at the micro spatial scale. It was found that the local epidemic can be significantly divided into two stages which are asymmetric in time. A significant spatial spillover effect of COVID-19 was identified in both global and local modeling estimation. The dominant role of the "source-case" distance effect, which was reflected in both global and local scales, was revealed. Relatively, the role of gathering places is not significant at the initial stage of the epidemic, but the upward trend of the significance of some places is obvious. The trend from "distance-driven" to "density-driven" of the localized spatial clustering of COVID-19 was predicted. The effectiveness of blocking the transformation trend will be a key issue for the global response to the local COVID-19.
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Affiliation(s)
- Sui Zhang
- School of Geography and EnvironmentShandong Normal UniversityJinanChina
| | - Zhao Yang
- School of Geography and EnvironmentShandong Normal UniversityJinanChina
| | - Minghao Wang
- School of Geography and EnvironmentShandong Normal UniversityJinanChina
| | - Baolei Zhang
- School of Geography and EnvironmentShandong Normal UniversityJinanChina
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16
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Yang XD, Su XY, Li HL, Ma RF, Qi FJ, Cao YE. Impacts of socio-economic determinants, spatial distance and climate factors on the confirmed cases and deaths of COVID-19 in China. PLoS One 2021; 16:e0255229. [PMID: 34314442 PMCID: PMC8315531 DOI: 10.1371/journal.pone.0255229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2021] [Accepted: 07/12/2021] [Indexed: 01/09/2023] Open
Abstract
This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p < 0.05), but not obviously different in Hubei province (p > 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p < 0.05), while was only significantly related with GDP in Hubei province (p < 0.05). The DOPSPTT showed significant correlation with socio-economic determinants, DW, time and CCOPSPTT outside Hubei province (p < 0.05), while was significantly correlated with GDP and CCOPSPTT in Hubei province (p < 0.05). Compared with other factors, socio-economic determinants have the largest relative contribution to variance of CCOPSPTT in all studied cities (> 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors.
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Affiliation(s)
- Xiao-Dong Yang
- Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo, China
- Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, China
| | - Xin-Yi Su
- Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo, China
| | - Hong-Li Li
- Department of Geography and Spatial Information Techniques/Center for Land and Marine Spatial Utilization and Governance Research, Ningbo University, Ningbo, China
- Ningbo Universities Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research at Ningbo University, Ningbo, China
| | - Ren-Feng Ma
- Institute of East China Sea, Ningbo University, Ningbo, China
| | - Fang-Jie Qi
- Global Centre for Environmental Research, Advanced Technology Center (ATC) Building, Faculty of Science, The University of Newcastle, Callaghan, NSW, Australia
- Cooperative Research Centre for Contamination Assessment and Remediation of Environment (CRC CARE), The University of Newcastle, Callaghan, NSW, Australia
| | - Yue-E Cao
- School of Environmental and Geographical Science, Shanghai Normal University, Shanghai, China
- Institute of Resources and Environment Science, Xinjiang University, Urumqi, China
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Li T, Luo J, Huang C. Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index. Sci Rep 2021; 11:14663. [PMID: 34282250 PMCID: PMC8290012 DOI: 10.1038/s41598-021-94144-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 07/06/2021] [Indexed: 02/06/2023] Open
Abstract
Multiple small- to middle-scale cities, mostly located in northern China, became epidemic hotspots during the second wave of the spread of COVID-19 in early 2021. Despite qualitative discussions of potential social-economic causes, it remains unclear how this unordinary pattern could be substantiated with quantitative explanations. Through the development of an urban epidemic hazard index (EpiRank) for Chinese prefectural districts, we came up with a mathematical explanation for this phenomenon. The index is constructed via epidemic simulations on a multi-layer transportation network interconnecting local SEIR transmission dynamics, which characterizes intra- and inter-city population flow with a granular mathematical description. Essentially, we argue that these highlighted small towns possess greater epidemic hazards due to the combined effect of large local population and small inter-city transportation. The ratio of total population to population outflow could serve as an alternative city-specific indicator of such hazards, but its effectiveness is not as good as EpiRank, where contributions from other cities in determining a specific city's epidemic hazard are captured via the network approach. Population alone and city GDP are not valid signals for this indication. The proposed index is applicable to different epidemic settings and can be useful for the risk assessment and response planning of urban epidemic hazards in China. The model framework is modularized and the analysis can be extended to other nations.
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Affiliation(s)
- Tianyi Li
- grid.10784.3a0000 0004 1937 0482Department of Decision Sciences and Managerial Economics, CUHK Business School, Hong Kong, China
| | - Jiawen Luo
- grid.5801.c0000 0001 2156 2780Institute of Geophysics, ETH Zurich, Zurich, Switzerland
| | - Cunrui Huang
- grid.12981.330000 0001 2360 039XDepartment of Health Policy and Management, School of Public Health, Sun Yat-sen University, Guangzhou, China ,Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Service, Shanghai, China ,grid.207374.50000 0001 2189 3846School of Public Health, Zhengzhou University, Zhengzhou, China
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18
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Dales R, Blanco-Vidal C, Romero-Meza R, Schoen S, Lukina A, Cakmak S. The association between air pollution and COVID-19 related mortality in Santiago, Chile: A daily time series analysis. ENVIRONMENTAL RESEARCH 2021; 198:111284. [PMID: 33971125 PMCID: PMC8547777 DOI: 10.1016/j.envres.2021.111284] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 04/13/2021] [Accepted: 05/03/2021] [Indexed: 05/20/2023]
Abstract
BACKGROUND Exposure to ambient air pollution is a risk factor for morbidity and mortality from lung and heart disease. RESEARCH QUESTION Does short term exposure to ambient air pollution influence COVID-19 related mortality? STUDY DESIGN AND METHODOLOGY Using time series analyses we tested the association between daily changes in air pollution measured by stationary monitors in and around Santiago, Chile and deaths from laboratory confirmed or suspected COVID-19 between March 16 and August 31, 2020. Results were adjusted for temporal trends, temperature and humidity, and stratified by age and sex. RESULTS There were 10,069 COVID-19 related deaths of which 7659 were laboratory confirmed. Using distributed lags, the cumulative relative risk (RR) (95% CI) of mortality for an interquartile range (IQR) increase in CO, NO2 and PM2.5 were 1.061 (1.033-1.089), 1.067 (1.023-1.103) and 1.058 (1.034-1.082), respectively There were no significant differences in RR by sex.. In those at least 85 years old, an IQR increase in NO2 was associated with a 12.7% (95% CI 4.2-22.2) increase in daily mortality. CONCLUSION This study provides evidence that daily increases in air pollution increase the risk of dying from COVID-19, especially in the elderly.
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Affiliation(s)
- Robert Dales
- Population Studies Division, Environmental Health Science & Research Bureau, Health Canada, Canada; University of Ottawa and Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Rafael Romero-Meza
- School of Economics and Business, Universidad Alberto Hurtado, Santiago, Chile
| | | | - Anna Lukina
- Population Studies Division, Environmental Health Science & Research Bureau, Health Canada, Canada
| | - Sabit Cakmak
- Population Studies Division, Environmental Health Science & Research Bureau, Health Canada, Canada.
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19
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Ingram C, Min E, Seto E, Cummings BJ, Farquhar S. Cumulative Impacts and COVID-19: Implications for Low-Income, Minoritized, and Health-Compromised Communities in King County, WA. J Racial Ethn Health Disparities 2021; 9:1210-1224. [PMID: 34128216 PMCID: PMC8202963 DOI: 10.1007/s40615-021-01063-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/15/2021] [Accepted: 05/17/2021] [Indexed: 11/12/2022]
Abstract
Few studies have assessed how the intersection of social determinants of health and environmental hazards contributes to racial disparities in COVID-19. The aim of our study was to compare COVID-19 disparities in testing and positivity to cumulative environmental health impacts, and to assess how unique social and environmental determinants of health relate to COVID-19 positivity in Seattle, King County, WA, at the census tract level. Publicly available data (n = 397 census tracts) were obtained from Public Health–Seattle & King County, 2018 ACS 5-year estimates, and the Washington Tracking Network. COVID-19 testing and positive case rates as of July 12, 2020, were mapped and compared to Washington State Environmental Health Disparities (EHD) Map cumulative impact rankings. We calculated odds ratios from a series of univariable and multivariable logistic regression analyses using cumulative impact rankings, and community-level socioeconomic, health, and environmental factors as predictors and having ≥ 10% or < 10% census tract positivity as the binary outcome variable. We found a remarkable overlap between Washington EHD cumulative impact rankings and COVID-19 positivity in King County. Census tracts with ≥ 10 % COVID-19 positivity had significantly lower COVID-19 testing rates and higher proportions of people of color and faced a combination of low socioeconomic status–related outcomes, poor community health outcomes, and significantly higher concentrations of fine particulate matter (PM2.5). King County communities experiencing high rates of COVID-19 face a disproportionate cumulative burden of environmental and social inequities. Cumulative environmental health impacts should therefore systematically be considered when assessing for risk of exposure to and health complications resulting from COVID-19.
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Affiliation(s)
- Carolyn Ingram
- School of Public Health, Physiotherapy, and Sports Science, University College Dublin, Belfield, Dublin 4, Ireland. .,ISPED (Bordeaux School of Public Health) , University of Bordeaux , Bordeaux, France.
| | - Esther Min
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Edmund Seto
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - B J Cummings
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, USA
| | - Stephanie Farquhar
- Department of Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, USA.,Department of Health Services, University of Washington, Seattle, WA, USA
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Kong JD, Tekwa EW, Gignoux-Wolfsohn SA. Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries. PLoS One 2021; 16:e0252373. [PMID: 34106993 PMCID: PMC8189449 DOI: 10.1371/journal.pone.0252373] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 05/15/2021] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE To assess whether the basic reproduction number (R0) of COVID-19 is different across countries and what national-level demographic, social, and environmental factors other than interventions characterize initial vulnerability to the virus. METHODS We fit logistic growth curves to reported daily case numbers, up to the first epidemic peak, for 58 countries for which 16 explanatory covariates are available. This fitting has been shown to robustly estimate R0 from the specified period. We then use a generalized additive model (GAM) to discern both linear and nonlinear effects, and include 5 random effect covariates to account for potential differences in testing and reporting that can bias the estimated R0. FINDINGS We found that the mean R0 is 1.70 (S.D. 0.57), with a range between 1.10 (Ghana) and 3.52 (South Korea). We identified four factors-population between 20-34 years old (youth), population residing in urban agglomerates over 1 million (city), social media use to organize offline action (social media), and GINI income inequality-as having strong relationships with R0, across countries. An intermediate level of youth and GINI inequality are associated with high R0, (n-shape relationships), while high city population and high social media use are associated with high R0. Pollution, temperature, and humidity did not have strong relationships with R0 but were positive. CONCLUSION Countries have different characteristics that predispose them to greater intrinsic vulnerability to COVID-19. Studies that aim to measure the effectiveness of interventions across locations should account for these baseline differences in social and demographic characteristics.
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Affiliation(s)
- Jude Dzevela Kong
- Centre for Diseases Modeling (CDM), York University, Toronto, ON, Canada
- Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | - Edward W. Tekwa
- Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, NJ, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States of America
- Department of Zoology, University of British Columbia, BC, Canada
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21
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Cao Y, Shao L, Jones T, Oliveira MLS, Ge S, Feng X, Silva LFO, BéruBé K. Multiple relationships between aerosol and COVID-19: A framework for global studies. GONDWANA RESEARCH : INTERNATIONAL GEOSCIENCE JOURNAL 2021; 93:243-251. [PMID: 33584115 PMCID: PMC7871891 DOI: 10.1016/j.gr.2021.02.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 02/03/2021] [Accepted: 02/03/2021] [Indexed: 05/03/2023]
Abstract
COVID-19 (Corona Virus Disease 2019) is a severe respiratory syndrome currently causing a human global pandemic. The original virus, along with newer variants, is highly transmissible. Aerosols are a multiphase system consisting of the atmosphere with suspended solid and liquid particles, which can carry toxic and harmful substances; especially the liquid components. The degree to which aerosols can carry the virus and cause COVID-19 disease is of significant research importance. In this study, we have discussed aerosol transmission as the pathway of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), and the aerosol pollution reduction as a consequence of the COVID-19 lockdown. The aerosol transmission routes of the SARS-CoV-2 can be further subdivided into proximal human-exhaled aerosol transmission and potentially more distal ambient aerosol transmission. The human-exhaled aerosol transmission is a direct dispersion of the SARS-CoV-2. The ambient aerosol transmission is an indirect dispersion of the SARS-CoV-2 in which the aerosol acts as a carrier to spread the virus. This indirect dispersion can also stimulate the up-regulation of the expression of SARS-CoV-2 receptor ACE-2 (Angiotensin Converting Enzyme 2) and protease TMPRSS2 (Transmembrane Serine Protease 2), thereby increasing the incidence and mortality of COVID-19. From the aerosol quality data around the World, it can be seen that often atmospheric pollution has significantly decreased due to factors such as the reduction of traffic, industry, cooking and coal-burning emissions during the COVID-19 lockdown. The airborne transmission potential of SARS-CoV-2, the infectivity of the virus in ambient aerosols, and the reduction of aerosol pollution levels due to the lockdowns are crucial research subjects.
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Affiliation(s)
- Yaxin Cao
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining and 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, Cardiff, CF10, 3YE, Wales, UK
| | - Marcos L S Oliveira
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
- Departamento de Ingeniería Civil y Arquitectura, Universidad de Lima, Avenida Javier Prado Este 4600 - Santiago de Surco 1503, Peru
| | - Shuoyi Ge
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
| | - Luis F O Silva
- Department of Civil and Environmental, Universidad de la Costa, Calle 58 #55-66, 080002 Barranquilla, Atlántico, Colombia
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, Wales, UK
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Economic Role of Population Density during Pandemics-A Comparative Analysis of Saudi Arabia and China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18084318. [PMID: 33921729 PMCID: PMC8073490 DOI: 10.3390/ijerph18084318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/10/2021] [Accepted: 04/15/2021] [Indexed: 12/23/2022]
Abstract
As a novel infection with relatively high contagiousness, the coronavirus disease emerged as the most pertinent threat to the global community in the twenty-first century. Due to Covid-19's severe economic impacts, the establishment of reliable determining factors can help to alleviate future pandemics. While a population density is often cited as a major determinant of infectious cases and mortality rates, there are both proponents and opponents to this claim. In this framework, the study seeks to assess the role of population density as a predictor of Covid-19 cases and deaths in Saudi Arabia and China during the Covid-19 pandemic. With high infectivity and mortality being a definitive characteristic of overpopulated regions, the authors propose that Henry Kissinger's population reduction theory can be applied as a control measure to control future pandemics and alleviate social concerns. If high-density Chinese regions are more susceptible to Covid-19 than low-density Saudi cities, the authors argue that Neo-Malthusian models can be used as a basis for reducing the impacts of the coronavirus disease on the economic growth in countries with low population density. However, the performed correlation analysis and simple linear regression produced controversial results with no clear connection between the three studied variables. By assessing population density as a determinant of health crises associated with multiple socio-economic threats and epidemiological concerns, the authors seek to reinvigorate the scholarly interest in Neo-Malthusian models as a long-term solution intended to mitigate future disasters. The authors recommend that future studies should explore additional confounding factors influencing the course and severity of infectious diseases in states with different population densities.
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Gujral H, Sinha A. Association between exposure to airborne pollutants and COVID-19 in Los Angeles, United States with ensemble-based dynamic emission model. ENVIRONMENTAL RESEARCH 2021; 194:110704. [PMID: 33417905 PMCID: PMC7836725 DOI: 10.1016/j.envres.2020.110704] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 12/13/2020] [Accepted: 12/29/2020] [Indexed: 05/09/2023]
Abstract
This study aims to find the association between short-term exposure to air pollutants, such as particulate matters and ground-level ozone, and SARS-CoV-2 confirmed cases. Generalized linear models (GLM), a typical choice for ecological modeling, have well-established limitations. These limitations include apriori assumptions, inability to handle multicollinearity, and considering differential effects as the fixed effect. We propose an Ensemble-based Dynamic Emission Model (EDEM) to address these limitations. EDEM is developed at the intersection of network science and ensemble learning, i.e., a specialized approach of machine learning. Generalized Additive Model (GAM), i.e., a variant of GLM, and EDEM are tested in Los Angeles and Ventura counties of California, which is one of the biggest SARS-CoV-2 clusters in the US. GAM depicts that a 1 μg/m3, 1 μg/m3, and 1 ppm increase (lag 0-7) in PM 2.5, PM 10, and O3 is associated with 4.51% (CI: 7.01 to -2.00) decrease, 1.62% (CI: 2.23 to -1.022) decrease, and 4.66% (CI: 0.85 to 8.47) increase in daily SARS-CoV-2 cases, respectively. Subsequent increment in lag resulted in the negative association between pollutants and SARS-CoV-2 cases. EDEM results in an R2 score of 90.96% and 79.16% on training and testing datasets, respectively. EDEM confirmed the negative association between particulates and SARS-CoV-2 cases; whereas, the O3 depicts a positive association; however, the positive association observed through GAM is not statistically significant. In addition, the county-level analysis of pollutant concentration interactions suggests that increased emissions from other counties positively affect SARS-CoV-2 cases in adjoining counties as well. The results reiterate the significance of uniformly adhering to air pollution mitigation strategies, especially related to ground-level ozone.
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Affiliation(s)
- Harshit Gujral
- Department of Computer Science Engineering and IT, Jaypee Institute of Information Technology, Noida, India.
| | - Adwitiya Sinha
- Department of Computer Science Engineering and IT, Jaypee Institute of Information Technology, Noida, India.
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24
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Cimolai N. The semantics of airborne microbial spread and environmental relevance: Back to Anderson and Cox. ENVIRONMENTAL RESEARCH 2021; 193:110448. [PMID: 33212132 DOI: 10.1016/j.envres.2020.110448] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 10/29/2020] [Accepted: 11/08/2020] [Indexed: 06/11/2023]
Affiliation(s)
- Nevio Cimolai
- Faculty of Medicine, The University of British Columbia, Children's and Women's Health Centre of British Columbia, 4480 Oak Street Vancouver, B.C. V6H3V4, Canada
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25
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Salom I, Rodic A, Milicevic O, Zigic D, Djordjevic M, Djordjevic M. Effects of Demographic and Weather Parameters on COVID-19 Basic Reproduction Number. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2020.617841] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
It is hard to overstate the importance of a timely prediction of the COVID-19 pandemic progression. Yet, this is not possible without a comprehensive understanding of environmental factors that may affect the infection transmissibility. Studies addressing parameters that may influence COVID-19 progression relied on either the total numbers of detected cases and similar proxies (which are highly sensitive to the testing capacity, levels of introduced social distancing measures, etc.), and/or a small number of analyzed factors, including analysis of regions that display a narrow range of these parameters. We here apply a novel approach, exploiting widespread growth regimes in COVID-19 detected case counts. By applying nonlinear dynamics methods to the exponential regime, we extract basic reproductive number R0 (i.e., the measure of COVID-19 inherent biological transmissibility), applying to the completely naïve population in the absence of social distancing, for 118 different countries. We then use bioinformatics methods to systematically collect data on a large number of potentially interesting demographics and weather parameters for these countries (where data was available), and seek their correlations with the rate of COVID-19 spread. While some of the already reported or assumed tendencies (e.g., negative correlation of transmissibility with temperature and humidity, significant correlation with UV, generally positive correlation with pollution levels) are also confirmed by our analysis, we report a number of both novel results and those that help settle existing disputes: the absence of dependence on wind speed and air pressure, negative correlation with precipitation; significant positive correlation with society development level (human development index) irrespective of testing policies, and percent of the urban population, but absence of correlation with population density per se. We find a strong positive correlation of transmissibility on alcohol consumption, and the absence of correlation on refugee numbers, contrary to some widespread beliefs. Significant tendencies with health-related factors are reported, including a detailed analysis of the blood type group showing consistent tendencies on Rh factor, and a strong positive correlation of transmissibility with cholesterol levels. Detailed comparisons of obtained results with previous findings, and limitations of our approach, are also provided.
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26
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Khan W, Hussain A, Khan SA, Al-Jumailey M, Nawaz R, Liatsis P. Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201823. [PMID: 33614100 PMCID: PMC7890495 DOI: 10.1098/rsos.201823] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 01/21/2021] [Indexed: 05/15/2023]
Abstract
Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 202012/01) such as potential symptoms and predictive tools. However, limited work has been performed towards the modelling of complex associations between the combined demographic attributes and varying nature of the COVID-19 infections across the globe. This study presents an intelligent approach to investigate the multi-dimensional associations between demographic attributes and COVID-19 global variations. We gather multiple demographic attributes and COVID-19 infection data (by 8 January 2021) from reliable sources, which are then processed by intelligent algorithms to identify the significant associations and patterns within the data. Statistical results and experts' reports indicate strong associations between COVID-19 severity levels across the globe and certain demographic attributes, e.g. female smokers, when combined together with other attributes. The outcomes will aid the understanding of the dynamics of disease spread and its progression, which in turn may support policy makers, medical specialists and society, in better understanding and effective management of the disease.
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Affiliation(s)
- Wasiq Khan
- Department of Computing and Mathematics, Liverpool John Moores University, Liverpool L33AF, UK
| | - Abir Hussain
- Department of Computing and Mathematics, Liverpool John Moores University, Liverpool L33AF, UK
| | - Sohail Ahmed Khan
- Department of Computer Science, DeepCamera Research Lab, Interactive Media, Smart System, and Emerging Technologies Center, Nicosia, Cyprus
| | - Mohammed Al-Jumailey
- The Regenerative Clinic, Queen Anne Medical Centre, Harley Street Medical Area, London
| | - Raheel Nawaz
- Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M156BH, UK
| | - Panos Liatsis
- Department of Electrical Engineering and Computer Science, Khalifa University, PO Box 127788, Abu Dhabi, UAE
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27
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Tung NT, Cheng PC, Chi KH, Hsiao TC, Jones T, BéruBé K, Ho KF, Chuang HC. Particulate matter and SARS-CoV-2: A possible model of COVID-19 transmission. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 750:141532. [PMID: 32858292 PMCID: PMC7403850 DOI: 10.1016/j.scitotenv.2020.141532] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 08/04/2020] [Accepted: 08/04/2020] [Indexed: 04/13/2023]
Abstract
Coronavirus disease 2019 (COVID-19), an acute respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly developed into a pandemic throughout the world. This disease is a highly infectious novel coronavirus and can affect people of all ages. Previous reports observed that particulate matter (PM) provided a platform for intermixing with viruses (i.e., influenza). However, the role of PM in SARS-CoV-2 transmission remains unclear. In this paper, we propose that PM plays a direct role as a "carrier" of SARS-CoV-2. SARS-CoV-2 is reported to have a high affinity for the angiotensin-converting enzyme 2 (ACE2) receptor. Indirectly, exposure to PM increases ACE2 expression in the lungs which facilitates SARS-CoV-2 viral adhesion. Thus, the high risk of SARS-CoV-2 in heavily polluted regions can be explained by upregulation of ACE2 caused by PM. PM could be both a direct and indirect transmission model for SARS-CoV-2 infection.
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Affiliation(s)
- Nguyen Thanh Tung
- International PhD Program in Medicine, Taipei Medical University, Taipei, Taiwan; Otorhinolaryngology Department, Cho Ray Hospital, Ho Chi Minh City, Viet Nam.
| | - Po-Ching Cheng
- Department of Molecular Parasitology and Tropical Diseases, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Center for International Tropical Medicine, School of Medicine, Taipei Medical University, Taipei, Taiwan.
| | - Kai-Hsien Chi
- Institute of Environmental and Occupational Health Sciences, National Yang Ming University, Taipei, Taiwan.
| | - Ta-Chi Hsiao
- Graduate Institute of Environmental Engineering, National Taiwan University, Taipei, Taiwan.
| | - Timothy Jones
- School of Earth and Oceanic Sciences, Cardiff University, Museum Avenue, Cardiff CF10 3US, UK.
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3US, UK.
| | - Kin-Fai Ho
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong.
| | - Hsiao-Chi Chuang
- Division of Pulmonary Medicine, Department of Internal Medicine, Shuang Ho Hospital, Taipei Medical University, New Taipei City, Taiwan; School of Respiratory Therapy, College of Medicine, Taipei Medical University, Taipei, Taiwan; Cell Physiology and Molecular Image Research Center, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.
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28
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Camerotto A, Sartorio A, Mazzetto A, Gusella M, Luppi O, Lucianò D, Sofritti O, Pelati C, Munno E, Tessari A, Bedendo S, Bellè M, Fenzi F, Formaglio A, Boschini A, Busson A, Spigolon E, De Pieri P, Casson P, Contato E, Compostella A. Early Phase Management of the SARS-CoV-2 Pandemic in the Geographic Area of the Veneto Region, in One of the World's Oldest Populations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17239045. [PMID: 33291638 PMCID: PMC7730116 DOI: 10.3390/ijerph17239045] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/29/2020] [Accepted: 12/02/2020] [Indexed: 12/14/2022]
Abstract
The first cases of Coronavirus disease-2019 (COVID-19) were reported on 21 February in the small town of Vo’ near Padua in the Veneto region of Italy. This event led to 19,286 infected people in the region by 30 June 2020 (39.30 cases/10,000 inhabitants). Meanwhile, Rovigo Local Health Unit n. 5 (ULSS 5), bordering areas with high epidemic rates and having one of the world’s oldest populations, registered the lowest infection rates in the region (19.03 cases/10,000 inhabitants). The aim of this study was to describe timing and event management by ULSS 5 in preventing the propagation of infection within the timeframe spanning from 21 February to 30 June. Our analysis considered age, genetic clusters, sex, orography, the population density, pollution, and economic activities linked to the pandemic, according to the literature. The ULSS 5 Health Director General’s quick decision-making in the realm of public health, territorial assistance, and retirement homes were key to taking the right actions at the right time. Indeed, the number of isolated cases in the Veneto region was the highest among all the Italian regions at the beginning of the epidemic. Moreover, the implementation of molecular diagnostic tools, which were initially absent, enabled health care experts to make quick diagnoses. Quick decision-making, timely actions, and encouraging results were achieved thanks to a solid chain of command, despite a somewhat unclear legislative environment. In conclusion, we believe that the containment of the epidemic depends on the time factor, coupled with a strong sense of awareness and discretion in the Health Director General’s decision-making. Moreover, real-time communication with operating units and institutions goes hand in hand with the common goal of protecting public health.
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Affiliation(s)
- Alessandro Camerotto
- UOC Laboratory Medicine AULSS 5, 45100 Rovigo, Italy; (M.G.); (E.M.)
- Correspondence: ; Tel.: +39-0425-393251
| | - Andrea Sartorio
- UOC Cure Primarie AULSS 5, 45100 Rovigo, Italy; (A.S.); (O.L.)
| | - Anna Mazzetto
- Dipartimento di Scienze della Vita e Biotecnologie, Università degli Studi di Ferrara, 44121 Ferrara, Italy;
| | - Milena Gusella
- UOC Laboratory Medicine AULSS 5, 45100 Rovigo, Italy; (M.G.); (E.M.)
| | - Ornella Luppi
- UOC Cure Primarie AULSS 5, 45100 Rovigo, Italy; (A.S.); (O.L.)
| | | | - Olga Sofritti
- UOC Medicina Trasfusionale AULSS 5, 45100 Rovigo, Italy;
| | - Cristiano Pelati
- UOS Direzione Professioni Sanitarie Ospedale AULSS 5, 45100 Rovigo, Italy; (C.P.); (S.B.)
| | - Emilia Munno
- UOC Laboratory Medicine AULSS 5, 45100 Rovigo, Italy; (M.G.); (E.M.)
| | | | - Simone Bedendo
- UOS Direzione Professioni Sanitarie Ospedale AULSS 5, 45100 Rovigo, Italy; (C.P.); (S.B.)
| | - Margherita Bellè
- UOC Servizio Igiene e Sanità Pubblica AULSS 5, 45100 Rovigo, Italy; (M.B.); (F.F.); (A.F.)
| | - Federica Fenzi
- UOC Servizio Igiene e Sanità Pubblica AULSS 5, 45100 Rovigo, Italy; (M.B.); (F.F.); (A.F.)
| | - Andrea Formaglio
- UOC Servizio Igiene e Sanità Pubblica AULSS 5, 45100 Rovigo, Italy; (M.B.); (F.F.); (A.F.)
| | - Annalisa Boschini
- Ufficio Relazione Pubbliche e Comunicazione AULSS 5, 45100 Rovigo, Italy; (A.B.); (A.B.)
| | - Alberto Busson
- Ufficio Relazione Pubbliche e Comunicazione AULSS 5, 45100 Rovigo, Italy; (A.B.); (A.B.)
| | | | - Paolo De Pieri
- Direzione Funzione Ospedaliera AULSS 5, 45100 Rovigo, Italy;
| | - Paola Casson
- Direzione Generale AULSS 5, 45100 Rovigo, Italy; (P.C.); (E.C.); (A.C.)
| | - Edgardo Contato
- Direzione Generale AULSS 5, 45100 Rovigo, Italy; (P.C.); (E.C.); (A.C.)
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29
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Hernández-Flores MDLL, Escobar-Sánchez J, Paredes-Zarco JE, Franyuti Kelly GA, Carranza-Ramírez L. Prediction and Potential Spatially Explicit Spread of COVID-19 in Mexico's Megacity North Periphery. Healthcare (Basel) 2020; 8:E453. [PMID: 33147698 PMCID: PMC7712471 DOI: 10.3390/healthcare8040453] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/12/2020] [Accepted: 10/16/2020] [Indexed: 11/16/2022] Open
Abstract
The novel COVID-19, detected in Wuhan, China, has reached almost every city across the globe, and researchers from many countries have used several epidemiologic models to describe the epidemic trends. In this context, it is also important to know the geographic extent of the infected population. Following this approach, a Gumpertz model was adapted with official data from the state of Hidalgo, Mexico, in order to estimate the people infected during this COVID-19 pandemic. We found, based on the adjusted data, the highest value in infected people according to official and theoretical data. Furthermore, using a geographical analysis based on geostatistical measures related to density of demographic and economic data, traffic level and geolocation, raster files were generated to estimate probability of coronavirus cases occurrence using the areas where the contagion may occur. We also distributed the maximum contagion obtained by the epidemic model, using these raster files, and a regression model to weight factors according their importance. Based on this estimated distribution, we found that most of the infected people were located in the southern border, a trend related to the economic strip in the southern part of Hidalgo State, associated with its vicinity to the Megacity of Mexico.
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Affiliation(s)
- Maria de la Luz Hernández-Flores
- Consejo Ejecutivo del Complejo Científico y Tecnológico Sincrotrón, Boulevard Ciudad del Conocimiento y la Cultura, Manzana 10 Lote 1, Col. Santa Catarina, San Miguel Tornacuxtla, San Agustín Tlaxiaca 42163, Mexico; (J.E.-S.); (L.C.-R.)
| | - Jair Escobar-Sánchez
- Consejo Ejecutivo del Complejo Científico y Tecnológico Sincrotrón, Boulevard Ciudad del Conocimiento y la Cultura, Manzana 10 Lote 1, Col. Santa Catarina, San Miguel Tornacuxtla, San Agustín Tlaxiaca 42163, Mexico; (J.E.-S.); (L.C.-R.)
| | - Jesús Eduardo Paredes-Zarco
- INABISA, Investigación Aplicada para el Bienestar Social y Ambiental, Rio Papagayo #10, Ampliación el Palmar, Pachuca 42088, Mexico;
| | - Giorgio Alberto Franyuti Kelly
- Medical IMPACT, Dept. of Infectious Diseases, Gutemberg 51, Verónica Anzures, Miguel Hidalgo Ciudad de Mexico 54050, Mexico;
| | - Lamán Carranza-Ramírez
- Consejo Ejecutivo del Complejo Científico y Tecnológico Sincrotrón, Boulevard Ciudad del Conocimiento y la Cultura, Manzana 10 Lote 1, Col. Santa Catarina, San Miguel Tornacuxtla, San Agustín Tlaxiaca 42163, Mexico; (J.E.-S.); (L.C.-R.)
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30
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Cano-Pérez E, Torres-Pacheco J, Fragozo-Ramos MC, García-Díaz G, Montalvo-Varela E, Pozo-Palacios JC. Negative Correlation between Altitude and COVID-19 Pandemic in Colombia: A Preliminary Report. Am J Trop Med Hyg 2020; 103:2347-2349. [PMID: 33124543 PMCID: PMC7695107 DOI: 10.4269/ajtmh.20-1027] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
It has been suggested that high altitude can reduce the infectivity and case fatality rate of COVID-19. We investigated the relationship between altitude and the COVID-19 pandemic in Colombia. Epidemiological data included the number of positive cases, deaths, and the case fatality rate of COVID-19. In particular, we analyzed data from 70 cities with altitudes between 1 and 3,180 m. Correlations and linear regression models adjusted to population density were performed to examine the relationship and contribution of altitude to epidemiological variables. The case fatality rate was negatively correlated with the altitude of the cities. The incidence of cases and deaths from COVID-19 had an apparent correlation with altitude; however, these variables were better explained by population density. In general, these findings suggest that living at high altitude can reduce the impact of COVID-19, especially the case fatality rate.
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Affiliation(s)
- Eder Cano-Pérez
- Molecular Research Unit Group (UNIMOL), Laboratory of Tropical Medicine, University of Cartagena, Cartagena de Indias, Colombia
| | - Jaison Torres-Pacheco
- Molecular Research Unit Group (UNIMOL), Laboratory of Tropical Medicine, University of Cartagena, Cartagena de Indias, Colombia
| | | | - Génesis García-Díaz
- Department of Clinical Biochemistry, Faculty of Chemical Sciences, Central University of Ecuador, Quito, Ecuador.,Centro Especializado en Genética Médica (CEGEMED), Quito, Ecuador
| | - Eduardo Montalvo-Varela
- Department of Clinical Biochemistry, Faculty of Chemical Sciences, Central University of Ecuador, Quito, Ecuador
| | - Juan Carlos Pozo-Palacios
- Department of Epidemiology, Faculty of Medical Science, University of Cuenca, Cuenca, Ecuador.,Centro Especializado en Genética Médica (CEGEMED), Quito, Ecuador
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