Book Review
In “Fighting Goliath: Exposing the Flawed Science and Statistics Behind the COVID-19 Event,” Norman Fenton and Martin Neil present a meticulous and comprehensive critique of the statistical and scientific foundations underlying the global response to the COVID-19 pandemic. This work offers profound and detailed counterpoints based on the fundamentals of data analysis, drawing on disciplined analytic norms to challenge many of the assumptions and decisions made by public health authorities, vaccine manufacturers, and media outlets. The book stands out not only for its depth but also for its preservation of objective analysis, an esteemed professional activity that, in the current era of digital volatility, remains vulnerable to erasure by fiat. In an age where electronic content can vanish with little notice, the permanence of a hard copy makes this contribution especially valuable.
The authors structure the book chronologically, which provides readers with a clear view of how their contemporaneous analyses aligned—or starkly contrasted—with the unfolding media narrative. The chronological approach also underscores the evolving nature of their critiques, offering a sophisticated real-time evaluation of events as they transpired. The early insights presented by Fenton and Neil resonate with and validate those who pointed out some of these flaws in the design of analysis of COVID-19 clinical trials. Still, their work is detailed and refined and represents an important and noteworthy contribution.
Several key issues in the pandemic response are examined with precision: the fluid and often inconsistent clinical definitions, the complexities and biases inherent in testing protocols, and the important challenges baked into trial design and data interpretation that make their interpretation and translational reliability fruitless. The authors’ analysis reveals significant concerns regarding the modeling approaches that informed public policy, issues with record-keeping, and a troubling lack of transparency in releasing crucial information. The extent of censorship—especially of preprint articles and dissenting viewpoints—presents a disturbing picture of the pandemic’s intellectual climate, with the authors documenting instances that raise fundamental questions about academic freedom and scientific discourse.
The now-infamous adage, “There are three kinds of lies: lies, damned lies, and statistics,” aptly captures the spirit of Fighting Goliath. Fenton and Neil provide a masterclass in how statistical manipulation via the two-dose regime with delayed case counting can obscure the truth, and they offer a detailed exposition of the precise manner in which data sampling was shaped to reinforce particular narratives. Despite the dense presentation of technical material, the book remains accessible to those with a background in statistics, though its complexity might challenge the casual reader. The multitude of details can be reassuring. While they can feel overwhelming at times, but they serve an important purpose: to underscore the extent of the discrepancies and inconsistencies the authors have highlighted.
One of the most compelling aspects of the book is its exploration of alternative hypotheses surrounding the dynamics of the pandemic. Fenton and Neil engage with data-driven analyses to present these hypotheses, though this section could benefit from further engagement with experts such as Dr. Peter McCullough, particularly concerning the relatively brief mention of potential “blood issues.” The omission of deeper exploration into this line of inquiry, despite media reports from coroners and medical examiners, leaves room for further discussion.
The book concludes with a chapter on recommendations that is both concise and impactful. Fenton and Neil argue convincingly for a complete overhaul of how infectious disease outbreak data are classified, coded, and made available to the public. Their call for greater transparency, including unrestricted access to Freedom of Information Act (FOIA) requests, is particularly timely given the numerous data-related controversies that arose during the pandemic. The authors’ recommendations are well-supported by their earlier analyses, and their conclusions are sobering and compelling.
Ultimately, Fighting Goliath is not a book for the faint-hearted. It will demand a level of intellectual engagement from the reader that may even challenge some professionals. However, the payoff is significant for those willing to invest the time: a masterful dissection of the data, models, and policies that shaped the global pandemic response. It raises the critical question: if censorship had not been so pervasive, and if the dissenting views documented by Fenton and Neil had been given a fair hearing, might the global response to COVID-19 have looked markedly different?
In the end, the book serves both as a record of the pandemic and as a testament to the importance of intellectual courage and scientific rigor. Fenton and Neil’s work provides a crucial counterpoint to the dominant narrative, and their contributions will remain an essential resource for those seeking to understand the full scope of the pandemic’s scientific, statistical, and ethical dimensions.
