In the early phases of the pandemic, it was estimated that more than 70% of the population would need to have been infected to achieve herd immunity (more). The toll of COVID-19 and the extraordinary strains placed on the healthcare services meant that this was quickly discarded as a reasonable strategy. Since then, there has been much discussion as to whether heterogeneity in the transmission of the virus meant that that herd immunity might be achieved through a lower level of infection, but lockdowns and social distancing restricted the spread of the virus. However, with the widespread roll-out of vaccines across different priority groups in the UK, more than 50% of the population have evidence of antibodies (more) and the question of herd immunity has arisen again.
The Dynamic Causal Modelling group at UCL under Professor Karl Friston have made a series of predictions about most likely scenarios, comparing estimated levels of effective vaccination with seasonally adjusted viral transmission rates to posit a cross over point on 9 April by when it was estimated that 73.4% of the UK population over age 16 would have effective immunity thanks to vaccination or prior infection as set out in Figure 3.2 (more).
Figure 3.2 – Relationship between vaccine effectiveness and herd immunity
Source: Dynamic Causal Modelling, UCL
Other modelling groups have questioned whether these conclusions are precipitous (more), citing evidence from the REACT-1 study over the period 11 to 30 March that shows a R value of 1, suggesting that social distancing restrictions are still needed to stop infections increasing. The expectation is that increased social contacts after relaxing lockdown will lead to a further surge of infections, potentially exacerbated by increasing prevalence of new variants and attrition in the effectiveness of the immune response.