Journal Article

Spatiotemporal pattern of hemorrhagic fever with renal syndrome and driving factors in Shandong Province of China, 2018–2024

Guo, Suying, Xu, Jing, Huang, Shiyi, Li, Shizhu, Zhang, Yuwei, Duan, Qing, Li, Ruixiao, Li, Yan, Lv, Shan, Liu, Ti, Li, Yinlong, Kou, Zengqiang

2026

Overview

Hemorrhagic fever with renal syndrome (HFRS) is a widespread zoonotic disease transmitted by rodents, posing a serious public health threat in People's Republic of China. Due to the higher incidence of HFRS occurred in Shandong Province, this study aims to understand the spatiotemporal pattern of HFRS, identify the driving factors and predict potential high-risk areas in Shandong Province, to provide guidance for public health policy making. Case information on HFRS occurred in Shandong Province from 2018 to 2024 was collected from the China Information System for Disease Control and Prevention (CISDCP). Incidence rate of HFRS was calculated monthly and annually to explore its preliminary distribution trend. Spatiotemporal scanning analysis was used to determine the temporal and spatial clustering characteristics of HFRS cases. The maximum entropy (MaxEnt) model was employed to explore the major factors influencing HFRS and predict high-risk areas of HFRS in Shandong Province. From 2018 to 2024, a total of 4,837 cases of HFRS were reported in Shandong Province, with the incidence rate showing a fluctuating downward trend. The peak incidence period occurred annually from October to December. Spatiotemporal scanning analysis showed the first cluster involved 29 counties across 5 prefecture-level cities in eastern Shandong Province, spanning October to November 2018. The second cluster involved 16 counties across 6 prefecture-level cities in central Shandong Province, spanning November to December 2021. The third cluster area involved 4 counties across 2 prefecture-level cities in southwestern Shandong Province, spanning March to April 2018. The fourth cluster area was located in Shanghe County, north of Jinan City, spanning November to December 2021. When optimizing the MaxEnt model, the optimal performance was achieved with the feature class (FC) set to linear, quadratic, hinge, product, and threshold (LQHPT) and the regularization multiplier (RM) set to 0.2. Yearly average air temperature, normalized difference vegetation index, yearly average relative humidity and yearly average sunshine duration were identified as the main factors influencing the occurrence of HFRS. The risk prediction map showed that high-risk areas for HFRS were primarily concentrated in the eastern and central regions of Shandong Province, covering an area of 26682.92 square kilometers, accounting for 16.90% of the province's total area. HFRS in Shandong Province exhibited obvious spatiotemporal patterns and was influenced by multiple factors, including temperature, vegetation, humidity and sunshine. These findings highlight the need for health authorities to integrate environmental and socio-economic considerations into the design of strategy or countermeasures against HFRS, particularly during high-incidence season and in high-risk areas.

• Publisher: PLOS,Public Library of Science (PLoS)
• Subject: Animals / Biology and Life Sciences / China - epidemiology / Computer and Information Sciences / Earth Sciences / Engineering and Technology / Female / Hemorrhagic Fever with Renal Syndrome - epidemiology / Hemorrhagic Fever with Renal Syndrome - virology / Humans / Incidence / Male / Medicine and Health Sciences / People and Places / Risk Factors / Social Sciences / Spatio-Temporal Analysis