by James Lyons-Weiler, PhD, Popular Rationalism, ©2024
(Aug. 14 2024) — The COVID-19 pandemic was met with a high priority on diagnostic testing in managing public health crises. Central to this effort has been the widespread deployment of Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests, widely regarded as the gold standard for detecting SARS-CoV-2.
However, the entire testing enterprise is fraught. As the pandemic has progressed, significant concerns have emerged regarding the reliability of these tests, mainly because unacceptably high cycle thresholds (CT values) are employed. These concerns are not just theoretical—they have profound implications for public health, resource allocation, and, critically, the surveillance of wildlife populations.
RT-PCR testing, though powerful, is inherently limited by its sensitivity to even the smallest fragments of viral RNA from off-target nucleotide sources, such as other viruses or bacteria, or the patient’s or animal’s genome. When CT values exceed 35 cycles, the likelihood of detecting clinically irrelevant, off-target viral fragments increases dramatically, leading to false positives. Such results can misinform public health policies, drive unnecessary quarantines, and, as this critique will argue, skew our understanding of the presence of the virus in wildlife. These issues have been addressed in high technical detail from early 2020 (see articles here, here, and here).
Unfortunately, methods like one published by Ceci et al., 2021 are dangerously lax. The implications of misinterpreting RT-PCR results are far-reaching. In human populations, they can lead to inflated infection rates, misdiagnosed cases, and an exaggerated sense of the virus’s spread. In wildlife studies, these false positives can create a misleading narrative that wildlife species are significant reservoirs of SARS-CoV-2, prompting unnecessary and potentially harmful interventions. As I have pointed out, since early 2020, using high CT values without proper validation, such as sequencing to confirm amplicons, has led to an overestimation of viral prevalence, with severe consequences for science and policy.
This critique will dissect the flaws in RT-PCR testing methodologies used in a recent study of the prevalence of SARS-CoV-2 in wildlife that employed the flawed method of Ceci et al. (2021), and explore the broader risks of relying on these results. By scrutinizing these practices with precision and rigor, we aim to challenge the notion that wildlife is teeming with SARS-CoV-2 and advocate for more reliable, scientifically sound approaches to disease surveillance.
METHODOLOGICAL FLAWS in Goldberg et al., 2024
The methodology employed in the wildlife study, which claims widespread detection of SARS-CoV-2 in various animal species, is central to understanding the validity of the conclusions by Goldberg et al. (2024). A thorough examination of the methodological approach reveals significant concerns that undermine the reliability of the findings. These concerns revolve around the design of the study, the RT-PCR testing protocol used, and the handling of samples. Each of these aspects contributes to the overall accuracy and credibility of the study, making it essential to scrutinize them in detail.
The study aimed to assess the prevalence of SARS-CoV-2 across various wildlife species. However, several critical flaws in the study’s design raise questions about the validity of the results. The selection of species appears to have been influenced by convenience rather than a strategic approach considering ecological or epidemiological relevance. This introduces a potential bias, as certain species might be overrepresented while others that could be significant reservoirs of zoonotic diseases are underrepresented or excluded entirely. Without a clear rationale for species selection, the study risks drawing conclusions that may not be generalizable to other wildlife populations. The potential for bias in species selection can lead to skewed data, where the results might incorrectly suggest that certain species are more likely to carry SARS-CoV-2 than others. This could lead to inappropriate or misdirected conservation and public health efforts, potentially focusing resources on species that do not play a significant role in public health.
Another concern is the sample sizes used in the study. Insufficient sample sizes can lead to a lack of statistical power, making it difficult to detect true differences or associations. Furthermore, the geographical distribution of the samples is critical in understanding the scope of the study. If the samples are concentrated in specific areas, the findings may not accurately reflect the broader wildlife population. This limitation is particularly problematic in studies of zoonotic diseases, where regional differences can be significant due to variations in species ecology, human-wildlife interaction, and environmental factors. Wildlife populations are not uniform across regions; factors like climate, human population density, and local biodiversity can all influence viral prevalence. A study with a limited or skewed geographical focus might miss these nuances, leading to results that do not accurately reflect the accurate distribution of the virus.
The study does not appear to have adequately controlled for potential confounding factors that could influence the detection of SARS-CoV-2. The RT-PCR testing protocol is the cornerstone of the methodology of the study, and it is essential to examine the choice of primers, cycle thresholds, and the use of controls, as these elements directly impact the accuracy of the results. The primers and probes used in RT-PCR are critical for the specificity of the test. The choice of primers must be scrutinized to ensure they are highly specific to SARS-CoV-2 and do not cross-react with other coronaviruses or non-target sequences from the animals’ genomes. The virus has evolved significantly, and tests will thereby also “age out” unless the primers are updated every three or four months.
Without rigorous testing for cross-reactivity, there is a risk that the detected viral RNA could belong to a related but non-pathogenic coronavirus, leading to incorrect conclusions about the presence of SARS-CoV-2 in wildlife. This is particularly concerning in wildlife studies, where multiple coronaviruses might coexist.
The study employed high CT values, often exceeding 35 cycles, to detect SARS-CoV-2 in wildlife samples. High CT values are associated with a greater likelihood of detecting off-target fragments or non-specific sequences, leading to false positives. Using such high thresholds without appropriate validation significantly undermines the credibility of the results. In scientific studies, particularly those involving public health, the choice of parameters such as CT values must be rigorously justified. The absence of such justification in this study indicates a potential oversight that could have led to the overestimation of viral prevalence. Proper controls are essential in any RT-PCR assay to ensure the reliability of the results. The failure of the authors of the paper to include negative controls (e.g, to use a template to calculate sample-specific cycle thresholds), such as the Delta Delta CT method) is a major methodological flaw. Without these controls, it is impossible to accurately distinguish true positive results from false positives caused by non-specific amplification. Adequate controls, including positive and negative controls, are critical to validating the results of PCR assays. Their absence in this study is a significant oversight that calls into question the reliability of the reported findings. Furthermore, sequencing the amplicons to confirm their identity is the only way to be 100% certain that the virus, not something else, is triggering a positive PCR result.
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