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Abstract:

Exploring the quantitative impact of short-term weather variability intensity (SWVI) on influenza incidence in Hubei Prov⁃ ince is of significant importance for conducting early risk warning and formulating prevention policies. Based on the influenza inci⁃ dence data and meteorological station observation, an index of SWVI has been built, which can measure the cumulative changes over a short-term in minimum temperature between two consecutive weeks. Based on the Distributed Lag Nonlinear Model (DLNM), the rela⁃ tion between SWVI index and influenza incidence risk was evaluated and a set of method for level classification of influenza incidence risk was developed. The results show that the intra-annual variation of number of Influenza-Like Illnesses (ILI) exhibited bimodal struc⁃ ture, with the first peak occurring in autumn and winter, and the second peak appearing in early summer months. The SWVI index also exhibited a bimodal distribution, but the peak occurring earlier than the peak of ILI. From November to March of the following year, SWVI index had a strong indicative significance for the change of ILI morbidity. In this period, when SWVI reaches 8.0 ℃, the cumula tive relative risk (RR) of ILI incidence at the same period and the next week was 1.16 (95% confidence interval: 1.087-1.250). In addition, SWVI index also had an indirect effect on the risk of ILI with a lag of 4-9 weeks, which was less affected than the immediate effect, but lasted longer. Using the percentile method and the relationship model between the SWVI index and the ILI incidence risk, a set of influenza risk early warning method was established. When the SWVI index was greater than or equal to 8.0 ℃, the influenza incidence reached high risk level

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