Part I: Estimating and Simulating Dynamic Health Risks.- Chapter 1: Scientific Method for Health Risk Analysis: The Example of Fine Particulate Matter Air Pollution and COVID-19 Mortality Risk.- Chapter 2: Modeling Nonlinear Dose-Response Functions: Regression, Simulation, and Causal Bayesian Networks.- Chapter 3: Simulating Exposure-Related Health Effects: Basic Ideas.- Chapter 4: Case Study: Occupational Health Risks from Crystalline Silica.- Chapter 5: Case Study: Health Risks from Asbestos Exposures.- Chapter 6: Nonlinear Dose-Time-Response Risk Models for Protecting Worker Health.- Part 2: Statistics, Causality, and Machine Learning for Health Risk Assessment.- Chapter 7: Why Not Replace Quantitative Risk Assessment Models with Regression Models.- Chapter 8: Causal vs. Spurious Spatial Exposure-Response Associations in Health Risk Analysis.- Chapter 9: Methods of Causal Analysis for Health Risk Assessment.- Chapter 10: Clarifying Exposure-Response Regression Coefficients with Bayesian Networks: Blood Lead-Mortality Associations an Example.- Chapter 11: Case Study: Does Molybdenum Decrease Testosterone.- Chapter 12: Case Study: Are Low Concentrations of Benzene Disproportionately Dangerous.- Part III: Public Health Effects Of Fine Particulate Matter Air Pollution.- Chapter 13: Socioeconomic Correlates of Air Pollution and Heart Disease.- Chapter 14: How Realistic are Estimates of Health Benefits from Air Pollution Control.- Chapter 15: Do Causal Exposure Concentration-Response Relations.- Chapter 16: How Do Exposure Estimation Errors Affect Estimated Exposure-Response Relations.- Chapter 17: Have Decreases in Air Pollution Reduced Mortality Risks in the United States.- Chapter 18: Improving Causal Determination.- Chapter 19: Communicating More Clearly about Deaths Caused by Air Pollution.