Modeling-based Framework for Analysis of Toxin Pathways through Water to
Address Some Aspects of Chronic Kidney Diseases with Unknown Etiology
(CKDu) in Sri Lanka
Abstract
Since first diagnosed in the early 1990s, chronic kidney disease of
unknown etiology (CKDu) has markedly increased in the North Central
Province in the dry zone of Sri Lanka. CKDu has been identified as a
global health issue in more than a dozen countries in Asia, South
America, and the Middle East. It has been reported that out of these
countries, Sri Lanka is the most affected, with the highest cases of
CKDu patients and mortality rates. In Sri Lanka, the disease primarily
affects male paddy (rice) farmers from low socioeconomic levels. A major
river diversion scheme completed in the 70s feeds water from wet zones
to ancient tanks that rely on rainwater only. The drinking water for the
CKDu affected farming communities comes from the irrigation canals,
shallow regolith water table aquifers recharged by canal seepage and
precipitation, and deep-bored wells. Many contributing factors and
hypotheses have been presented and discussed in the literature. Out of
these multiple factors, the suspected environmental exposure pathways
are through water (potable water and food) and air (unprotected
pesticide spraying). Extensive data on water quality have been collected
to develop, test, and support hypotheses on the role of water on the
disease. However, no systematic investigations have been conducted to
identify, study and analyze how pathways develop through the water
storage and distribution systems from sources to the receptors where
human exposure occurs. This study proposes a systems-based framework to
conduct such analysis using numerical models of the intergraded surface
and subsurface system. The models will simulate the fate and transport
of naturally occurring toxins and agrichemicals and their
geo-bio-chemicals transformation products. These models should
incorporate characterization parameters of the surface water storage and
distribution system and hydrogeologic data for shallow and deep
aquifers, water quality data, epidemiological data, and climate drivers.
Innovations methods to use the downscaled climate and regional
hydrological model simulations to evaluate exposure pathways at local
scales (e.g., villages) under different climate scenarios.