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Predicting the impact of urban flooding using open data.

ABSTRACT: This paper aims to explore whether there is a relationship between search patterns for flood risk information on the Web and how badly localities have been affected by flood events. We hypothesize that localities where people stay more actively informed about potential flooding experience less negative impact than localities where people make less effort to be informed. Being informed, of course, does not hold the waters back; however, it may stimulate (or serve as an indicator of) such resilient behaviours as timely use of sandbags, relocation of possessions from basements to upper floors and/or temporary evacuation from flooded homes to alternative accommodation. We make use of open data to test this relationship empirically. Our results demonstrate that although aggregated Web search reflects average rainfall patterns, its eigenvectors predominantly consist of locations with similar flood impacts during 2014-2015. These results are also consistent with statistically significant correlations of Web search eigenvectors with flood warning and incident reporting datasets.

SUBMITTER: Tkachenko N

PROVIDER: S-EPMC4892441 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Predicting the impact of urban flooding using open data.

Tkachenko Nataliya N Procter Rob R Jarvis Stephen S

Royal Society open science 20160525 5

This paper aims to explore whether there is a relationship between search patterns for flood risk information on the Web and how badly localities have been affected by flood events. We hypothesize that localities where people stay more actively informed about potential flooding experience less negative impact than localities where people make less effort to be informed. Being informed, of course, does not hold the waters back; however, it may stimulate (or serve as an indicator of) such resilien ...[more]

PMID: 27293779

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Project description:BackgroundOpen drains are common methods of transporting solid waste and excreta in low-income urban neighborhoods. Open drains can overflow due to blockages with solid waste and during rainfall, posing exposure risks. The goal of this study was to evaluate whether pediatric enteric infection was associated with open drains and flooding in a dense, low-income, urban neighborhood.MethodsAs part of the MAL-ED study in Vellore, India, a cohort of 230 children provided stool specimens at 14-17 scheduled home visits and during diarrheal episodes in the first two years of life. All specimens were analyzed for enteric pathogens. Caregivers in 100 households reported on flooding of drains and households and monthly frequency of contact with open drains and flood water. Household GPS points were collected. Monthly rainfall totals for the Vellore district were collected from the Indian Meteorological Department. Clustering of reported drain and house flooding were identified by Kulldorff's Bernoulli Spatial Scan. Differences in enteric infection were assessed for household responses and spatial clusters, with interactions between reported flooding and rainfall to approximate monthly drain flooding retrospectively, using multivariable, mixed-effects logistic regression models.ResultsCoverage of household toilets was low (33%), and most toilets (82%) discharged directly into open drains, suggesting poor neighborhood fecal sludge management. Odds of enteric infection increased significantly with total monthly rainfall for children who lived in households that reported that the nearby drain flooded (4% increase per cm of rain: OR: 1.04, 95% CI: 1.00-1.08) and for children in households in a downstream spatial cluster of reported drain flooding (5% increase per cm of rain: OR: 1.05, 95% CI: 1.01-1.09). There was no association between odds of enteric infection and frequency of reported contact with drain or floodwater.ConclusionsChildren in areas susceptible to open drain flooding had increased odds of enteric infection as rainfall increased. Results suggested that infection increased with rainfall due to neighborhood infrastructure (including poor fecal sludge management) and not frequency of contact. Thus, these exposures may not be mitigated by changes in personal behaviors alone. These results underscore the importance of improving the neighborhood environment to improve children's health in low-income, urban settings.

Dataset Information

Predicting the impact of urban flooding using open data.

Publications

Predicting the impact of urban flooding using open data.

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