Estimating epidemiological parameters of highly pathogenic avian influenza in common terns using exact Bayesian inference

Highly pathogenic avian influenza (HPAI) is a contagious viral disease
that has led to the culling of huge amounts of poultry as well as the
mortality of countless wild birds. The recent panzootic that began in 2021
has been particularly notable for its devastating effect on seabird
populations around the globe. Whilst transmission of HPAI within poultry
has been relatively well studied, the recency of the current panzootic,
combined with data collection challenges, means that much less is known
about key epidemiological parameters, such as reproduction numbers, R0, of
HPAI in wild populations. We develop methodology to carry out exact
Bayesian parameter inference using reversible jump Markov chain Monte
Carlo applied to mortality data in the form of daily carcass counts over
the duration of subsequent outbreaks in a colony of common terns, Sterna
hirundo, in 2022 and 2023. We estimate R0 to be 3.7 (95% CI 2.3; 7.2) in
2022, and 3.2 (95% CI 1.7; 7.0) in 2023. The probability of mortality for
an infected bird was estimated to drop from 0.26 (95% CI 0.24; 0.28) in
2022 to 0.14 (95% CI 0.11; 0.20) in 2023. Our findings furthermore suggest
direct bird-to-bird transmission to be the predominant driver of infection
within the colony, with environmental transmission playing a negligible
role.