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Subsewershed SARS-CoV-2 Wastewater Surveillance & COVID-19 Epidemiology Using Building-specific Occupancy & Case Data

Abstract/Summary: To evaluate the use of wastewater-based surveillance and epidemiology to monitor and predict SARS-CoV-2 virus trends, over the 2020–2021 academic year we collected wastewater samples twice weekly from 17 manholes across Virginia Tech’s main campus. We used data from external door swipe card readers and student isolation/quarantine status to estimate building-specific occupancy and COVID-19 case counts at a daily resolution. After analyzing 673 wastewater samples using reverse transcription quantitative polymerase chain reaction (RT-qPCR), we reanalyzed 329 samples from isolation and nonisolation dormitories and the campus sewage outflow using reverse transcription digital droplet polymerase chain reaction (RT-ddPCR). Population-adjusted viral copy means from isolation dormitory wastewater were 48% and 66% higher than unadjusted viral copy means for N and E genes (1846/100 mL to 2733/100 mL/100 people and 2312/100 mL to 3828/100 mL/100 people, respectively; n = 46). Prespecified analyses with random-effects Poisson regression and dormitory/cluster-robust standard errors showed that the detection of N and E genes were associated with increases of 85% and 99% in the likelihood of COVID-19 cases 8 days later (incident–rate ratio (IRR) = 1.845, p = 0.013 and IRR = 1.994, p = 0.007, respectively; n = 215), and one-log increases in swipe card normalized viral copies (copies/100 mL/100 people) for N and E were associated with increases of 21% and 27% in the likelihood of observing COVID-19 cases 8 days following sample collection (IRR = 1.206, p < 0.001, n = 211 for N; IRR = 1.265, p < 0.001, n = 211 for E). One-log increases in swipe normalized copies were also associated with 40% and 43% increases in the likelihood of observing COVID-19 cases 5 days after sample collection (IRR = 1.403, p = 0.002, n = 212 for N; IRR = 1.426, p < 0.001, n = 212 for E). Our findings highlight the use of building-specific occupancy data and add to the evidence for the potential of wastewater-based epidemiology to predict COVID-19 trends at subsewershed scales.

Poverty, Water, & Health Indicators in Sub-Saharan Africa

As described below (see other project summaries), the Multidimensional Poverty Assessment Tool (MPAT) was created in two phases (from 2008 to 2014) via a collaborative, international initiative to develop, test, and pilot a new tool for local-level rural poverty assessment. The work was guided by a Sounding Board of experts from the International Fund for Agricultural Development (IFAD), other United Nations agencies, international and regional organizations, and universities around the world (see www.ifad.org/mpat).

Following MPAT’s finalization and institutionalization in 2014, it was used in multiple countries including many in Sub-Saharan Africa. We are currently working on multiple research studies with a variety of collaborators to analyze data from ~7,000 households across Eswatini, Kenya, Lesotho, Mali, Tanzania, and Zimbabwe. Because MPAT was developed based primarily on data from Bangladesh, China, India, and Mozambique, one study we are leading is an updated assessment and evaluation of MPAT’s indicator structure and robustness based on its use in the sub-Saharan region. Another study we will be leading will focus on a cross-county analysis of MPAT’s water and health focused components and sub-components. In addition, we are assisting other colleagues leading studies focused on climate change and rural poverty with their statistical analyses.

Wastewater Surveillance & Epidemiology at Multiple Scales

Led by VT colleagues in Environmental Engineering (Dr.s Pruden & Vikesland – pictured), the purpose of this study was to develop a coronavirus disease-2019 (COVID-19) surveillance program based on the analysis of wastewater samples collected over the 2020/21 academic year from different buildings and sites on the Virginia Tech (VT) university campus. This type of wastewater-based epidemiology approach has been used by other researchers, as well as wastewater utilities, to monitor SARS-CoV-2 (i.e., the virus that causes COVID-19) load trends and to attempt to estimate future trends. Our primary research objective was to assess whether wastewater samples at the dormitory level could help predict future cases of SARS-CoV-2 infection, via testing the water for viral loads. The overarching goal of our research for this project was to help support the VT administration with their efforts to monitor and control SARS-CoV-2 infections on the VT campus. We pre-specified our statistical analysis plan (uploaded to OSF) and expect to publish our findings by/before early 2022.

Led by colleagues at the Virginia Department of Health (Dr. Degen), UVA (Dr. Taniuchi), Radford University (Dr. Tolliver), and others, we are also assisting the Roanoke Health District with analysis of wastewater sample data collected at sub-sewershed scales in and around the Roanoke City (VA) region.

Refinement & Finalization of the Multidimensional Poverty Assessment Tool (MPAT)

Following the release of the working-paper User’s Guide for the Multidimensional Poverty Assessment Tool (MPAT) in 2009, a number of agencies and universities used the beta-version of MPAT in a variety of settings. In order to finalize MPAT and develop a comprehensive User’s Guide and associated resources, we built on the lessons learned from early adopters of the the tool (e.g., an NGO in Kenya) and iteratively used and evaluated the tool with IFAD-supported projects in Bangladesh and Mozambique. Details on the participatory expert elicitation methods we used are provided in a Journal of Development Studies paper. We developed an Excel-based data entry platform so users could easily calculate MPAT’s indicators at household, village, and project levels. We also wrote a comprehensive, 300+ page, 2014 MPAT User’s Guide which provides step-by-step instructions for using MPAT as well as training modules and materials, all with the goal of making MPAT an accessible open-source tool. The User’s Guide and accompanying resources were presented at a 2014 launch event in Rome. Since its 2014 release, MPAT has been translated into a number of languages, an optional 11th component focused on climate change was added, and MPAT has been used by a variety of agencies and institutions around the world. MPAT publications and related resources are available at www.ifad.org/mpat.

Wastewater & Coastal Environmental Health in the Philippines

This research collaboration between colleagues at the University of California Berkeley (UCB) and the University of the Philippines (UPD) was designed to advance methods for measuring, modelling, and assessing marine water quality and environmental health at three sites in the Philippines. One of the three study sites for this multi-year project is Boracay Island. A popular tourist destination, in recent years sewage and other contaminants have adversely impacted Boracay’s beaches and coastal water quality, with implications for both environmental and human health. This research project centers on the use of an autonomous surface vessel to collect a wide range of spatially referenced data which can be combined with data from water samples and lab-based analyses, as well as satellite and other remote sensed data. At the Boracay site, proxy sensor data (e.g., optical brighteners and tryptophan) and laboratory analyses of grab samples will be combined to map and model actual and estimated water quality and environmental health impacts from point and non-point runoff and wastewater effluent. Our planned research activities and associated timelines suffered from a variety of logistical setbacks and delays, but we are now working under a no-cost extension to complete our primary research objectives for Boracay, as well as the other research sites (Bolinao and Tubbataha).

Developing a Thematic Indicator for Rural Poverty Assessment (MPAT)

The Multidimensional Poverty Assessment Project was a collaborative, international initiative to develop, test, and pilot a new tool for local-level rural poverty assessment. The work was supported by IFAD and guided by a Sounding Board of experts from IFAD, other United Nations agencies, international and regional organizations, and universities around the world, with the majority of its members coming from the Asia region where we developed and tested the tool in China and India. Surveys (household and village level) were developed and tested in an iterative and participatory fashion, as was the indicator structure used to aggregate sub-components and components. The resulting Multidimensional Poverty Assessment Tool (MPAT) provides an assessment, an overview, of ten dimensions central to rural livelihoods, highlighting where additional support or interventions are likely to be most needed. The tool was designed to be universal enough to be relevant to most rural contexts around the world, yet specific enough to provide project managers and others a detailed overview of key dimensions relevant to rural poverty reduction efforts. MPAT was independently evaluated by the European Commission Joint Research Center and a working-paper version of MPAT User’s Guide was released in 2009 as well as the 2009 MPAT Book, which provides a detailed description of why and how the tool was developed. MPAT’s theoretical foundations are described in a 2010 article in Development and Practice.

Implementation of Water Safety Plans in China: 2004-2018

Abstract/Summary:The application of Water Safety Plans (WSPs) in China varies throughout the country. Although pilot WSP projects in China were initiated shortly after WSP was introduced by the World Health Organization (WHO) in 2004, they have yet to be used for water supply facilities at a large scale. To better understand the evolution of WSP application in China, a systematic review was conducted to identify all published WSP related studies in China. Eighteen studies, which included 311 water systems, were included in the final analysis. Risk matrix, water supply risk factors, and other data were extracted and analyzed. Text mining methods were also used to better understand risks that can be addressed by WSPs (both potential and actual risks). This study revealed a number of noteworthy differences between and among urban and rural water systems in China. The primary risks associated with most urban water supply systems tended to be related to mechanical failure/s in the water treatment process. Rural water supply systems appear to suffer from similar problems, but insufficient overall management capacity was more prevalent in rural systems. Overall, the evidence suggests that, to date, the use of WSPs in China has been primarily limited to pilot studies, and full implementation of WSPs in China appears to still be in the early stages. The paper closes with a summary of the key obstacles identified as well as a discussion of policies and technical options which could increase the use of WSPs in both urban and rural China. Among other recommendations, the data indicate that there is strong need for the development and implementation of a simplified WSP approach designed specifically for small rural systems in China.

The Multidimensional Poverty Assessment Tool: Brochure (& Infographics)

Abstract/Summary: The Multidimensional Poverty Assessment Tool (MPAT) provides data that can inform all levels of decision making by providing a clearer understanding of rural poverty at the household and village level. As a result, MPAT can significantly strengthen the planning, design, monitoring and evaluation of a project, and thereby contribute to rural poverty reduction.

This brochure explains:

    • What MPAT is
    • How MPAT works
    • When to use MPAT and why
    • How to use MPAT
    • What resources are available for implementing MPAT

The tool allows project managers, government officials, researchers and others to identify and monitor sectors that require support in order to reduce rural poverty and improve livelihoods. It also provides an objective means of justifying resource allocation or planning priorities. MPAT is based on a bottom-up, participatory approach that reflects communities’ voices, wants and perspectives.

The Multidimensional Poverty Assessment Tool: User’s Guide

Abstract/Summary: The Multidimensional Poverty Assessment Tool (MPAT) provides a method for simplifying the complexity of rural poverty in order to support poverty alleviation efforts. MPAT uses thoroughly designed and tested purpose-built surveys to collect data on people’s perceptions about fundamental and interconnected aspects of their lives, livelihoods and environments. Standardized indicators, developed through a comprehensive participatory process, are then employed to combine, distil and present these data in an accessible way. MPAT was developed through a participatory, collaborative process based on expert feedback from dozens of international development experts from IFAD, other United Nations agencies, international and regional organizations, and universities from around the world. It was field-tested in countries in both Asia and Africa. In the pages that follow, we explain what MPAT is, how it works and how it is used, providing step-by-step instructions, training materials and other resources. The ultimate objective of this User’s Guide and the accompanying Excel Spreadsheet is to make MPAT a truly free and open-source tool, so that any institution or agency, big or small, may implement MPAT on its own.

The Multidimensional Poverty Assessment Tool: Design, development & application of a new framework for measuring rural poverty

Abstract/Summary: The purpose of this book is to describe the theoretical foundations upon which the Multidimensional Poverty Assessment Tool (MPAT) was built, to tell the story of how it was created, developed, tested and piloted in rural China and India, and to explain how MPAT can be used to benefit rural communities around the world. Lasting poverty alleviation is achieved by fostering a comprehensive enabling environment within which people have a sufficiently high level of well-being and are able to pursue their livelihood goals based on their aspirations and initiative. To ensure that such environments are in place requires, at a minimum, an understanding of the key constraints rural people face – the fundamental dimensions central to their lives and livelihoods. MPAT does not try to define rural poverty per se; rather it takes a step back from assessment modalities that are overly focused on economic- and consumption-oriented indicators and strives to provide an overview of fundamental and relatively universal dimensions germane to rural livelihoods, rural life, and thus to rural poverty. By summarizing rural communities’ perceptions about key dimensions of rural poverty and focusing them through a quantitative lens, MPAT transparently illuminates problem areas so that all stakeholders can see where deficiencies lie and can begin to discuss which interventions may be most appropriate to address them, based on the local context.