Equitable Access to Affordable and Clean Water in Pre-Pandemic, Pandemic, and Post-Pandemic Modes of Work

The distribution of clean water through public systems can be inequitable, as variations in water quality are common drivers for negative health outcomes and can lead households to spend more on water treatment or alternative sources of water, such as bottled water. The COVID-19 pandemic caused complex, location dependent changes to demands due to social distancing that led to changes in water quality. The first wave of social distancing was characterized by wide-spread adoption of work-from-home practices and social distancing, causing water demands to shift from places of employment and recreation to residences. Subsequent changes have ushered in a new post-pandemic regime that is characterized by a hybrid work force. The hybrid work force includes many individuals who have adopted a personal schedule of working from home and working from the office that increases the uncertainty in modeling daily population movement changes and demands. The changes in water quality that followed the change from pre-pandemic, business-as-usual scenarios to COVID-19 social distancing scenarios were modeled using an agent-based modeling framework coupled with a virtual WDS network, but further research is needed to explore how changes to hybrid work generate changes in demands and water quality. Water quality changes caused by the transition from pandemic to post-pandemic regimes have not been quantified, and this research develops a tool to test and compare water quality, equitable access to clean water, and the cost of water in pre-pandemic, pandemic, and post-pandemic scenarios. An agent-based model (ABM) is developed to simulate the movement of individual agents to and from home, work, and leisure locations. The cost of buying water is calculated using the demand specified in the hydraulic network. Equity is assessed using the cost of water as a percentage of income for households in the lower 20% of incomes. In this work, an ABM is applied to a hydraulic system synthesized for Clinton, North Carolina. The hydraulic model is created using street maps to place pipes and nodes, well locations to place water sources, and census data to determine the demand required. Household incomes are distributed to represent Clinton, North Carolina, using census data. The ABM is applied for three scenarios, pre-pandemic, pandemic, and post-pandemic, and results demonstrate changes in water quality that lead to economic inequities. The modeling framework that is developed in this research can be applied to assess equity impacts of water quality changes such as those associated with pandemic scenarios.

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Publication Details

Published
2025-05-15
DOI
https://doi.org/10.1061/9780784486184.056
Citations
1
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
1.11
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article

Equitable Access to Affordable and Clean Water in Pre-Pandemic, Pandemic, and Post-Pandemic Modes of Work

Shimon Komarovsky, Emily Zechman Berglund, Brent Vizanko, Avi Ostfeld et al.
1 citations
Impact of Light on Environment and Health
1.11
article

Equitable Access to Affordable and Clean Water in Pre-Pandemic, Pandemic, and Post-Pandemic Modes of Work

Shimon Komarovsky, Emily Zechman Berglund, Brent Vizanko, Avi Ostfeld, Elias Zauscher
article en
1 citations

Abstract

The distribution of clean water through public systems can be inequitable, as variations in water quality are common drivers for negative health outcomes and can lead households to spend more on water treatment or alternative sources of water, such as bottled water. The COVID-19 pandemic caused complex, location dependent changes to demands due to social distancing that led to changes in water quality. The first wave of social distancing was characterized by wide-spread adoption of work-from-home practices and social distancing, causing water demands to shift from places of employment and recreation to residences. Subsequent changes have ushered in a new post-pandemic regime that is characterized by a hybrid work force. The hybrid work force includes many individuals who have adopted a personal schedule of working from home and working from the office that increases the uncertainty in modeling daily population movement changes and demands. The changes in water quality that followed the change from pre-pandemic, business-as-usual scenarios to COVID-19 social distancing scenarios were modeled using an agent-based modeling framework coupled with a virtual WDS network, but further research is needed to explore how changes to hybrid work generate changes in demands and water quality. Water quality changes caused by the transition from pandemic to post-pandemic regimes have not been quantified, and this research develops a tool to test and compare water quality, equitable access to clean water, and the cost of water in pre-pandemic, pandemic, and post-pandemic scenarios. An agent-based model (ABM) is developed to simulate the movement of individual agents to and from home, work, and leisure locations. The cost of buying water is calculated using the demand specified in the hydraulic network. Equity is assessed using the cost of water as a percentage of income for households in the lower 20% of incomes. In this work, an ABM is applied to a hydraulic system synthesized for Clinton, North Carolina. The hydraulic model is created using street maps to place pipes and nodes, well locations to place water sources, and census data to determine the demand required. Household incomes are distributed to represent Clinton, North Carolina, using census data. The ABM is applied for three scenarios, pre-pandemic, pandemic, and post-pandemic, and results demonstrate changes in water quality that lead to economic inequities. The modeling framework that is developed in this research can be applied to assess equity impacts of water quality changes such as those associated with pandemic scenarios.

North Carolina State University (US), Technion – Israel Institute of Technology (IL)
Openalex Percentile: Top 24%
Impact of Light on Environment and Health
1.11
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