A study, published in the Lancet Public Health, reports on the impact of social distancing measures on the COVID-19 epidemic in Wuhan, China.
Prof Tom Solomon, Director, NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, University of Liverpool, said:
“The world is holding its breath waiting to see what happens when Wuhan eases the physical distancing measures that it imposed some months ago. The measures clearly brought the outbreak under control. But will easing them lead to a second wave of Covid-19? This modelling paper suggests rather than easing the measures in March in Wuhan, they should be held in place till April to give the health systems more time to recover and prepare for a likely second wave. There are so many uncertainties, however, that I suspect the only way we will know for sure is to see what happens when the measures are eased. One alternative approach for the authorities in Wuhan to adopt would be a very slight easing of control measures for 3 weeks, e.g. allowing people to spend more time outdoors, but to minimise contact. We would then be able to see the impact on infection rates, and lock down again if needed. Ultimately a slow increase in infection rates is what public health officials are aiming for. It’s the large number of cases in a short time window that we have to try and avoid.”
Dr James Gill, Honorary Clinical Lecturer, Warwick Medical School, said:
“The latest article from the Lancet has looked back at data from the lock down of Wuhan, and extrapolated out the impacts of different timed reductions of restrictions.
“The study model is designed to provide comment on the rate of epidemic, rather than pandemic, growth by looking at the risk of infection after exposure. Rate of infections post exposure is a very useful statistic for use in health policy models underpinning the current large scale lock downs many countries have implemented. What separates this study from existing research is the forward looking view taken, specifically modelling the possible outcomes relating to different timing when movement restrictions are stopped.
“Even recognising that a series of assumptions within the study data have been made to account for unknowns, such as the number of asymptomatic and subclinical cases and whether they are infectious, this model has produced some encouraging results. Prem et al demonstrate that a phased return to work in Wuhan, if started in April as opposed to now, resulted in a 25% reduction in rates of infection. The implications of this are profound – namely the soought after ‘flattening of the curve’, along with the reduction of total cumulative infections, whilst also demonstrating a delay in the peak of the outbreak by two months.
“Prem et al has used estimates for certain pieces of epidemiological data with the model, which is clearly a potential source of error and bias, but the study authors have attempted to mitigate this effect by providing both highest and lowest ranges for possible outcomes. Maintaining restrictions until April appears to have a significant effect on ‘flattening the curve’ and has the potential to delay any second peak – benefits which the model shows are significantly lost if restrictions are abruptly lifted, rather than reduced in a staggered manner. The proposals put forward here align with current practices, and support the continuation of the quarantine efforts to reduce the case load burden on health infrastructures. Given the current levels of assumptions already in use for government public health responses, it is gratifying to see a reasoned model which may be able to further guide policy makers. As additional data is collated from other countries, this will allow the refinement of the Prem et al model, and similar works, further reducing any inherent over optimism lurking in the data holes filled in with assumptions, or possibly low quality data, to which the authors allude. Hopefully this study will allow governments greater clarity in balancing population restrictions against their economic impact given the power demonstrated here.”
‘The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study’ by Kiesha Prem et al. was published in the Lancet Public Health at 23:30 UK time on Wednesday 25 March 2020.