Haas | Environmental Engineering for Pathogen Control | Buch | 978-1-394-25338-8 | www.sack.de

Buch, Englisch, 576 Seiten

Haas

Environmental Engineering for Pathogen Control


1. Auflage 2026
ISBN: 978-1-394-25338-8
Verlag: John Wiley & Sons Inc

Buch, Englisch, 576 Seiten

ISBN: 978-1-394-25338-8
Verlag: John Wiley & Sons Inc


Control pathogen exposure through unified environmental engineering interventions

Environmental engineers and public health professionals require systematic approaches to pathogen control across air, water, dust, and soil. Environmental Engineering for Pathogen Control delivers a unified framework for mitigating infectious diseases through environmental interventions. Written by Charles N. Haas, a National Academy of Engineering member and distinguished fellow of the International Water Association, this book grounds the emerging intersection of environmental engineering and public health.

The text covers dispersion and transmission of environmental pathogens, disinfection interventions, drinking water contamination, aerosol transmission of disease, and bioterrorist attack response. Detailed coverage addresses air transmission and movement in indoor environments, viability and growth-decay dynamics of microbes in environmental media, and quantitative microbial risk assessment methodologies. Case studies demonstrate practical risk assessment applications across diverse contamination scenarios.

Readers will also find: - Systematic methods for analyzing pathogen dispersion across environmental media including air, water, dust, and soil transmission pathways
- Quantitative frameworks for assessing microbial viability, growth rates, and decay patterns in diverse environmental conditions and media
- Engineering approaches to disinfection interventions with detailed coverage of drinking water treatment and contamination response protocols
- Indoor air quality analysis techniques addressing aerosol transmission mechanics and ventilation strategies for pathogen control measures
- Risk assessment case studies with step-by-step guidance for evaluating exposure scenarios and determining appropriate intervention strategies

Environmental Engineering for Pathogen Control serves advanced environmental engineering students, public health professionals, and practitioners in environmental health and industrial hygiene. This authoritative resource equips readers with the quantitative tools and engineering frameworks needed to reduce human exposure to pathogens and control associated health risks.

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Contents i

List of Figures ix

List of Tables xiv

1 Introduction 1

1.1 Scope of Coverage 2

1.2 Instructor Notes 3

1.3 Bibliography 3

I Environmental Engineering and Pathogen Basics 5

2 Who, How, Where 7

2.1 Pathogens of Concern 8

2.1.1 Sub-Viral Agents 9

2.1.2 Viruses 9

2.1.3 Bacteria 14

Classification by Metabolic Strategy 15

Other Important Characteristics 18

Formal Taxonomy and Classification 19

2.1.4 Protozoa 22

2.1.5 Fungi 26

Zoosporic Fungi 28

Zygomycetous Fungi 28

Dikarya 29

2.1.6 Other Agents of Concern 30

2.2 Portals of Entry 30

2.3 Venues of Concern 32

2.3.1 Indoor Environments 32

2.3.2 Outdoor Environments 34

2.3.3 In Vehicles 35

2.4 Discussion Questions and Problems 35

2.5 Bibliography 35

3 Key Paradigms of Environmental Engineering 45

3.1 Risk Framework 45

3.1.1 Problem Definition 48

3.1.2 Risk Assessment 48

Hazard Characterization 48

Dose Response Assessment 49

Exposure Assessment 49

Risk Characterization 50

3.1.3 Risk Management 51

3.1.4 Risk Communication 53

3.2 Source, Fate, Transport, Receptor 54

3.3 Uncertainty & Variability 57

3.4 Discussion Questions and Problems 60

3.5 Bibliography 60

4 Unique Features of Pathogens 63

4.1 Stochastic Variability and Low concentrations 63

4.2 Growth as well as Decay 66

4.3 Humans as Sources and Receptors 69

4.4 Dose Response 71

4.5 Contagiousness and Population Spread 72

4.6 Key Takeaways 73

4.7 Discussion Questions and Problems 73

4.8 Bibliography 74

5 Pathogen Sampling 77

5.1 Workflow 77

5.2 Taking the Sample 79

5.2.1 Wastewater 79

5.2.2 DrinkingWater, Other Liquids 85

Backflow and Cross Connections 88

Groundwater 89

Rainwater Collection 90

Premise (Building) Plumbing 91

5.2.3 RecreationalWaters 93

5.2.4 Air 94

Ambient Air Sampling 94

Passive Air Samplers 99

5.2.5 Dusts, Surfaces, Fomites 100

5.2.6 Solids and Semisolids 102

5.3 Decontamination and Biosafety 103

5.4 Isolation, Concentration, and Separation 105

5.5 Discussion Questions and Problems 107

5.6 Bibliography 108

6 How Pathogens Are Quantified 117

6.1 Selection of Targets 117

6.1.1 Indicator Organisms 117

6.1.2 Microbial Source Tracking 119

6.1.3 Direct Measurement of Pathogens. 120

6.2 Count, Quantal, and Time to Response Methods 120

6.2.1 Count Methods 120

Statistics of Count Methods 122

6.2.2 Quantal Methods 136

Statistics of Quantal Methods 138

6.2.3 Time to Response Methods 141

6.3 Direct Microscopy 142

6.3.1 Optical Microscopy 142

Quantification by Optical Microscopy 147

6.3.2 Electron Microscopy 148

6.4 Flow Cytometry 151

6.5 Culture Methods 154

6.5.1 Pre-enrichment or Pre-selection 154

6.5.2 Culture Media Types, Selection, Incubation 154

6.5.3 Whole Organism, Organ or Cell Culture 155

6.6 Molecular Methods 158

6.6.1 Microbial Nucleic Acids 158

Molecules of Interest 158

Extraction, Separation and Concentration of Nucleic Acids 160

6.6.2 Polymerase Chain Reaction Based Methods 160

6.6.3 Sequencing Approaches 165

Amplicon Based Sequencing 166

Shotgun sequencing methods 168

6.6.4 Use for Quantitative Exposure Estimation 171

Relationship to Viability and Infectiousness 171

6.7 Implications for Exposure 173

6.8 Discussion Questions and Problems 173

6.9 Bibliography 175

II Quantifying Exposure 189

7 Sources of Pathogens 191

7.1 Generic Approach 191

7.2 Human Excreta 192

7.3 Exhalation 195

7.4 Other Bodily Discharges 198

7.5 Skin Associated Pathogens 200

7.6 Our biological cohabitants 202

7.6.1 Plants 202

7.6.2 Pets 203

7.6.3 Agricultural Animals 205

7.6.4 Wild Animals 207

7.7 Waste Management Practices 210

7.7.1 Sanitary Landfills 210

7.7.2 Biosolids Application to Land 211

7.7.3 Wastewater Treatment 213

7.8 Other Sources via Aerosolization of Water. 216

7.9 Discussion Questions and Problems 216

7.10 Bibliography 217

8 Transport, Growth and Decay in the Environment 231

8.1 Chapter Overview 231

8.2 Taxonomy of Models. 232

8.2.1 Batch and Simple Flow Systems 234

8.2.2 Modeling Approaches for Complex Flow Systems 242

8.3 Quantitative description of Transport 243

8.3.1 Box Models 243

8.3.2 Box Models with Particle Tracking 246

8.3.3 Advection Reaction Processes -Eulerian-Eulerian Approach 250

Brief Outline of Fluid Flow Modeling 250

Contaminants in a Flowing System 252

8.3.4 A Priori Estimation of Dispersion 257

8.3.5 Advection Reaction Processes - Eulerian-Lagrangian Approach 261

8.4 Quantitative Description of Rate Processes 264

8.4.1 Physical 264

Processes Unique to Air 265

Generally Applicable Processes 267

8.4.2 Decay 271

Reaction Rate Approach 274

Hazard Rate Approach 276

Phenomenological and Empirical Models 278

Fitting Decay Rate Models to Data 279

Modulators of Decay Rates and Data Sources 287

8.4.3 Growth 292

8.4.4 Stochastic Treatment of Growth and Decay 299

8.4.5 Predator-Prey and Other Biotic Interactions 301

8.5 Quantitative Description of Other Flux Processes 305

8.5.1 External Fields 305

Gravitational Force 305

Electrical Force 309

Magnetic Force 312

8.5.2 Interphase Transfer Processes 313

Indoor Environments 313

Outdoor Land Air Exchange 314

Water Sediment Exchange 315

Liquid Air Exchange 315

8.6 Longer range and more complex models 317

8.6.1 Atmospheric Dispersion Models 317

8.6.2 Indoor Air Models 320

8.6.3 Water Quality Models 321

8.7 Discussion Questions and Problems 325

8.8 Bibliography 326

III Mitigating Exposure 343

9 Characterizing Interventions 345

9.1 Multiple Barriers. 345

9.2 Typology of Interventions 348

9.3 Quantifying Performance 349

9.4 Incorporating Variability and Uncertainty 352

9.5 Estimating Performance of Multiple Barriers with Variability and Uncertainty 360

9.6 Discussion Questions and Problems 366

9.7 Bibliography 367

10 Physical Removal and Reduction 369

10.1 Removal by Action of Gravitational Forces 369

10.1.1 Water Applications 370

10.1.2 Air Applications 374

10.1.3 Cyclonic Separators 374

10.2 Removal by Virtue of Size 377

10.2.1 Depth Filters. 378

Air Filtration. 378

Water Filtration 383

Depth Filter Removal Efficiency 384

Depth Filter Pressure Drop 391

Depth Filter Regeneration 395

10.2.2 Membranes 395

10.3 Removal by Virtue of Charge 397

10.4 Surface Cleaning. 398

10.5 Discussion Questions and Problems 400

10.6 Bibliography 401

11 Inactivation Fundamentals 407

11.1 Disinfecting Agents 408

11.1.1 Chemical Disinfectants 408

Halogens 409

Hydrogen Peroxide 414

Ozone 415

Peracetic and Other Peroxy Acids 418

Ethylene Dioxide 419

Organic Disinfecting Compounds 420

11.1.2 Physical Disinfectants 422

Heat 422

Light 422

Ionizing Radiation 424

11.1.3 Advanced Oxidation - Combinations of Processes 424

11.2 Kinetics of Disinfection 425

11.2.1 General Inactivation Models 425

11.2.2 Chemical Disinfection 435

11.2.3 Thermal Inactivation 451

11.2.4 UV and Radiation Disinfection 457

11.3 Discussion Questions and Problems 470

11.4 Bibliography 471

12 Inactivation Applications 483

12.1 Fitting Performance Models to Data 483

12.1.1 Basic Count Data 486

12.1.2 Basic Quantal Data 491

12.1.3 Basic Continuous Data 494

12.1.4 Continuous Data With Censoring 497

12.1.5 Complex Models 498

12.1.6 Comparing Models 505

12.2 Byproducts 509

12.2.1 Chlorine and Halogen Compounds 509

12.2.2 Non Halogen Oxidants 510

12.2.3 UV and Other Radiation Systems 510

12.3 Coincidental Inactivation by Other Processes 511

12.4 Applications 511

12.4.1 Liquids 511

Chlorine 512

Ozone 516

Peracetic Acid 518

UV and Light 518

12.4.2 Air 519

Chemical Agents 520

UV 527

12.4.3 Solids and Semi-Solids 528

12.4.4 Surface Disinfection 530

12.5 Questions and Problems 531

12.6 Bibliography 533

13 Exposure Assessment 543

13.1 Microorganism Distributions 545

13.1.1 Direct Measurement 545

13.1.2 From Source to Receptor Models 546

13.1.3 Uncertainty of Distributions 548

13.2 Medium Contact 548

13.2.1 Ingestion 548

13.2.2 Inhalation 549

13.2.3 Fomites 550

13.2.4 Miscellaneous Other Routes 550

13.3 Formal Computation of Uncertainty and Variability 551

13.3.1 Determining Best Distributional Forms 551

13.3.2 Parametric Uncertainty of Distributional Parameters 552

13.3.3 Combining Multiple Distributions 561

13.3.4 Advanced Concepts 564

Correlated Variables 564

Copulas 568

Sampling Methods 572

13.4 Discussion Questions and Problems 576

13.5 Bibliography 577

IV Balancing and Deciding 583

14 From Dose Response to Risk Characterization 585

14.1 Dose Response 585

14.1.1 Dose Response Models 588

Generation 0 588

Generation 1 Dose Response 589

Generation 2 Dose Response with Modulating Factors 596

Generation 3 Dose Response Models with Dynamics 599

Beyond Generation 3 602

14.1.2 Fitting Dose Response Models 604

14.1.3 Multiple Exposures 611

14.1.4 Uncertainty in Dose Response Models 614

14.2 Combining with Exposure 616

14.2.1 Example Risk Characterization 616

14.3 Integrating to Populations 621

14.4 Risk Characterization Applications 627

14.5 Research Needs for Risk Assessment 629

14.6 Discussion Questions and Problems 630

14.7 Bibliography 631

15 Balancing Interventions and Risk 641

15.1 Introduction 641

15.2 Implementation of Strategies 642

15.3 Concept of Acceptable Risk 644

15.3.1 Historical 644

15.3.2 HALY, QALY, DALY Concept 645

Critiques of HALY 648

15.4 Balancing Interventions with Benefits 649

15.4.1 Direct economic valuation 649

Direct Adverse Effects 650

Healthcare Costs 650

Indirect Factors 651

Propagation of Uncertainties 653

Secondary and Indirect costs and Benefits 653

Future Costs and Benefits 653

15.4.2 Cost-Effectiveness Analysis 655

15.4.3 Formal Cost Benefit Analysis 657

History 657

Methodology 658

Critiques 660

15.4.4 Formal Multicriteria Decision Analysis 661

15.5 Discussion Questions and Problems 667

15.6 Bibliography 669

List of Figures

2.1 The Disease Triad 8

2.2 Various Shapes and Sizes of Pathogenic Viruses 10

2.3 Schematic Definition of Baltimore Virus Groups 11

2.4 Depiction of Poliovirus Type 3 13

2.5 Structure of the Encapsulated Influenza A Virus 14

2.6 Different Bacterial Shapes 16

2.7 GC Ratio of Various Bacterial Groups 21

2.8 Microscopic Image of Endamoeba histolytica 24

2.9 Microscopic Image of Giardia muris 25

2.10 Microscopic Image of Balantidium coli 25

2.11 Life Cycle of Giardia 27

2.12 Photomicrograph of Fungus Showing Hyphae and Spores 29

2.13 Chain of Infection 31

2.14 Time Indoors vs Outdoors based on Average U.S. Lifespan 33

3.1 Risk Analysis Framework 47

3.2 Conceptual Dose Response for a Single Exposure 49

3.3 Ratings of Different Risks by Experts and Members of the League of Women Voters 54

3.4 Source Transport Receptor Framework 56

3.5 Taxonomy of forms of Epistemic Uncertainty 58

3.6 Effect of Subdividing Populations on Distribution 59

4.1 Poisson Distribution for Different Values of _ 65

4.2 Impact of Subsampling from EnvironmentWith Few Organisms 66

4.3 Relative Standard Deviation based on Poisson Distribution 67

4.4 Effect of Overdispersion and Underspersion Relative to Poisson at Constant Mean 68

4.5 Exhaled Liquid Volume Produced During Certain Activities 70

4.6 January/February 2020 COVID-19 Cluster in Guangzhou Restaurant associated with a Lunch on January 24 72

5.1 ConceptualWorkflow Pipeline for Methods 78

5.2 Schematic of an Idealized Sewer Network 80

5.3 Sampling from a Sewer Maintenance Hole 82

5.4 SimplifiedWater Distribution System 87

5.5 A Simple ResidentialWell 89

5.6 Residential Rainwater Harvesting System 91

5.7 Schematic of a Residential Water System 92

5.8 Classification of Types of RecreationalWaters 94

5.9 Schematic of Impinger Used for Bioaserosol Sampling 96

5.10 Cascade Impoctor Sampler 98

5.11 Cyclone Sampler 99

5.12 Petri dish culture plate left on a rooftop for a period of 30 minutes, then incubated at a temperature of 25oC 100

5.13 Technician Swabbing Mockup of Indoor Surface of NASA International Space Station 101

5.14 Filter that has been used to sample water showing captured solid material 105

6.1 Effect of Amount Cultured on Recovery 123

6.2 Effect of Negative Binomial k on Probability for Fixed Mean=5 128

6.3 Fermentation Tube Design of Durham 137

6.4 Bacterial Growth Curve 141

6.5 Relationship Between Sizes of Microorganisms and Use of Types of Microscopy. 143

6.6 Parts of a Basic Optical Microscope 144

6.7 Micrograph of Candida albicans with Bright Field and Phase Contrast illumination.146

6.8 Hemocytometer Top View and Side View 147

6.9 Hemocytometer Slide Grid 148

6.10 Transmission Electron Micrograph of Adenovirus 150

6.11 SEM of Vibrio vulnificus 152

6.12 Structure of DNA and Nucleotides 159

6.13 Basics of Conventional Quantitative PCR Calibration 162

6.14 Cost of DNA Sequencing 166

6.15 Simple Example Illustrating Sequence Assembly from Fragments 170

7.1 Particle Size Distribution of Emitted Aerosols vs. Activity198

7.2 Activated Sludge Aeration Tank 214

7.3 Photograph of a Trickling Filter 215

8.1 Output of Solution to Example 7-2 238

8.2 Dimensionless Concentration versus Dimensionless Time for a CSTR Washout Tracer Experiment 239

8.3 Output of Complete Mix Flow System with First Order Reaction and Time-Varying Inputs and Source Term 241

8.4 Analogy of a Plug Flow System as a Conveyor Belt of Discrete Closed Volumes 242

8.5 Schematic of TwoWell Mixed Volumes in Series 244

8.6 E Curves for Multiple Well Mixed Systems in Series with Mean Residence Time=10 245

8.7 Trajectories of 10 Runs for a Complete Mix Volume Initialized with 20 Particles 248

8.8 Trajectories of 10 Runs for a Complete Mix Volume Initialized with 20 Particles, with Growth Rate and Internal Source 250

8.9 Laminar vs Turbulent Flow 252

8.10 Comparison of Axial Dispersion to Compartment in Series Model for Mean Residence Time of 1.0 and Variance Equal to Three Compartment Model. 255

8.11 Dispersion of Particles from an Infector in a Room for Various Scenarios 263

8.12 Types of Rate Processes Considered 264

8.13 Schematic of Exponential and More Complex Decay Relationships in Closed Batch Systems 273

8.14 Electron Micrograph (left) of Aggregate of Delta Variant of SARS-CoV-2 Grown on Cell Culture, and Histogram of Aggregate Size (right) 276

8.15 Comparison of Different Decay Models with Similar Values for t90 and t99 280

8.16 Fit of Decay Data to the Log-Normal Model 288

8.17 Comparison of Gompertz vs Logistic Curves 294

8.18 Model Output of Growth with Lag and Inhibitor Excretion 298

8.19 Williams Birth Death Model Output 301

8.20 Conceptual Model of Legionella Colonization of Biofilm on the Side of a Pipe Wall.303

8.21 Force Balance on Particle Moving in Gravitational Field 307

8.22 Electrical Environment of Particles Moving in a Fluid 310

8.23 Microbial and Chemical Interactions in Surface Microlayer 316

8.24 Production of Aerosols Immediately After Toilet Flushing, visualized using Fluorescent Dyes 320

8.25 Conceptual Model of Some Processes in Modeling Fate and Transport in a Single Mixed Room 321

8.26 Schematic of an Aquifer 324

8.27 Processes Included in EPANET-C Model 325

9.1 Swiss Cheese Model of Multiple Barriers 346

9.2 Relationship Between k_ and Survival Ratio for Weibull Decay in a CSTR for Different Values of the Exponent “m” 352

9.3 Schematic of Input and Output Time Series from a Process 353

9.4 Cumulative Distribution Function for Giardia Data in Table 9.2 356

9.5 Time Series Plot for Giardia Data from Table 9.2 357

9.6 Correlation Plots and Histograms of Natural Log Transformed Giardia Concentrations for Data in Table 9.2 358

9.7 Histogram of LRVs For Secondary and Tertiary Giardia Removal and Correlations.359

9.8 Schematic of Three Process Cascade with Probabilistic Approach 361

9.9 Logic Flow for Monte Carlo Analysis 361

9.10 Scatter Plot of Points in 2 Dimensional Space Generated by Pseudorandom vs Sobol Quasirandom Algorithms 363

9.11 Comparison of Simulation Standard Deviations For Mean, Median, and First Decile of the Giardia Example as a Function of Number of Monte Carlo Replications 365

10.1 Types of Settling 370

10.2 Rectangular Sedimentation Tank 371

10.3 Cyclone Separator for Air Treatment 375

10.4 Flat Air Filter Module. 379

10.5 Corsi-Rosenthal Box 381

10.6 Depth Versus Surface Filtration 384

10.7 Mechanisms of Filtration. 386

10.8 Evolution of Head Loss and Effluent Quality During Filtration 393

10.9 Categorization of Membrane Types 396

11.1 Classification of Chemical Disinfectants 408

11.2 Combinations of Hydrogen Ion and Chloride at which [Cl2(aq)]=[HOCl] 411

11.3 Idealized Chlorine Breakpoint Curve 412

11.4 Structure of Trichloroisocyanuric Aci 413

11.5 Structure of Peracetic Acid 419

11.6 Structure of Ethylene Oxide 420

11.7 Structure of Quaternary Ammonium Ion 420

11.8 The Electromagnetic Spectrum 423

11.9 Plots of ChickWatson Kinetics in a Batch System with no Decay 426

11.10 Examples of the Hom Power Law Model with Different Parameter values 429

11.11 Effect of _0 on Power Law Kinetics (k0Cn = 1) 429

11.12 Comparison of Series Event, Multitarget and Hom Models 431

11.13 Inactivation Curves for Two Population Mixtures of Chick-Watson and Hom-Chick-Watson 434

11.14 Uniform Decay vs Biphasic Decay of a Chemical Disinfectant in a BatchWell Mixed System 436

11.15 Time Course of Disinfectant Residual and Survival for the Example of Hom Inactivation with Second Order Decay Kinetics 438

11.16 Illustration of a CSTR and a PFR Connected in Series in Two Different Manners. 442

11.17 Idealized Conceptual Diagram of a Water Heater 456

11.18 Schematic of Batch UV Collimated Beam Apparatus 462

11.19 Comparison of Batch UV Systems for the Mixed versus Stratified Models at Ad = 0:5 466

12.1 Flowchart for Parameter Estimation of Models 485

12.2 Observed versus Predicted Colonies for Hom fit to Anotai Data 490

12.3 Plot of Hom Fitted Model versus Observations 497

12.4 Comparison of Predicted Hom Fit to Anotai Data Analyzed Using the Censored Regression Method 501

12.5 Conceptual Subsetting of Data 507

12.6 Schematic of a Vacuum Chlorinator 512

12.7 Schematic of a Submerged Diffuser Downstream of a Weir 514

12.8 One Type of Static Mixer Insert 515

12.9 Common Geometric Configurations for Contact Tank 517

12.10Schematic of Three Chamber Ozone Contactor 518

12.11Upper Air UV Wall Mounted Fixture 527

13.1 Fit of Sylvestre Cryptosporidium data to Inverse Gaussian Distribution 553

13.2 Parameter Pairs for the Inverse Gaussian that are in the 90 Percentile Confidence Region of the Fit to Sylvestre Data 555

13.3 Schematic of Simple Bootstrap Method 555

13.4 Bootstrapped Parameters (1000 replicates) for Inverse Gaussian Fit to Sylvestre Data 559

13.5 Pairs Plot for Bootstrapping Regression Residuals of Hom Model Fit to Data of B. subtilis Inactivation 562

13.6 Scatter Plot of Five Years of Fecal and Coliform Organisms Measured at Peoria, IL.565

13.7 Examples of Associations Between Random Variables with Misleading Correlations 569

13.8 Beta and Gamma Correlated Random Deviates with a Spearman Correlation of 0.7 576

14.1 Exponential vs. Beta-Poisson Dose-Response on Semilog and Log-Log Scales 594

14.2 Deposition Fraction of Particles in Different Portions of the Human Respiratory Tract from Nasal Inhaled Exposures 598

14.3 Effect of Incubation Time Distribution on the Case Distribution 600

14.4 Plot of Fitted Dose Response Time Model to 2.1_ Franciscella tularensis Model 602

14.5 Observed Proportion of Positives Compared to Exact Beta-Poisson Best Fit 607

14.6 Effect of Dose Splitting on Approximate Beta Poisson Risk 613

14.7 Schematic of Construction of Bootstrap Pseudosamples from a Dose-Response Experiment 614

14.8 Bootstrap Parameters for Exact Beta-Poisson Fit to Rotavirus Data 615

14.9 Distribution of Log10 Risk from 10,000 Simulations 619

14.10Tornado Plot of Spearman Rank Correlation Coefficients for Inputs to Rotavirus Risk Characterization from 10,000 Monte Carlo Simulations 620

14.11Basic SIR ModelWith Possibility of Incomplete Immunity 622

14.12Basic SEIR ModelWith Possibility of Incomplete Immunity 622

14.13Environmental Mediated Infectious Disease Model. From [10], CC-By-4 License 624

15.1 Hypothetical Time Course of Disability Weights for Three Circumstances 646

15.2 Schematic Cost-Effectiveness Curve with a Continuum of Alternatives 657

15.3 Cost Effectiveness Curve with Countervailing Risk 658

15.4 Hierarchy of Criteria, Attributes and Sub-attributes 663

15.5 Example Sub-Attribute Utility Functions for Cost 666

List of Tables

2.1 Example Pathogens in Each Baltimore Group 12

2.2 Viral Realms and Example Human Pathogens 13

2.3 Examples of Gram Negative and Gram Positive Genera with Pathogenic Bacteria. 17

2.4 Bacterial Phyla with no Currently Known Human Pathogens 23

2.5 Bacterial Phyla with Known Pathogens 23

2.6 Some Important Pathogenic Protozoa Genera 26

3.1 Attributes of Two Factors Associated with Risk Amplification or Attenuation 55

3.2 Stages in Risk Communication 55

4.1 Measurement of Influenza Virus - Infectious Particles and RNA - in Symptomatic Individuals 71

5.1 Some Significant Requirements of Different Biosafety Levels 104

6.1 Plaque counts for Poliovirus after 4 Days of Incubation as a Function of Sample Dilution 126

6.2 Data on Secondary Effluent Coliform Measured by Membrane Filter. 135

6.3 Some QA/QC Considerations for Each Step in Flow of a qPCR Assay 164

7.1 Bacterial, Viral, Protozoal and Helminth Pathogens in Human Excreta 193

7.2 Emission Rate (nL/h) of Aerosols from Individuals Engaged in Different Activities 195

7.3 Emission Rate (ng/h) of Aerosols from Individuals Engaged in Different Activities 195

7.4 PCR gene copies of SARS-CoV-2 detected in respiratory aerosols of patients during different activities 196

7.5 Pet Ownership Statistics in the US (2024) 203

7.6 Example Pet Related Infectious Diseases 204

7.7 Inventory of Major Animal Groups in Agriculture 205

7.8 Fecal Output of Different Livestock 206

7.9 Bacterial Pathogens in Dairy Manure 206

7.10 Protozoans in Animal Fecal Samples in Sydney, Australia Watershed 209

7.11 Pathogen Percent Positivity in Biosolids Receiving Various Treatments (determined by PCR) 213

7.12 Partition Factors (air/water) for Microbial Groups in Biological Wastewater Treatment 215

8.1 Examples of Simple Reaction Rates for Decay 235

8.2 Example Reactions and Rates for a Viable to Injured to Killed Process 236

8.3 Definition of Variables in Lighthart Evaporation Model 266

8.4 Condition for Perikinetic and Orthokinetic Rates to be Equal at 20oC 270

8.5 Common Two Parameter Survival Distributions and Hazard Functions 277

8.6 Empirical Survival Functions 279

8.7 Burr Type XII and III Complementary Cumulative Distributions Expressed as Survival Functions 279

8.8 Schema of Decay Experiment Using Count Data Presented in “Tidy” Form 281

8.9 Data for a Hypothetical Decay Experiment with Count Data 282

8.10 Results of Fitting Data in Equation 8.4.2 to Candidate Survival Distributions 284

8.11 AIC and BIC for Different Models Fitting Data in Equation 8.4.2 to Candidate Survival Distributions 285

8.12 Upper Percentiles of the _2 Distribution 285

8.13 Survival of E. coli O157:H7 in Creek Water 286

8.14 Fit of Data in Table 8.13 To Candidate Decay Models 287

8.15 AIC and BIC Criteria for Analysis of Concentration Decay Experiment of Eaton et al 287

8.16 Generalizations of the Logistic Growth Rate Expressions 293

8.17 Coefficients in Two Population Model Describing Two Population Interactions 304

8.18 Isoelectric Points for Selected Minerals in Water 312

8.19 Stability Classes based on Meterological Conditions[129] 318

8.20 Coefficients for Atmospheric Dispersion Correlations as a Function of Stability Class 319

9.1 Removal Expressions ((E = N Nin in PFR and CSTR Reactors for Different Orders of Removal 350

9.2 Giardia Concentrations in a Pilot Wastewater Treatment System (#/L) in Raw,

Secondary Effluent and Tertiary Effluent 355

9.3 Mean and Median Concentrations of the Giardia data from Table 9.2 355

9.4 Shapiro Wilk Test of Normality of Giardia LRVs 357

9.5 Summary Statistics for Fit of log10 Giardia Reduction Values to Alternative Distributions 359

9.6 Goodness of Fit Statistics for fit of LRVs from Data in Table 9.5 and Best Fit Parameters of the Weibull Distribution 360

10.1 Geometric Ratios and Euler and Stokes Numbers for Two Common Cyclone Designs 377

10.2 Particle Removal Efficiency by MERV Category 380

10.3 Porosity and Ergun Equation Parameters for Some Water and Air Filter Media. 392

10.4 Size Cutoffs, Pressure Drop, and Permeability of Various Membrane Types Used in Water Systems 396

11.1 Inactivation Expressions for Batch Systems with First Order Demand 437

11.2 Levels of Elaboration of CFD Models for Inactivation Processes 449

11.3 Antoine Equation Parameters for Water Vapor Pressures 455

11.4 Rates for UV Inactivation of Selected Microorganisms in Water 461

11.5 Rates for UV Inactivation of Selected Microorganisms on Surfaces 463

12.1 Batch Inactivation of E. coli by Free Chlorine at pH 10, 25oC 487

12.2 Initial E. coli Concentrations in Anotai Experiments 487

12.3 Survival of Giardia muris After Chlorination at pH 7 and 5oC 493

12.4 Survival of Bacillus subtilis Spores on Paper in Presence of Gas Phase Chlorine Dioxide 496

12.5 Anotai data Presented as Censored Concentration Data 499

12.6 Survival of spores of Bacillus subtilis Exposed to Ozone in Water in a CSTR at 15oC and pH 8 503

12.7 Comparison of Models Fit to Hibler Data on Giardia muris Inactivation 506

12.8 Correlation Parameters for Number of Mixing Modules to Get to 5% Coefficient of Variation Under Turbulent Conditions 515

12.9 Comparison of Textile Damage from Vaporized Hydrogen Peroxide (VHP)Exposure 525

12.10 Comparison of Pathogen Reduction Processes: PSRP vs. PFRP 529

13.1 qPCR Abundance of Campylobacter jejuni in Water Column at a State Park Recreational Area 545

13.2 Key Chapters of the US EPA Exposure Factors Handbook 549

13.3 Short Term Inhalation Rates Versus Activity Level, Individuals 6 years and older 549

13.4 Oocyst Concentration in Raw Water of Utility C1 552

13.5 Fit of Two Parameter Distributions to Data of Sylvestre et al 552

13.6 Bootstrap Replicates for Campylobacter data 556

13.7 Best Principles for Monte Carlo Methods in Risk Assessment 563

13.8 Measurements of Enterococcus in Wastewater and Environmental Waters by Culture and qPCR 567

14.1 Modifications of Dose Response Models for Time to Effect (_ ) 601

14.2 Human Response to Rotavirus 605

14.3 Model Fit and Dose-Response Parameter estimates forWard Rotavirus Data 606

14.4 Test of Pooling Multiple Strains 610

14.5 Dose-Response Data for Rhesus Monkey Exposure to Aerosolized Franciscella tularensis of Different Particle Sizes 611

14.6 Response of Mice to Interperitoneal Injection of Yersinia pestis 612

14.7 Model variables and parameters for an environmentally mediated infectious disease transmission model with dose–response and a latency period 625

14.8 Selected Recreational Water QMRA Examples 628

15.1 Ratio between Disability Adjusted Life Years and Infections for Selected Pathogens

Transmissible by Ingestion or Inhalation. Based on Data from The Netherlands. 647

15.2 Value of Statistical Life by Several US Agencies 650

15.3 Medical and Productivity Costs for 1993 Milwaukee Cryptosporidium Outbreak Per Case 651

15.4 Estimated Costs for Cryptosporidium Outbreak in Galway, Ireland 652

15.5 Weighting Factors for Criteria and Sub-attributes for Nanomaterial Risk Assessment.


CHARLES N. HAAS, PhD, is the L.D. Betz Professor of Environmental Engineering and Distinguished Professor at Drexel University and a member of the National Academy of Engineering. He co-directed the USEPA/DHS Center for Advancing Microbial Risk Assessment and is a fellow in multiple societies, including the International Water Association, American Academy for the Advancement of Science, Society for Risk Analysis, Association of Environmental Engineering and Science Professors, and American Academy of Microbiology. His honors include the Dr. John Leal Award, AP Black Award, and Clarke Water Prize from the American Water Works Association. He is a Board Certified Environmental Engineering Member by eminence of the American Academy of Environmental Engineers and Scientists.



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