Background The epidemiological characteristics of influenza vary among districts and regions. Many studies exploit influenza-like illness surveillance data; however, more accurate demographic and spatial-temporal distributions of influenza can be achieved by using local influenza incidence data.
Objective This study depicts demographic and spatial-temporal distributions of influenza cases in Huangpu District of Shanghai.
Methods Descriptive epidemiological method was utilized to describe the epidemiological characteristics of 2 500 influenza cases in Huangpu District of Shanghai sourced from the information platform of Chinese Center for Disease Control and Prevention. The onset time of all cases was between 1 April, 2013 and 31 March, 2019. An influenza cycle was defined as from 1 April to 31 March next calendar year, and 6 influenza cycles were included in this study. Flu activity peaked between December and February next year, and between July and August. The proportions of influenza A and B cases in different influenza cycles, populations, and subdistricts were calculated. ArcGIS 10.1 was used to establish a database of influenza incidences in each residential committee and geographic information about 23 hospitals in Huangpu District. Spatial autocorrelation and hot spot analysis were performed to visualize the geographic hot spot distribution of influenza cases.
Results The average influenza incidence was 64.14 per 105. Winter peaks were seen during each influenza season and summer peaks were observed in three seasons of 2014-2015, 2015-2016, and 2017-2018. Of all the cases, influenza A, mainly subtype H3, accounted for 71.52%, whereas influenza B, mainly Yamagata linage virus, did 28.48%. There were significant differences between the proportions of influenza A and B in each influenza cycle (P=0.003). During the influenza cycle of 2018-2019, the proportion of influenza A was significantly higher in epidemic season than that in non-epidemic season (P=0.002). The overall male to female ratio of the influenza cases was 1:1.25 and the median age was 47 years. Significant differences between the proportions of influenza A and B cases were shown among age groups (P < 0.001) and occupation groups (P=0.031). Influenza A infection cases were more in residents aged ≥ 65 years, while influenza B infection cases were more in those aged 5-17 years. Workers topped in influenza A cases (75.47%), while students did in influenza B cases (37.15%). Significant positive spatial autocorrelations of influenza cases were found within Huangpu District (Moran's I=0.42, P < 0.001). Hot spots for influenza A were detected in 29 residential committees in eastern area and 6 in western area of the district, where Gi ranged from -2.13 to 7.65. Hot spots for influenza B were seen in 24 residential committees in eastern area, where Gi ranged from -2.19 to 7.68. Along with the distribution of hospitals, those hot spots were close to two national influenza sentinel hospitals.
Conclusion Influenza A is prevalent in Huangpu District of Shanghai, and students are more sensitive to influenza B. Influenza control strategies, therefore, should focus on influenza clusters among students. There are spatial autocorrelations between the influenza cases, and influenza hot spots are distributed in eastern and western areas of the study area.
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