Izel Avkan, etc.,al. [preprint]Controlling avian influenza spillover events: a modelling study. https://doi.org/10.1101/2025.07.22.25331905
Avian influenza is a highly contagious viral disease that affects both domestic and wild birds, with occasional spillover to mammals, including humans. As of June 2025, 117 H5N1 infections in humans have been reported worldwide since 2020. Given the ability of the virus to infect mammals, there is a growing concern about its potential for human-to-human transmission. Currently, contact tracing and self-isolation are used in the UK to manage contacts of confirmed human cases of avian influenza. In this study, we aimed to estimate potential outbreak sizes and evaluate the effectiveness of contact tracing and self-isolation in managing avian influenza spillover events.
We used a novel dataset from the Avian Contact Study to analyse contact patterns within an underrepresented agricultural population at high risk of avian influenza exposure through contact with birds. We modelled outbreak sizes using a stochastic branching process model with measured contact data.
Most simulations resulted in small-scale outbreaks, ranging from 0 to 10 cases. When the basic reproduction number was 1.1, contact tracing and self-isolation reduced the average outbreak size from 41 cases (95% Confidence Interval (CI): 37-46 cases) to 7 cases (95% CI: 6-8 cases), preventing, on average, 8 out of every 10 infections. However, they became less effective in reducing the outbreak size when a higher proportion of cases were asymptomatic. Overall, our findings suggest that contact tracing and self-isolation can be effective at preventing zoonotic infections. Increasing awareness, encouraging self-isolation, and detecting asymptomatic cases through routine surveillance are important components of zoonotic infection containment strategies.
We used a novel dataset from the Avian Contact Study to analyse contact patterns within an underrepresented agricultural population at high risk of avian influenza exposure through contact with birds. We modelled outbreak sizes using a stochastic branching process model with measured contact data.
Most simulations resulted in small-scale outbreaks, ranging from 0 to 10 cases. When the basic reproduction number was 1.1, contact tracing and self-isolation reduced the average outbreak size from 41 cases (95% Confidence Interval (CI): 37-46 cases) to 7 cases (95% CI: 6-8 cases), preventing, on average, 8 out of every 10 infections. However, they became less effective in reducing the outbreak size when a higher proportion of cases were asymptomatic. Overall, our findings suggest that contact tracing and self-isolation can be effective at preventing zoonotic infections. Increasing awareness, encouraging self-isolation, and detecting asymptomatic cases through routine surveillance are important components of zoonotic infection containment strategies.
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