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Human metapneumovirus (HMPV)
have similar symptoms to those caused by respiratory syncytial virus (RSV). The modes of transmission and
dynamics of these epidemics still remain poorly understood. Climatic factors
have long been suspected to be implicated in impacting on the number of cases
for these epidemics. Currently, only a few models satisfactorily capture the
dynamics of time series data of these two viruses. In this study, we used a
negative binomial model to investigate the relationship between RSV and HMPV
while adjusting for climatic factors. We specifically aimed at establishing the
heterogeneity in the autoregressive effect to account for the influence between
these viruses. Our findings showed that RSV contributed to the severity of
HMPV. This was achieved through comparison of models of various structures,
including those with and without interaction between climatic cofactors. The
study has improved our understanding of the dynamics of RSV and HMPV in
relation to climatic cofactors; thereby, setting a platform to devise better
intervention measures to combat the epidemics. We conclude that, preventing and
controlling RSV infection subsequently reduces the incidence of HMPV.

人类偏肺病毒（Human metapneumovirus, HMPV）引发的临床症状与呼吸道合胞病毒（respiratory syncytial virus, RSV）感染高度相似。目前，这两类病毒所引发流行病的传播途径与流行动力学特征仍未得到充分阐释。长期以来，学界推测气候因素会对这类流行病的病例数产生显著影响。当前仅有少数模型能够较好地复现这两种病毒的时间序列数据动态变化规律。本研究采用负二项模型（negative binomial model），在校正气候因素混杂影响的前提下，探究RSV与HMPV之间的关联。本研究的核心目标在于明确自回归效应（autoregressive effect）的异质性，以刻画两类病毒间的相互影响。通过对比包含与不包含气候协变量交互项的多种模型结构，本研究证实RSV感染会加重HMPV的病情严重程度。本研究增进了学界对RSV与HMPV流行动力学及其与气候协变量关联的理解，为制定更高效的流行病防控干预措施搭建了理论基础。最终研究结论表明：防控RSV感染可有效降低HMPV的新发感染率。