DISCLAIMER: The tools, as they currently stand, are provided for research and informational purposes only. The underlying models, assumptions, data sources, and methodologies are experimental and might have not yet been peer-reviewed or independently validated. Outputs may be incomplete, uncertain, or inaccurate and should be interpreted with caution. The tools do not provide regulatory, medical, legal, toxicological, or professional risk assessment advice. For the time being, it must not be used as a substitute for expert judgment, regulatory review, or established risk-assessment frameworks, nor relied upon for decision-making related to human health, environmental protection, occupational safety, product registration, compliance, or policy.
Use of these tools for unlawful, harmful, misleading, or unethical purposes—including but not limited to regulatory circumvention, misrepresentation of risk, or inappropriate application to real-world pesticide use decisions—is strictly prohibited. The tool is provided “as is,” without warranties of any kind, express or implied, including but not limited to accuracy, fitness for a particular purpose, or non-infringement.

Additional information and tools

GitHub for SPRINT HIA:

https://github.com/ArashDer/SPRINT-HIA/

Shiny app for calculation of attributable fraction and cases:

To facilitate simulation of HIA in different scenarios of exposure levels, exposure-response-function, we have made a simple Shiny app. In this app, the user can enter the desired exposure level in the biological sample, the ERF with the option to provide the 95%CI, as well as extra options to provide the baseline prevalence of the outcome (and total population). The app will return the calculated attributable fraction as well as attributable cases, with a graphical representation of the changes of AF and prevalence with the increase in exposure.

Go to app: Shiny HIA

https://aderakhshan.shinyapps.io/SPRINT-HIA4/

Monte Carlo simulation Shiny App

https://aderakhshan.shinyapps.io/Monte_Carlo_Simulation/

This is a Monte Carlo simulation tool to estimate potential health effects from exposure to multiple pesticides. It lets the user define exposure distributions and dose–response slopes for three pesticides, combine them under different interaction assumptions (additive, synergistic, antagonistic), and then calculate population‑level health impacts.

How it works:

  1. Inputs (sidebar):
    • Number of simulations (e.g. 10,000).
    • Exposure parameters for pesticide 1– pesticide 3 (lognormal mean & SD).
    • Dose–response slope ranges (95% CI).
    • Interaction type (additive, synergistic, antagonistic) with multiplier.
    • Population size and disease prevalence.
  2. Simulation (server):
    • For each pesticide:
      • Draw exposures from a lognormal distribution.
      • Draw slopes from a normal distribution based on CI.
      • Multiply exposure × slope → effect distribution.
    • Combine pesticides effects:
      • Additive = sum of effects.
      • Synergistic = sum × multiplier (>1).
      • Antagonistic = sum × multiplier (<1).
    • Interpret combined effect as Relative Risk (RR).
    • Compute Attributable Fraction (AF) = (RR-1)/RR.
    • Compute Attributable Cases (AC) = AF × (population × prevalence).
  3. Outputs (main panel):
  • Histogram: distribution of simulated health effects.
  • CDF plot: cumulative distribution of health effects.
  • Summary stats: mean and 95% CI for AF and AC, plus descriptive stats of effects.

This app lets you explore how uncertain exposures and dose–response relationships for multiple pesticides translate into population‑level health risks. It shows both the distribution of possible outcomes and summary measures like attributable fraction and cases.

Further information on the methods and interpretation of the results are provided in the README section of the app.