Stochastic Models of Zoonotic Avian Influenza with Multiple Hosts, Environmental Transmission, and Migration in the Natural Reservoir.

IF 2 4区 数学 Q2 BIOLOGY Bulletin of Mathematical Biology Pub Date : 2024-12-15 DOI:10.1007/s11538-024-01396-9
Rowan L Hassman, Iona M H McCabe, Kaia M Smith, Linda J S Allen
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Abstract

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 R 0 , 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.

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具有多重宿主、环境传播和自然水库迁移的人畜共患禽流感随机模型。
甲型禽流感病毒是一种传染性疾病,在野生鸟类种群中流行,并经常蔓延到家禽和猪等驯养动物中。病毒在这些中间宿主体内复制时会发生变异,从而增加了出现新变种的可能性,这种变种对人类的传播力更强,对公共健康构成潜在威胁。以前的禽流感传播模型包括以下几个部分的组合:多宿主种群、向人类的溢出、环境传播、季节性和迁移。我们建立了一个结合所有这些因素的低致病性禽流感病毒传播常微分方程(ODE)模型,并将其转化为随机连续时间马尔可夫链模型。无疾病解附近的 ODE 线性化导致基本繁殖数 R 0,这是 ODE 和马尔可夫链中疾病灭绝的阈值。线性化马尔科夫链导致了一个分支过程近似值,它提供了疾病灭绝概率的估计值,即在多宿主系统中没有重大疾病爆发的概率。疾病灭绝概率取决于引入感染的时间和种群,并反映了系统固有的季节性。对模型结果最敏感的参数包括野鸟恢复和环境传播。我们发现,即使其他种群的传播参数较低,野鸟迁徙也能驱动这些种群的感染数量,而且环境传播也是感染的重要驱动因素。
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来源期刊
CiteScore
3.90
自引率
8.60%
发文量
123
审稿时长
7.5 months
期刊介绍: The Bulletin of Mathematical Biology, the official journal of the Society for Mathematical Biology, disseminates original research findings and other information relevant to the interface of biology and the mathematical sciences. Contributions should have relevance to both fields. In order to accommodate the broad scope of new developments, the journal accepts a variety of contributions, including: Original research articles focused on new biological insights gained with the help of tools from the mathematical sciences or new mathematical tools and methods with demonstrated applicability to biological investigations Research in mathematical biology education Reviews Commentaries Perspectives, and contributions that discuss issues important to the profession All contributions are peer-reviewed.
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