Anàlisi de dades de potabilització d’aigua per estimar el risc microbiològic de l’aigua potable
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Outbreaks of waterborne diseases still are a public health problem in the 21st century,
especially on developing countries, but also in developed countries.
Drinking Water Treatment Plants (DWTP) are in charge of guaranteeing that tap water
has a good quality (in terms of both microbiological and physicochemical aspects), so
that, among other things, they minimize the risk of suffering an infectious disease.
Nevertheless, perturbations during the treatment process, extreme meteorological
conditions or tap water pollution during its distribution can trigger microbiological risk
and can provoke epidemic outbreaks.
To quantify microbiological risk QMRA (Quantitative Microbiological Risk Assessment)
methodology can be applied. QMRA is a four steps methodology that explores several
aspects as: type of pathogenic microorganisms, inlet water characteristics, treatment
operation, epidemiological data, etc.
In the present report microbiological risk of tap water treated by DWTP Ter is analyzed
according to the QMRA methodology.
First of all, a classification algorithm has been developed to estimate the microbiological
concentration on the DWTP inlet by using different environmental conditions daily
monitored. The algorithm has been developed using big volumes of data (daily data from
historical series of 20 years), and for this reason it was necessary to use Data Mining
tools.
Finally, estimated microbiological concentrations have been used to calculate one of the
most common metrics used for quantifying microbiological risk: DALY (Disability
Adjusted Life Years). This metric has been calculated following the WHO’s and
Microrisk’s manuals directrices. DALY has allowed to quantify the risk in a range of
values and has allowed to visualize under which conditions a dangerous situation could
arise.
Microbiological risk calculus for tap water treated in DWTP Ter has been resulted to be
low in most of the cases, but some scenarios where the risk would overcome the WHO’s
limit have been detected. Special focus should be paid on these scenarios, where water
treatment should be more accurate
This document is licensed under a Creative Commons:Attribution - Non commercial - No Derivate Works (by-nc-nd)

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