COVID-19 Contributed Talks II

eSMB2020 eSMB2020 Follow Tuesday at 11:15am EDT
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Nicholas Steyn

University of Auckland
"The effect of border controls on the risk of COVID-19 re-incursion in New Zealand"
As of mid-July, New Zealand appears to have eliminated community transmission of COVID-19, allowing for almost no domestic restrictions on activity. The risk of re-incursion is mitigated by strict quarantine requirements at the border. These measures include a mandatory 14-day stay in a government managed facility, multiple RT-PCR tests, and regular symptom checkups. We use a simple individual based model to investigate the risk that international arrivals pose. Arriving individuals are randomly assigned an infection status and, if relevant, an exposure date. False negative testing rates and infectiousness vary over time; while the asymptomatic status, symptom onset date, and daily contacts are assigned according to estimated distributions. Results suggest that minimising mixing in the facilities should be the primary focus of risk reduction efforts. We also propose a measure that can be used to estimate the level of transmission occurring within the facilities: the ratio of cases detected in their second week of stay to cases detected in their first week.

Lin Wang

University of Cambridge
"Serial interval of SARS-CoV-2 was substantially shortened over time by non-pharmaceutical interventions"
Studies of novel coronavirus disease (COVID-19) have reported varying estimates of epidemiological parameters including serial interval distributions, i.e. the time between illness onset in successive cases in a transmission chain, and reproduction numbers. By compiling a line-list database of transmission pairs in mainland China, we show that mean serial intervals of COVID-19 have shortened substantially from 7.8 days to 2.6 days within a month (January 9 to February 13, 2020). This change is driven by enhanced non-pharmaceutical interventions, in particular case isolation. We also show that using real-time estimation of serial intervals allowing for variation over time, provides more accurate estimates of reproduction numbers than using conventionally fixed serial interval distributions. These findings would improve assessment of transmission dynamics, forecasting future incidence, and estimating the impact of control measures.

Louise Dyson

University of Warwick
"The impact of contact networks upon SARS-CoV-2 transmission in workplaces and universities"
Following the first cases of COVID-19 being reported in the UK in late January 2020, by early March it was evident that sustained community transmission was occurring. As part of social distancing measures enforced to tackle the epidemic, non-key workers were not allowed into the workplace and universities moved to online teaching and examination for the remainder of the 2019/2020 academic year. As steps are taken to relax social distancing measures, questions surround the ramifications on community disease spread of workers returning to the workplace and students returning to university. To study these aspects, we present a network model to capture the transmission of SARS-CoV-2 over four overlapping sets of networks: (i) fixed workplace contacts; (ii) social contacts; (iii) contacts at home; and (iv) dynamic workplace contacts (for workers who see people from multiple places, such as in the service sector). Additionally, we showcase the flexibility offered by the framework by describing its use in a university setting. We assess the impact of contact tracing adherence upon the spread of infection and the total number of individuals in isolation. We also consider the impact of backwards tracing, whereby resources are focused upon identifying the source of any reported infected cases, and larger scale isolation of portions of the population if case level alerts are triggered. Our results suggest that high adherence with contact tracing can result in a significant reduction in the number of infected individuals and the total number of people who would be required to isolate over the duration of the epidemic. We observe only a weak effect of backwards contact tracing - there is a slight reduction in epidemic size as the probability of successfully tracing the source of infection increases. Finally, we observe that, in order for reactive closures to be effective, such a policy needs to be enacted when only a small proportion of those that interact with that setting have recently begun to display symptomatic infection. We conclude that ensuring high adherence to contact tracing should be prioritised in order to reduce future infection levels.

Robin Thompson

University of Oxford
"Mathematical modelling in the earliest stages of the COVID-19 pandemic"
In the early stages of the COVID-19 pandemic, when cases had only been reported in China, it was important to assess the risk that cases exported elsewhere would lead on to local epidemics. In this talk, I will show how the epidemic risk was assessed in countries worldwide. I will also present a simple approach for extending this analysis for models in which additional epidemiological complexity is included (e.g. presymptomatic transmission, age-structure, time-varying infection rates). This shows how epidemic risk estimates can be generated, informed using outbreak data, and then adjusted in real-time as more information becomes available about any newly invading pathogen.

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Virtual conference of the Society for Mathematical Biology, 2020.