Abstract
Influenza is a major cause of morbidity and mortality worldwide, as well as in China. Knowledge of the spatial and temporal characteristics of influenza is important in evaluating and developing disease control programs. This study aims to describe an accurate spatiotemporal pattern of influenza at the prefecture level and explore the risk factors associated with influenza incidence risk in mainland China from 2005 to 2018. The incidence data of influenza were obtained from the Chinese Notifiable Infectious Disease Reporting System (CNIDRS). The Besag York Mollié (BYM) model was extended to include temporal and space-time interaction terms. The parameters for this extended Bayesian spatiotemporal model were estimated through integrated nested Laplace approximations (INLA) using the package R-INLA in R. A total of 702,226 influenza cases were reported in mainland China in CNIDRS from 2005–2018. The yearly reported incidence rate of influenza increased 15.6 times over the study period, from 3.51 in 2005 to 55.09 in 2008 per 100,000 populations. The temporal term in the spatiotemporal model showed that much of the increase occurred during the last 3 years of the study period. The risk factor analysis showed that the decreased number of influenza vaccines for sale, the new update of the influenza surveillance protocol, the increase in the rate of influenza A (H1N1)pdm09 among all processed specimens from influenza-like illness (ILI) patients, and the increase in the latitude and longitude of geographic location were associated with an increase in the influenza incidence risk. After the adjusting for fixed covariate effects and time random effects, the map of the spatial structured term shows that high-risk areas clustered in the central part of China and the lowest-risk areas in the east and west. Large space-time variations in influenza have been found since 2009. In conclusion, an increasing trend of influenza was observed from 2005 to 2018. The insufficient flu vaccine supplements, the newly emerging influenza A (H1N1)pdm09 and expansion of influenza surveillance efforts might be the major causes of the dramatic changes in outbreak and spatio-temporal epidemic patterns. Clusters of prefectures with high relative risks of influenza were identified in the central part of China. Future research with more risk factors at both national and local levels is necessary to explain the changing spatiotemporal patterns of influenza in China.
Highlights
Influenza is associated with notable mortality and morbidity worldwide, as well as in China[1,2,3]
Of the 2,702,226 influenza cases that were reported in mainland China via Chinese Notifiable Infectious Diseases Reporting System (CNIDRS)
Based on the incidence data of influenza gained from the Chinese Notifiable Infectious Disease Reporting System, we used the Bayesian spatiotemporal model in this study to assess the space-time patterns of the influenza epidemic at the prefecture level in mainland China from 2005 to 2018 and explored several factors that may be associated with the changing spatial and temporal patterns in the influenza incidence risk
Summary
Influenza is associated with notable mortality and morbidity worldwide, as well as in China[1,2,3]. New emerging influenza virus types and subtypes, such as avian influenza A H5N111–14, influenza A (H1N1)pdm0915–17, and influenza A H7N918,19, have been reported continuously in China, the disease burden of influenza has been dominated by A(H3N2), A(H1N1)pdm2009 influenza viruses, pre-pandemic A(H1N1) or influenza B in recent years, which account for the majority of cases[20]. The influenza A(H1N1)pdm2009 virus was first introduced to mainland China on May 9, 200921, and has been one of the dominant viruses in the seasonal influenza epidemics since [20]. The Sentinel Influenza-Like Illness (ILI) Surveillance System and the Chinese Notifiable Infectious Diseases Reporting System (CNIDRS), have been widely used for influenza surveillance and research in China[16,30,33,34]
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