Coronavirus (1) Behind the questions and answers from WHO

The outbreak of the new coronavirus COVID-19 has caused much concern. The World Health Organization has set up specific web pages, https://web.archive.org/web/20200217030319/https://www.who.int/health-topics/coronavirus, and https://web.archive.org/web/20200215214737/https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public/myth-busters to answer common questions about coronaviruses in general and the newly emerged one in particular. I would like to share with you the scientific factors on some of their sayings and my thoughts.

"Coronaviruses (CoVs) are a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV). A novel coronavirus is a new strain that has not been previously identified in humans." (WHO)

Coronaviruses are enveloped viruses with a positive sense, single-stranded RNA genome. With genome sizes ranging from 26 to 32 kilobases in length, CoVs have the largest genomes for RNA viruses. Not all coronaviruses cause severe diseases. Human coronaviruses 229E (HCoV-229E), OC43 (HCoV-OC43), NL63 (HCoV-NL63), and HKU1 (HCoV-HKU1) have been circulating in humans for a long time. These viruses cause syndromes related to the common cold.

SARS-CoV, MERS-CoV and COVID-19 have recently been introduced to the human population and therefore the humans are immunologically naive to the viruses. These newly-emerged viruses can cause serious respiratory tract infections and high mortality rate (SARS, ~10%¹; MERS, > 35%²). For the COVID-19, we don't yet know the average mortality rate. According to a report on Lancet,³ the mortality rate of the 99 patients who were among the earliest discovered cases was ~11%. According to the official reports from the government of China, the mortality rate of the confirmed cases is about 2.1%.

"Coronaviruses are zoonotic, meaning the viruses are transmitted between animals and people. Detailed investigations found that SARS-CoV was transmitted from civet cats to humans and MERS-CoV from dromedary camels to humans. Several known CoVs are circulating in animals that have not yet infected humans." (WHO)

There are 7 strains of CoVs that can infect humans while more than 200 strains of coronaviruses infect animals. The coronavirus family is composed of 4 genogroups:1. alpha; 2. beta; 3. gamma; and 4. delta. Groups 1 to 4 infect birds and a variety of mammals, while coronavirus groups 1 and 2 are known to infect humans. SARS-CoV, MERS-CoV and COVID-19 belong to group 2. Recent studies have suggested that bats are the natural reservoir of a range of coronaviruses.^4,5,6

Both SARS-CoV, and MERS-CoV are believed to have originated from bats, with civet cats⁷ and dromedary camels⁸ are respective intermediate transmitters of the viruses to humans. According to a virologist at the University of Hong Kong, Kwok-Yung Yuen, who co-discovered the SARS virus, the best way to prevent the outbreak of another new emerging disease is "to avoid disturbing wildlife habitats and never put wildlife into markets. Respecting nature is the way to stay away from the harm of emerging infections."⁹

"Can I catch COVID-19 from my pet?" "No, at present there is no evidence that companion animals or pets such as cats and dogs have been infected or have spread COVID-19."(WHO)

For enveloped CoV to enter into host cells, spike (S) glycoprotein on CoV, is needed to mediate the virus entry. The spike protein is a principle cell entry protein responsible for attachment and membrane fusion.¹⁰ The protein receptors on humans for spike protein identified so far are all ectopeptidases. These include angiotensin-converting enzyme 2 (ACE2) for SARS-CoV¹¹ and COVID-19¹² and dipeptidyl peptidase 4 (DPP4) for MERS-CoV.¹³ The protein receptors are highly expressed in the epithelial cells of the respiratory and enteric tissue, making them attractive targets for viruses to enter the host.

The ACE2 is also expressed in cats and dogs, indicating the potential of pets contracting COVID-19. In fact, several types of coronaviruses can cause illness in animals and spread between animals and people. Therefore, we should avoid letting our pets wander around infectious areas, and wear facemask if we care for a sick pet.

However, it is not necessary to abandon our pets for fear they may transmit COVID-19. There have not been any reports of pets or other animals becoming sick with COVID-19. In fact, for a type of virus to jump from one species to another species and successfully replicate and spread , it must undergo a series of mechanisms* which most commonly results in the complete absence of the disease in the targeted host species. The jump from bats to humans does not mean it is likely to occur again and infect another species.^#

"Can COVID-19 be caught from a person who presents no symptoms?" "Understanding the time when infected patients may spread the virus to others is critical for control efforts. Detailed medical information from people infected is needed to determine the infectious period of COVID-19. According to recent reports, it may be possible that people infected with COVID-19 may be infectious before showing significant symptoms. However, based on currently available data, the people who have symptoms are causing the majority of virus spread."(WHO)

According to a preprint posted on medRxiv, the incubation period of COVID-19 can be as long as 24 days. This generates more difficulty to exclude the possibility of the infected person having a second unrelated contact. This also increases the possibility of coronavirus becoming a pandemic disease, like the influenza but with higher mortality rate, affecting everyone globally. The development of vaccine for the coronavirus may reduce the harm it causes to humans.

"Is it safe to receive a package from China or any other place where the virus has been identified?" "Yes, it is safe. People receiving packages are not at risk of contracting the new coronavirus. From experience with other coronaviruses, we know that these types of viruses don't survive long on objects, such as letters or packages."(WHO)

Information on the survival data of several coronaviruses, on different environments, that infected humans can give us an idea of what and where we should be mindful to avoid contracting the new coronavirus. Below is some useful information from some of the reports:

- HCoV-229E was found not fully inactivated for at least 7 days after deposition on different environmental surfaces at ambient temperature and relative humidity condition of approximately 50%.¹⁴ This is alarming as the minimum infective dose of respiratory viruses can be very low.¹⁵

-Among the frequently-touched surfaces in a classroom, the doorknob was found to have high content of HCoV-229E.¹⁴ This reminds us to be mindful of doorknobs in public places.

-In outbreaks units, SARS-CoV nucleic acids were detected on air samples, surfaces and inanimate objects. This suggests droplets and aerosol generation by a patient with SARS-CoV, and that surfaces could be sources of virus transmission.¹⁶

-SARS-CoV can survive for 36 hours on stainless steel.¹⁷

-SARS-CoV on a polystyrene surface showed slower inactivation.¹⁸

-In suspension, SARS-CoV retained its infectivity for up to 9 days; in the dried state, survival time was 6 days.¹⁸

-Most SARS cases were the result of direct transmission via respiratory droplets during close personal contact, and adequate respiratory protective measures were shown to be effective.¹⁹

-At the Amoy Gardens high-rise housing estate in Hong Kong, transmission probably occurred through SARS-CoV shed in the faeces of a patient.²⁰ The spreading of virus can be minimized if we flush with the toilet lid closed.

*Viruses can be carried from one type of animal to another in a variety of ways. By far the most common result is the complete absence of disease. This is because when replication in the new host does occur, the innate defenses from the new host can suppress the infection. Moreover, the adaptive responses of the new host can eliminate the illness even if the infection from the virus overcomes innate defenses. Very rarely, virus replication evades innate and adaptive immune responses and causes overwhelming disease.

^#For a virus to replicate and spread, it must be able to 1) bind to a cell-surface molecule; 2) carry out membrane fusion; 3) deliver critical components into the cytoplasm of the host; 4) avoid triggering apoptosis and highly suppressive type I interferon response; 5) interact successfully with cellular cofactors to replicate its genome and structural proteins; and 6) carry out virion assembly and exit the cells.

Therefore successful transfer of a virus to a new host species is not a simple random process.

References

1. Drosten C, Gunther S, and Preiser W, et al. Identification of a novel coronavirus in patients with severe acute respiratory syndrome. N Engl J Med. 2003; 348:1967-1976.

2. Baharoon S and Memish ZA. MERS-CoV as an emerging respiratory illness: A review of prevention methods. Travel Med Infect Dis 2019-Review. PMID 31730910

3. Nanshan Chen, Min Zhou, Xuan Dong, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet Published online: January 30, 2020. DOI: https://doi.org/10.1016/S0140-6736(20)30211-7.

4. Li W, Shi Z, Yu M, et al. Bats are natural reservoirs of SARS-like coronaviruses. Science 2005; 310:676-9.

5. Lau SK, Woo PC, Li KS, et al. Severe acute respiratory syndrome coronavirus-like virus in Chinese horseshoe bats. Proc Natl Acad Sci U S A 2005;102:14040-5.

6. Simmons NB Order Chiroptera. In: Wilson DE, Reeder DM, editors. Mammal species of the world. Baltimore: Johns Hopkins University Press; 2005. p. 312-529.

7. Guan Y, Zheng BJ, He YQ, et al. Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China. Science 10 Oct 2003: Vol. 302, Issue 5643, pp. 276-278.

8. Raj VS, Farag EA, Reusken CB, et al. Isolation of MERS coronavirus from a dromedary camel, Qatar, 2014. Emerg Infect Dis. 2014; 20(8): 1339-42.

9. Cyranoski D. Bat cave solves mystery of deadly SARS virus - and suggests new outbreak could occur. Nature 2017: 552, 15-16.

10. Li F. Structure, function, and evolution of coronavirus spike proteins. Annu Rev Virol. 2016 Sep 29; 3(1): 237-261.

11. Li W, Moore MJ, Vasilieva N, et al. Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus. Nature 2003, 426:450-454.

12. Zhou P, Yang XL, Wang XG, et al. A Pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 2020, DOI: 10.1038/s41586-020-2012-7.

13. Raj VS, Mou H, Smits SL, et al. Dipeptidyl peptidase 4 is a functional receptor for the emerging human coronavirus-EMC. Nature 2013, 495:251-254.

14. Bonny TS, Yezli S, and Lednicky JA. Isolation and identification of human coronavirus 229E from frequently touched environmental surfaces of a university classroom that is cleaned daily. American Journal of Infection Control 46 (2018) 105-7.

15. Yezli S, Otter JA. Minimum infective dose of the major human respiratory and enteric viruses transmitted through food and the environment. Food Environ Virol 2011; 3: 1-30.

16. Booth TB, Kournikakis N, Bastien J, et al. Detection of airborne Severe Acute Respiratory Syndrome (SARS) coronavirus and environmental contamination in SARS outbreak units. J. Infect. Dis. 191:1472-1477.

17. World Health Organization. 2003. First data on stability and resistance of SARS coronavirus compiled by members of WHO laboratory network. World Health Organization, Geneva, Switzerland. http://www.who.int/csr/sars/survival_2003_05_04/en/index.html.

18. Rabenau HF, Cinatl J, Morgenstern B, et al. Stability and inactivation of SARS coronavirus. Med. Microbiol. Immunol. 2005, 194:1-6.

19. Seto WH, Tsang D, Yung RW et al. Effectiveness of precautions against droplets and contact in prevention of nosocomial transmission of severe acute respiratory syndrome (SARS). Lancet 2003 361:1519-1520.

20. Hong Kong Department of Health (2003) Outbreak of severe acute respiratory syndrome (SARS) at Amoy Gardens, Kowloon Bay, Hong Kong.http://www.info.gov.hk/info/ap/pdf/amoy_e.pdf

Novel Coronavirus in Wuhan City: how to estimate the number of cases

Scientists including Professor Ferguson from Imperial College London published articles on 17th January and 22nd January estimating the number of cases of a new coronavirus, 2019-nCoV, in Wuhan, China. How did they estimate the number based on cases detected overseas? Let us have a look at their calculation formula.

They used the same calculation formula in the two reports. Let us use the second report to illustrate how they get the estimated number out.

The scientists estimated that “a total of 4,000 cases of 2019-nCoV in Wuhan City (uncertainty range: 1,000 – 9,700) had onset of symptoms by 18th January (the last reported onset date of any case).” “As of 4am 21st January (Beijing Time), 440 cases (including nine deaths) have been confirmed across 13 provinces in China, plus suspected cases in multiple other provinces. As of 9:00 GMT 22nd January, 7 confirmed cases in travellers from Wuhan with symptom onset on or before the 18th January were detected outside mainland China, in Thailand (3 cases), Japan (1 case), South Korea (1 case), Taiwan (1 case) and the United States (1 case).” Their estimation is based on the following assumptions: • “Wuhan International Airport has a catchment population of 19 million individuals. • There is a mean 10-day delay between infection and detection, comprising a 5-6 day incubation period and a 4-5 day delay from symptom onset to detection/hospitalisation of a case (the cases detected in Thailand and Japan were hospitalised 3 and 7 days after onset, respectively). • Total volume of international travel from Wuhan over the last two months has been about 3,300 passengers per day. This estimate is derived from the 3,418 foreign passengers per day in the top 20 country destinations based on 2018 IATA data, and uses 2016 IATA data held by Imperial College London to correct for the travel surge at Chinese New Year present in the latter data (which has not happened yet this year) and for travel to countries outside the top 20 destination list.”

Calculation Formula:

The total number of cases = number of cases detected overseas / probability any one case will be detected overseas (p)

where the probability any one case will be detected overseas (p) = daily probability of international travel x mean time to detection of a case.

This is incorrect, as evidenced by the fact that (a) if the mean time to detect a case goes up, the probability that any one case will be detected, according to this formula, goes up, and hence the total number of cases goes down (because probability is on the denominator of the first division), whereas we would expect the opposite to be true; and (b) if the probability of a patient being overseas were 100%, a mean time to detection of more than one day would, according to this formula, lead to a probability higher than 100%, which is clearly impossible. The correct formula should take the difference between 100% and the probability that the case will not be detected overseas, which is (1-(1/t))^d where t is mean time to detection after the incubation period (assuming a very low probability of detection during the incubation period), and d is the expected number of days any particular patient has been overseas with their incubation period completed. The expected number of days any particular patient has been overseas at all will be the daily probability of international travel multiplied by half the number of days since January 1st (assuming that passenger-flights were evenly distributed between January 1st and January 17th, that hardly any travellers returned during this time, and that the virus spread quickly enough for us to assume for the purposes of this calculation that everyone in Wuhan who was going to catch it did so by January 1st), i.e. probability of international travel x 9, but the expected number of days they will have been overseas post-incubation will depend on the incubation period: if it’s 5 days, and everyone who flew between January 1st and January 5th ended their incubation on the 5th, then that 5/18 of passengers will have had 13 days overseas post-incubation and the other 13/18 of the passengers will have had an average of 6.5 days, so the average overseas post-incubation days per passenger is 13*5/18+6.5*13/18 = 8.31. So (p) = 1 – ((1 – (1/t)) ^ (Ptravel * 8.31)).

and the daily probability of daily international travel = daily outbound of international travellers from Wuhan / catchment population of Wuhan international airport

Finally, the mean time to detection can be approximated by:

incubation period + mean time from onset of symptoms to detection

Putting the numbers into their formula, we have Total number of estimated cases = 7 detected overseas /（（3301 passengers / 19000000 catchment area）x 10 days)

giving an estimated number of 4029 (the number difference from the report most probably due to the difference of rounding up of digit during the multiplication and division).

Putting the numbers into the formula derived from us, we have an estimated number of

7 cases / (1 - ((1 - (1 / (5 days post-incubation))) ^ ((3301.0/19000000) * 8.31))) = about 22,000.

At a 95% statistical confidence interval, the report says Wuhan has a minimum of about 1700 cases of 2019-nCoV, while the maximum number of cases is about 9800. According to the report, confidence intervals “can be calculated from the observation that the number of cases detected overseas, X, is binomially distributed as Bin(p,N), where p = probability any one case will be detected overseas, and N is the total number of cases. N is therefore a negative binomially distributed function of X.” The result is the maximum likelihood estimates obtained using this negative binomial likelihood function and their incorrect formula.

After a while, we may like to calculate the estimated new coronavirus cases based on the above formula and compare with the announced data from the local government. Before doing that, we need to consider a couple of things. Is the overseas cases are still only confined to be exported from Wuhan? Any other city from China involved by that time will affect both the catchment population number and the number of flights to consider. Moreover, by the time you do the calculation, has the local authority started the prevention measurement by restricting local people from travelling? If this is the case, this would certainly decrease the reliability of the result by making use of detected overseas cases’ number.

Ideally, the calculation formula should be applied 4-5 days (allowing the 4-5 days of detection delay from the day symptom onset) before the local government started restricting the local people from travelling overseas.

The report also mentioned some factors which could affect the number of the estimated cases. Please follow the following links (internet archived link) for the two reports if you would like to know more in detail. https://web.archive.org/web/20200123095105/http://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/news--wuhan-coronavirus/

Diagnosis from breath—Owlstone Medical

Most diagnosis samples nowadays are either from tissue biopsies or blood. Today I would like to share with you a non-invasive sample collection and diagnosis method being developed by a nearly 4-year-old start-up company in Cambridge—Owlstone Medical.

Why can breath be used for diagnosis? Breath contains thousands of volatile organic compounds (VOCs), gaseous molecules that are produced as the end product of metabolic processes within the body or from foods, drugs, or the environment to which the body has been exposed. “Volatile organic compounds are produced throughout the body, and are picked up and distributed in the bloodstream. In your lungs, gases are exchanged between circulating blood and inhaled air. Alongside O2 and CO2, volatile metabolites also pass from the blood into the lungs extremely efficiently. These VOCs are exhaled and provide a source of useful biomarkers directly linked to the body's metabolism.” “It takes roughly 1 minute for blood to flow around the entire circulatory system. By sampling breath for a minute or longer, even very low levels of systemic VOC biomarkers can be pre-concentrated, collected and analyzed.”

“Endogenous volatile organic compounds (VOCs) are produced as the end product of metabolic processes within the body, meaning that underlying changes in metabolic activity, including that from your gut microbiome, can produce patterns of VOCs characteristic of specific diseases. As disease has an immediate effect on metabolism, the pattern of VOCs exhaled will change, making Breath Biopsy® an excellent tool with the potential to enable ….disease diagnosis.”

Other than exhaled breath, VOCs can be excreted via metabolite secretions such as urine, sweat, and stool. There have been a few research projects investigating the sensitivity and specificity to detect diseases by VOCs measuring from metabolite secretion other than breath with equipment and technology from Owlstone. Hopefully this can help to expand the application of VOCs as biomarkers for disease diagnosis from different sources of metabolite secretion.

According to Owlstone Medical’s website, research has been done on gaseous metabolites measurement in cancer, inflammatory disease, and infectious disease. Particularly for cancer, the Owlstone Medical focus on the research in early detection when treatments are more effective and thus the chances of survival can be as good at 95%. The company is applying this insight to their research programs in early detection of lung cancer (LuCID), colon cancer (InTERCEPT) and bladder, kidney, stomach, renal and prostate cancers (PAN).

Co-founder and CEO of Owlstone Medical, Billy Boyle, is not a medical professional. He is an engineering graduate from Cambridge University in 2000. A year later, he got a master degree in Engineering. After graduation, Billy worked as a Research Associate in the Microsystems and Nanotech group at Cambridge University. During that period, he and other founders developed a solid state detector (one hundred times smaller and one thousand times cheaper than existing technology) that used micro- and nanofabrication techniques to detect a wide range of airborne or dissolved chemical agents in extremely small quantities.

In 2004, Billy and the others spun out of Cambridge University and established a company, Owlstone Nanotech Inc., selling miniature chemical sensors on a silicon chip which is based on a patented technique called Field Asymmetric Ion Mobility Spectrometry (FAIMS). The company was initially developed for military applications. It is then grew into a profitable business providing FAIMS technology for a range of military and industrial applications globally.

Billy started to think about the medical applications of FAIMS technology after his wife, Kate, was diagnosed and later died of colon cancer. In March 2016, Billy led the process to spin out Owlstone Medical Ltd and became the founding CEO.

With the help of getting mature technology developed by its mother company, and with the recruitment of team of people covering a wide range of professional areas, Owlstone Medical is a performing well in terms of hardware and software. At the moment, the company is collaborating with different research institutes and National Health Service to collect data and build a holistic database in order to work out the gaseous biomarkers of different diseases.

Please go to the Owlstone Medical website, https://www.owlstonemedical.com, for more information.

Cambridge–University and Industry

Cambridge in England is a world famous university city. Besides the 800-year-old University which is composed of 31 colleges, the city is also well known for its science productions.

Lake on Cambridge Science Park. (From geograph.graph.uk, Keith Edkins)

Clusters of tech companies in Cambridgeshire give rise to this place being called “Silicon Fen”––the “Silicon Valley” of Europe. Cambridge University is a research-based institute. Many research findings have been developed into the basis of the start-up companies’ businesses. With professional experts graduated from or working in the University, this also attracts global giant tech/ life science companies such as Oracle, Apple, Microsoft, and GlaxoSmithKline, to establish themselves in the Cambridge area. The vast research findings and the availability of a large amount of professional experts in the vicinity have turned the university city into a thriving, rapidly expanding place with development of several science parks in the past 30/40 years. Cambridge University and the science parks surrounding it make up the “most successful innovation engine in Europe.”

In October 2019, the published collated data by the University showed that this largest technology cluster in Europe establishes with more than 5000 “knowledge intensive” companies (among which 440 belong to life-science and health-care companies) which employs over 61,000 people, and produces total turnover of £15.5 billion in 2018. The proportion of patent applications from the city is the highest in the UK: 316 patent applications published per 100,000 residents. The number is more than the next two cities combined.

According to a Financial Times article, Cambridge was the first city to develop the idea of science park in the UK. “The first UK science parks appeared in Cambridge in the early 1970s, when Trinity College, one of the UK’s wealthiest educational institutions, set up Cambridge Science Park on land that it owned to the north-west of the city. Aping the US model pioneered by Stanford in the 1950s, the initiative was prompted by government pressure to boost links between higher education and industry. Other colleges, including St John’s and Peterhouse, followed Trinity’s lead.”

Nowadays, Cambridgeshire has about 10 science parks. “To the south of the city, where the life-sciences industry is concentrated, Babraham Research Campus and Granta Park together accommodate about 80 start-ups, spinouts and established companies.”

References

1. Financial Times, 19th Novembr, 2019, Sarah Proven. “Cambridge science parks attract record funding for ‘spinouts’.” https://www.ft.com/content/40174572-d54e-11e9-8d46-8def889b4137
2. Collated data by Cambridge University. Published in October, 2019. /web/20200123223356/https://www.cam.ac.uk/sites/www.cam.ac.uk/files/inner-images/innovation_in_numbers_oct_2019.pdf