Spatial Video and EpiExplorer

A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments

Bibliographic Data

ID15513255
AuthorsJayakrishnan Ajayakumar (0000-0001-9564-7728, Case Western Reserve University, corresponding author), Andrew Curtis (0000-0001-6046-6476, Case Western Reserve University), Vanessa Rouzier (0000-0002-9672-9474, Gheskio Centers), Jean W Pape (0000-0002-2948-2774, Gheskio Centers), Jean Pape (Les Centres Haitian Group for the Study of Kaposi’s Sarcoma and Opportunistic Infections (GHESKIO), Port-au-Prince HT6110, Haiti), Sandra Bempah (0000-0002-5374-2951, Kent State University), Meer T Alam (0000-0002-0703-740X, University of Florida), Meer Alam (Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA), Md Khorshed Alam (0000-0002-1227-002X, University of Florida), Md Alam (Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA), Mohammed H Rashid (0000-0001-9189-5126, University of Florida), Mohammed Rashid (0000-0002-3863-3212, Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA), Afsar Ali (0009-0008-5419-1777, University of Florida), J Glenn Morris (0000-0001-9347-1984, University of Florida)
Year2022
Volume19
Issue15
Pages8902-8902
Publication date2022-07-22
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19158902
PMID35897275
OpenAlexW4286586313
LanguageEN
Citations received1
References cited33

Disease risk associated with contaminated water, poor sanitation, and hygiene in informal settlement environments is conceptually well understood. From an analytical perspective, collecting data at a suitably fine scale spatial and temporal granularity is challenging. Novel mobile methodologies, such as spatial video (SV), can complement more traditional epidemiological field work to address this gap. However, this work then poses additional challenges in terms of analytical visualizations that can be used to both understand sub-neighborhood patterns of risk, and even provide an early warning system. In this paper, we use bespoke spatial programming to create a framework for flexible, fine-scale exploratory investigations of simultaneously-collected water quality and environmental surveys in three different informal settlements of Port-au-Prince, Haiti. We dynamically mine these spatio-temporal epidemiological and environmental data to provide insights not easily achievable using more traditional spatial software, such as Geographic Information System (GIS). The results include sub-neighborhood maps of localized risk that vary monthly. Most interestingly, some of these epidemiological variations might have previously been erroneously explained because of proximate environmental factors and/or meteorological conditions

Bespoke · Business · Cartography · Data science · Environmental health · Environmental planning · Environmental resource management · Geographic information system · Geography · Human settlement · Remote sensing · Sanitation · Scale (ratio · Slum · Spatial analysis · Spatial epidemiology · Water quality · Waterborne diseases · Work (physics · Computer Science · Data-Driven Disease Surveillance · Engineering · Environmental Science · Flood Risk Assessment and Management · Human Mobility and Location-Based Analysis · Ecology · Epidemiology

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