As scientists with relevant expertise, we agree with the WHO director-general (5), the United States and 13 other countries (6), and the European Union (7) that greater clarity about the origins of this pandemic is necessary and feasible to achieve. We must take hypotheses about both natural and laboratory spillovers seriously until we have sufficient data. A proper investigation should be transparent, objective, data-driven, inclusive of broad expertise, subject to independent oversight, and responsibly managed to minimize the impact of conflicts of interest. Public health agencies and research laboratories alike need to open their records to the public. Investigators should document the veracity and provenance of data from which analyses are conducted and conclusions drawn, so that analyses are reproducible by independent experts.
Author(s): Jesse D. Bloom, Yujia Alina Chan, Ralph S. Baric, Pamela J. Bjorkman, Sarah Cobey, Benjamin E. Deverman, David N. Fisman, Ravindra Gupta, Akiko Iwasaki, Marc Lipsitch, Ruslan Medzhitov, Richard A. Neher, Rasmus Nielsen, Nick Patterson, Tim Stearns, Erik van Nimwegen, Michael Worobey, David A. Relman
Now, in a letter in the journal Science, 18 prominent biologists—including the world’s foremost coronavirus researcher—are lending their weight to calls for a new investigation of all possible origins of the virus, and calling on China’s laboratories and agencies to “open their records” to independent analysis.
“We must take hypotheses about both natural and laboratory spillovers seriously until we have sufficient data,” the scientists write.
The letter, which was organized by the Stanford University microbiologist David Relman and the University of Washington virologist Jesse Bloom, takes aim at a recent joint study of covid origins undertaken by the World Health Organization and China, which concluded that a bat virus likely reached humans via an intermediate animal and that a lab accident was “extremely unlikely.”
Why did it take so long to accept that SARS-CoV-2 was being transmitted through aerosols, respiratory particles that are small enough to remain suspended in the air, rather than through short-range respiratory droplets that could not travel more than a few feet because of their (bigger) size?
The reasons for this delay go back more than a century, to the fight against (incorrect but prevalent) theories that blame miasma—noxious odors, especially from rotting organic material—for diseases. While trying to counter erroneous but millenia-long folk-beliefs, some of the founders of public health and the field of infectious control of diseases around the world made key errors and conflations around the turn of the 20th century. These errors essentially froze into tradition and dogma that went unchanged and uncorrected for more than a century, until a pandemic forced our hand.
But clear evidence doesn’t easily overturn tradition or overcome entrenched feelings and egos. John Snow, often credited as the first scientific epidemiologist, showed that a contaminated well was responsible for a 1854 London cholera epidemic by removing the suspected pump’s handle and documenting how the cases plummeted afterward. Many other scientists and officials wouldn’t believe him for 12 years, when the link to a water source showed up again and became harder to deny. (He died years earlier.)
Similarly, when the Hungarian physician Ignaz Semmelweis realized the importance of washing hands to protect patients, he lost his job and was widely condemned by disbelieving colleagues. He wasn’t always the most tactful communicator, and his colleagues resented his brash implication that they were harming their patients (even though they were). These doctors continued to kill their patients through cross-contamination for decades, despite clear evidence showing how death rates had plummeted in the few wards where midwives and Dr. Semmelweis had succeeded in introducing routine hand hygiene. He ultimately died of an infected wound.
That’s a reasonable theory: other bat coronaviruses have jumped to humans the same way. In fact, it was the origin of SARS, a similar coronavirus that panicked the world in 2003 when it spread out of southern China and sickened 8,000 people. With SARS, researchers tested caged market animals and quickly found a nearly identical virus in Himalayan palm civet cats and raccoon dogs, which are also eaten locally.
This time, though, the intermediate-host hypothesis has one big problem. More than a year after covid-19 began, no food animal has been identified as a reservoir for the pandemic virus. That’s despite efforts by China to test tens of thousands of animals, including pigs, goats, and geese, according to Liang Wannian, who leads the Chinese side of the research team. No one has found a “direct progenitor” of the virus, he says, and therefore the pandemic “remains an unsolved mystery.”
Results I included 61 studies (74 estimates) and eight preliminary national estimates. Seroprevalence estimates ranged from 0.02% to 53.40%. Infection fatality rates ranged from 0.00% to 1.63%, corrected values from 0.00% to 1.54%. Across 51 locations, the median COVID-19 infection fatality rate was 0.27% (corrected 0.23%): the rate was 0.09% in locations with COVID-19 population mortality rates less than the global average (< 118 deaths/million), 0.20% in locations with 118–500 COVID-19 deaths/million people and 0.57% in locations with > 500 COVID-19 deaths/million people. In people < 70 years, infection fatality rates ranged from 0.00% to 0.31% with crude and corrected medians of 0.05%.
Author(s): John P A Ioannidis
Publication Date: 14 September 2020
Publication Site: Bulletin of the World Health Organization
In testimony before US Congress on March 11, 2020, members of the House Oversight and Reform Committee were informed that estimated mortality for the novel coronavirus was 10-times higher than for seasonal influenza. Additional evidence, however, suggests the validity of this estimation could benefit from vetting for biases and miscalculations. The main objective of this article is to critically appraise the coronavirus mortality estimation presented to Congress. Informational texts from the World Health Organization and the Centers for Disease Control and Prevention are compared with coronavirus mortality calculations in Congressional testimony. Results of this critical appraisal reveal information bias and selection bias in coronavirus mortality overestimation, most likely caused by misclassifying an influenza infection fatality rate as a case fatality rate. Public health lessons learned for future infectious disease pandemics include: safeguarding against research biases that may underestimate or overestimate an associated risk of disease and mortality; reassessing the ethics of fear-based public health campaigns; and providing full public disclosure of adverse effects from severe mitigation measures to contain viral transmission.
Author(s): Ronald B. Brown
Publication Date: 12 August 2020
Publication Site: Cambridge University Press Public Health Emergency Collection