tetano
Editor, Senior Moderator
Bull Math Biol
. 2024 Dec 15;87(1):14.
doi: 10.1007/s11538-024-01396-9. Stochastic Models of Zoonotic Avian Influenza with Multiple Hosts, Environmental Transmission, and Migration in the Natural Reservoir
Rowan L Hassman[SUP] 1 [/SUP], Iona M H McCabe[SUP] 2 [/SUP], Kaia M Smith[SUP] 3 [/SUP], Linda J S Allen[SUP] 4 [/SUP]
Affiliations
Avian influenza virus type A causes an infectious disease that circulates among wild bird populations and regularly spills over into domesticated animals, such as poultry and swine. As the virus replicates in these intermediate hosts, mutations occur, increasing the likelihood of emergence of a new variant with greater transmission to humans and a potential threat to public health. Prior models for spread of avian influenza have included some combinations of the following components: multi-host populations, spillover into humans, environmental transmission, seasonality, and migration. We develop an ordinary differential equation (ODE) model for spread of a low pathogenic avian influenza virus that combines all of these factors, and we translate this into a stochastic continuous-time Markov chain model. Linearization of the ODE near the disease-free solution leads to the basic reproduction number R0
, a threshold for disease extinction in both the ODE and Markov chain. The linearized Markov chain leads to a branching process approximation which provides an estimate for probability of disease extinction, i.e., probability no major disease outbreak in the multi-host system. The probability of disease extinction depends on the time and the population into which infection is introduced and reflects the seasonality inherent in the system. Some of the most sensitive parameters to model outcomes include wild bird recovery and environmental transmission. We find that migratory wild birds can drive infection numbers in other populations even when transmission parameters for those populations are low, and that environmental transmission can be a significant driver of infections.
Keywords: Avian influenza; Branching process; Differential equations; Markov process; Seasonality.
. 2024 Dec 15;87(1):14.
doi: 10.1007/s11538-024-01396-9. Stochastic Models of Zoonotic Avian Influenza with Multiple Hosts, Environmental Transmission, and Migration in the Natural Reservoir
Rowan L Hassman[SUP] 1 [/SUP], Iona M H McCabe[SUP] 2 [/SUP], Kaia M Smith[SUP] 3 [/SUP], Linda J S Allen[SUP] 4 [/SUP]
Affiliations
- PMID: 39674959
- DOI: 10.1007/s11538-024-01396-9
Avian influenza virus type A causes an infectious disease that circulates among wild bird populations and regularly spills over into domesticated animals, such as poultry and swine. As the virus replicates in these intermediate hosts, mutations occur, increasing the likelihood of emergence of a new variant with greater transmission to humans and a potential threat to public health. Prior models for spread of avian influenza have included some combinations of the following components: multi-host populations, spillover into humans, environmental transmission, seasonality, and migration. We develop an ordinary differential equation (ODE) model for spread of a low pathogenic avian influenza virus that combines all of these factors, and we translate this into a stochastic continuous-time Markov chain model. Linearization of the ODE near the disease-free solution leads to the basic reproduction number R0
, a threshold for disease extinction in both the ODE and Markov chain. The linearized Markov chain leads to a branching process approximation which provides an estimate for probability of disease extinction, i.e., probability no major disease outbreak in the multi-host system. The probability of disease extinction depends on the time and the population into which infection is introduced and reflects the seasonality inherent in the system. Some of the most sensitive parameters to model outcomes include wild bird recovery and environmental transmission. We find that migratory wild birds can drive infection numbers in other populations even when transmission parameters for those populations are low, and that environmental transmission can be a significant driver of infections.
Keywords: Avian influenza; Branching process; Differential equations; Markov process; Seasonality.