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Lin WY, Lin HH, Chang SA, Chen Wang TC, Chen JC, Chen YS. Do Weather Conditions Still Have an Impact on the COVID-19 Pandemic? An Observation of the Mid-2022 COVID-19 Peak in Taiwan. Microorganisms 2024; 12:947. [PMID: 38792777 PMCID: PMC11123934 DOI: 10.3390/microorganisms12050947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/05/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024] Open
Abstract
Since the onset of the COVID-19 pandemic in 2019, the role of weather conditions in influencing transmission has been unclear, with results varying across different studies. Given the changes in border policies and the higher vaccination rates compared to earlier conditions, this study aimed to reassess the impact of weather on COVID-19, focusing on local climate effects. We analyzed daily COVID-19 case data and weather factors such as temperature, humidity, wind speed, and a diurnal temperature range from 1 March to 15 August 2022 across six regions in Taiwan. This study found a positive correlation between maximum daily temperature and relative humidity with new COVID-19 cases, whereas wind speed and diurnal temperature range were negatively correlated. Additionally, a significant positive correlation was identified between the unease environmental condition factor (UECF, calculated as RH*Tmax/WS), the kind of Climate Factor Complex (CFC), and confirmed cases. The findings highlight the influence of local weather conditions on COVID-19 transmission, suggesting that such factors can alter environmental comfort and human behavior, thereby affecting disease spread. We also introduced the Fire-Qi Period concept to explain the cyclic climatic variations influencing infectious disease outbreaks globally. This study emphasizes the necessity of considering both local and global climatic effects on infectious diseases.
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Affiliation(s)
- Wan-Yi Lin
- Department of Traditional Chinese Medicine, Chang Gung Memorial Hospital, Keelung 204201, Taiwan;
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (H.-H.L.); (S.-A.C.)
- Taiwan Huangdi-Neijing Medical Practice Association (THMPA), Taoyuan 330032, Taiwan
| | - Hao-Hsuan Lin
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (H.-H.L.); (S.-A.C.)
- Taiwan Huangdi-Neijing Medical Practice Association (THMPA), Taoyuan 330032, Taiwan
- Department of Chinese Acupuncture and Traumatology, Center of Traditional Chinese Medicine, Chang Gung Memorial Hospital, Taoyuan 333008, Taiwan
| | - Shih-An Chang
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (H.-H.L.); (S.-A.C.)
- Taiwan Huangdi-Neijing Medical Practice Association (THMPA), Taoyuan 330032, Taiwan
- Department of Chinese Acupuncture and Traumatology, Center of Traditional Chinese Medicine, Chang Gung Memorial Hospital, Taoyuan 333008, Taiwan
| | - Tai-Chi Chen Wang
- Department of Atmospheric Sciences, National Central University, Taoyuan 320317, Taiwan;
| | - Juei-Chao Chen
- Department of Statistics and Information Science, Fu Jen Catholic University, New Taipei City 242062, Taiwan;
| | - Yu-Sheng Chen
- School of Traditional Chinese Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (H.-H.L.); (S.-A.C.)
- Taiwan Huangdi-Neijing Medical Practice Association (THMPA), Taoyuan 330032, Taiwan
- Department of Chinese Acupuncture and Traumatology, Center of Traditional Chinese Medicine, Chang Gung Memorial Hospital, Taoyuan 333008, Taiwan
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Miah MM, Faruk MO, Pingki FH, Al Neyma M. The effects of meteorological factors on the COVID-19 omicron variant in Bangladesh. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:514-525. [PMID: 36469810 DOI: 10.1080/09603123.2022.2154326] [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: 05/17/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
The COVID-19 omicron variant is exceptionally complicated and uncertain due to its rapid transmission and volume of infections. This study examines the impact of climatic factors on daily confirmed cases of COVID-19 omicron variant in Bangladesh. The secondary data of daily confirmed cases from 1 January 2022, to 31 March 2022, of eight distinct geographic divisions have been used for the current study. The multivariate generalized linear negative binomial regression model was applied to determine the effects of climatic factors on omicron transmission. The model revealed that the maximum temperature (Odds: 0.67, p < 0.05), sky clearness (Odds: 0.05, p < 0.05), wind speed (Odds: 0.76, p < 0.05), relative humidity (Odds: 1.02, p < 0.05), and air pressure (Odds: 0.27, p < 0.05) significantly impacted COVID-19 omicron transmission in Bangladesh. The study's findings can assist the concerned authorities and decision-makers take necessary measures to control the spread of omicron cases in Bangladesh.
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Affiliation(s)
- Md Mamun Miah
- Department of Statistics, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Mohammad Omar Faruk
- Department of Statistics, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Farjana Haque Pingki
- Department of Fisheries and Marine Science, Noakhali Science and Technology University, Noakhali, Bangladesh
| | - Mahmuda Al Neyma
- Department of Statistics, Noakhali Science and Technology University, Noakhali, Bangladesh
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3
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Mohammadpour A, Rezaei Z, Parvari A, Alami A, Taghavi M, Hajighasemkhan A, Khosravan S, Kalankesh LR. Covid-19 outbreak associated with demographic-meteorological factors in the arid and semi-arid region Iran: case study Gonabad city, 2020-2021. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2024; 34:30-39. [PMID: 36175180 DOI: 10.1080/09603123.2022.2125161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/09/2022] [Indexed: 06/16/2023]
Abstract
Since the (Covid-19) pandemic outbreak, questioning regarding climate and incident of Covid-19 infection rates has been debated, while there is no clear research evidence until now in Iran. This study has focused on investigating the association between Covid-19 cases and demographic -meteorological factors in arid and semi-arid zones of Iran (from March 1, 2020, to January 31, 2022) by analyzing with Via Poisson and negative binomial regression. As a result, the incidence rate of both Covid-19 hospitalization and mortality cases reached peaks in the summer followed by the autumn. Interestingly, Covid-19 hospitalization cases are associated with humidity, temperature, and wind factors seasonally and monthly, but mortality cases are just associated with wind. In conclusion, the result demonstrated that demographicand meteorological factorsare positively and negatively associated with Covid-19 cases. Therefore, identifying the environmental factors contributing to the excess Covid-19 can help to prevent future pandemic waves in Iranian arid and semi-arid zone.
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Affiliation(s)
- Ali Mohammadpour
- Social Determinants of Health Research Center, Gonabad University of Medical sciences, Gonabad, Iran
| | - Zahed Rezaei
- Social Determinants of Health Research Center, Gonabad University of Medical sciences, Gonabad, Iran
| | - Arash Parvari
- Department of Epidemiology and Biostatistics school of public Health, Tehran University of Medical Science, Tehran, Iran
| | - Ali Alami
- Social Determinants of Health Research Center, Gonabad University of Medical sciences, Gonabad, Iran
| | - Mahmoud Taghavi
- Social Determinants of Health Research Center, Gonabad University of Medical sciences, Gonabad, Iran
| | - AliReza Hajighasemkhan
- School of Public Health and Safety, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Shahla Khosravan
- Social Determinants of Health Research Center, Gonabad University of Medical sciences, Gonabad, Iran
| | - Laleh R Kalankesh
- Social Determinants of Health Research Center, Gonabad University of Medical sciences, Gonabad, Iran
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Hashim BM, Al-Naseri SK, Hamadi AM, Mahmood TA, Halder B, Shahid S, Yaseen ZM. Seasonal correlation of meteorological parameters and PM 2.5 with the COVID-19 confirmed cases and deaths in Baghdad, Iraq. INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION : IJDRR 2023; 94:103799. [PMID: 37360250 PMCID: PMC10277160 DOI: 10.1016/j.ijdrr.2023.103799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 06/09/2023] [Accepted: 06/10/2023] [Indexed: 06/28/2023]
Abstract
The COVID-19 pandemic was a serious global health emergency in 2020 and 2021. This study analyzed the seasonal association of weekly averages of meteorological parameters, such as wind speed, solar radiation, temperature, relative humidity, and air pollutant PM2.5, with confirmed COVID-19 cases and deaths in Baghdad, Iraq, a major megacity of the Middle East, for the period June 2020 to August 2021. Spearman and Kendall correlation coefficients were used to investigate the association. The results showed that wind speed, air temperature, and solar radiation have positive and strong correlations with the confirmed cases and deaths in the cold season (autumn and winter 2020-2021). The total COVID-19 cases negatively correlated with relative humidity but were not significant in all seasons. Besides, PM2.5 strongly correlated with COVID-19 confirmed cases for the summer of 2020. The death distribution by age group showed the highest deaths for those aged 60-69. The highest number of deaths was 41% in the summer of 2020. The study provided useful information about the COVID-19 health emergency and meteorological parameters, which can be used for future health disaster planning, adopting prevention strategies and providing healthcare procedures to protect against future infraction transmission.
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Affiliation(s)
- Bassim Mohammed Hashim
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Saadi K Al-Naseri
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Alaa M Hamadi
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Tahani Anwar Mahmood
- Environment, Water and Renewable Energy Directorate, Ministry of Science and Technology, Baghdad, Iraq
| | - Bijay Halder
- Department of Remote Sensing and GIS, Vidyasagar University, Midnapore, 721102, India
- New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen University, Nasiriyah, 64001, Iraq
| | - Shamsuddin Shahid
- Department of Water & Environmental Engineering, University of Teknologi Malaysia, 81310, Johor, Malaysia
| | - Zaher Mundher Yaseen
- Civil and Environmental Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
- Interdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
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Wang Y, Gong G, Shi X, Huang Y, Deng X. Investigation of the effects of temperature and relative humidity on the propagation of COVID-19 in different climatic zones. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:83495-83512. [PMID: 37341939 DOI: 10.1007/s11356-023-28237-x] [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: 03/20/2023] [Accepted: 06/09/2023] [Indexed: 06/22/2023]
Abstract
This study aims to evaluate the effects of temperature and relative humidity on the propagation of COVID-19 for indoor heating, ventilation, and air conditioning design and policy development in different climate zones. We proposed a cumulative lag model with two specific parameters of specific average temperature and specific relative humidity to evaluate the impact of temperature and relative humidity on COVID-19 transmission by calculating the relative risk of cumulative effect and the relative risk of lag effect. We considered the temperature and relative humidity corresponding to the relative risk of cumulative effect or the relative risk of lag effect equal to 1 as the thresholds of outbreak. In this paper, we took the overall relative risk of cumulative effect equal to 1 as the thresholds. Data on daily new confirmed cases of COVID-19 since January 1, 2021, to December 31, 2021, for three sites in each of four climate zones similar to cold, mild, hot summer and cold winter, and hot summer and warm winter were selected for this study. Temperature and relative humidity had a lagged effect on COVID-19 transmission, with peaking the relative risk of lag effect at a lag of 3-7 days for most regions. All regions had different parameters areas with the relative risk of cumulative effect greater than 1. The overall relative risk of cumulative effect was greater than 1 in all regions when specific relative humidity was higher than 0.4, and when specific average temperature was higher than 0.42. In areas similar to hot summer and cold winter, temperature and the overall relative risk of cumulative effect were highly monotonically positively correlated. In areas similar to hot summer and warm winter, there was a monotonically positive correlation between relative humidity and the overall relative risk of cumulative effect. This study provides targeted recommendations for indoor air and heating, ventilation, and air conditioning system control strategies and outbreak prevention strategies to reduce the risk of COVID-19 transmission. In addition, countries should combine vaccination and non-pharmaceutical control measures, and strict containment policies are beneficial to control another pandemic of COVID-19 and similar viruses.
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Affiliation(s)
- Yuxin Wang
- College of Civil Engineering of Hunan University (HNU), Changsha, 410082, People's Republic of China
| | - Guangcai Gong
- College of Civil Engineering of Hunan University (HNU), Changsha, 410082, People's Republic of China.
| | - Xing Shi
- College of Civil Engineering of Hunan University (HNU), Changsha, 410082, People's Republic of China
| | - Yuting Huang
- College of Civil Engineering of Hunan University (HNU), Changsha, 410082, People's Republic of China
| | - Xiaorui Deng
- College of Civil Engineering of Hunan University (HNU), Changsha, 410082, People's Republic of China
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Parvin R. A Statistical Investigation into the COVID-19 Outbreak Spread. ENVIRONMENTAL HEALTH INSIGHTS 2023; 17:11786302221147455. [PMID: 36699646 PMCID: PMC9868487 DOI: 10.1177/11786302221147455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVE Coronavirus-19 (COVID-19) outbreaks have been reported in a range of climates worldwide, including Bangladesh. There is less evidence of a link between the COVID-19 pandemic and climatic variables. This research article's purpose is to examine the relationship between COVID-19 outbreaks and climatic factors in Dhaka, Bangladesh. METHODS The daily time series COVID-19 data used in this study span from May 1, 2020, to April 14, 2021, for the study area, Dhaka, Bangladesh. The Climatic factors included in this study were average temperature, particulate matter ( P M 2 . 5 ), humidity, carbon emissions, and wind speed within the same timeframe and location. The strength and direction of the relationship between meteorological factors and COVID-19 positive cases are examined using the Spearman correlation. This study examines the asymmetric effect of climatic factors on the COVID-19 pandemic in Dhaka, Bangladesh, using the Nonlinear Autoregressive Distributed Lag (NARDL) model. RESULTS COVID-19 widespread has a substantial positive association with wind speed (r = .781), temperature (r = .599), and carbon emissions (r = .309), whereas P M 2 . 5 (r = -.178) has a negative relationship at the 1% level of significance. Furthermore, with a 1% change in temperature, the incidence of COVID-19 increased by 1.23% in the short run and 1.53% in the long run, with the remaining variables remaining constant. Similarly, in the short-term, humidity was not significantly related to the COVID-19 pandemic. However, in the long term, it increased 1.13% because of a 1% change in humidity. The changes in PM2.5 level and wind speed are significantly associated with COVID-19 new cases after adjusting population density and the human development index.
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Affiliation(s)
- Rehana Parvin
- Rehana Parvin, Department of Statistics, International University of Business Agriculture and Technology (IUBAT), 4 Embankment Drive Road, Sector 10, Uttara, Dhaka, Bangladesh.
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Magnano San Lio R, Favara G, Maugeri A, Barchitta M, Agodi A. How Antimicrobial Resistance Is Linked to Climate Change: An Overview of Two Intertwined Global Challenges. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:ijerph20031681. [PMID: 36767043 PMCID: PMC9914631 DOI: 10.3390/ijerph20031681] [Citation(s) in RCA: 186] [Impact Index Per Article: 186.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/12/2023] [Accepted: 01/13/2023] [Indexed: 05/13/2023]
Abstract
Globally, antimicrobial resistance (AMR) and climate change (CC) are two of the top health emergencies, and can be considered as two interlinked public health priorities. The complex commonalities between AMR and CC should be deeply investigated in a One Health perspective. Here, we provided an overview of the current knowledge about the relationship between AMR and CC. Overall, the studies included pointed out the need for applying a systemic approach to planetary health. Firstly, CC increasingly brings humans and animals into contact, leading to outbreaks of zoonotic and vector-borne diseases with pandemic potential. Although it is well-established that antimicrobial use in human, animal and environmental sectors is one of the main drivers of AMR, the COVID-19 pandemic is exacerbating the current scenario, by influencing the use of antibiotics, personal protective equipment, and biocides. This also results in higher concentrations of contaminants (e.g., microplastics) in natural water bodies, which cannot be completely removed from wastewater treatment plants, and which could sustain the AMR spread. Our overview underlined the lack of studies on the direct relationship between AMR and CC, and encouraged further research to investigate the multiple aspects involved, and its effect on human health.
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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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Meskher H, Belhaouari SB, Thakur AK, Sathyamurthy R, Singh P, Khelfaoui I, Saidur R. A review about COVID-19 in the MENA region: environmental concerns and machine learning applications. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:82709-82728. [PMID: 36223015 PMCID: PMC9554385 DOI: 10.1007/s11356-022-23392-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
Coronavirus disease 2019 (COVID-19) has delayed global economic growth, which has affected the economic life globally. On the one hand, numerous elements in the environment impact the transmission of this new coronavirus. Every country in the Middle East and North Africa (MENA) area has a different population density, air quality and contaminants, and water- and land-related conditions, all of which influence coronavirus transmission. The World Health Organization (WHO) has advocated fast evaluations to guide policymakers with timely evidence to respond to the situation. This review makes four unique contributions. One, many data about the transmission of the new coronavirus in various sorts of settings to provide clear answers to the current dispute over the virus's transmission were reviewed. Two, highlight the most significant application of machine learning to forecast and diagnose severe acute respiratory syndrome coronavirus (SARS-CoV-2). Three, our insights provide timely and accurate information along with compelling suggestions and methodical directions for investigators. Four, the present study provides decision-makers and community leaders with information on the effectiveness of environmental controls for COVID-19 dissemination.
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Affiliation(s)
- Hicham Meskher
- Division of Process Engineering, College of Applied Science, Kasdi-Merbah University, 30000, Ouargla, Algeria
| | - Samir Brahim Belhaouari
- Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Education City, Qatar Foundation, P.O. Box 34110, Doha, Qatar
| | - Amrit Kumar Thakur
- Department of Mechanical Engineering, KPR Institute of Engineering and Technology, Arasur, Coimbatore, Tamil Nadu, 641407, India
| | - Ravishankar Sathyamurthy
- Department of Mechanical Engineering, King Fahd University of Petroleum and Minerals, Dammam, Saudi Arabia.
| | - Punit Singh
- Institute of Engineering and Technology, Department of Mechanical Engineering, GLA University Mathura, Mathura, Uttar Pradesh, 281406, India
| | - Issam Khelfaoui
- School of Insurance and Economics, University of International Business and Economics, Beijing, China
| | - Rahman Saidur
- Research Centre for Nano-Materials and Energy Technology (RCNMET), School of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, Bandar Sunway, 47500, Petaling Jaya, Malaysia
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Association Between Air Pollution, Climate Change, and COVID-19 Pandemic: A Review of the Recent Scientific Evidence. HEALTH SCOPE 2022. [DOI: 10.5812/jhealthscope-122412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Background: Recent studies indicated the possible relationship between climate change, environmental pollution, and Coronavirus Disease 2019 (COVID-19) pandemic. This study reviewed the effects of air pollution, climate parameters, and lockdown on the number of cases and deaths related to COVID-19. Methods: The present review was performed to determine the effects of weather and air pollution on the number of cases and deaths related to COVID-19 during the lockdown. Articles were collected by searching the existing online databases, such as PubMed, Science Direct, and Google Scholar, with no limitations on publication dates. Afterwards, this review focused on outdoor air pollution, including PM2.5, PM10, NO2, SO2, and O3, and weather conditions affecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/COVID-19. Results: Most reviewed investigations in the present study showed that exposure to air pollutants, particularly PM2.5 and NO2, is positively related to COVID-19 patients and mortality. Moreover, these studies showed that air pollution could be essential in transmitting COVID-19. Local meteorology plays a vital role in coronavirus spread and mortality. Temperature and humidity variables are negatively correlated with virus transmission. The evidence demonstrated that air pollution could lead to COVID-19 transmission. These results support decision-makers in curbing potential new outbreaks. Conclusions: Overall, in environmental perspective-based COVID-19 studies, efforts should be accelerated regarding effective policies for reducing human emissions, bringing about air pollution and weather change. Therefore, using clean and renewable energy sources will increase public health and environmental quality by improving global air quality.
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11
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Sohel MS, Ehsan SMA, Zaman NT, Hossain B, Shi G, Sarker MNI, Ali HM. Understanding rural local government response during COVID-19-induced lockdown: perspective from Bangladesh. SN SOCIAL SCIENCES 2022; 2:216. [PMID: 36193448 PMCID: PMC9520961 DOI: 10.1007/s43545-022-00516-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022]
Abstract
This study intends to explore the responses of local government during the COVID-19-induced lockdown in the rural areas, with particular emphasis on Bangladesh. By adopting a qualitative phenomenological research approach and employing multi-method data collection techniques (for instance, Key Informant Interview (KII), Focus Group Discussion (FGD), participant observation, and content analysis), this study found that the local governments managed the crisis of the pandemic relatively well with its limited manpower and funding through adequate preparedness and prevention strategies; effective emergency responses; and consolidated post-lockdown measures. The study revealed that the Bangladesh local government promptly took some essential actions, such as preparedness and prevention, arrangement of home quarantine and isolation, the training program for readiness, and disseminated crucial information to the local people during the pandemic, such as using masks, hand washing and sanitizing, and social distancing. Besides, the local government delivered relief, such as food and non-food items and financial support. Furthermore, the rural local government took post-lockdown responses to tackle pandemic in rural Bangladesh. Nevertheless, the service delivery individuals from local governance encountered numerous challenges, like scarcity of manpower, less support, and superstition, while providing services during the pandemic.
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Affiliation(s)
- Md Salman Sohel
- National Research Center for Resettlement, Hohai University, Nanjing, China
| | | | - Noshin Tasnim Zaman
- School of Humanities and Social Sciences, BRAC University, Dhaka, Bangladesh
| | - Babul Hossain
- National Research Center for Resettlement, Hohai University, Nanjing, 210000 China
| | - Guoqin Shi
- National Research Center for Resettlement, Hohai University, Nanjing, 210000 China
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12
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Karmokar J, Islam MA, Uddin M, Hassan MR, Yousuf MSI. An assessment of meteorological parameters effects on COVID-19 pandemic in Bangladesh using machine learning models. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:67103-67114. [PMID: 35522407 PMCID: PMC9073515 DOI: 10.1007/s11356-022-20196-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 04/07/2022] [Indexed: 06/14/2023]
Abstract
Coronavirus (COVID-19) is a highly contagious virus (SARS-CoV-2) that has caused a global pandemic since January 2020. Scientists around the world are doing extensive research to control this disease. They are working tirelessly to find out the origin and causes of the disease. Several studies and experiments mentioned that there are some meteorological parameters which are highly correlated with COVID-19 transmission. In this work, we studied the effects of 11 meteorological parameters on the transmission of COVID-19 in Bangladesh. We first applied statistical analysis and observed that there is no significant effect of these parameters. Therefore, we proposed a novel technique to analyze the insight effects of these parameters by using a combination of Random Forest, CART, and Lasso feature selection techniques. We observed that 4 parameters are highly influential for COVID-19 where [Formula: see text] and Cloud have positive association whereas WS and AQ have negative impact. Among them, Cloud has the highest positive impact which is 0.063 and WS has the highest negative association which is [Formula: see text]. Moreover, we have validated our performance using DLNM technique. The result of this investigation can be used to develop an alert system that will assist the policymakers to know the characteristics of COVID-19 against meteorological parameters and can impose different policies based on the weather conditions.
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Affiliation(s)
- Jaionto Karmokar
- Department of Computer Science and Mathematics, Bangladesh Agricultural University, Mymensingh, 2202 Bangladesh
| | - Mohammad Aminul Islam
- Department of Computer Science and Mathematics, Bangladesh Agricultural University, Mymensingh, 2202 Bangladesh
| | - Machbah Uddin
- Department of Computer Science and Mathematics, Bangladesh Agricultural University, Mymensingh, 2202 Bangladesh
| | - Md. Rakib Hassan
- Department of Computer Science and Mathematics, Bangladesh Agricultural University, Mymensingh, 2202 Bangladesh
| | - Md. Sayeed Iftekhar Yousuf
- Department of Computer Science and Mathematics, Bangladesh Agricultural University, Mymensingh, 2202 Bangladesh
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Chien LC, Chen LWA, Lin RT. Lagged meteorological impacts on COVID-19 incidence among high-risk counties in the United States-a spatiotemporal analysis. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2022; 32:774-781. [PMID: 34211113 PMCID: PMC8247626 DOI: 10.1038/s41370-021-00356-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 06/16/2021] [Accepted: 06/17/2021] [Indexed: 05/16/2023]
Abstract
BACKGROUND The associations between meteorological factors and coronavirus disease 2019 (COVID-19) have been discussed globally; however, because of short study periods, the lack of considering lagged effects, and different study areas, results from the literature were diverse and even contradictory. OBJECTIVE The primary purpose of this study is to conduct more reliable research to evaluate the lagged meteorological impacts on COVID-19 incidence by considering a relatively long study period and diversified high-risk areas in the United States. METHODS This study adopted the distributed lagged nonlinear model with a spatial function to analyze COVID-19 incidence predicted by multiple meteorological measures from March to October of 2020 across 203 high-risk counties in the United States. The estimated spatial function was further smoothed within the entire continental United States by the biharmonic spline interpolation. RESULTS Our findings suggest that the maximum temperature, minimum relative humidity, and precipitation were the best meteorological predictors. Most significantly positive associations were found from 3 to 11 lagged days in lower levels of each selected meteorological factor. In particular, a significantly positive association appeared in minimum relative humidity higher than 88.36% at 5-day lag. The spatial analysis also shows excessive risks in the north-central United States. SIGNIFICANCE The research findings can contribute to the implementation of early warning surveillance of COVID-19 by using weather forecasting for up to two weeks in high-risk counties.
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Affiliation(s)
- Lung-Chang Chien
- Department of Epidemiology and Biostatistics, School of Public Health, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - L-W Antony Chen
- Department of Environmental and Occupational Health, School of Public Health, University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Ro-Ting Lin
- Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, Taiwan.
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14
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Sidibé ML, Yonaba R, Tazen F, Karoui H, Koanda O, Lèye B, Andrianisa HA, Karambiri H. Understanding the COVID-19 pandemic prevalence in Africa through optimal feature selection and clustering: evidence from a statistical perspective. ENVIRONMENT, DEVELOPMENT AND SUSTAINABILITY 2022; 25:1-29. [PMID: 36061268 PMCID: PMC9424840 DOI: 10.1007/s10668-022-02646-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 08/18/2022] [Indexed: 06/15/2023]
Abstract
The COVID-19 pandemic, which outbroke in Wuhan (China) in December 2019, severely hit almost all sectors of activity in the world as a consequence of the restrictive measures imposed. Two years later, Africa still emerges as the least affected continent by the pandemic. This study analyzed COVID-19 prevalence across African countries through country-level variables prior to clustering. Using Spearman-rank correlation, multicollinearity analysis and univariate filtering, 9 country-level variables were identified from an initial set of 34 variables. These variables relate to socioeconomic status, population structure, healthcare system and environment and the climatic setting. A clustering of the 54 African countries is further carried out through the use of agglomerative hierarchical clustering (AHC) method, which generated 3 distinctive clusters. Cluster 1 (11 countries) is the most affected by COVID-19 (median of 63,508.6 confirmed cases and 946.5 deaths per million) and is composed of countries with the highest socioeconomic status. Cluster 2 (27 countries) is the least affected (median of 4473.7 confirmed cases and 81.2 deaths per million), and mainly features countries with the least socioeconomic features and international exposure. Cluster 3 (16 countries) is intermediate in terms of COVID-19 prevalence (median of 2569.3 confirmed cases and 35.7 deaths per million) and features countries the least urbanized and geographically close to the equator, with intermediate international exposure and socioeconomic features. These findings shed light on the main features of COVID-19 prevalence in Africa and might help refine effectively coping management strategies of the ongoing pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s10668-022-02646-3.
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Affiliation(s)
- Mohamed Lamine Sidibé
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Roland Yonaba
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Fowé Tazen
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Héla Karoui
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Ousmane Koanda
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Babacar Lèye
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Harinaivo Anderson Andrianisa
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
| | - Harouna Karambiri
- Laboratoire Eaux, Hydro-Systèmes Et Agriculture (LEHSA), Institut International d’Ingénierie de l’Eau Et de l’Environnement (2iE), 1 Rue de la Science, 01 BP 594, Ouagadougou 01, Burkina Faso
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15
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Correlation between COVID-19 and weather variables: A meta-analysis. Heliyon 2022; 8:e10333. [PMID: 35996423 PMCID: PMC9387066 DOI: 10.1016/j.heliyon.2022.e10333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 06/22/2022] [Accepted: 08/12/2022] [Indexed: 01/09/2023] Open
Abstract
Background COVID-19 has significantly impacted humans worldwide in recent times. Weather variables have a remarkable effect on COVID-19 spread all over the universe. Objectives The aim of this study was to find the correlation between weather variables with COVID-19 cases and COVID-19 deaths. Methods Five electronic databases such as PubMed, Science Direct, Scopus, Ovid (Medline), and Ovid (Embase) were searched to conduct the literature survey from January 01, 2020, to February 03, 2022. Both fixed-effects and random-effects models were used to calculate pooled correlation and 95% confidence interval (CI) for both effect measures. Included studies heterogeneity was measured by Cochrane chi-square test statistic Q, I2 and τ2. Funnel plot was used to measure publication bias. A Sensitivity analysis was also carried out. Results Total 38 studies were analyzed in this study. The result of this analysis showed a significantly negative impact on COVID-19 fixed effect incidence and weather variables such as temperature (r = -0.113∗∗∗), relative humidity (r = -0.019∗∗∗), precipitation (r = -0.143∗∗∗), air pressure (r = -0.073∗), and sunlight (r = -0.277∗∗∗) and also found positive impact on wind speed (r = 0.076∗∗∗) and dew point (r = 0.115∗∗∗). From this analysis, significant negative impact was also found for COVID-19 fixed effect death and weather variables such as temperature (r = -0.094∗∗∗), wind speed (r = -0.048∗∗), rainfall (r = -0.158∗∗∗), sunlight (r = -0.271∗∗∗) and positive impact for relative humidity (r = 0.059∗∗∗). Conclusion This meta-analysis disclosed significant correlations between weather and COVID-19 cases and deaths. The findings of this analysis would help policymakers and the health professionals to reduce the cases and fatality rate depending on weather forecast techniques and fight this pandemic using restricted assets.
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16
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Culqui DR, Díaz J, Blanco A, Lopez JA, Navas MA, Sánchez-Martínez G, Luna MY, Hervella B, Belda F, Linares C. Short-term influence of environmental factors and social variables COVID-19 disease in Spain during first wave (Feb-May 2020). ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:50392-50406. [PMID: 35230631 PMCID: PMC8886199 DOI: 10.1007/s11356-022-19232-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
This study aims to identify the combined role of environmental pollutants and atmospheric variables at short term on the rate of incidence (TIC) and on the hospital admission rate (TIHC) due to COVID-19 disease in Spain. This study used information from 41 of the 52 provinces of Spain (from Feb. 1, 2021 to May 31, 2021). Using TIC and TIHC as dependent variables, and average daily concentrations of PM10 and NO2 as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). Generalized linear models (GLM) with Poisson link were carried out for each provinces The GLM model controlled for trend, seasonalities, and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 μg/m3 in PM10 and NO2 and by 1 °C in the case of Tmax and 1 g/m3 in the case of HA. Later, a linear regression was carried out that included the social determinants of health. Statistically significant associations were found between PM10, NO2, and the rate of COVID-19 incidence. NO2 was the variable that showed greater association, both for TIC as well as for TIHC in the majority of provinces. Temperature and HA do not seem to have played an important role. The geographic distribution of RR in the studied provinces was very much heterogeneous. Some of the health determinants considered, including income per capita, presence of airports, average number of diesel cars per inhabitant, average number of nursing personnel, and homes under 30 m2 could explain the differential geographic behavior. As findings indicates, environmental factors only could modulate the incidence and severity of COVID-19. Moreover, the social determinants and public health measures could explain some patterns of geographically distribution founded.
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Affiliation(s)
- Dante R. Culqui
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - Julio Díaz
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - Alejandro Blanco
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - José A. Lopez
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | - Miguel A. Navas
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
| | | | | | | | | | - Cristina Linares
- Reference Unit on Climate Change, Health and Urban Environment National School of Health, Carlos III Health Institute, Monforte de Lemos, 5 (Aveniu), 28029, Madrid, Spain
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17
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Bañuelos Gimeno J, Blanco A, Díaz J, Linares C, López JA, Navas MA, Sánchez-Martínez G, Luna Y, Hervella B, Belda F, Culqui DR. Air pollution and meteorological variables' effects on COVID-19 first and second waves in Spain. INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY : IJEST 2022; 20:2869-2882. [PMID: 35529588 PMCID: PMC9065237 DOI: 10.1007/s13762-022-04190-z] [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: 11/15/2021] [Revised: 03/18/2022] [Accepted: 04/10/2022] [Indexed: 06/14/2023]
Abstract
UNLABELLED The aim of this research is to study the influence of atmospheric pollutants and meteorological variables on the incidence rate of COVID-19 and the rate of hospital admissions due to COVID-19 during the first and second waves in nine Spanish provinces. Numerous studies analyze the effect of environmental and pollution variables separately, but few that include them in the same analysis together, and even fewer that compare their effects between the first and second waves of the virus. This study was conducted in nine of 52 Spanish provinces, using generalized linear models with Poisson link between levels of PM10, NO2 and O3 (independent variables) and maximum temperature and absolute humidity and the rates of incidence and hospital admissions of COVID-19 (dependent variables), establishing a series of significant lags. Using the estimators obtained from the significant multivariate models, the relative risks associated with these variables were calculated for increases of 10 µg/m3 for pollutants, 1 °C for temperature and 1 g/m3 for humidity. The results suggest that NO2 has a greater association than the other air pollution variables and the meteorological variables. There was a greater association with O3 in the first wave and with NO2 in the second. Pollutants showed a homogeneous distribution across the country. We conclude that, compared to other air pollutants and meteorological variables, NO2 is a protagonist that may modulate the incidence and severity of COVID-19, though preventive public health measures such as masking and hand washing are still very important. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s13762-022-04190-z.
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Affiliation(s)
- J. Bañuelos Gimeno
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
- Department of Preventive Medicine and Public Health and Microbiology, Autonomous University of Madrid, Arzobispo Morcillo, 4, 28029 Madrid, Spain
| | - A. Blanco
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
| | - J. Díaz
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
| | - C. Linares
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
| | - J. A. López
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
| | - M. A. Navas
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
| | | | - Y. Luna
- State Meteorological Agency (AEMET), CALLE RIOS ROSAS, 44, Madrid, Spain
| | - B. Hervella
- State Meteorological Agency (AEMET), CALLE RIOS ROSAS, 44, Madrid, Spain
| | - F. Belda
- State Meteorological Agency (AEMET), CALLE RIOS ROSAS, 44, Madrid, Spain
| | - D. R. Culqui
- Reference Unit on Climate Change, Health and Urban Environment, National School of Health, Carlos III Health Institute, Monforte de Lemos, 5, 28029 Madrid, Spain
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18
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Iqbal A, Haq W, Mahmood T, Raza SH. Effect of meteorological factors on the COVID-19 cases: a case study related to three major cities of the Kingdom of Saudi Arabia. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:21811-21825. [PMID: 34767172 PMCID: PMC8586838 DOI: 10.1007/s11356-021-17268-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/25/2021] [Indexed: 06/13/2023]
Abstract
The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA. The distribution of the COVID-19 case counts was observed for all three cities followed by cross-correlation analysis which was carried out to estimate the lag effects of meteorological factors on COVID-19 case counts. Moreover, the Poisson model and negative binomial (NB) model with their zero-inflated versions (i.e., ZIP and ZINB) were fitted to estimate city-specific impacts of weather variables on confirmed case counts, and the best model is evaluated by comparative analysis for each city. We found significant associations between meteorological factors and COVID-19 case counts in three cities of KSA. We also perceived that the ZINB model was the best fitted for COVID-19 case counts. In this case study, temperature, humidity, and wind speed were the factors that affected COVID-19 case counts. The results can be used to make policies to overcome this pandemic situation in the future such as deploying more resources through testing and tracking in such areas where we observe significantly higher wind speed or higher humidity. Moreover, the selected models can be used for predicting the probability of COVID-19 incidence across various regions.
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Affiliation(s)
- Anam Iqbal
- Department of Statistics, Government Graduate College for Women, Sargodha, Punjab, Pakistan
| | - Wajiha Haq
- Department of Economics, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, H-12, Pakistan.
| | - Tahir Mahmood
- Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
- Interdisciplinary Research Centre for Smart Mobility & Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
| | - Syed Hassan Raza
- School of Economics, Quaid-i-Azam University, Islamabad, Pakistan
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19
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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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20
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Olak AS, Santos WS, Susuki AM, Pott-Junior H, V Skalny A, Tinkov AA, Aschner M, Pinese JPP, Urbano MR, Paoliello MMB. Meteorological parameters and cases of COVID-19 in Brazilian cities: an observational study. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART A 2022; 85:14-28. [PMID: 34474657 DOI: 10.1080/15287394.2021.1969304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Meteorological parameters modulate transmission of the SARS-Cov-2 virus, the causative agent related to coronavirus disease-2019 (COVID-19) development. However, findings across the globe have been inconsistent attributed to several confounding factors. The aim of the present study was to investigate the relationship between reported meteorological parameters from July 1 to October 31, 2020, and the number of confirmed COVID-19 cases in 4 Brazilian cities: São Paulo, the largest city with the highest number of cases in Brazil, and the cities with greater number of cases in the state of Parana during the study period (Curitiba, Londrina and Maringa). The assessment of meteorological factors with confirmed COVID-19 cases included atmospheric pressure, temperature, relative humidity, wind speed, solar irradiation, sunlight, dew point temperature, and total precipitation. The 7- and 15-day moving averages of confirmed COVID-19 cases were obtained for each city. Pearson's correlation coefficients showed significant correlations between COVID-19 cases and all meteorological parameters, except for total precipitation, with the strongest correlation with maximum wind speed (0.717, <0.001) in São Paulo. Regression tree analysis demonstrated that the largest number of confirmed COVID-19 cases was associated with wind speed (between ≥0.3381 and <1.173 m/s), atmospheric pressure (<930.5mb), and solar radiation (<17.98e+3). Lower number of cases was observed for wind speed <0.3381 m/s and temperature <23.86°C. Our results encourage the use of meteorological information as a critical component in future risk assessment models.
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Affiliation(s)
- André S Olak
- Department of Architecture and Urbanism; State University of Londrina (Uel), Londrina, PR, Brazil
- Department of Statistics, State University of Londrina (Uel), Londrina, Pr, Brazil
| | - Willian S Santos
- Department of Geoscience, State University of Londrina (Uel), Londrina, PR, Brazil
| | - Aline M Susuki
- Department of Architecture and Urbanism; State University of Londrina (Uel), Londrina, PR, Brazil
| | - Henrique Pott-Junior
- Department of Medicine, Federal University of São Carlos (Ufscar), São Carlos, SP, Brazil
| | - Anatoly V Skalny
- Department of Bioelementology, K.g. Razumovsky Moscow State University of Technologies and Management, Moscow, Russia
- World-Class Research Center "Digital Biodesign and Personalized Healthcare," Im Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Alexey A Tinkov
- World-Class Research Center "Digital Biodesign and Personalized Healthcare," Im Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
- IM Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
| | - Michael Aschner
- World-Class Research Center "Digital Biodesign and Personalized Healthcare," Im Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - José P P Pinese
- Department of Geoscience, State University of Londrina (Uel), Londrina, PR, Brazil
- Centre of Studies in Geography and Spatial Planning, CEGOT, Coimbra, Portugal
| | - Mariana R Urbano
- Department of Statistics, State University of Londrina (Uel), Londrina, Pr, Brazil
| | - Monica M B Paoliello
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA
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21
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Hridoy AEE, Tipo IH, Sami MS, Babu MR, Ahmed MS, Rahman SM, Tusher SMSH, Rashid KJ, Naim M. Spatio-temporal estimation of basic and effective reproduction number of COVID-19 and post-lockdown transmissibility in Bangladesh. SPATIAL INFORMATION RESEARCH 2022; 30:23-35. [PMCID: PMC8237036 DOI: 10.1007/s41324-021-00409-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/28/2021] [Accepted: 06/04/2021] [Indexed: 11/04/2023]
Abstract
The ongoing COVID-19 pandemic has caused unprecedented public health concern in Bangladesh. This study investigated the role of Non-Pharmaceutical Interventions on COVID-19 transmission and post-lockdown scenarios of 64 administrative districts and the country as a whole based on the spatiotemporal variations of effective reproduction number (R t) of COVID-19 incidences. The daily confirmed COVID-19 data of Bangladesh and its administrative districts from March 8, 2020, to March 10, 2021, were used to estimate R t. This study finds that the maximum value of R t reached 4.15 (3.43, 4.97, 95% CI) in late March 2020, which remained above 1 afterwards in most of the districts. Containment measures are moderately effective in reducing transmission by 24.03%. The R t was established below 1 from early December 2020 for overall Bangladesh and a gradual increase of R t above 1 has been seen from early February 2021. The basic reproduction number (R 0) in Bangladesh probably varied around 2.02 (1.33–3.28, 95% CI). This study finds a significant positive correlation (r = 0.75) between population density and COVID-19 incidence and explaining 56% variation in Bangladesh. The findings of this study are expected to support the policymakers to adopt appropriate measures for curbing the COVID-19 transmission effectively.
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Affiliation(s)
- Al-Ekram Elahee Hridoy
- Department of Geography and Environmental Studies, University of Chittagong, Chattogram, 4331 Bangladesh
| | - Imrul Hasan Tipo
- Department of Biochemistry and Molecular Biology, University of Chittagong, Chattogram, 4331 Bangladesh
| | - Md. Shamsudduha Sami
- Department of Geography and Environment, Jagannath University, Dhaka, 1100 Bangladesh
| | - Md. Ripon Babu
- Department of Biochemistry and Molecular Biology, University of Chittagong, Chattogram, 4331 Bangladesh
| | - Md. Sayem Ahmed
- Department of Pharmacy, East West University, Dhaka, 1212 Bangladesh
| | - Syed Masiur Rahman
- Center for Environment & Water, Research Institute, King Fahd University of Petroleum & Minerals, KFUPM Box 713, Dhahran, 31261 Saudi Arabia
| | | | - Kazi Jihadur Rashid
- Center for Environmental and Geographic Information Services (CEGIS), Dhaka, 1212 Bangladesh
| | - Mohammad Naim
- Department of Electrical and Computer Engineering, North South University, Dhaka, 1229 Bangladesh
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22
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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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Zheng HL, Guo ZL, Wang ML, Yang C, An SY, Wu W. Effects of climate variables on the transmission of COVID-19: a systematic review of 62 ecological studies. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:54299-54316. [PMID: 34398375 PMCID: PMC8364942 DOI: 10.1007/s11356-021-15929-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 08/07/2021] [Indexed: 04/15/2023]
Abstract
The new severe acute respiratory syndrome coronavirus 2 was initially discovered at the end of 2019 in Wuhan City in China and has caused one of the most serious global public health crises. A collection and analysis of studies related to the association between COVID-19 (coronavirus disease 2019) transmission and meteorological factors, such as humidity, is vital and indispensable for disease prevention and control. A comprehensive literature search using various databases, including Web of Science, PubMed, and Chinese National Knowledge Infrastructure, was systematically performed to identify eligible studies from Dec 2019 to Feb 1, 2021. We also established six criteria to screen the literature to obtain high-quality literature with consistent research purposes. This systematic review included a total of 62 publications. The study period ranged from 1 to 8 months, with 6 papers considering incubation, and the lag effect of climate factors on COVID-19 activity being taken into account in 22 studies. After quality assessment, no study was found to have a high risk of bias, 30 studies were scored as having moderate risks of bias, and 32 studies were classified as having low risks of bias. The certainty of evidence was also graded as being low. When considering the existing scientific evidence, higher temperatures may slow the progression of the COVID-19 epidemic. However, during the course of the epidemic, these climate variables alone could not account for most of the variability. Therefore, countries should focus more on health policies while also taking into account the influence of weather.
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Affiliation(s)
- Hu-Li Zheng
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Ze-Li Guo
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Mei-Ling Wang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Chuan Yang
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Shu-Yi An
- Liaoning Provincial Centers for Disease Control and Prevention, Shenyang, Liaoning, China
| | - Wei Wu
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang, Liaoning, China.
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Amnuaylojaroen T, Parasin N. The Association Between COVID-19, Air Pollution, and Climate Change. Front Public Health 2021; 9:662499. [PMID: 34295866 PMCID: PMC8290155 DOI: 10.3389/fpubh.2021.662499] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 06/10/2021] [Indexed: 12/23/2022] Open
Abstract
This mini-review aims to highlight both the positive and negative relationship between COVID-19 and air pollution and climate change based on current studies. Since, COVID-19 opened a bibliographic door to scientific production, so there was a limit to research at the moment. There were two sides to the relationship between COVID-19 and both air pollution and climate change. The associated with climate change, in particular, defines the relationship very loosely. Many studies have revealed a positive correlation between COVID-19 and each air pollutants, while some studies shown a negative correlation. There were a few studies that focused on the relationship between COVID-19 in terms of climate. Meanwhile, there were many studies explained the relationship with meteorological factors instead.
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Affiliation(s)
- Teerachai Amnuaylojaroen
- School of Energy and Environment, University of Phayao, Phayao, Thailand
- Atmospheric Pollution and Climate Change Research Unit, School of Energy and Environment, University of Phayao, Phayao, Thailand
| | - Nichapa Parasin
- School of Allied Health Science, University of Phayao, Phayao, Thailand
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25
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Arefin MA, Nabi MN, Islam MT, Islam MS. Influences of weather-related parameters on the spread of Covid-19 pandemic - The scenario of Bangladesh. URBAN CLIMATE 2021; 38:100903. [PMID: 34226864 PMCID: PMC8241598 DOI: 10.1016/j.uclim.2021.100903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 04/29/2021] [Accepted: 06/27/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVE Weather parameters such as temperature, humidity, air quality index and wind speed are the important factors influencing the infectious diseases like Covid-19. Therefore, this study aims to discuss and analyse the relation between weather parameters and the spread of Coronavirus disease (Covid-19) from the perspective of Bangladesh. METHODS Correlation among weather parameters and infection and death rate were established using several graphical plots and wind rose diagrams, Kendall and Spearman correlation and appropriate discussion with relevancy and reference. Information presented in this study has been extracted from 1st April 2020 to 30th December 2020. RESULTS Analyses show that with the decrease in temperature, infection rate increased significantly. Also, the number of infection increases as wind speed increases. As the absolute humidity rate of Bangladesh is almost constant; therefore, the authors are unable to predict any relation of absolute humidity with the number of infection. Further, the prediction for the number of infections based on the wind direction for the several regions of seven divisions in Bangladesh is vulnerable for the upcoming several months. CONCLUSION This study has analysed the dependency of weather parameters on a number of infections along with predicting the upcoming danger zones.
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Affiliation(s)
- Md Arman Arefin
- Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Bangladesh
| | - Md Nurun Nabi
- School of Engineering and Technology, Central Queensland University, WA 6000, Australia
| | - Mohammad Towhidul Islam
- Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Bangladesh
| | - Md Shamiul Islam
- Department of Mechanical Engineering, Rajshahi University of Engineering & Technology, Bangladesh
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26
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Hamd A, Abdulraheem DE, Khan AAP, Shaban M, Alamry KA, Asiri AM. Statistical study on the impact of different meteorological changes on the spread of COVID-19 pandemic in Egypt and its latitude. ACTA ACUST UNITED AC 2021; 8:2225-2231. [PMID: 34222613 PMCID: PMC8236310 DOI: 10.1007/s40808-021-01222-4] [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: 02/28/2021] [Accepted: 06/19/2021] [Indexed: 12/14/2022]
Abstract
Abstract More than 1 million illnesses and 70,000 deaths were reported due to novel COVID-19 by the end of the first quarter of 2020. In April 2020, the World Health Organization declared COVID-19 a pandemic. The striking resemblance between COVID-19 and its forerunners SARS and MERS, as well as earlier findings on the impact of meteorological conditions on the spread of SARS and MERS, prompted researchers to investigate the relationship between meteorological conditions and the spread of COVID-19. In this work, we statistically studied the effect of different meteorological parameters such as average temperature, humidity, dew point, and wind speed on the spread of COVID-19 pandemic in Egypt and its latitude (Algeria, Egypt, Iran, Saudi Arabia, Turkey). Our findings revealed that there is a correlation between several meteorological parameters and the spread of COVID-19, but that, contrary to popular belief, the virus does not disappear when the temperature rises. Our theory is that either the virus became active in Egypt and its latitude as the temperature rose, or the humidity became unstable when the temperature rose during the summer season. A log-linear quasi-Poisson regression model was used to estimate the relationship between the studied metrological parameters and the spread of COVID-19. The findings of the study will have ramifications for future control and prevention efforts in Egypt and its latitude. Graphic abstract ![]()
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Affiliation(s)
- Ahmed Hamd
- Basic Science Department, Faculty of Oral and Dental Medicine, Nahda University in Beni-Suef (NUB), Beni-Suef, Egypt
| | | | - Aftab Aslam Parwaz Khan
- Center of Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, 21589 Saudi Arabia.,Chemistry Department, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mohamed Shaban
- Nanophotonics and Applications (NPA) Lab, Physics Department, Faculty of Science, Beni-Suef University, Beni-Suef, 62514 Egypt
| | - Khalid A Alamry
- Center of Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, 21589 Saudi Arabia
| | - Abdullah M Asiri
- Center of Excellence for Advanced Materials Research, King Abdulaziz University, Jeddah, 21589 Saudi Arabia.,Chemistry Department, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia
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27
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Sangkham S, Thongtip S, Vongruang P. Influence of air pollution and meteorological factors on the spread of COVID-19 in the Bangkok Metropolitan Region and air quality during the outbreak. ENVIRONMENTAL RESEARCH 2021; 197:111104. [PMID: 33798521 PMCID: PMC8007536 DOI: 10.1016/j.envres.2021.111104] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Revised: 03/24/2021] [Accepted: 03/26/2021] [Indexed: 05/20/2023]
Abstract
This study investigated the effects of weather conditions, air pollutants, and the air quality index (AQI) on daily cases of COVID-19 in the Bangkok Metropolitan Region (BMR). In this research, we collected data from January 1 to March 30, 2020 (90 days). This study used secondary data of meteorological and air pollutant parameters obtained from the Pollution Control Department of the Ministry of Natural Resources and Environment as well as daily confirmed COVID-19 case data in the BMR obtained from the official webpage of the Department of Disease Control, Ministry of Public Health, Thailand. We employed descriptive statistics, and Spearman and Kendall rank correlation tests were used to investigate the associations of weather variables, air pollutants, AQI with daily confirmed COVID-19 cases. Our findings indicate that CO, NO2, SO2, O3 PM10, PM2.5, AQI have a significantly negative association with daily confirmed COVID-19 cases in the BMR, whereas meteorological parameters such as temperature, relative humidity (RH), absolute humidity (AH) and wind speed (WS) showed significant positive associations with daily confirmed COVID-19 cases in the BMR. Our study is a useful supplement to encourage regulatory bodies to promote environmental strategies, as air pollution regulation could be a sustainable policy for mitigating the harmful effects of air pollutants. Furthermore, this study provides new insights into the relationship between daily meteorological factors, AQI, and air pollutants and daily confirmed COVID-19 cases in the BMR. These data may provide useful information to the public health authorities and decision makers in Thailand, as well as to the World Health Organization (WHO), in order to set proper strategic aimed at reducing the impact of the COVID-19. Future studies concerning SARS-CoV-2 and other viruses should investigate the possibility of infectious droplet dispersion in indoor and outdoor air during and after the epidemic outbreak.
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Affiliation(s)
- Sarawut Sangkham
- Department of Environmental Health, School of Public Health, University of Phayao, Muang District, Phayao, 56000, Thailand.
| | - Sakesun Thongtip
- Department of Environmental Health, School of Public Health, University of Phayao, Muang District, Phayao, 56000, Thailand; Atmospheric Chemistry and Climate Model Laboratory, Atmospheric Pollution and Climate Change Research Unit, School of Energy and Environment, University of Phayao, Muang District, Phayao, 56000, Thailand
| | - Patipat Vongruang
- Department of Environmental Health, School of Public Health, University of Phayao, Muang District, Phayao, 56000, Thailand; Atmospheric Chemistry and Climate Model Laboratory, Atmospheric Pollution and Climate Change Research Unit, School of Energy and Environment, University of Phayao, Muang District, Phayao, 56000, Thailand
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28
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Ganegoda NC, Wijaya KP, Amadi M, Erandi KKWH, Aldila D. Interrelationship between daily COVID-19 cases and average temperature as well as relative humidity in Germany. Sci Rep 2021; 11:11302. [PMID: 34050241 PMCID: PMC8163835 DOI: 10.1038/s41598-021-90873-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 05/16/2021] [Indexed: 02/04/2023] Open
Abstract
COVID-19 pandemic continues to obstruct social lives and the world economy other than questioning the healthcare capacity of many countries. Weather components recently came to notice as the northern hemisphere was hit by escalated incidence in winter. This study investigated the association between COVID-19 cases and two components, average temperature and relative humidity, in the 16 states of Germany. Three main approaches were carried out in this study, namely temporal correlation, spatial auto-correlation, and clustering-integrated panel regression. It is claimed that the daily COVID-19 cases correlate negatively with the average temperature and positively with the average relative humidity. To extract the spatial auto-correlation, both global Moran's [Formula: see text] and global Geary's [Formula: see text] were used whereby no significant difference in the results was observed. It is evident that randomness overwhelms the spatial pattern in all the states for most of the observations, except in recent observations where either local clusters or dispersion occurred. This is further supported by Moran's scatter plot, where states' dynamics to and fro cold and hot spots are identified, rendering a traveling-related early warning system. A random-effects model was used in the sense of case-weather regression including incidence clustering. Our task is to perceive which ranges of the incidence that are well predicted by the existing weather components rather than seeing which ranges of the weather components predicting the incidence. The proposed clustering-integrated model associated with optimal barriers articulates the data well whereby weather components outperform lag incidence cases in the prediction. Practical implications based on marginal effects follow posterior to model diagnostics.
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Affiliation(s)
- Naleen Chaminda Ganegoda
- grid.267198.30000 0001 1091 4496Department of Mathematics, University of Sri Jayewardenepura, Nugegoda, 10250 Sri Lanka
| | | | - Miracle Amadi
- grid.12332.310000 0001 0533 3048Department of Mathematics and Physics, Lappeenranta University of Technology, 53851 Lappeenranta, Finland
| | - K. K. W. Hasitha Erandi
- grid.8065.b0000000121828067Department of Mathematics, University of Colombo, Colombo, 00300 Sri Lanka
| | - Dipo Aldila
- grid.9581.50000000120191471Department of Mathematics, Universitas Indonesia, Depok, 16424 Indonesia
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29
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Islam MN, Islam ARMT, Hasan MS, Prodhan MTR, Chowdhury MH, Mamun MHA. Mass Media Influence on Changing Healthy Lifestyle of Community People During COVID-19 Pandemic in Bangladesh: A Cross-Sectional Survey. Asia Pac J Public Health 2021; 33:617-619. [PMID: 33870719 DOI: 10.1177/10105395211011030] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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30
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Rahman MS, Azad MAK, Hasanuzzaman M, Salam R, Islam ARMT, Rahman MM, Hoque MMM. How air quality and COVID-19 transmission change under different lockdown scenarios? A case from Dhaka city, Bangladesh. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 762:143161. [PMID: 33129520 PMCID: PMC7577272 DOI: 10.1016/j.scitotenv.2020.143161] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Revised: 10/11/2020] [Accepted: 10/12/2020] [Indexed: 05/07/2023]
Abstract
The transmission of novel coronavirus (COVID-19) can be reduced by implementing a lockdown policy, which has also been proven as an effective control measure for air pollution in the urban cities. In this study, we applied ground- and satellite-based data of five criteria air pollutants (PM2.5, NO2, SO2, O3, and CO) and meteorological factors from March 8 to May 15, 2020 (before, partial-, and full-lockdown). The generalized additive models (GAMs), wavelet coherence, and random forest (RF) model were employed to explore the relationship between air quality indicators and COVID-19 transmission in Dhaka city. Results show that overall, 26, 20.4, 17.5, 9.7 and 8.8% declined in PM 2.5, NO2, SO2, O3, and CO concentrations, respectively, in Dhaka City during the partial and full lockdown compared to the period before the lockdown. The implementation of lockdown policy for containing COVID-19 transmission played a crucial role in reducing air pollution. The findings of wavelet coherence and partial wavelet coherence demonstrate no standalone coherence, but interestingly, multiple wavelet coherence indicated a strong short-term coherence among air pollutants and meteorological factors with the COVID-19 outbreak. Outcomes of GAMs indicated that an increase of 1-unit in long-term exposure to O3 and CO (lag1) was associated with a 2.9% (95% CI: -0.3%, -5.6%), and 53.9% (95% CI: 0.2%, -107.9%) decreased risk of COVID-19 infection rate during the full-lockdown period. Whereas, COVID-19 infection and MT (mean temperature) are modulated by a peak during full-lockdown, which is mostly attributed to contact transmission in Dhaka city. RF model revealed among the parameters being studied, MT, RH (relative humidity), and O3 were the dominant factors that could be associated with COVID-19 cases during the study period. The outcomes reported here could elucidate the effectiveness of lockdown scenarios for COVID-19 containment and air pollution control in Dhaka city.
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Affiliation(s)
- Md Siddiqur Rahman
- Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh
| | - Md Abul Kalam Azad
- Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh
| | - Md Hasanuzzaman
- Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh
| | - Roquia Salam
- Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh
| | | | - Md Mostafizur Rahman
- Department of Environmental Sciences, Jahangirnagar University, Dhaka 1342, Bangladesh.
| | - Mir Md Mozammal Hoque
- Department of Environmental Science and Resource Management, Mawlana Bhashani Science and Technology University, Tangail 1902, Bangladesh
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31
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Alam GMM, Khatun MN. Impact of COVID-19 on vegetable supply chain and food security: Empirical evidence from Bangladesh. PLoS One 2021; 16:e0248120. [PMID: 33667256 PMCID: PMC7949487 DOI: 10.1371/journal.pone.0248120] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 02/21/2021] [Indexed: 11/18/2022] Open
Abstract
In Bangladesh, the COVID-19 pandemic is likely to have substantial effects on the
livelihood of people, but smallholder vegetables growers will be even more
affected because of the perishability nature of the product. The first case of
COVID-19 was confirmed in Bangladesh on 8th March, 2020 and consequently the
country went into lockdown on 26 March, 2020. This study has made a survey of
vegetables farmers through a mobile phone to understand the impact of COVID-19
on vegetables supply chain, gross margin and the future production plan of the
growers. In Bangladesh, the lockdown has disrupted the food supply chain and
increases the likelihood of food insecurity. Lockdown has impeded vegetable
farmers’ access to markets, thus limiting their productive and sales capacities.
The price of yield has dropped by more than half resulting in huge loss for
vegetable growers. The loss incurred by the farmers for producing Brinjal,
Cucumber, Pointed gourd, Yardlong beans and Bottle gourd are BDT 4900, BDT
10900, BDT 57400, BDT 52500 and BDT 18500 per acre respectively as a result of
COVID-19. The decreased income increases farmers’ likelihood of vulnerability
and food insecurity and poses a challenge to continued produce. ‘Cash support’
is more important than ‘food support’ in order to keep vegetable farmers in
farming, to ensure a ready supply of necessary low-cost resources, and to help
fight against the upcoming food shortage.
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Affiliation(s)
- G. M. Monirul Alam
- Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur,
Bangladesh
- University of Southern Queensland, Toowoomba, Australia
- * E-mail: ,
| | - Most Nilufa Khatun
- Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur,
Bangladesh
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32
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Islam ARMT, Hasanuzzaman M, Shammi M, Salam R, Bodrud-Doza M, Rahman MM, Mannan MA, Huq S. Are meteorological factors enhancing COVID-19 transmission in Bangladesh? Novel findings from a compound Poisson generalized linear modeling approach. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:11245-11258. [PMID: 33118070 PMCID: PMC7594949 DOI: 10.1007/s11356-020-11273-2] [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: 05/28/2020] [Accepted: 10/15/2020] [Indexed: 05/06/2023]
Abstract
Novel coronavirus (SARS-CoV-2) causing COVID-19 disease has arisen to be a pandemic. Since there is a close association between other viral infection cases by epidemics and environmental factors, this study intends to unveil meteorological effects on the outbreak of COVID-19 across eight divisions of Bangladesh from March to April 2020. A compound Poisson generalized linear modeling (CPGLM), along with a Monte-Carlo method and random forest (RF) model, was employed to explore how meteorological factors affecting the COVID-19 transmission in Bangladesh. Results showed that subtropical climate (mean temperature about 26.6 °C, mean relative humidity (MRH) 64%, and rainfall approximately 3 mm) enhanced COVD-19 onset. The CPGLM model revealed that every 1 mm increase in rainfall elevated by 30.99% (95% CI 77.18%, - 15.20%) COVID-19 cases, while an increase of 1 °C of diurnal temperature (TDN) declined the confirmed cases by - 14.2% (95% CI 9.73%, - 38.13%) on the lag 1 and lag 2, respectively. In addition, NRH and MRH had the highest increase (17.98% (95% CI 22.5%, 13.42%) and 19.92% (95% CI: 25.71%, 14.13%)) of COVID-19 cased in lag 4. The results of the RF model indicated that TDN and AH (absolute humidity) influence the COVID-19 cases most. In the Dhaka division, MRH is the most vital meteorological factor that affects COVID-19 deaths. This study indicates the humidity and rainfall are crucial factors affecting the COVID-19 case, which is contrary to many previous studies in other countries. These outcomes can have policy formulation for the suppression of the COVID-19 outbreak in Bangladesh.
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Affiliation(s)
| | - Md Hasanuzzaman
- Department of Disaster Management, Begum Rokeya University, Rangpur, 5400, Bangladesh
| | - Mashura Shammi
- Department of Environmental Sciences, Jahangirnagar University, Dhaka, 1342, Bangladesh
| | - Roquia Salam
- Department of Disaster Management, Begum Rokeya University, Rangpur, 5400, Bangladesh
| | | | - Md Mostafizur Rahman
- Department of Environmental Sciences, Jahangirnagar University, Dhaka, 1342, Bangladesh.
| | - Md Abdul Mannan
- Bangladesh Meteorological Department, Meteorological Complex Agargaon, Dhaka, 1207, Bangladesh
| | - Saleemul Huq
- ICCCAD, Independent University Bangladesh, Dhaka, Bangladesh
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33
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Burnham JP. Climate change and antibiotic resistance: a deadly combination. Ther Adv Infect Dis 2021; 8:2049936121991374. [PMID: 33643652 PMCID: PMC7890742 DOI: 10.1177/2049936121991374] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 01/09/2021] [Indexed: 11/16/2022] Open
Abstract
Climate change is driven primarily by humanity's use of fossil fuels and the resultant greenhouse gases from their combustion. The effects of climate change on human health are myriad and becomingly increasingly severe as the pace of climate change accelerates. One relatively underreported intersection between health and climate change is that of infections, particularly antibiotic-resistant infections. In this perspective review, the aspects of climate change that have already, will, and could possibly impact the proliferation and dissemination of antibiotic resistance are discussed.
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Affiliation(s)
- Jason P Burnham
- Division of Infectious Diseases, Washington University School of Medicine, 4523 Clayton Avenue, Campus Box 8051, St. Louis, MO 63110, USA
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34
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Hridoy AEE, Mohiman MA, Tusher SMSH, Nowraj SZA, Rahman MA. Impact of meteorological parameters on COVID-19 transmission in Bangladesh: a spatiotemporal approach. THEORETICAL AND APPLIED CLIMATOLOGY 2021; 144:273-285. [PMID: 33551528 PMCID: PMC7854875 DOI: 10.1007/s00704-021-03535-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 01/11/2021] [Indexed: 05/03/2023]
Abstract
It has been more than 10 months since the first COVID-19 case was reported in Wuhan, China, still menacing the world with a possible second wave. This study aimed to analyze how meteorological variables can affect the spread of local COVID-19 transmission in Bangladesh. Nine spatial units were considered from a meteorological standpoint to characterize COVID-19 transmission in Bangladesh. The daily COVID-19 incidence and meteorological variable (e.g., mean temperature, relative humidity, precipitation, and wind speed) data from April 5 to September 20, 2020, were collected. The Spearman rank correlation, heat maps, and multivariate quasi-Poisson regression were employed to understand their association. The effect of meteorological variables on COVID-19 transmission was modeled using a lag period of 10 days. Results showed that mean temperature, relative humidity, and wind speed are substantially associated with an increased risk of COVID-19. On the other hand, daily precipitation is significantly associated with a decreased risk of COVID-19 incidence. The relative risks (RR) of mean temperature for daily COVID-19 incidences were 1.222 (95% confidence interval [CI], 1.214-1.232). For wind speed, the RR was 1.087 (95% CI, 1.083-1.090). For relative humidity, the RR was 1.027 (95% CI, 1.025-1.029). Overall, this study found the profound effect of meteorological parameters on COVID-19 incidence across selected nine areas in Bangladesh. This study is probably the first study to explore the impact of region-specific meteorological conditions on COVID-19 incidence in Bangladesh. Moreover, adjustments on the areal-aggregated and regional levels were made for three confounding factors, including lockdown, population density, and potential seasonal effects. The study's findings suggest that SARS-CoV-2 can be transmitted in high temperatures and humidity conditions, which contradicts many other countries' prior studies. The research outcomes will provide implications for future control and prevention measures in Bangladesh and other countries with similar climate conditions and population density.
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Affiliation(s)
- Al-Ekram Elahee Hridoy
- Department of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331 Bangladesh
| | - Md. Abdul Mohiman
- Department of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331 Bangladesh
| | | | - Sayed Ziaul Amin Nowraj
- Department of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331 Bangladesh
| | - Mohammad Atiqur Rahman
- Department of Geography and Environmental Studies, University of Chittagong, Chittagong, 4331 Bangladesh
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Kokubun K, Yamakawa Y. Social Capital Mediates the Relationship between Social Distancing and COVID-19 Prevalence in Japan. INQUIRY : A JOURNAL OF MEDICAL CARE ORGANIZATION, PROVISION AND FINANCING 2021; 58:469580211005189. [PMID: 33858247 PMCID: PMC8053753 DOI: 10.1177/00469580211005189] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 02/15/2021] [Accepted: 04/01/2021] [Indexed: 12/17/2022]
Abstract
The threat of coronavirus disease (COVID-19) is increasing. Regarding the differences in the infection rate observed in each region, additionally to studies investigating the causes of differences in population density as a proxy for social distancing, an increasing trend of studies investigating the causes of differences in social capital has also been seen (ie, value sharing, acceptance of norms, unity, and trust through reciprocity). However, studies investigating whether social capital that controls the effects of population density also influences the infection rate are limited. Therefore, in this study, we analyzed the relationship between infection rate, population density, and social capital using statistical data of Japan's every prefecture. Statistical analysis showed that social capital not only negatively correlates with infection rates and population densities, but also negatively correlates with infection rates controlling for the effects of population density. Additionally, controlling the relationship between the variables by mean age showed that social capital had a greater correlation with infection rate than population density. In other words, social capital mediates the relationship between population density and infection rates, indicating that social distancing alone is not enough to deter coronavirus disease; social capital needs to be recharged.
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Affiliation(s)
- Keisuke Kokubun
- Japan Society for the Promotion of Machine Industry, Tokyo, Japan
- Tohoku University, Sendai, Japan
| | - Yoshinori Yamakawa
- Kyoto University, Kyoto, Japan
- Tokyo Institute of Technology, Tokyo, Japan
- Kobe University, Kobe, Japan
- Brain Impact, Kyoto, Japan
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