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expert reaction to paper on transmission dynamics and modelling future social distancing strategies for COVID-19

Research, published in Science, reports on the transmission dynamics and modelling future social distancing strategies for COVID-19.


Prof Gordon Dougan, Department of Medicine, University of Cambridge, said:

“These are a leading group on modelling and have expertise in genomics and transmission tracking. I know Marc personally and he is regarded as a highly respected investigator and I share that view. Much of this is common sense based around how we currently know epidemics oscillate. Having said that, there are so many variables around COVID-19 that these are intelligent and calculated estimates. I am not sure comparing with other coronaviruses is helpful as SARS-Cov19 is much more pathogenic and invasive. However, overall there is little to compare SARS-Cov2 with.

“I think it is likely that some measures will still be in place if we do not have good and freely available vaccines. In reality, the balance between the health issues and economic challenges will be an important consideration and we mustn’t forget that social distancing to avoid transmission of this virus is challenging. Any disease or vaccine with short lived immunity may rebound depending on where it can persist (host or environment etc). Typhoid, measles etc.”


Prof Sir Roy Anderson, Professor of Infectious Disease Epidemiology, Imperial College London, said:

“This is an excellent paper by a very good group at Harvard – the results should be taken very seriously.

“There is only one ‘longer term’ solution and that is a vaccine – the mitigation effects are all ’suck it and see’ in terms of effect on the effective R number – and can only be evaluated retrospectively. 

“All governments should be thinking how they encourage all of the big Pharma vaccine companies to produce a product that works and then the difficult bit – manufacturing on a huge scale. Secondly, governments need to be thinking of ways to speed up the development of a vaccine in the first place such as safely removing the need for phase 3 trials.”


Prof Rowland Kao, Sir Timothy O’Shea Professor of Veterinary Epidemiology and Data Science, University of Edinburgh, said:

“The underlying science behind this paper is based on some simple principles. First, the decline of Covid-19 cases in many places around the world is due to a combination of the natural dynamics of the infection, where individuals who have been infected are assumed to acquire some level of immunity (and therefore induce a level of ‘herd immunity’), and the impact of control – a combination of testing and either voluntary and enforced social distancing.  Another difficult to quantify factor is the influence of seasonality. We know other respiratory diseases decline in the warmer months, and in this analysis, the authors use patterns established by other coronaviruses and makes the assumption that Covid-19 will display similar patterns, in particular in regards to the effect of seasonality on transmission rates. Fatalities may also play a role in reducing transmission, but unless these numbers are high, it is unlikely to be of primary importance.

“As the pandemic declines, one possible outcome is that the numbers of cases will drop sufficiently so that the disease will be eradicated. If not, then there is a possibility that enough cases will occur through the summer months so that, through a combination of increases in the number of susceptible individuals, plus increased contact as social distancing measures plus a possible increase in inherent transmission due to the return of colder months, that Covid-19 will return, with sufficient cases to place a severe burden on ICUs.  

“At this point, such reasoned analyses are important speculations, and they present a strong argument for the need for both extensive serological testing to determine how widespread immunity might be, plus a better understanding of how long individuals will retain immunity following infection. However, as a prediction of the future, it depends on being able to disentangle the combined effects of three factors (herd immunity, social distancing and seasonality) all of which are occurring simultaneously; as this is an extremely difficult task, its predictive power should be viewed with caution, despite the excellence of the work itself.”


Prof Mark Woolhouse, Professor of Infectious Disease Epidemiology, University of Edinburgh, said:

“This is an excellent study that uses mathematical models to explore the dynamics of COVID-19 over a period of several years, in contrast to previously published studies that have focused on the coming weeks or months. It is important to recognise that it is a model; it is consistent with current data but is nonetheless based on a series of assumptions – for example about acquired immunity – that are yet to be confirmed. The study should therefore be regarded as suggesting possible scenarios rather than making firm predictions.

“The study raises the possibility that repeated social distancing measures (such as lockdowns) will be needed to keep levels of COVID-19 hospitalisations and deaths to manageable levels for a period of several years. That prospect has been highlighted previously and is an important consideration as we attempt to manage this pandemic.

“However, one weakness of the paper is that the authors do not model specific social interventions. So it is hard to evaluate what the wider impacts of those interventions might be. In particular, they do not consider interventions targeted at subsets of the population, ‘segmenting’, nor interventions designed to protect people most vulnerable to COVID-19, ‘shielding’.

“In the absence of treatments or vaccines, segmenting and shielding offer ways to minimize the wider impacts of social distancing. That will be even more important if, as this analysis suggests, we will be living with COVID-19 for a long time to come.”


Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period by Stephen Kissler et al. was published today Tuesday 14 April


DOI: 10.1126/science.abb5793


All our previous output on this subject can be seen at this weblink:


Declared interests

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