Table of Contents
Introduction
On April 15, 2020, a study was published in Nature Medicine that was widely cited to support the claim that people without symptoms accounted for nearly half of community transmission of SARS‑CoV‑2, the coronavirus that causes COVID‑19. That study, conducted by Xi He et al. and titled “Temporal dynamics in viral shedding and transmissibility of COVID‑19”, estimated that 44 percent of transmission occurred before the onset of symptoms, or the “presymptomatic” stage of infection.
It was that same team’s research that the New York Times had cited, for example, to support the claim that 20 to 40 percent of transmission occurs before symptoms, as reported on March 31, 2020, under the headline “Infected but Feeling Fine: The Unwitting Coronavirus Spreaders”. It was based upon this fear that the US Centers for Disease Control and Prevention (CDC) subsequently issued its recommendation for universal mask use by members of the public in the community setting.
It also was based upon this fear that transmission was largely driven by symptomless people that the New York Times published an opinion piece on April 26, 2020, advocating “widespread testing of people with no known symptoms”.
On June 9, 2020, after a World Health Organization (WHO) official publicly acknowledged that studies had shown asymptomatic transmission to be “very rare”, the New York Times published an article criticizing the statement and falsely reporting that, after an outcry from the scientific community, the WHO had “walked back” the statement.
The truth was that the media had simply misreported the WHO official’s statement as meaning that it was very rare for people without symptoms to spread the virus, when in fact the WHO official had distinguished between transmission from “asymptomatic” individuals, meaning those who never developed any symptoms, and “presymptomatic” individuals, meaning those who would go on to develop symptoms. Far from walking back the statement, the WHO had simply clarified the distinction once again for incompetent reporters.
In the context of its false claim that the WHO had “walked back” the truthful statement, the Times cited the “widely cited” study in Nature Medicine as finding that “people are most infectious up to two days before the onset of symptoms”—as though this finding belied the WHO official’s statement when in fact it did not (since it was a study estimating presymptomatic and not asymptomatic transmission).
The same day, the Washington Post ran an article acknowledging that “it remains an open question” whether truly asymptomatic individuals “are a large force driving transmission”, but the Post cited the “influential” Nature Medicine study as support for the claim that a very high proportion of people “can be very infectious roughly two days before symptoms appear.”
When the CDC published its “best estimate” in July 2020 that 50 percent of community transmission occurred “prior to symptom onset”, it cited “the upper 95% confidence interval” from the Nature Medicine study as its “upper bound”.
Of course, as advocated in the pages of the New York Times, mass testing of individuals regardless of any clinical presentations of disease is precisely what occurred. The result was that “up to 90 percent of people testing positive” with PCR tests were unlikely to be contagious, as the Times finally admitted in August 2020, despite it being well understood from the start within the scientific community that running these tests at high cycle threshold values resulted in a high rate of false positive tests, with people testing positive for the presence of non-viable viral RNA or “background noise”, rather than positive tests indicating the presence of infectious virus.
In fact, it was for precisely this reason that the World Health Organization (WHO) had issued guidance to test only those presenting with symptoms or who had had a clear exposure to someone with COVID‑19.
This misuse of PCR tests as a sole basis for diagnosis resulted in systematic scientific fraud in the counting of “COVID‑19 cases”—all based upon the idea that “silent spreaders” were major drivers of community transmission of the coronavirus.
On February 1, 2022, a preprint study by Ben Killingley et al. was published at Research Square that overturned the primary basis for the conclusion that 44 percent of transmission occurred during the presymptomatic phase of infection. Uniquely, it was a SARS‑CoV‑2 human challenge study that enabled researchers to overcome certain limitations inherent to other studies relevant for estimating how contagious people are before they develop symptoms.
The study’s authors include Neil Ferguson from Imperial College London, whose infamously flawed modeling study in March 2020, which advocated continued lockdown measures until a vaccine could be rapidly developed and mass administered, served as the basis for policymakers’ decision to inflict the devastating authoritarian lockdown measures on the population.
The human challenge study subsequently underwent peer review and was published in Nature Medicine on March 31, 2022, with the title “Safety, tolerability and viral kinetics during SARS‑CoV‑2 human challenge in young adults”.
Providing a useful illustration of how researchers’ conclusions are frequently contradicted by their own findings, the authors asserted that their findings are “consistent with modeling data indicating that up to 44% of transmissions occur before symptoms are noted”—a reference to the earlier study in the same journal by Xi He et al.
In fact, the findings of the human challenge study directly contradict the basis for that 44 percent estimate, showing that, rather than viral loads in the upper respiratory tract peaking about two days prior to symptom onset, viral loads peak at about the same time as symptoms.
How the 44% Presymptomatic Transmission Rate Was Estimated
Importantly, the estimated rate of presymptomatic transmission of 44 percent in the April 2020 Nature Medicine study was in turn dependent on estimates of the “incubation period” and the “serial interval” of SARS‑CoV‑2 infection.
The incubation period refers to the duration from infection until the development of symptoms.
This is relevant for all cases in which a person infected with SARS‑CoV‑2 develops the clinical disease known as COVID‑19. Not everyone who is infected develops the disease. As already noted, those who do not are described as “asymptomatic”, a term not to be confused with “presymptomatic”.
The serial interval is relevant for cases in which transmission occurs and refers to the duration from symptom onset until transmission of the virus.
By definition, this is only relevant for cases in which the individuals transmitting the virus do ultimately present with symptoms, as opposed to individuals who become infected but never develop COVID‑19. If transmission occurs before symptom onset, the value of the serial interval is negative.
As the study authors stated, “If the observed mean serial interval is shorter than the observed mean incubation period, this indicates that a significant portion of transmission may have occurred before infected persons have developed symptoms.”
As corresponding author Eric Lau further explained to me in email correspondence we had back in June 2020, “If the mean serial interval and mean incubation period are the same, there’s actually a 50% chance of pre-symptomatic transmission. If the observed mean serial interval is longer than the mean incubation period, then the chance of pre-symptomatic transmission is lower.”
Consequently, if the true incubation period was less than their estimated incubation period, it means that they overestimated the rate of presymptomatic transmission with their 44 percent figure.
For the mean incubation period, the authors cited a prior study providing an estimate of 5.2 days. The incubation period is represented in the study with the following graph.
For the mean serial interval, they obtained information on 77 transmission pairs from a wide variety of sources, including reports of public health authorities in China and Japan, news articles, and Wikipedia, to arrive at an estimate of 5.8 days. The serial interval is represented with the following graph.
Since the mean incubation period was slightly less than the mean serial interval, it meant that something less than 50 percent of transmission was likely to have occurred during the presymptomatic phase of infection.
Based on their estimates of mean incubation period and mean serial interval, they modeled transmission dynamics, the results of which inferred that patients could transmit the virus starting from “2.3 days before symptom onset” and peaking at “0.7 days before symptom onset”.
This is represented in the following graph, with the area in the negative territory constituting 44 percent of the total area under the curve.
Additionally, to support the theoretical basis for their estimate, the research team examined data on throat swabs collected from 94 patients for up to 32 days after symptom onset that were tested for viral RNA using reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays.
More commonly referred to simply as “PCR tests”, the cycle threshold (Ct) values from this technology serve as a proxy measure of “viral load”. A fewer number of cycles required to reach the threshold of positivity indicates a greater amount of viral RNA in the sample, whereas a very high number of cycles indicates only a small amount of viral RNA in the sample. Consequently, a high Ct value is less likely to represent the presence of infectious virus.
The results of this analysis indicated “high viral loads after symptom onset, which then gradually decreased” over time (emphasis added). As the authors noted, they “did not have data on viral shedding before symptom onset” (emphasis added).
The overall results of viral load estimates from PCR test Ct values were shown in the following graph.
One notable feature of this graph is that the thick trend line indicates that people were initially testing positive at Ct values over 30. While the authors describe the initial viral loads as “high” relative to the subsequent decline inferred by increasing Ct values over time, any Ct value over 30 actually suggests a relatively low viral load.
One study, for example, found that viable virus was only culturable when Ct values were below 24, suggesting that values higher than this indicated only non-viable RNA fragments.
The fact that many people counted as “COVID‑19 cases” were unlikely to have been contagious was tacitly acknowledged in a July 2020 interview by Dr. Anthony Fauci, the notorious director of the National Institute for Allergy and Infectious Diseases (NIAID) under the National Institutes of Health (NIH), Chief Medical Advisor to the President, and member of the White House Coronavirus Task Force.
With Ct values of 35 or more, Fauci acknowledged, “the chances of it being replication competent are miniscule”. At such high Ct values, “you almost never can culture” the virus in cell culture experiments.
Since the study subjects had shown up at the hospital with symptoms, their positive PCR tests were more likely to represent true positives, indicating that their illness was indeed caused by SARS‑CoV‑2 infection. It is nevertheless interesting that the trend line falls entirely under the Ct value of 30, indicating Ct values higher than that for the duration of their visit.
This accords with the observation of one of the study’s authors, Benjamin Cowling, in an article he coauthored with Dillon Adam that was published in the New York Times on June 2, 2020, which was that a minority of infected individuals were responsible for the majority of community transmission of the coronavirus.
As Cowling and Adam explained under the headline “Just Stop the Superspreading”, it appeared that certain individuals were “superspreaders”, which was due to either the circumstances in which transmission occurred or to host factors. His team of researchers in Hong Kong had found that “just 20 percent of cases, all of them involving social gatherings, accounted for an astonishing 80 percent of transmissions.”
Equally astonishing was their conclusion that “Seventy percent of the people infected did not pass on the virus to anyone.”
The data on viral loads shown in Cowling and colleagues’ Nature Medicine study likewise suggest that a minority of patients had PCR test results indicating probable contagiousness.
Based on the viral load data along with their modeling from the estimated incubation period and serial interval, the research team concluded that “viral shedding may begin 2 to 3 days before the appearance of the first symptoms”, with viral loads generally peaking about 17 hours before the first symptoms started to appear.
However, as I reported on August 21, 2020, in an article exposing the New York Times’ lie that the WHO had “walked back” the truthful admission that studies had suggested that truly asymptomatic transmission was “very rare”, the Nature Medicine study had numerous limitations and methodological flaws that called into question their key finding that 44 percent of transmission occurred during the presymptomatic phase of infection.
The Limitations of the Study Estimating 44% Presymptomatic Transmission
For one, the authors of the modeling study acknowledged that most patients for which they had obtained data on transmission pairs “were isolated after symptom onset”, which limited the potential for post-symptomatic transmission. “Places with active case finding”, they explained, “would tend to have a higher proportion of presymptomatic transmission, mainly due to quick quarantine of close contacts and isolation, thus reducing the probability of secondary spread later on in the course of illness.”
In other words, the transmission pairs for which they obtained data were more likely to have contributed to a shorter mean serial interval than if the cases had gone unidentified or otherwise had not been isolated. This ascertainment bias limited the generalizability of their estimate to populations where rigorous contact tracing and quarantining wasn’t being done, including in the US, where it wasn’t practically feasible to identify and quarantine every case.
This ascertainment bias was also noted in a study published in BMJ Open on June 28, 2021. “Interventions such as rapid isolation of symptomatic people”, the authors of that study pointed out, “result in a greater proportion of transmission occurring earlier in the infectious period (shorter serial intervals and relatively more presymptomatic transmission).”
Another limitation of the Nature Medicine study was that it relied on patients’ recollections of when their symptoms began, which introduced “recall bias” that “would probably have tended toward the direction of under-ascertainment, that is, delay in recognizing first symptoms.” This would result in overestimation of the incubation period, which would similarly bias their results toward an estimated rate of presymptomatic transmission that was “artifactually inflated.”
Furthermore, the authors noted that their study was relevant to “settings with substantial household clustering”, thus introducing yet another bias likely resulting in an overestimate of the proportion of presymptomatic transmission.
In China, where people with infection were required to isolate themselves in their homes under strict lockdown measures, over 70 percent of SARS‑CoV‑2 transmission was estimated to have occurred within the household. Where compulsory home quarantine or “stay-at-home” lockdown measures were in place, it is unsurprising that a high proportion of transmission occurred in the household as opposed to the community setting.
As Eric Lau confirmed to me in our email correspondence, transmission “within a household with frequent and more intensive contact, especially during a lockdown, results in shorter serial intervals.”
Consequently, the lockdown measures themselves were a confounding factor in estimates of the proportion of presymptomatic transmission that was occurring, biasing results toward overestimation relative to the rate of presymptomatic transmission that would have otherwise been observed in the absence of lockdown measures like executive “stay-at-home” orders. (Ironically, such artifactually high estimates of presymptomatic transmission were, with circular reasoning, cited as justification for continuation of those lockdown measures.)
Another issue relates to the confidence intervals of the estimated mean incubation period and serial interval. For the mean incubation period of 5.2 days, turning to their cited source, we can learn that the 95 percent confidence intervals were 4.1 to 7.0 days (indicating a high level of certainty that the true mean fell somewhere between those two values). For their own estimated mean serial interval of 5.8 days, the 95 percent confidence intervals were 4.8 to 6.8 days. Thus, the confidence intervals for the serial interval fell entirely within the confidence intervals for the incubation period.
The problem that arises from this was discussed in a systematic review of studies on asymptomatic and presymptomatic transmission of SARS‑CoV‑2 published on the preprint server medRxiv on June 17, 2020.
The study in Nature Medicine, as well as other studies, had compiled data from sources that made it “difficult to control for quality and bias” and introduced variability in “standards of reporting cases or symptom onset.”
Additionally, “all of the serial interval studies are confounded by their reliance on self-reported symptom start date”, which introduced the problem of recall bias.
The review authors also commented on the ascertainment bias introduced by using data from household transmission clusters (emphasis added):
In household transmission cases, newly infected individuals will likely be exposed to a much higher dose of viral particulates than would occur in a more casual transmission case. Exposure to higher inoculum may result in a decreased incubation period for household transmission. Given that the papers compared serial intervals to estimates of incubation period, the difference in inoculum between household transmission and community transmission may account for the difference between the calculated serial interval and incubation period.
Moreover, researchers had observed that “no isolates were obtained” via cell culture “after day 8, despite continuing high viral loads” as determined by the proxy measure of PCR test Ct values. “This finding suggests persistent RNA detection represents non-viable virus that is not infectious. This finding demonstrates that while viral load can be predictive of transmissibility, it is not a perfect correlation.”
Most relevantly for our purpose here, as the review authors also observed (emphasis added):
Furthermore, in the datasets, the authors report the date of symptom onset rounded to the nearest day. This is especially problematic because the difference in serial interval and incubation period calculated in these studies often differed by less than a day. It is therefore not possible to ascertain if the difference between calculated serial interval and incubation period are true differences, or an artefact of rounding error.
The modelers had interpreted the available data as supportive of the hypothesis that contagiousness began two to three days before the appearance of symptoms. However, since the calculated mean serial interval fell within the confidence intervals of the estimated incubation period, the data were also “compatible with the hypothesis that infectiousness appears to emerge at symptom onset.” (Emphasis added.)
That alternative hypothesis is supported by the findings of the human challenge study, as we will come to.
This problem was compounded, the review authors further noted, by the fact that “patients often will not see a clinician immediately after symptom onset”. One study of patients in China had found that “an average of 2.5 days elapsed between symptom onset and first healthcare consultation.” Therefore, the possibility could not be ruled out “that viral load peaks after symptom onset.” (Emphasis added.)
Additionally, there was a lack of specificity in studies about “how soon the first swab was taken after symptoms were reported; a margin of error of a day might dramatically change the viral load in patients.”
While the viral load data indicated the plausibility of presymptomatic transmission, there was “not enough information about the distribution of SARS‑CoV‑2 viral kinetics in [the] presymptomatic stage to conclude when infectiousness begins.”
Indeed, while the authors of the Nature Medicine study stated that they utilized data on throat swabs collected from patients “from symptom onset”, that statement is obviously untrue.
All 94 of the patients from whom this data was obtained had already been admitted to the hospital in Guangzhou, China, and 66 percent were already “moderately ill” at the time of their admission. The supplementary data further reveal that only two patients had no symptoms at the time of admission. Furthermore, no information is presented on how long after admission the first samples were collected. It seems likely that, in most cases, the first samples were not collected until a considerable amount of time had already passed since symptoms first appeared.
As the review authors concluded, the available studies, including the widely cited paper in Nature Medicine, “have been inadequate to ascertain the contribution of asymptomatic and presymptomatic transmission in the spread of SARS‑CoV‑2 infection.”
While not aimed at estimating the rate of presymptomatic transmission, the human challenge study published in Nature Medicine earlier this year provides valuable insights by overcoming many of the limitations of the earlier studies that did attempt to estimate the proportion of transmission that occurred before the onset of symptoms.
Contrary to the claim made by the authors of the human challenge study that their findings are “consistent with modeling data indicating that up to 44% of transmissions occur before symptoms are noted”, their data in fact directly contradict the basis for that fear-inducing estimate.
The Findings of the SARS-CoV-2 Human Challenge Study
The study by Killingley et al. in Nature Medicine was aimed at establishing a model for additional human challenge studies, which would be useful for overcoming the limitations inherent to other types of studies investigating issues like viral kinetics, immunological responses, transmission dynamics, and duration of viral shedding. The subjects were thirty-six healthy volunteers between the ages of eighteen and twenty-nine.
All subjects were inoculated with an early variant containing the D614G mutation, which predated the emergence of the mutations that prompted authorities to start uniquely identifying variants according to the Greek alphabet (Alpha, Beta, Delta, Omicron, etc.).
The dose of inoculation was sufficient to produce infection in eighteen (53 percent) of the study participants. In these individuals, viral shedding became quantifiable by PCR in throat swabs by about 40 hours (1.67 days) and in nose swabs by about 58 hours (2.4 days) after inoculation.
Additionally, viral loads were quantified using cell culture and focus forming assay (FFA), an immunostaining technique that detects infected host cells and infectious virus particles using fluorescently labeled antibodies specific to SARS‑CoV‑2.
Viral loads as measured using PCR peaked in the throat at 112 hours (4.7 days) and in the throat at 148 hours (6.2 days). Although starting later, peak viral loads were significantly higher in the nasal samples.
In both nose and throat, viral loads “continued at high levels for several days”, with viral RNA still detectable by PCR at 14 days (2 weeks), after inoculation. At 28 days (4 weeks), six subjects (33 percent) remained test positive in the nose and two (11 percent) remained test positive in the throat. By 90 days (about 3 months), all participants were PCR negative.
In contrast to the PCR results, “viable virus was detectable by FFA for a more limited duration”, which was a median of 156 hours (6.5 days) in the nose and 150 hours (6.25 days) in the throat. The average time to clearance of viable virus was 244 hours (10.2 days) in the nose and 208 hours (8.7 days) in the throat.
Thus, while subjects continued to test positive by PCR, they were unlikely to have been contagious after one week since exposure to the virus.
Viral loads by PCR and FFA “were significantly correlated”, but, again, the duration of detection of viable virus by FFA was significantly shorter than the duration of PCR test positivity, once again indicating that the PCR tests were returning positive results for non-viable RNA fragments.
Using PCR, the earliest that swabs returned negative results was at 352 hours (14.6 days) in the nose and 340 hours (14.7 days) in the throat. “Despite relatively high levels of late qPCR detection,” the authors noted, “the latest that viable virus could be detected was day 12 after inoculation in the nose of one participant and day 11 in the throat of two participants.”
The contrasting results between viral loads as measured by PCR and quantitative culture are presented in the following graph.
Summarizing these findings, the authors stated, “Thus, after SARS‑CoV‑2 human challenge, viral shedding begins within 2 days of exposure, rapidly reaching high levels with viable virus detectable up to 12 days after inoculation and significantly higher [viral load] in the nose than the throat despite its later onset.”
Neutralizing antibodies were generated in all infected participants, detectable by 14 days (2 weeks) and increasing to 28 days (4 weeks).
From diaries kept by study participants, the researchers determined that symptoms “became apparent from 2–4 days after inoculation”, at which time “symptoms started diverging from challenged but uninfected participants, who reported both fewer and milder symptoms with no consistent pattern.”
As the authors further reported, “Symptoms were most frequent in the upper respiratory tract and included nasal stuffiness, rhinitis, sneezing and sore throat. Systemic symptoms of headache, muscle/joint aches, malaise and feverishness were also recorded.” The researchers also assessed smell disturbance using University of Pennsylvania smell identification tests (UPSITs). The results are shown in the following graph. (Pay most attention to the red line.)
All symptoms were mild to moderate. Symptoms peaked at 112 hours (4.67 days), “aligning closely with peak [viral load] in the nose, which was significantly later than peak [viral load] in the throat by FFA.”
The authors reported the median time to peak viral load in the throat of 88 hours (3.67 days), but they curiously left the reader to believe that the median time to peak viral load in the nose was about 112 hours (4.67 days). However, by simply eyeballing the accompanying graph they present, we can see that viral loads peaked in the nose at approximately 136 hours (roughly 5.67 days).
In the discussion section of the paper, the researchers summarized their key findings as follows (bold and italic emphasis added):
Although some studies have measured the response to SARS‑CoV‑2 infection longitudinally in humans, none can capture host features at the time of virus exposure, the early events before symptom onset or the detailed course of infection that can be shown by experimental challenge. Although the incubation period from the estimated time of natural exposure to perceived symptom onset has previously been estimated as ~5 days, this best aligns with peak symptoms and is longer than the true incubation period. With close questioning, symptoms were found to be associated with viral shedding within 2–4 days of inoculation but did not peak until days 4–5. Thus, virus was first detected (first in the throat, then the nose) ~2 days before peak symptoms and increased steeply to achieve a sustained peak, in many cases before peak symptoms were reached, consistent with modeling data indicating that up to 44% of transmissions occur before symptoms are noted.
In fact, their own findings directly contradict that estimate of the proportion of transmission that occurs during the presymptomatic phase of infection. What is consistent is merely the plausibility that some of the volunteers in their human challenge study were contagious prior to symptom onset. Beyond that, though, their results reveal that the rate of 44 percent presymptomatic transmission must be overestimated.
Summary and Conclusion
Recall that the estimated rate of presymptomatic transmission of 44 percent was based on an estimated mean incubation period of 5.2 days and an estimated serial interval of 5.8 days, from which it was inferred that patients could transmit the virus starting from “2.3 days before symptom onset” and peaking at “0.7 days before symptom onset”.
This human challenge study, by contrast, showed that the estimated duration of about 5 days from infection until the onset of symptoms was, at least for this particular group of volunteers, incorrect. Rather than symptoms merely beginning to appear at about day 5, reported symptoms among the infected had already significantly diverged from the uninfected between days 2 and 3, and by day 5, symptoms had already peaked.
Thus, the incubation period observed in the human challenge study was days shorter than that used by Xi He et al. to estimate the proportion of presymptomatic transmission. Since this makes the estimated serial interval relatively longer, as explained by Eric Lau, this must mean that the likelihood of presymptomatic transmission is considerably lower than their estimate of 44 percent—even setting aside the other problems with that modeling study biasing it toward overestimation.
Taken together, it is clear that the figure of 44 percent is grossly inflated.
Rather than symptoms only beginning to appear shortly after peak viral loads, indicating that a very large proportion of people must have been contagious before they ever started showing symptoms, significant symptoms in the human challenge study were already apparent between days 2 and 3, consistent with the hypothesis that infectiousness begins around the same time as the first symptoms appear, and symptoms peaked at around the same time as viral loads (about a day later than peak viral loads in the throat but a day before peak viral loads in the nose), indicating that symptoms are a reasonable proxy measure of contagiousness.
A caveat to this conclusion is that these findings are relevant for relatively young and healthy individuals and for transmission of the originally circulating strain of SARS‑CoV‑2. Omicron and its subvariants are more highly transmissible, have a shorter serial interval and a shorter incubation period, and generally cause milder illness than earlier variants.
The remark by the study authors that their findings are “consistent” with the estimate of 44 percent presymptomatic transmission is a useful example of how conclusions drawn by researchers are frequently either unsupported or directly contradicted by their own findings.
As another illustration of this drawn from the same study, the authors remark in their opening paragraph that younger people who typically have mild or asymptomatic infection “likely drive community transmission”. To support that statement, they cite a systematic review and meta-analysis published in August 2020. But that review instead pointed out how people with asymptomatic infection were “believed to be less contagious” and merely noted that it was “still too early to conclude that asymptomatic patients are less likely to transmit the virus”; therefore, the possibility of asymptomatic transmission was “still a concern”. This is a far cry from concluding, much less demonstrating, that asymptomatic people were likely driving community transmission.
When study authors make statements that are contradicted by their own findings or their own cited sources, it is a clear demonstration of their own biases. In this case, the authors clearly wished to reconcile their own findings with the justifications provided by policymakers for the lockdown measures, despite this being a logical impossibility.
The findings of this human challenge study simply do not support the claim that community transmission was being driven by asymptomatic or presymptomatic individuals. Instead, it bolsters the conclusion that, regardless of whether we are discussing asymptomatic or presymptomatic transmission, people without symptoms are far less likely to be contagious.
This is empowering knowledge because it goes to show how people could have exercised reasonable judgment about whether, for example, to go visit other family members without putting them at excessive risk. A simple rule of thumb that follows from this study’s findings is that if you feel any symptoms, like a bit of a sore throat or a stuffy nose, just stay home, whereas if you haven’t had any obvious exposure to someone with COVID‑19 and otherwise feel totally fine, there is little likelihood that you will unwittingly transmit SARS‑CoV‑2 to your loved ones, especially if other precautions are also taken, like maintaining a reasonable distance when conversing and either hanging out outdoors or in a well-ventilated room of the house.
This is not to offer any kind of advice but simply to make the point that given proper knowledge, individuals can reasonably assess their own risk and make their own informed choices based on their unique personal circumstances. The idea that government bureaucrats are capable of exercising superior judgment on behalf of every individual and every household is ludicrous. The lockdown measures not only failed utterly to protect those at highest risk but caused devastating harms to global society.
The close correlation of symptoms with viral loads observed in the human challenge study does not mean that presymptomatic transmission could not or did not occur earlier in the pandemic or that it does not occur today, but it does go to show how the fear of “silent spreaders” being major drivers of community transmission was greatly overblown by “public health” officials and the mainstream media. Such fearmongering and outright lies were utilized to manufacture consent for the devastatingly harmful authoritarian measures, which were implemented with the ultimate aim of coercing the population into accepting experimental mass vaccination.
As ever, what the government and media say science says and what we can actually learn by carefully examining the scientific literature are two completely different things.
