# Global Health Research in Practice > Companion website for *Global Health Research in Practice*, a textbook by Eric Green (published as E. Philip Green) on research design and causal inference for global health. The site hosts the canonical online presence for the book and a growing set of code-driven companion notes that extend specific chapters with real-world worked examples. The book teaches practical methods for designing and interpreting health research in diverse, resource-constrained settings: causal reasoning, experimental and quasi-experimental design, statistical inference, external validity, and the feasibility and implementation realities of fieldwork. The companion notes connect a single methodological concept to a concrete, current case (a trial, a policy, a regulatory decision) with reproducible R code and figures. Author: Eric Green (E. Philip Green), global health methods scholar. ## Key resources - [Book home](https://ghrbook.com/): overview of the book and where to read or buy it. - [About the book](https://ghrbook.com/about): synopsis and table of contents. - [About the author](https://ghrbook.com/author): background and contact. - [Read online](https://read.ghrbook.com): the full book as an online reader. - [Course](https://learn.ghrbook.com/): the companion course. - [Resources](https://ghrbook.com/resources): index of all companion notes. - [Research Notes podcast](https://ghrbook.com/podcast): interviews tied to the notes. ## Companion notes - [What Would It Take to Stop This Outbreak?](https://ghrbook.com/notes/bundibugyo-outbreak-model.html): An Interactive Branching-Process Model of the 2026 Bundibugyo Epidemic. Reproduce the CDC's 2026 Bundibugyo outbreak projections in your browser, then change the assumptions behind them. An interactive branching-process model that shows how modeling studies inform a public health response: every conclusion is conditional on a stated mechanism, and isolation coverage near 70% is where containment tips. (Ch. 14 Other Designs; topics: Outbreak Modeling, Branching Process, Reproduction Number, Uncertainty) (Research Notes podcast episode with LCDR Eric Mooring, U.S. Centers for Disease Control and Prevention) - [Inside the Bundibugyo Outbreak Model](https://ghrbook.com/notes/bundibugyo-model-technical.html): Parameters, Code, and Validation Against the CDC's Published Figures. The technical companion to the interactive Bundibugyo model: every parameter from the MMWR prior box, the core of the code, and a side-by-side validation showing the reimplementation reproduces the report's three supplementary figures and inferred spillover dates. (Ch. 14 Other Designs; topics: Outbreak Modeling, Branching Process, Model Validation, Reproducibility) - [What Is the Role of AI in Peer Review?](https://ghrbook.com/notes/ai-peer-review.html): A Small Illustration Using Open Peer Review. A blind panel of AI reviewers and the real human referees of a published BMJ trial reached the same verdict and overlapped on the essentials, but were strongest in different places—the AI on mechanical and citation checks, the humans on judgment. A worked example of what an AI reviewer adds to, and misses from, peer review. (Ch. 21 Publishing; topics: Peer Review, AI in Research, Open Science, Research Integrity) - [Shifting the True Endpoint](https://ghrbook.com/notes/surrogate-endpoints-survival.html): Major Progress in Pancreatic Cancer Treatment. In the 2026 RASolute 302 trial, daraxonrasib improved overall survival in metastatic pancreatic cancer, a shift in the true endpoint rather than a surrogate. Use it to separate surrogate endpoints from survival, see why most oncology approvals lean on surrogates, and learn what a randomized survival comparison can and cannot tell you. (Ch. 9 Measurement; topics: Surrogate Endpoints, Overall Survival, Randomized Trials, Outcome Measurement) - [Testing Ebola Drugs in an Epidemic](https://ghrbook.com/notes/ebola-trial-methods-therapeutics.html): How a decade of Ebola research produced licensed treatments — and what happens next. Trace how Ebola therapeutic trials evolved from single-arm triage designs to a four-arm adaptive platform trial run in an active conflict zone, and what the resulting WHO recommendations can and cannot tell us about the 2026 Bundibugyo outbreak. (Ch. 10 Experimental Designs; topics: Adaptive Trials, Platform Trials, Single-Arm Designs, Outbreak Research) - [Testing Ebola Vaccines in an Epidemic](https://ghrbook.com/notes/ebola-trial-methods-vaccines.html): How the same crisis produced two licensed vaccines — by two very different standards of evidence. Ervebo's efficacy was measured in humans through a ring-vaccination trial; Janssen's two-dose regimen was inferred from animal challenge via immunobridging. Follow how that distinction was made — and what each design choice cost in interpretability. (Ch. 10 Experimental Designs; topics: Ring Vaccination, Cluster-Randomized Trials, Immunobridging, Outbreak Research) (Research Notes podcast episode with Dr. Ana Maria Henao-Restrepo, World Health Organization (former)) - [When Should a Trial Stop?](https://ghrbook.com/notes/adaptive-trial.html): Bayesian Adaptive Design in a Kenyan Eye Care Program. How a research team embedded a Bayesian adaptive trial directly inside a mobile eye-screening app in Kenya, why it stopped after just four weeks, and what the design tradeoff between speed and certainty looks like in real-world implementation research. (Ch. 10 Experimental Designs; topics: Adaptive Trials, Bayesian Methods, Implementation Science, Randomized Trials) (Research Notes podcast episode with Dr. David Macleod) - [Is ChatGPT a Substitute for Research Participants?](https://ghrbook.com/notes/synthetic-control.html): Making Sense of Silicon Subjects, Digital Twins, and Synthetic Control. Separate three concepts being conflated in public discourse — synthetic participants, the synthetic control method, and AI-augmented inference — using South Africa's tobacco tax policy as a worked example of how synthetic control builds counterfactuals from real data. (Ch. 11 Quasi-Experimental Designs; topics: Synthetic Control, Causal Inference, Digital Twins, AI in Research) (Research Notes podcast episode with Dr. Grieve Chelwa) - [When an Algorithm Encodes Inequity](https://ghrbook.com/notes/race-kidney-transplants.html): Using Interrupted Time Series to Evaluate a National Policy to Undo Race-Based Harm in Kidney Transplantation. Use a recent study of the OPTN wait time modification policy to learn how interrupted time series designs evaluate policies implemented at a known point in time, with a comparison group, washout period, and real OPTN data. (Ch. 11 Quasi-Experimental Designs; topics: Interrupted Time Series, Health Equity, Kidney Transplantation, Policy Evaluation) (Research Notes podcast episode with Dr. Rohan Khazanchi) - [Can You Blind a Psychedelic?](https://ghrbook.com/notes/blinding-psychedelics.html): Functional Unblinding, Expectancy Bias, and What It Means for Psychedelic Trial Design. Use Compass Pathways' psilocybin trials to explore how functional unblinding challenges the interpretation of psychedelic trial results, and what sensitivity analysis, interaction models, and design innovations can tell us about the boundary between pharmacology and expectancy. (Ch. 10 Experimental Designs; topics: Blinding, Expectancy Bias, Psychedelic Trials, Sensitivity Analysis) (Research Notes podcast episode with Dr. Gabe Loewinger, National Institute of Mental Health) - [What Does 'Clinically Meaningful' Mean?](https://ghrbook.com/notes/clinically-meaningful.html): MADRS Thresholds, MCID, and the Difference Between Statistical and Clinical Significance. Use Compass Pathways' Phase 3 psilocybin trials to examine how remission thresholds, response definitions, and the minimum clinically important difference shape the interpretation of trial results. (Ch. 6 Statistical Inference; Ch. 10 Experimental Designs; topics: Clinical Significance, MCID, Depression Trials, Outcome Measurement) (Research Notes podcast episode with Dr. Jerry Rosenbaum, MGH Center for the Neuroscience of Psychedelics) - [What Counts as a 'Clinical Trial'?](https://ghrbook.com/notes/clinical-trial-definition.html): How the NIH's Shifting Definition Reshapes Transparency in Research. Use the NIH's 2026 decision to exclude basic experimental studies from its clinical trial definition to explore what counts as a trial, why definitions matter for transparency, and how ClinicalTrials.gov registration has shaped modern research. (Ch. 10 Experimental Designs; topics: Trial Registration, ClinicalTrials.gov, NIH Policy, Research Transparency) - [What Makes a Trial 'Adequate and Well-Controlled'?](https://ghrbook.com/notes/adequate-and-well-controlled.html): Lessons from the FDA's Refusal to Review an mRNA Flu Vaccine. Use the FDA's 2026 refusal to review Moderna's mRNA flu vaccine to understand why comparator choice defines what a trial can prove — and how regulatory, clinical, and global health considerations shape the meaning of 'adequate and well-controlled.' (Ch. 10 Experimental Designs; topics: Trial Design, Active Controls, FDA Regulation, Comparator Choice) - [Drawing Your Assumptions](https://ghrbook.com/notes/dags-causal-inference.html): How a DAG Guided a Real Causal Analysis. Walk through a real research example to see how directed acyclic graphs (DAGs) help you identify confounders, select adjustment sets, and justify your analytical strategy. (Ch. 7 Causal Inference; topics: DAGs, Confounding, Adjustment Sets, Causal Analysis) (Research Notes podcast episode with Dr. Judith Lieber, London School of Hygiene and Tropical Medicine) - [Non-Significant ≠ No Effect](https://ghrbook.com/notes/significance-vs-effect.html): A Permutation-Based Demonstration. Use a permutation-based simulation to understand why a non-significant p-value does not mean there is no effect — and why effect sizes and confidence intervals tell a richer story. (Ch. 6 Statistical Inference; topics: P-values, Effect Sizes, Permutation Tests, Statistical Power) ## Research Notes podcast > A conversation series with the researchers behind the companion notes. Each episode pairs with a note above; listen, watch on YouTube, or read. Subscribe via Apple Podcasts, Spotify, YouTube, or RSS (https://anchor.fm/s/10f7865bc/podcast/rss). - [What Would It Take to Stop This Outbreak?](https://ghrbook.com/notes/bundibugyo-outbreak-model.html): conversation with LCDR Eric Mooring, U.S. Centers for Disease Control and Prevention. Watch on YouTube (https://www.youtube.com/watch?v=61QGrkgH-yA) or read the companion note. - [Testing Ebola Vaccines in an Epidemic](https://ghrbook.com/notes/ebola-trial-methods-vaccines.html): conversation with Dr. Ana Maria Henao-Restrepo, World Health Organization (former). Watch on YouTube (https://www.youtube.com/watch?v=Zobs-8WBm0w) or read the companion note. - [When Should a Trial Stop?](https://ghrbook.com/notes/adaptive-trial.html): conversation with Dr. David Macleod. Watch on YouTube (https://www.youtube.com/watch?v=Vlf70-JNGp8) or read the companion note. - [Is ChatGPT a Substitute for Research Participants?](https://ghrbook.com/notes/synthetic-control.html): conversation with Dr. Grieve Chelwa. Watch on YouTube (https://www.youtube.com/watch?v=mOAe9GqUO6w) or read the companion note. - [When an Algorithm Encodes Inequity](https://ghrbook.com/notes/race-kidney-transplants.html): conversation with Dr. Rohan Khazanchi. Watch on YouTube (https://www.youtube.com/watch?v=e3DQYsoxN8U) or read the companion note. - [Can You Blind a Psychedelic?](https://ghrbook.com/notes/blinding-psychedelics.html): conversation with Dr. Gabe Loewinger, National Institute of Mental Health. Watch on YouTube (https://www.youtube.com/watch?v=fs6zz3Gzv-w) or read the companion note. - [What Does 'Clinically Meaningful' Mean?](https://ghrbook.com/notes/clinically-meaningful.html): conversation with Dr. Jerry Rosenbaum, MGH Center for the Neuroscience of Psychedelics. Watch on YouTube (https://www.youtube.com/watch?v=Eb3dQgJ2Coo) or read the companion note. - [Drawing Your Assumptions](https://ghrbook.com/notes/dags-causal-inference.html): conversation with Dr. Judith Lieber, London School of Hygiene and Tropical Medicine. Watch on YouTube (https://www.youtube.com/watch?v=1Vg1qBroU6I) or read the companion note.