Hogan Alexandra B, Glass Kathryn, Moore Hannah C, Anderssen Robert S
National Centre for Epidemiology and Population Health, Building 62, Corner Mills and Eggleston Roads, The Australian National University, Canberra ACT 2601, Australia.
National Centre for Epidemiology and Population Health, Building 62, Corner Mills and Eggleston Roads, The Australian National University, Canberra ACT 2601, Australia.
Theor Popul Biol. 2016 Aug;110:78-85. doi: 10.1016/j.tpb.2016.04.003. Epub 2016 May 4.
Respiratory syncytial virus (RSV) is the main cause of lower respiratory tract infections in children. Whilst highly seasonal, RSV dynamics can have either one-year (annual) or two-year (biennial) cycles. Furthermore, some countries show a 'delayed biennial' pattern, where the epidemic peak in low incidence years is delayed. We develop a compartmental model for RSV infection, driven by a seasonal forcing function, and conduct parameter space and bifurcation analyses to document parameter ranges that give rise to these different seasonal patterns. The model is sensitive to the birth rate, transmission rate, and seasonality parameters, and can replicate RSV dynamics observed in different countries. The seasonality parameter must exceed a threshold for the model to produce biennial cycles. Intermediate values of the birth rate produce the greatest delay in these biennial cycles, while the model reverts to annual cycles if the duration of immunity is too short. Finally, the existence of period doubling and period halving bifurcations suggests robust model dynamics, in agreement with the known regularity of RSV outbreaks. These findings help explain observed RSV data, such as regular biennial dynamics in Western Australia, and delayed biennial dynamics in Finland. From a public health perspective, our findings provide insight into the drivers of RSV transmission, and a foundation for exploring RSV interventions.
呼吸道合胞病毒（RSV）是儿童下呼吸道感染的主要病因。虽然RSV具有高度季节性，但其动态变化可能呈现一年（年度）或两年（两年一次）的周期。此外，一些国家呈现出“延迟两年一次”的模式，即低发病率年份的流行高峰会延迟出现。我们构建了一个由季节性强迫函数驱动的RSV感染 compartmental 模型，并进行参数空间和分岔分析，以记录导致这些不同季节性模式的参数范围。该模型对出生率、传播率和季节性参数敏感，能够复制在不同国家观察到的RSV动态变化。季节性参数必须超过一个阈值，模型才能产生两年一次的周期。出生率的中间值会使这些两年一次的周期延迟最大，而如果免疫持续时间过短，模型则会恢复为年度周期。最后，倍周期分岔和周期减半分岔的存在表明模型动力学具有稳健性，这与已知的RSV爆发规律一致。这些发现有助于解释观察到的RSV数据，如西澳大利亚的定期两年一次动态变化以及芬兰的延迟两年一次动态变化。从公共卫生的角度来看，我们的发现为RSV传播的驱动因素提供了见解，并为探索RSV干预措施奠定了基础。
