Analysis of spatial-temporal distribution characteristics and natural infection status of SFTS cases in Hefei from 2015 to 2021.

Background: To analyze the prevalence and spatial-temporal characteristics of severe fever with thrombocytopenia syndrome (SFTS), clustering mode of transmission, and the serological dynamic detection results in multiple areas in Hefei from 2015 to 2021, and to provide the basis for SFTS prevention and control.

Method: Case data were obtained from the Chinese Disease Control and Prevention Information System. Information on the clustering outbreak was obtained from the outbreak investigation and disposal report. Population latent infection rate information was obtained from field sampling in multiple-incidence counties in 2016 and 2021 by multi-stage random sampling. Epi data3.2 and SPSS 16.0 softwares were used to perform a statistical analysis of the data on SFTS cases, and QGIS 3.26 software was used to draw the incidence map with township (street) as unit.

Results: The an average annual reported incidence rate of SFTS in Hefei from 2015 to 2021 was 0.65/100,000, and the case fatality rate was 9.73%. The overall prevalence of SFTS epidemics in Hefei City showed a fluctuating upward trend from 2015 to 2021 (χtrends = 103.353, P < 0.001). Chaohu City, Feixi County, Feidong County and Lujiang County ranked the top 4 in the city in terms of average annual incidence rate. The number of epidemic-involved towns (streets) kept increasing ((χ = 47.640, P = 0.000)). Co-exposure to ticks accounted for the majority of clustered outbreaks and also human-to-human outbreaks. Population-based latent infection rate surveys were conducted in four SFTS multi-incidence counties, with 385 people surveyed in 2016 and 403 people surveyed in 2021, increasing the population-based latent infection rate from 6.75% to 10.91%, just as the incidence rate increased.

Conclusions: The incidence rate of SFTS in Hefei is obviously regional, with an expanding trend in the extent of the epidemic involved. Co-exposure to ticks accounted for the majority of clustered outbreaks and the latent infection rate cannot be ignored.