Exploration of influenza incidence prediction model based on meteorological factors in Lanzhou, China, 2014–2017

Meixia Du, Hai Zhu, Xiaochun Yin, Ting Ke, Yonge Gu, Sheng Li, Yongjun Li and Guisen Zheng

PLOS ONE, 2022, vol. 17, issue 12, 1-14

Abstract: Humans are susceptible to influenza. The influenza virus spreads quickly and behave seasonally. The seasonality and spread of influenza are often associated with meteorological factors and have spatio-temporal differences. Based on the influenza cases and daily average meteorological factors in Lanzhou from 2014 to 2017, this study firstly aimed to analyze the characteristics of influenza incidence in Lanzhou and the impact of meteorological factors on influenza activities. Then, SARIMA(X) models for the prediction were established. The influenza cases in Lanzhou from 2014 to 2017 was more male than female, and the younger the age, the higher the susceptibility; the epidemic characteristics showed that there is a peak in winter, a secondary peak in spring, and a trough in summer and autumn. The influenza cases in Lanzhou increased with increasing daily pressure, decreasing precipitation, average relative humidity, hours of sunshine, average daily temperature and average daily wind speed. Low temperature was a significant driving factor for the increase of transmission intensity of seasonal influenza. The SARIMAX (1,0,0)(1,0,1)[12] multivariable model with average temperature has better prediction performance than the university model. This model is helpful to establish an early warning system, and provide important evidence for the development of influenza control policies and public health interventions.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0277045

DOI: 10.1371/journal.pone.0277045

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