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The COVID-19 R0 factor is 2-3, while SARS had an R0 factor of 2-5. However, COVID-19 has infected around 130,000 people and growing, while SARS totalled just under 9000 people infected.

Why is COVID-19 spreading faster and wider than SARS? What other factors have let COVID-19 reach pandemic levels, while SARS was contained and eradicated? Could the R0 factor be higher than believed? Was it initially slower to be contained?

Full disclosure, I'm not in medicine or a medical scientist. I'm a software developer and data scientist, and this has piqued my interested in the spread of infectious disease.

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The viruses are acting differently. SARS-CoV-2 virus is much more infectious with a much higher viral replication rate, and with people exhaling the virus in the pre-symptomatic phase whereas SARS this was not happening. Once the infected individual becomes symptomatic their bodies are producing antibodies which helps shut down viral particle shedding though virus is still being transmitted by cough which aerolizes the virus at a further distance then just by exhalation.

The nine patients, who were admitted to the same Munich hospital, were studied because they had had close contact with an index case. Cell cultures and real-time polymerase chain reaction (RT-PCR) were done on throat swabs and samples of sputum, stool, blood, and urine. Throat swabs showed very high viral shedding during the first week of symptoms.

The findings contrasted starkly with those from the 2003 outbreak of SARS in terms of viral load. "In SARS, it took 7 to 10 days after onset until peak RNA concentrations (of up to 5x105 copies per swab) were reached," the researchers wrote. "In the present study, peak concentrations were reached before day 5, and were more than 1,000 times higher."

but the mean incubation period is 5 days.

http://www.cidrap.umn.edu/news-perspective/2020/03/study-highlights-ease-spread-covid-19-viruses

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    It's interesting. Early on they were saying that pre-symptomatic transmission was not likely to be a major factor in spreading. Now they're saying it's 48%-62% of transmission, ecdc.europa.eu/sites/default/files/documents/…
    – duct_tape_coder
    Commented Mar 19, 2020 at 22:00
  • @duct_tape_coder: that's also confirmed from studies from China "We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 25–69%) of secondary cases were infected during the index cases’ presymptomatic stage" Those are stats for 94 cases in a specialized clinic in Guangzhou between 21 January 2020 to 14 February 2020. doi.org/10.1038/s41591-020-0869-5
    – got trolled too much this week
    Commented May 5, 2020 at 7:26
  • A modelling paper based on this science.sciencemag.org/content/sci/early/2020/03/30/… (See table 2 and the graphs.) For an R0 of 2.0 they estimate that the presymptomatic transmission contributes about half (Rp = 0.9) of that (in an additive model).
    – got trolled too much this week
    Commented May 5, 2020 at 7:35
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It is possible that with SARS fewer people were transmitting the virus, but those who were were "super-spreaders". R_0 is an average of those transmitting.

Source:

http://www.cidrap.umn.edu/news-perspective/2020/01/data-suggest-ncov-more-infectious-1918-flu-what-does-mean

Another possibility is that the high mortality rate in SARS actually prevented it from spreading widely.

Source:

http://nautil.us/issue/83/intelligence/the-man-who-saw-the-pandemic-coming

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  • Ahh, that would make sense, I do remember reading that a person with SARS was a super spreader, and he infected 140ish people, I hope I'm remembering correct, I can't find the source, sorry.
    – WindDude
    Commented Mar 13, 2020 at 18:04
  • are outliers not removed before creating the average R0 factor?
    – WindDude
    Commented Mar 13, 2020 at 18:09
  • @WindDude not as far as I know..
    – Mariah
    Commented Mar 13, 2020 at 18:18
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    @WindDude: and they probably shouldn't be removed: superspreaders are not like a gross and avoidable error in a data generation process that would lead to wrong conclusions about the underlying distribution, they are part of some underlying distribution: while they are rare and "high leverage", they "happen" sufficiently often that excluding them would distort the epidemiological conclusions at population level.
    – cbeleites
    Commented Mar 14, 2020 at 0:11

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