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      Digital Surveillance for Monitoring Environmental Health Threats: A Case Study Capturing Public Opinion from Twitter about the 2019 Chennai Water Crisis

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          Abstract

          Globally, water scarcity has become a common challenge across many regions. Digital surveillance holds promise for monitoring environmental threats to population health due to severe drought. The 2019 Chennai water crisis in India resulted in severe disruptions to social order and daily life, with local residents suffering due to water shortages. This case study explored public opinion captured through the Twitter social media platform, and whether this information could help local governments with emergency response. Sentiment analysis and topic modeling were used to explore public opinion through Twitter during the 2019 Chennai water crisis. The latent Dirichlet allocation (LDA) method identified topics that were most frequently discussed. A naïve Tweet classification method was built, and Twitter posts (called tweets) were allocated to identified topics. Topics were ranked, and corresponding emotions were calculated. A cross-correlation was performed to examine the relationship between online posts about the water crisis and actual rainfall, determined by precipitation levels. During the Chennai water crisis, Twitter users posted content that appeared to show anxiety about the impact of the drought, and also expressed concerns about the government response. Twitter users also mentioned causes for the drought and potential sustainable solutions, which appeared to be mainly positive in tone. Discussion on Twitter can reflect popular public opinion related to emerging environmental health threats. Twitter posts appear viable for informing crisis management as real-time data can be collected and analyzed. Governments and public health officials should adjust their policies and public communication by leveraging online data sources, which could inform disaster prevention measures.

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          Most cited references57

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          Rapid assessment of disaster damage using social media activity

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            The world’s road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability

            Water scarcity is a rapidly growing concern around the globe, but little is known about how it has developed over time. This study provides a first assessment of continuous sub-national trajectories of blue water consumption, renewable freshwater availability, and water scarcity for the entire 20th century. Water scarcity is analysed using the fundamental concepts of shortage (impacts due to low availability per capita) and stress (impacts due to high consumption relative to availability) which indicate difficulties in satisfying the needs of a population and overuse of resources respectively. While water consumption increased fourfold within the study period, the population under water scarcity increased from 0.24 billion (14% of global population) in the 1900s to 3.8 billion (58%) in the 2000s. Nearly all sub-national trajectories show an increasing trend in water scarcity. The concept of scarcity trajectory archetypes and shapes is introduced to characterize the historical development of water scarcity and suggest measures for alleviating water scarcity and increasing sustainability. Linking the scarcity trajectories to other datasets may help further deepen understanding of how trajectories relate to historical and future drivers, and hence help tackle these evolving challenges.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                14 July 2020
                July 2020
                : 17
                : 14
                : 5077
                Affiliations
                [1 ]Department of Biostatistics, Vanderbilt University, Nashville, TN 37203, USA; jx2348@ 123456columbia.edu
                [2 ]Computational Epidemiology Lab, Harvard Medical School, Boston, MA 02215, USA; yulin.hswen@ 123456ucsf.edu
                [3 ]Innovation Program, Boston Children’s Hospital, Boston, MA 02215, USA
                [4 ]Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
                [5 ]Bakar Computational Health Sciences Institute, University of California, San Francisco, CA 94158, USA
                [6 ]Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA 02115, USA
                Author notes
                Article
                ijerph-17-05077
                10.3390/ijerph17145077
                7400361
                32674441
                b2f0f99b-2f31-4c9c-b8bd-252f3b5042b6
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 May 2020
                : 07 July 2020
                Categories
                Case Report

                Public health
                digital surveillance,disasters,crisis,water,public opinion,social media,natural language processing

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