Spatial Modeling of Personalized Exposure Dynamics: The Case of Pesticide Use in Small-Scale Agricultural Production Landscapes of the Developing World

Abstract

Background: Pesticide poisoning is a global health issue with the largest impacts in the developing countries where residential and small-scale agricultural areas are often integrated and pesticides sprayed manually. To reduce health risks from pesticide exposure approaches for personalized exposure assessment (PEA) are needed. We present a conceptual framework to develop a spatial individual-based model (IBM) prototype for assessing potential exposure of farm-workers conducting small-scale agricultural production, which accounts for a considerable portion of global food crop production. Our approach accounts for dynamics in the contaminant distributions in the environment, as well as patterns of movement and activities performed on an individual level under different safety scenarios. We demonstrate a first prototype using data from a study area in a rural part of Colombia, South America.Results: Different safety scenarios of PEA were run by including weighting schemes for activities performed under different safety conditions. We examined the sensitivity of individual exposure estimates to varying patterns of pesticide application and varying individual patterns of movement. This resulted in a considerable variation in estimates of magnitude, frequency and duration of exposure over the model runs for each individual as well as between individuals. These findings indicate the influence of patterns of pesticide application, individual spatial patterns of movement as well as safety conditions on personalized exposure in the agricultural production landscape that is the focus of our research. Conclusion:This approach represents a conceptual framework for developing individual based models to carry out PEA in small-scale agricultural settings in the developing world based on individual patterns of movement, safety conditions, and dynamic contaminant distributions.The results of our analysis indicate our prototype model is sufficiently sensitive to differentiate and quantify the influence of individual patterns of movement and decision-based pesticide management activities on potential exposure. This approach represents a framework for further understanding the contribution of agricultural pesticide use to exposure in the small-scale agricultural production landscape of many developing countries, and could be useful to evaluate public health intervention strategies to reduce risks to farm-workers and their families. Further research is needed to fully develop an operational version of the model.

An Overview of Agrochemicals and Their Effects on Environment in Nepal

“…Agricultural safety and the resulting environmental and health problems from pesticide application are increasingly attracting global attention [18,21,42]. However, a large input of pesticides leads to excessive residues that adversely affect the quality of agricultural goods [52].…”

“…Pesticide residues affect human health. In fact, pesticide application has become a great threat to human health [12,25,42,54]. Studies have shown that long-term lowdose exposure to pesticides leads to the development of respiratory diseases such as asthma [30].…”

An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas

“…These approaches were often seen in mobility-related exposure studies using empirical or experimental traffic data for specific individuals [43,50]. Leyk, et al (2009), presenting a spatial individual-based model prototype for assessing potential pesticide exposure of farm-workers with their individual level track of movement and activities. Similarly, more complex modeling tools were developed for quantification of human exposure to traffic-related air pollution within distinct micro-environments by using GPS trajectory analysis of the individuals in the city area [10,24].…”

“…Figure 1 illustrates the ABM used in this paper. [45] In this framework, spatial data of the changing concentration patterns of the environmental stress factors are the key pre-set inputs that build up the natural aspects of the system (center layer in Figure 1). A specific map will be used to represent the city with buildings, streets, shops, green areas, etc.…”

Spatial Dimensions of the Risks of Rodenticide Use to Non-target Small Mammals and Applications in Spatially Explicit Risk Modeling

“…These movements may correspond to different needs including foraging for food, searching for sexual partner, colonization of new habitats or juvenile dispersal. The spatial activity pattern of an individual is often considered as one of the drivers of its exposure to chemicals because it determines partly both the frequency and intensity of contact with the pollutant and thus the quantity that can be transferred into a receptor (Leyk et al 2009;Loos 2011;Spurgeon et al 2011). According to Loos (2011), the spatial variation in habitat quality (including food availability), the habitat patch connectivity, population density and foraging behavior govern the home range of an animal, the time it spends per unit area within its home range and also its diet in terrestrial ecosystems.…”