Short-term Projections based on Early Omicron Variant Dynamics in England (preprint)

Throughout the ongoing COVID-19 pandemic, the worldwide transmission and replication of SARS-COV-2, the causative agent of COVID-19 disease, has resulted in the opportunity for multiple mutations to occur that may alter the virus transmission characteristics, the effectiveness of vaccines and the severity of disease upon infection. The Omicron variant (B.1.1.529) was first reported to the WHO by South Africa on 24 November 2021 and was declared a variant of concern by the WHO on 26 November 2021. The variant was first detected in the UK on 27 November 2021 and has since been reported in a number of countries globally where it is frequently associated with rapid increase in cases. Here we present analyses of UK data showing the earliest signatures of the Omicron variant and mathematical modelling that uses the UK data to simulate the potential impact of this variant in the UK. In order to account for the uncertainty in transmission advantage, vaccine escape and severity at the time of writing, we carry out a sensitivity analysis to assess the impact of these variant characteristics on future risk.

Vaccine breakthrough and the invasion dynamics of SARS-CoV-2 variants (preprint)

Vaccination provides a powerful tool for mitigating and controlling the COVID-19 pandemic. However, a number of factors reduce these potential benefits. The first problem arises from heterogeneities in vaccine supply and uptake: from global inequities in vaccine distribution, to local variations in uptake derived from vaccine hesitancy. The second complexity is biological: though several COVID-19 vaccines offer substantial protection against infection and disease, ‘breakthrough’ reinfection of vaccinees (and subsequent retransmission from these individuals) can occur, driven especially by new viral variants. Here, using a simple epidemiological model, we show that the combination of infection of remaining susceptible individuals and breakthrough infections of vaccinees can have significant effects in promoting infection of invading variants, even when vaccination rates are high and onward transmission from vaccinees relatively weak. Elaborations of the model show how heterogeneities in immunity and mixing between vaccinated and unvaccinated sub-populations modulate these effects, underlining the importance of quantifying these variables. Overall, our results indicate that high vaccination coverage still leaves no room for complacency if variants are circulating that can elude immunity, even if this happens at very low rates.

Coughs, Colds and “Freshers’ Flu” Survey in the University of Cambridge, 2007-2008 (preprint)

Universities provide many opportunities for the spread of infectious respiratory illnesses. Students are brought together into close proximity from all across the world and interact with one another in their accommodation, through lectures and small group teaching and in social settings. The COVID-19 global pandemic has highlighted the need for sufficient data to help determine which of these factors are important for infectious disease transmission in universities and hence control university morbidity as well as community spillover. We describe the data from a previously unpublished self-reported university survey of coughs, colds and flu-like symptoms collected in Cambridge, UK, during winter 2007-2008. The online survey collected information on symptoms and socio-demographic, academic and lifestyle factors. There were 1076 responses, 97% from University of Cambridge students (5.7% of the total university student population), 3% from staff and <1% from other participants, reporting onset of symptoms between September 2007 and March 2008. Undergraduates are seen to report symptoms earlier in the term than postgraduates; differences in reported date of symptoms are also seen between subjects and accommodation types, although these descriptive results could be confounded by survey biases. Despite the historic and exploratory nature of the study, this is one of few recent detailed datasets of flu-like infection in a university context and is especially valuable to share now to improve understanding of potential transmission dynamics in universities during the current COVID-19 pandemic.

Engagement and adherence trade-offs for SARS-CoV-2 contact tracing (preprint)

Contact tracing is an important tool for allowing countries to ease lockdown policies introduced to combat SARS-CoV-2. For contact tracing to be effective, those with symptoms must self-report themselves while their contacts must self-isolate when asked. However, policies such as legal enforcement of self-isolation can create trade-offs by dissuading individuals from self-reporting. We use an existing branching process model to examine which aspects of contact tracing adherence should be prioritised. We consider an inverse relationship between self-isolation adherence and self-reporting engagement, assuming that increasingly strict self-isolation policies will result in fewer individuals self-reporting to the programme. We find that policies that increase the verage duration of self-isolation, or that increase the probability that people self-isolate at all, at the expense of reduced self-reporting rate, will not decrease the risk of a large outbreak and may increase the risk, depending on the strength of the trade-off. These results suggest that policies to increase self-isolation adherence should be implemented carefully. Policies that increase self-isolation adherence at the cost of self-reporting rates should be avoided.

Effectiveness of isolation, testing, contact tracing and physical distancing on reducing transmission of SARS-CoV-2 in different settings (preprint)

Isolation of symptomatic cases and tracing of contacts has been used as an early COVID-19 containment measure in many countries, with additional physical distancing measures also introduced as outbreaks have grown. To maintain control of infection while also reducing disruption to populations, there is a need to understand what combination of measures - including novel digital tracing approaches and less intensive physical distancing - may be required to reduce transmission. Using a model of individual-level transmission stratified by setting (household, work, school, other) based on BBC Pandemic data from 40,162 UK participants, we simulated the impact of a range of different testing, isolation, tracing and physical distancing scenarios. As well as estimating reduction in effective reproduction number, we estimated, for a given level of COVID-19 incidence, the number of contacts that would be newly quarantined each day under different strategies. Under optimistic but plausible assumptions, we estimated that combined testing and tracing strategies would reduce transmission more than mass testing or self-isolation alone (50-65% compared to 2-30%). If limits are placed on gatherings outside of home/school/work (e.g. maximum of 4 daily contacts in other settings), then manual contact tracing of acquaintances only could have a similar effect on transmission reduction as detailed contact tracing. In a scenario where there were 10,000 new symptomatic cases per day, we estimated in most contact tracing strategies, 140,000 to 390,000 contacts would be newly quarantined each day. Consistent with previous modelling studies and country-specific COVID-19 responses to date, our analysis estimates that a high proportion of cases would need to self-isolate and a high proportion of their contacts to be successfully traced to ensure an effective reproduction number that is below one in the absence of other measures. If combined with moderate physical distancing measures, self-isolation and contact tracing would be more likely to achieve control.