Water quality laboratories in Colombia: a GIS-based study of urban and rural accessibility

July 2, 2014 · 0 comments

Water quality laboratories in Colombia: a GIS-based study of urban and rural accessibility. Sci Total Environ. 2014 Jul

Wright J1, Liu J2, Bain R3, Perez A4, Crocker J5, Bartram J6, Gundry S7.
Author information
1Geography and Environment, University of Southampton, Highfield, Southampton SO17 1BJ, UK. Electronic address: j.a.wright@soton.ac.uk.
2Geography and Environment, University of Southampton, Highfield, Southampton SO17 1BJ, UK. Electronic address: jenny19880813@gmail.com.
3The Water Institute at UNC, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 170 Rosenau Hall CB #7400, 135 Dauer Drive, Chapel Hill, NC 27599-7400, USA. Electronic address: rbain@email.unc.edu.
4Facultad de Ciencias e Ingeniería, Universidad de Boyacá, Campus Universitario Cra 2a este #64-169 Tunja, Boyacá, Colombia. Electronic address: aperezv@uniboyaca.edu.co.
5The Water Institute at UNC, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 170 Rosenau Hall CB #7400, 135 Dauer Drive, Chapel Hill, NC 27599-7400, USA. Electronic address: crockerj@live.unc.edu.
6The Water Institute at UNC, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 170 Rosenau Hall CB #7400, 135 Dauer Drive, Chapel Hill, NC 27599-7400, USA. Electronic address: jbartram@email.unc.edu.
7Water & Health Research Centre, Department of Civil Engineering, Queens Building, University Walk, Bristol BS8 1TR, UK. Electronic address: stephen.gundry@bristol.ac.uk.

The objective of this study was to quantify sample transportation times associated with mandated microbiological monitoring of drinking-water in Colombia. World Health Organization Guidelines for Drinking-Water Quality recommend that samples spend no more than 6h between collection and analysis in a laboratory. Census data were used to estimate the minimum number of operational and surveillance samples required from piped water supplies under national regulations. Drive-times were then computed from each supply system to the nearest accredited laboratory and translated into sample holding times based on likely daily monitoring patterns.

Of 62,502 surveillance samples required annually, 5694 (9.1%) were found to be more than 6 h from the nearest of 278 accredited laboratories. 612 samples (1.0%) were more than 24 hours’ drive from the nearest accredited laboratory, the maximum sample holding time recommended by the World Health Organization. An estimated 30% of required rural samples would have to be stored for more than 6 h before reaching a laboratory. The analysis demonstrates the difficulty of undertaking microbiological monitoring in rural areas and small towns from a fixed laboratory network. Our GIS-based approach could be adapted to optimise monitoring strategies and support planning of testing and transportation infra-structure development. It could also be used to estimate sample transport and holding times in other countries.

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