This project aims to understand the mechanisms of pesticide drift exposure among agricultural workers and prevent such exposures in the future. To accomplish this, we will work with Washington State Department of Health and Washington State University AgWeatherNet to determine the probability of drift events due to environmental conditions during spraying, develop a predictive model, and conduct field studies to validate our model. Study findings will be used to provide new user-friendly tools and trainings to predict drift event-prone weather conditions.
First, we will determine the probability of drift events due to environmental conditions during spraying by 1a. Estimating drift-related weather conditions at the time and location of all documented drift events in Washington State between 2000 and 2015; 1b. Conducting a case-crossover study of weather conditions on drift event days vs. non-drift event days to build a ‘drift determinants’ model.
Second, we will conduct validation studies of our Drift Determinants model: 2a. Comparing field meteorological measurements to AgWeatherNet-based estimates at representative sites in the Yakima Valley; 2b. Testing the validity of model predictions through field sampling for pesticide drift under variable weather conditions.
Third, we will translate study findings into exposure prevention tools for agricultural producers and workers by providing new training modules for regional “Drift Management Best Practices” courses, creating a user-friendly method for epidemiologic investigators to integrate weather conditions into drift event documentation, and developing a system to alert pesticide applicators about drift event-prone weather conditions. This work will result in the novel integration of environmental and health data systems and holds the potential to demonstrably reduce occupational illness due to pesticide drift.
Aim 1. Determine the probability of drift events due to environmental conditions during spraying.
Aim 2. Conduct validation studies of our Drift Determinants model.
Aim 3. Translate findings into exposure prevention tools for agricultural producers and workers.
Partners and Advisories
Washington State Department of Health
Washington State University, AgWeatherNet Program
Prado J. B., Mulay P. R., Kasner E. J., Bojes H. K., Calvert G. M. Acute Pesticide-Related Illness Among Farmworkers: Barriers to Reporting to Public Health Authorities. J of Agromedicine. 2017;22(4) 395-405. doi: 10.1080/1059924X.2017.1353936. Review. PubMed PMID: 28762882; PubMed Central PMCID: PMC5846675.
Kasner E. J. On Preventing Farmworker Exposure to Pesticide Drift in Washington Orchards. 2017 PhD Dissertation. Department of Environmental and Occupational Health Sciences, University of Washington.
Kasner E. J., Fenske R. A, Galvin K., Yost M., Palmández P. Review of Agricultural Spray Notification Systems. 2016 Technical Report. Pacific Northwest Agricultural Safety and Health Center, University of Washington.