A combination of robust vaccination programmes and strict physical distancing rules may be enough to prevent recurring peaks of covid-19 without greatly restricting the mobility of people, according to a modelling study.
The findings, published in the journal Nature Human Behaviour, can help policy-makers and public health authorities to identify appropriate levels of intervention to keep covid-19 outbreaks in check over time.
The study used anonymised mobile phone geolocation data with epidemiological and coronavirus case data from China to model the potential impact of vaccination and physical distancing on virus transmission.
Researchers from the University of Southampton, UK, and The Chinese University of Hong Kong predicted the effect of different combinations of interventions on low, medium and high density cities in the country.
They said the impact of physical distancing in containing future resurgences of covid-19 depends greatly on the intensity of measures, population density, and the availability of vaccines across geographical areas and time.
The researchers set out to gain a greater understanding of the relationship between these factors.
They predict that in most cities, vaccination programmes and physical distancing combined will be enough to contain virus resurgence without the need to enforce stay-at-home restrictions.
In the study, containment was defined as maintaining a low transmission rate, or 'R' number below one, which means one infected person will not spread the virus to more than one person.
The researchers noted that cities with medium and high density populations will need both vaccination and distancing to prevent future intense waves of covid-19, until herd immunity is reached.
Herd immunity occurs when a large number of people, usually 70 per cent, become immune to a contagious disease after being infected to it.
However, the team suggests that cities with low populations and effective vaccination could fully interrupt transmission without the need for physical distancing.
In all cities, full 'stay-at-home' lockdowns would no longer be necessary, according to the researchers.
The results also suggest strong physical distancing interventions implemented for short periods of time may be more effective than mild, longer term ones, they said.
"Our research provides a framework and set of outputs that can be used by policy-makers and public health authorities to identify appropriate levels of intervention to keep covid-19 outbreaks in check over time," said Shengjie Lai, senior research fellow at the University of Southampton.
"Although our study was based on data from China, our methods and findings are applicable to cities worldwide with similar levels of population density and social contact patterns," Lai said.
The researchers noted previous studies have assumed that when people reduce mobility, they proportionately reduce their social contacts.
However, they said, this isn't necessarily the case and as more SARS-CoV-2 vaccines come online, there is an urgent need to understand the relationship between these factors.
The researchers recognise some limitations to their study, for example, the absence of data on the contribution of handwashing and face masks and challenges of vaccine supply.
However, they emphasise that their approach can be quickly adapted to provide near real-time data to address emerging, time critical needs.
While the use of face masks has been touted as a key factor in reducing the number of covid-19 infections, evidence highlighting the importance of social and physical distancing has also emerged in recent research. A study conducted by researchers at the Ohio State University found that following health advice and staying away from others reduces an individual person's chances of contracting covid-19.
For the study, which was published earlier this month in the Proceedings of the National Academy of Sciences, researchers presented participants with virtual behavior scenarios of various public settings -- a grocery store, a crowded beach, a crosswalk -- and asked them to place themselves or fictional people in those contexts based on their social distancing preferences.
After four months, the same participants were asked if they had tested positive for SARS-CoV-2 or otherwise believed they had been sick with a case of covid-19. Statistical analyses showed that the more participants demonstrated a preference for social distancing in the scenarios, the less likely they were to have been infected with covid-19.