R code and data to conduct the analysis of human fecal contamination in produce irrigation ponds using predictive models that is reported in:
Hofstetter J, Holcomb DA, Kahler AM, Rodrigues C, da Silva ALBR, Mattioli MC. (2024). Performance of conditional random forest and regression models at predicting human fecal contamination of produce irrigation ponds in the southeastern United States. ACS ES&T Water. https://doi.org/10.1021/acsestwater.4c00839.
Org: Division of Foodborne, Waterborne, and Environmental Diseases
Version: 4.1
Status: Maintained
Keywords: microbial source tracking, quantitative polymerase chain reaction (qPCR), dead-end ultrafiltration (DEUF), predictive modeling, conditional random forest, agricultural water, fresh produce safety, foodborne illness
Contact Email: ncezid_shareit@cdc.gov