Spatial Video and EpiExplorer: A Field Strategy to Contextualize Enteric Disease Risk in Slum Environments

Jayakrishnan Ajayakumar, Andrew J. Curtis, Vanessa Rouzier, Jean William Pape, Sandra Bempah, Meer Taifur Alam, Md. Mahbubul Alam, Mohammed H. Rashid, Afsar Ali and John Glenn Morris
Additional contact information
Jayakrishnan Ajayakumar: Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
Andrew J. Curtis: Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
Vanessa Rouzier: Les Centres Haitian Group for the Study of Kaposi’s Sarcoma and Opportunistic Infections (GHESKIO), Port-au-Prince HT6110, Haiti
Jean William Pape: Les Centres Haitian Group for the Study of Kaposi’s Sarcoma and Opportunistic Infections (GHESKIO), Port-au-Prince HT6110, Haiti
Sandra Bempah: Department of Geography, Kent State University, Kent, OH 44240, USA
Meer Taifur Alam: Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
Md. Mahbubul Alam: Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
Mohammed H. Rashid: Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
Afsar Ali: Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA
John Glenn Morris: Emerging Pathogens Institute, University of Florida, Gainesville, FL 32601, USA

IJERPH, 2022, vol. 19, issue 15, 1-18

Abstract: 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.

Keywords: spatial video; exploratory analysis; geospatial context; mobile methodologies (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/19/15/8902/pdf (application/pdf)
https://www.mdpi.com/1660-4601/19/15/8902/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:19:y:2022:i:15:p:8902-:d:868955

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().