Article
Public, Environmental & Occupational Health
Jinghua An, Shelley Hoover, Sreenivas Konda, Sage J. J. Kim
Summary: This study examines the effectiveness of a COVID-19 specific social vulnerability index and finds that COVID-19 specific themes play an important role in explaining COVID-19 mortality rates. However, further improvements are needed for the accuracy of the index, and the development of robust local data infrastructure is critical.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Environmental Sciences
Xinxuan Zhang, Viviana Maggioni, Paul Houser, Yuan Xue, Yiwen Mei
Summary: The study examines the impact of social activity factors and weather variables on the spread of COVID-19 cases in the U.S., finding weak correlations between case numbers and factors like temperature, humidity, and social distance index. The random forest regression model improves accuracy in estimating case numbers by incorporating weather variables, with population density and social distance index playing significant roles. Validation shows a general correlation coefficient of around 0.85 between estimated and observed case numbers.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2022)
Article
Engineering, Biomedical
Feng Shi, Liming Xia, Fei Shan, Bin Song, Dijia Wu, Ying Wei, Huan Yuan, Huiting Jiang, Yichu He, Yaozong Gao, He Sui, Dinggang Shen
Summary: The study proposed an infection size-aware random forest method for discriminating between COVID-19 and CAP patients, showing promising performance in experimental results and potential in assisting clinical decision-making.
PHYSICS IN MEDICINE AND BIOLOGY
(2021)
Article
Mathematics, Interdisciplinary Applications
Joseph Galasso, Duy M. Cao, Robert Hochberg
Summary: During the COVID-19 pandemic, a non-parametric random forest model is used to predict the number of COVID-19 cases at the U.S. county level. The model utilizes easily accessible epidemiological data and effective reproduction numbers from compartmental models. By aligning estimated reproduction numbers with real-time testing data, the model achieves better fit to the epidemic's trajectory. The model consistently outperforms or performs comparably with gold-standard compartmental models and holds potential for ensemble modeling.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Engineering, Environmental
Asha B. Chelani, Sneha Gautam
Summary: This study examines the impact of meteorological variables, previous day's deaths, and government interventions on the number of COVID-19 confirmed cases in 18 districts of India. The findings suggest that meteorological variables, when used with data on previous day's deaths and lockdown information, can predict the number of COVID-19 cases to some extent. Partial lockdown measures are found to be more influential than complete or no lockdown measures in predicting the number of confirmed COVID-19 cases. The study provides useful information for policymakers in balancing restriction activities and economic losses.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Engineering, Multidisciplinary
Eman H. Alkhammash, Sara Ahmad Assiri, Dalal M. Nemenqani, Raad M. M. Althaqafi, Myriam Hadjouni, Faisal Saeed, Ahmed M. Elshewey
Summary: This study presents an enhanced model for predicting COVID-19 samples in different regions of Saudi Arabia. The model utilizes binary particle swarm optimization for feature selection and evaluates the performance of three machine learning models. The results show that the gradient boosting model performs better in high-altitude areas, while the random forest model performs better in sea-level areas.
Article
Computer Science, Artificial Intelligence
Ankur Kumar, Subhas Chandra Misra, Felix T. S. Chan
Summary: The COVID-19 pandemic has severely impacted the tourism industry, necessitating swift action to support and enhance its recovery.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics
Erwin Cornelius, Olcay Akman, Dan Hrozencik
Summary: The study proposes a clustered random forest approach to predict COVID-19 patient mortality, showing comparable predictive performance to other methods. Analysis of demographic information and subsequent neural network modeling and k-means clustering provide insight into the mortality risks associated with COVID-19.
Article
Chemistry, Analytical
Mujeeb Ur Rehman, Arslan Shafique, Sohail Khalid, Maha Driss, Saeed Rubaiee
Summary: The COVID-19 pandemic has resulted in significant consequences globally, with millions of vaccine doses administered in several countries. However, the positive impact of these vaccines may be delayed. Rapid diagnosis remains crucial in slowing the virus spread, with machine learning algorithms potentially offering an effective method for diagnosing infected patients.
Article
Environmental Sciences
Brigita Dejus, Pavels Cacivkins, Dita Gudra, Sandis Dejus, Maija Ustinova, Ance Roga, Martins Strods, Juris Kibilds, Guntis Boikmanis, Karina Ortlova, Laura Krivko, Liga Birzniece, Edmunds Skinderskis, Aivars Berzins, Davids Fridmanis, Talis Juhna
Summary: Wastewater-based epidemiology (WBE) is a rapid and cost-effective method for detecting SARS-CoV-2 genomic components in wastewater and providing early warnings for COVID-19 outbreaks. However, the quantitative relationship between the epidemic intensity and pandemic progression is still unclear, requiring further research.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Environmental Sciences
Yixuan Lyu, Qianqian Zhang, Qian Sun, Mengna Gu, Yuexin He, Wendell W. Walters, Yele Sun, Yuepeng Pan
Summary: During the COVID-19 lockdown in Beijing, the concentration of atmospheric ammonia substantially decreased, but the effects of meteorology and chemistry masked the actual changes in observed ammonia concentrations. This study used machine learning techniques to separate the impacts of meteorology and emission changes, and found that unfavorable meteorological conditions caused an increase in ammonia concentration, while reductions in NOx and SO2 emissions elevated ammonia concentrations by favoring gas-phase partitioning. Nevertheless, the observed ammonia concentration significantly decreased, partially explained by the enhanced gas-to-particle conversion. The sum of ammonia and ammonium (NHx) is a more reliable tracer for estimating changes in ammonia emissions.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Computer Science, Information Systems
Savita Khurana, Gaurav Sharma, Neha Miglani, Aman Singh, Abdullah Alharbi, Wael Alosaimi, Hashem Alyami, Nitin Goyal
Summary: This study used a machine learning model to predict the COVID-19 pandemic, compared it with other models, and determined the predictive ability for the second wave in India. Analysis of the dataset showed an increasing trend in confirmed cases and deaths, and a model was developed to forecast future situations.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Infectious Diseases
Svetlana Rachina, Roman Kozlov, Anastasiya Kurkova, Ulyana Portnyagina, Shamil Palyutin, Aleksandr Khokhlov, Olga Reshetko, Marina Zhuravleva, Ivan Palagin
Summary: This study evaluated the patterns of community supply of antimicrobials from community pharmacies during the COVID-19 pandemic in five cities of Russia. It found a high rate of drugs dispensing without prescription, with systemic antibiotics being the most common antimicrobials and presumably viral upper respiratory tract infections being the main reason for their purchase.
Article
Multidisciplinary Sciences
Subhendu Paul, Emmanuel Lorin
Summary: By using a novel model based on coupled delay differential equations, we accurately estimated the average incubation period of COVID-19 to be 6.74 days, and the 90th percentile to be 11.64 days, showing good agreement with previous statistical studies.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Pei Yuan, Elena Aruffo, Evgenia Gatov, Yi Tan, Qi Li, Nick Ogden, Sarah Collier, Bouchra Nasri, Iain Moyles, Huaiping Zhu
Summary: Operating schools safely during the COVID-19 pandemic requires a balance between health risks and the need for in-person learning. A study conducted in Toronto, Canada, found that while there was a slight increase in infections among adults and children within the first eight weeks of school reopening, transmission in schools was not the main driver of the virus resurgence. Instead, community spread played a more significant role. The study highlights the importance of home transmission in epidemic progression and the need for strict adherence to public health measures in the community for safe school reopening.
ROYAL SOCIETY OPEN SCIENCE
(2022)
Article
Environmental Sciences
Malay Pramanik, Koushik Chowdhury, Md Juel Rana, Praffulit Bisht, Raghunath Pal, Sylvia Szabo, Indrajit Pal, Bhagirath Behera, Qiuhua Liang, Sabu S. Padnnadas, Parmeshwar Udmale
Summary: This study investigates the relationship between COVID-19 transmission risks and climate in 228 cities globally. The results reveal that temperature and humidity have significant impacts on COVID-19 transmission in temperate and subtropical regions, while diurnal temperature range and temperature seasonality are important factors in the tropical region. Moreover, positive cases decline sharply when the average temperature exceeds 10 degrees Celsius in cities of France, Turkey, the US, the UK, and Germany.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH
(2022)
Article
Water Resources
Koushik Chowdhury, Bhagirath Behera
Summary: This study found that management decisions at the local level have favored a few influential members of local communities, depriving a large number of poor households of resource use and making local institutions ineffective.
INTERNATIONAL JOURNAL OF WATER RESOURCES DEVELOPMENT
(2022)
Article
Green & Sustainable Science & Technology
Atul Kumar, Malay Pramanik, Shairy Chaudhary, Mahabir Singh Negi, Sylvia Szabo
Summary: The Himalayan region faces challenges in groundwater management due to its relief, slope, and rock surface, which affects infiltration. Urbanization, land-use change, over-abstraction, poor administration, and mismanagement exacerbate the decline in quantity and quality. This study used the Analytic Hierarchy Process (AHP) and geospatial techniques to identify groundwater potential sites in the Rudraprayag district. The results can help farmers, planners, and governments make decisions for groundwater development.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Agronomy
Krishna Viswanatha Reddy, Venkatesh Paramesh, Vadivel Arunachalam, Bappa Das, P. Ramasundaram, Malay Pramanik, Shankarappa Sridhara, D. Damodar Reddy, Abed Alataway, Ahmed Z. Dewidar, Mohamed A. Mattar
Summary: Climate change is a major obstacle for agricultural development in developing countries. Farmers' perceptions of climate change and their adaptation strategies are crucial in mitigating and adapting to climate change effects. A study in Goa, India, revealed that a majority of farmers have experienced climate change, leading to declining crop and livestock productivity. Farmers are adapting through crop diversification and integrated crop-livestock systems. Policymakers should support climate-resilient agriculture systems to help farmers cope with climate change and enhance their economic wellbeing.
Article
Geosciences, Multidisciplinary
Afshana Parven, Indrajit Pal, Apichon Witayangkurn, Malay Pramanik, Masahiko Nagai, Hiroyuki Miyazaki, Chanakan Wuthisakkaroon
Summary: Climate-related disasters pose a severe threat to the livelihoods and food security of people living in Bangladesh's deltaic areas. This study examines the impact of disasters on land use change, food security, and adaptive measures, using satellite images and interviews. The findings highlight significant changes in aquaculture and agriculture due to natural disasters, impacting socio-ecological systems, income, and migration in the area. The study emphasizes the importance of considering people's risk perceptions in local disaster management planning.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Environmental Sciences
Biplab Roy, Malay Pramanik, Ajay Kumar Manna
Summary: Groundwater contamination, especially heavy metal pollution, is a major concern in the North Tripura district. The study reveals high levels of Fe contamination and its impact on children's health. Additionally, it provides insights into the hydrogeochemical processes controlling groundwater chemistry and its suitability for irrigation and drinking purposes.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Infectious Diseases
Devojit Kumar Sarma, Manoj Kumar, Praveen Balabaskaran Nina, Karuppusamy Balasubramani, Malay Pramanik, Rintu Kutum, Swasti Shubham, Deepanker Das, Manoj Kumawat, Vinod Verma, Jigyasa Dhurve, Sekar Leo George, Alangar Balasundreshwaran, Anil Prakash, Rajnarayan R. Tiwari
Summary: This study assessed the impact of climatic factors and landscape variables on dengue incidence in Bhopal city, India. The results revealed a non-linear relationship between meteorological variables and dengue cases, with the risk increasing with higher temperature, rainfall, and absolute humidity. Rapid urbanization was also identified as a key factor driving dengue incidence. The study provides valuable insights into the transmission dynamics of dengue and offers baseline information for dengue prediction models in similar climatic conditions.
PLOS NEGLECTED TROPICAL DISEASES
(2022)
Article
Environmental Sciences
Sonu Kumar, Giriraj Amarnath, Surajit Ghosh, Edward Park, Triambak Baghel, Jingyu Wang, Malay Pramanik, Devesh Belbase
Summary: This study evaluates the performance of Satellite-based Precipitation Products (SPPs) in the Himalayas region and identifies the most suitable datasets for hydro-meteorological applications. CMORPH and IMERG_Final are recommended as the best SPPs for managing hydrological disasters in the data-sparse Himalayas. The study framework can be applied in other Himalayan regions to systematically rank and identify suitable datasets.
Article
Green & Sustainable Science & Technology
Venkatesh Paramesh, Parveen Kumar, Mohammad Shamim, Natesan Ravisankar, Vadivel Arunachalam, Arun Jyoti Nath, Trivesh Mayekar, Raghuveer Singh, Ashisa K. Prusty, Racharla Solomon Rajkumar, Azad Singh Panwar, Viswanatha K. Reddy, Malay Pramanik, Anup Das, Kallakeri Kannappa Manohara, Subhash Babu, Poonam Kashyap
Summary: Climate change affects agricultural productivity and farmers' income. Integrated farming systems offer a mechanism to cope with these impacts. A study found that farmers perceive an increase in temperature and decreasing rainfall due to climate change, and have adapted measures to mitigate these effects. However, farmers also face barriers in adapting to climate change.
Article
Water Resources
Atul Kumar, Sunil Singh, Malay Pramanik, Shairy Chaudhary, Mahabir Singh Negi
Summary: The study evaluates soil erosion in the Himalayan region using geographical information system and remote sensing integrated models. The findings help in proposing effective measures for soil erosion control and prioritizing soil conservation in the region.
INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT
(2022)
Article
Environmental Sciences
Bui Phan Quoc Nghia, Indrajit Pal, Malay Pramanik, Rajarshi Dasgupta
Summary: Drought is a frequent and widespread natural hazard in Tien Giang province, Vietnam, and its severity is worsening due to climate change. This study used climate circulation models and different climate change scenarios to examine the impacts of climate change on drought in the province. The findings suggest that drought will become more severe in the future. The survey results indicate that the household perception of drought is moderate, and current adaptation measures are sufficient for moderate drought but need improvement to cope with more extreme drought conditions. This study provides important insights for decision-makers in managing future drought situations in the Mekong region.
Article
Environmental Sciences
S. Mohanasundaram, Triambak Baghel, Vishal Thakur, Parmeshwar Udmale, Sangam Shrestha
Summary: Satellite data is crucial for monitoring vegetation dynamics and assessing vegetation health conditions. However, cloud and shadow cover can cause data gaps in the images. This study proposes algorithms for retrieving cloud-contaminated NDVI and LST information from satellite data, and the results show that these models can effectively recover missing values in cloud-contaminated pixel data.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2023)
Article
Green & Sustainable Science & Technology
Indrajit Pal, Ganesh Dhungana, Ayush Baskota, Parmeshwar Udmale, Mayuri Ashokrao Gadhawe, Puvadol Doydee, Tanh T. N. Nguyen, Seak Sophat
Summary: This paper examines the multi-hazard scenario and impacts in the Lower Mekong Basin (LMB) region and the interlinkages between livelihoods and resilience in LMB communities. Through a literature review and expert workshop, a localized assessment framework is proposed for stakeholders in decision-making process. Floods and droughts were identified as primary natural hazards, with wide spatial variation in hazard levels. A holistic framework is proposed to measure multi-hazard livelihood security and resilience in LMB communities, aiding government authorities and development partners in planning and implementing risk mitigation and preparedness activities.
Article
Health Policy & Services
Sylvia Szabo, Malay Pramanik, Sayem Ahmed, Kevin Leeson
Summary: Using the 2018 Korean Longitudinal Study of Aging (KLoSA) survey data, this study examines the determinants of cognitive impairment (CI) and explores the inequalities and geographic differences of CI among the elderly in South Korea. The findings show that being super-aged, poor general health, and lack of exercise are positively associated with CI, while household wealth, educational level, participation in social activities, and regular exercise have a significant negative effect on CI. Female respondents are more likely to experience CI compared to males. The study also finds little difference between the specific determinates for the two subsamples. Inequalities in CI prevalence are greatest in rural areas and among respondents living in the Chungcheong region, Seoul Metropolitan Area, and the Kangwan region. These results are helpful for early intervention and prevention strategies to address cognitive impairment in the elderly.
ASIA PACIFIC JOURNAL OF HEALTH MANAGEMENT
(2023)
