Department of Civil Engineering

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Subject: search.filters.subject.COVID-19

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Now showing 1 - 8 of 8
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    Impacts of COVID-19 pandemic on the wastewater pathway into surface water: a review
    (Elsevier, 2021-06) Goonetilleke, Ashantha
    With global number of cases 106 million and death toll surpassing 2.3 million as of mid-February 2021, the COVID-19 pandemic is certainly one of the major threats that humankind have faced in modern history. As the scientific community navigates through the overwhelming avalanche of information on the multiple health impacts caused by the pandemic, new reports start to emerge on significant ancillary effects associated with the treatment of the virus. Besides the evident health impacts, other emerging impacts related to the COVID-19 pandemic, such as water-related impacts, merits in-depth investigation. This includes strategies for the identification of these impacts and technologies to mitigate them, and to prevent further impacts not only in water ecosystems, but also in relation to human health. This paper has critically reviewed currently available knowledge on the most significant potential impacts of the COVID-19 pandemic on the wastewater pathway into surface water, as well as technologies that may serve to counteract the major threats posed, key perspectives and challenges. Additionally, current knowledge gaps and potential directions for further research and development are identified. While the COVID-19 pandemic is an ongoing and rapidly evolving situation, compiling current knowledge of potential links between wastewater and surface water pathways as related to environmental impacts and relevant associated technologies, as presented in this review, is a critical step to guide future research in this area.
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    An innovative approach for predicting pandemic hotspots in complex wastewater networks using graph theory coupled with fuzzy logic
    (Springer, 2023-05) Srinivas, Rallapalli
    Early prediction of COVID-19 infected communities (potential hotspots) is essential to limit the spread of virus. Diagnostic testing has limitations in big populations because it cannot deliver information at a fast enough rate to stop the spread in its early phases. Wastewater based epidemiology (WBE) experiments showed promising results for brisk detection of ‘SARS CoV-2’ RNA in urban wastewater. However, a systematic and targeted approach to track COVID-19 virus in the complex wastewater networks at a community level is lacking. This research combines graph network (GN) theory with fuzzy logic to determine the chances of a specific community being a COVID-19 hotspot in a wastewater network. To detect 'SARS-CoV-2' RNA, GN divides wastewater network into communities and fuzzy logic-based inference system is used to identify targeted communities. For the propose of tracking, 4000 sample cases from Minnesota (USA) were tested based on various contributing factors. With a probability score of greater than 0.8, 42% of cases were likely to be designated as COVID-19 hotspots based on multiple demographic characteristics. The research enhances the conventional WBE approach through two novel aspects, viz. (1) by integrating graph theory with fuzzy logic for quick prediction of potential hotspot along with its likelihood percentage in a wastewater network, and (2) incorporating the uncertainty associated with COVID-19 contributing factors using fuzzy membership functions. The targeted approach allows for rapid testing and implementation of vaccination campaigns in potential hotspots. Consequently, governmental bodies can be well prepared to check future pandemics and variant spreading in a more planned manner.
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    A review on presence, survival, disinfection/removal methods of coronavirus in wastewater and progress of wastewater-based epidemiology
    (Elsevier, 2020-10) Mandal, Pubali
    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the global pandemic coronavirus 2019 disease (COVID-19). The outbreak of COVID-19 as Public Health Emergency of International Concern is declared by World Health Organization on January 30, 2020. The known route of transmission is due to direct contact or via respiratory droplets. Recently, several studies reported SARS-CoV-2 ribonucleic acid (RNA) in wastewater treatment plant samples. The presence of SARS-CoV-2 RNA in wastewater may predict COVID-19 occurrence qualitatively and quantitatively. The concept is known as wastewater-based epidemiology (WBE) or sewage epidemiology. The present study reviewed the presence of coronavirus in wastewater and investigations relating to WBE development as a tool to detect COVID-19 community transmission. Few articles reported a correlation of SARS-CoV-2 RNA concentration in wastewater with the number of COVID-19 cases, whereas few reported higher prediction by wastewater surveillance than confirmed cases. The application of WBE is still in a preliminary stage but has the potential to indicate an early sign of transmission. The knowledge of persistence of coronavirus in municipal and hospital wastewater is needed for the application of WBE and to understand the chances of transmission. The studies reported more prolonged survival of coronavirus in low-temperature wastewater. Studies relating to the inactivation of coronavirus by disinfectants and removal of coronavirus are also presented. Research on the performance of the commonly adopted disinfection technologies in inactivating SARS-CoV-2 in municipal and hospital wastewater is required to reduce the risk associated with municipal and hospital wastewater.
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    Projecting the criticality of COVID-19 transmission in India using GIS and machine learning methods
    (Elsiever, 2021-06) Gupta, Rajiv
    There is a new public health catastrophe forbidding the world. With the advent and spread of 2019 novel coronavirus (2019-nCoV). Learning from the experiences of various countries and the World Health Organization (WHO) guidelines, social distancing, use of sanitizers, thermal screening, quarantining, and provision of lockdown in the cities being the effective measure that can contain the spread of the pandemic. Though complete lockdown helps in containing the spread, it generates complexity by breaking the economic activity chain. Besides, laborers, farmers, and workers may lose their daily earnings. Owing to these detrimental effects, the government has to open the lockdown strategically. Prediction of the COVID-19 spread and analyzing when the cases would stop increasing helps in developing a strategy. An attempt is made in this paper to predict the time after which the number of new cases stops rising, considering the strong implementation of lockdown conditions using three different techniques such as Decision Tree, Support Vector Machine, and Gaussian Process Regression algorithm are used to project the number of cases. Thus, the projections are used in identifying inflection points, which would help in planning the easing of lockdown in a few of the areas strategically. The criticality in a region is evaluated using the criticality index (CI), which is proposed by authors in one of the past of research works. This research work is made available in a dashboard to enable the decision-makers to combat the pandemic.
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    Preparedness and Mitigation by projecting the risk against COVID-19 transmission using Machine Learning Techniques
    (medRxiv, 2020) Gupta, Rajiv
    The outbreak of COVID-19 is first identified in China, which later spread to various parts of the globe and was pronounced pandemic by the World Health Organization (WHO). The disease of transmissible person-to-person pneumonia caused by the extreme acute respiratory coronavirus 2 syndrome (SARS-COV-2, also known as COVID-19), has sparked a global warning. Thermal screening, quarantining, and later lockdown were methods employed by various nations to contain the spread of the virus. Though exercising various possible plans to contain the spread help in mitigating the effect of COVID-19, projecting the rise and preparing to face the crisis would help in minimizing the effect. In the scenario, this study attempts to use Machine Learning tools to forecast the possible rise in the number of cases by considering the data of daily new cases. To capture the uncertainty, three different techniques: (i) Decision Tree algorithm, (ii) Support Vector Machine algorithm, and (iii) Gaussian process regression are used to project the data and capture the possible deviation. Based on the projection of new cases, recovered cases, deceased cases, medical facilities, population density, number of tests conducted, and facilities of services, are considered to define the criticality index (CI). CI is used to classify all the districts of the country in the regions of high risk, low risk, and moderate risk. An online dashpot is created, which updates the data on daily bases for the next four weeks. The prospective suggestions of this study would aid in planning the strategies to apply the lockdown/ any other plan for any country, which can take other parameters to define the CI.
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    Trade-off between Safety of Construction Workers and Economy in Backdrop of Covid-19
    (IAAM-VBRI Press, 2020) Gupta, Rajiv
    The Indian Construction industry, which contributes to 8-10% of the country's GDP, is suffering from an unprecedented crisis in the wake of the COVID-19 pandemic. The Indian Government is facing a strict trade-off between preventing and containing the spread of Coronavirus on the one hand and revitalizing the economic activities which have come to complete halt/resumed partially depending on the zone to which an area depends on the other side. Impact of the lockdown on the industry, stimulus measures announced by the Indian Government, and some other actions recommended by Industry experts' for the revival of the Construction sector are discussed in this paper. The detailed specific guidelines to be adopted by the site personnel for safely resuming the site work are presented for the benefit of Industry practitioners. Experimental study results on the stability of SARS-CoV-2 virus on surfaces of different materials are presented. Also, the potential and suitability of Construction material and technology for overcoming the current challenges posed by the pandemic is discussed. The main objective of the paper is to understand the current precarious situation of the Construction industry and the strategies to overcome it for moving forward.
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    An UID Number Based Tool to Enable Social Distancing Amid COVID -19
    (Elsiever, 2020-05) Gupta, Rajiv
    Various nations developed their rules of national quarantines to contain the spread of the coronavirus. Extending the national quarantine for indefinite time may consequently affect welfare outcomes and the economic activity. In this regard, authorities are easing the restrictions in the regions that are relatively unaffected with coronavirus as happened in China. These relaxations are fearsomely complex as these policies certainly spark a fresh wave of infections. The fear is intense in India because of the densely packed population and enfeebled health care systems. A strategy that can simultaneously ease the relaxations while ensuring the containment of COVID-19 spread would help to combat this scenario. In line with this need, a tool is developed to resume economic activity while ensuring social distancing. The developed tool is based on the Unique Identification (UID) Number of citizens. The proposed tool aid in controlling the movement of citizens in a region systematically while allowing them to meet their needs. For demonstration purpose, the demographic features of Kasaragod city, Kerala is considered, and it is observed that the interactions can be minimized nearly by 97% while allowing the citizens to meet their daily needs on every alternate day. The tool can be used in many other situation where movements of citizens are to be released in palnned and systematic way.
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    Current Scenario of Coronavirus Pandemic
    (VBRI Press, 2020) Gupta, Rajiv
    World Health Organization (WHO) has expressed great concern about the pandemic of Coronavirus (COVID-19) and said that there is a need to control it at the high end. To strengthen this fight against COVID-19, International Association of Advanced Materials (IAAM) intends to provide a forum for high-tech healthcare. Foreseeing the current crisis, IAAM called a multi-lateral consortium to discuss the possibilities of developing a medical technology to control the spreading of coronavirus with the help of interdisciplinary experts from multiple countries. This innovation is perpetuated to create multi-lateral cooperation in the area of ‘healthcare innovation and technology’. Adaptation of advanced technologies and their logical integration according to contemporary healthcare measures could be a smart strategy for epidemic management activities. Establishing an advanced phenotype model for prognosis is an important step in the prevention of infectious disease management such as COVID-19. This article has overviewed the global situation, efforts, and prospective of coronavirus pandemic.