Urbanization-Related Environmental Factors and Hemorrhagic Fever with Renal Syndrome: A Review Based on Studies Taken in China

Investigating the impact of climatic and environmental factors on HFRS prevalence in Anhui Province, China, using satellite and reanalysis data

Introduction

Hemorrhagic Fever with Renal Syndrome (HFRS) is the most commonly diagnosed zoonosis in Asia. Despite taking various preventive measures, HFRS remains prevalent across multiple regions in China. This study aims to investigate the impact of climatic and environmental factors on the prevalence of HFRS in Anhui Province, China, utilizing satellite and reanalysis data.

Methods

We collect monthly HFRS data from Anhui Province spanning 2005 to 2019 and integrated MODIS satellite datasets and ERA5 reanalysis data, including variables such as precipitation, temperature, humidity, solar radiation, aerosol optical depth (AOD), and Normalized Difference Vegetation Index (NDVI). Continuous wavelet transform, Spearman correlation analysis, and Poisson regression analysis are employed to assess the association between climatic and environmental factors and HFRS cases.

Results

Our findings reveal that HFRS cases predominantly occur during the spring and winter seasons, with the highest peak intensity observed in a 9-year cycle. Notably, the monthly average relative humidity exhibits a Spearman correlation coefficient of 0.404 at a 4-month lag, taking precedence over other contributing factors. Poisson regression analysis elucidates that NDVI at a 2-month lag, mean temperature (T) and solar radiation (SR) at a 4-month lag, precipitation (P), relative humidity (RH), and AOD at a 5-month lag exhibit the most robust explanatory power for HFRS occurrence. Moreover, the developed predictive model exhibiting commendable accuracy.

Discussion

This study provides key evidence for understanding how climatic and environmental factors influence the transmission of HFRS at the provincial scale. Insights from this research are critical for formulating effective preventive strategies and serving as a resource for HFRS prevention and control efforts.

Enhancing infectious disease prediction model selection with multi-objective optimization: an empirical study

As the pandemic continues to pose challenges to global public health, developing effective predictive models has become an urgent research topic. This study aims to explore the application of multi-objective optimization methods in selecting infectious disease prediction models and evaluate their impact on improving prediction accuracy, generalizability, and computational efficiency. In this study, the NSGA-II algorithm was used to compare models selected by multi-objective optimization with those selected by traditional single-objective optimization. The results indicate that decision tree (DT) and extreme gradient boosting regressor (XGBoost) models selected through multi-objective optimization methods outperform those selected by other methods in terms of accuracy, generalizability, and computational efficiency. Compared to the ridge regression model selected through single-objective optimization methods, the decision tree (DT) and XGBoost models demonstrate significantly lower root mean square error (RMSE) on real datasets. This finding highlights the potential advantages of multi-objective optimization in balancing multiple evaluation metrics. However, this study's limitations suggest future research directions, including algorithm improvements, expanded evaluation metrics, and the use of more diverse datasets. The conclusions of this study emphasize the theoretical and practical significance of multi-objective optimization methods in public health decision support systems, indicating their wide-ranging potential applications in selecting predictive models.

Epidemiology of Hemorrhagic Fever with Renal Syndrome and Host Surveillance in Zhejiang Province, China, 1990-2021

Hemorrhagic fever with renal syndrome (HFRS) is caused by hantaviruses (HVs) and is endemic in Zhejiang Province, China. In this study, we aimed to explore the changing epidemiology of HFRS cases and the dynamics of hantavirus hosts in Zhejiang Province. Joinpoint regression was used to analyze long-term trends in the incidence of HFRS. The comparison of animal density at different stages was conducted using the Mann-Whitney Test. A comparison of HV carriage rates between stages and species was performed using the chi-square test. The incidence of HFRS shows a continuous downward trend. Cases are widely distributed in all counties of Zhejiang Province except Shengsi County. There was a high incidence belt from west to east, with low incidence in the south and north. The HFRS epidemic showed two seasonal peaks in Zhejiang Province, which were winter and summer. It showed a marked increase in the age of the incidence population. A total of 23,073 minibeasts from 21 species were captured. Positive results were detected in the lung tissues of 14 rodent species and 1 shrew species. A total of 80% of the positive results were from striped field mice and brown rats. No difference in HV carriage rates between striped field mice and brown rats was observed (χ2 = 0.258, p = 0.611).

Epidemiological characteristics and prediction model construction of hemorrhagic fever with renal syndrome in Quzhou City, China, 2005-2022

Background

Hemorrhagic fever with renal syndrome (HFRS) is one of the 10 major infectious diseases that jeopardize human health and is distributed in more than 30 countries around the world. China is the country with the highest number of reported HFRS cases worldwide, accounting for 90% of global cases. The incidence level of HFRS in Quzhou is at the forefront of Zhejiang Province, and there is no specific treatment for it yet. Therefore, it is crucial to grasp the epidemiological characteristics of HFRS in Quzhou and establish a prediction model for HFRS to lay the foundation for early warning of HFRS.

Methods

Descriptive epidemiological methods were used to analyze the epidemic characteristics of HFRS, the incidence map was drawn by ArcGIS software, the Seasonal AutoRegressive Integrated Moving Average (SARIMA) and Prophet model were established by R software. Then, root mean square error (RMSE) and mean absolute error (MAE) were used to evaluate the fitting and prediction performances of the model.

Results

A total of 843 HFRS cases were reported in Quzhou City from 2005 to 2022, with the highest annual incidence rate in 2007 (3.93/100,000) and the lowest in 2022 (1.05/100,000) (P trend<0.001). The incidence is distributed in a seasonal double-peak distribution, with the first peak from October to January and the second peak from May to July. The incidence rate in males (2.87/100,000) was significantly higher than in females (1.32/100,000). Farmers had the highest number of cases, accounting for 79.95% of the total number of cases. The incidence is high in the northwest of Quzhou City, with cases concentrated on cultivated land and artificial land. The RMSE and MAE values of the Prophet model are smaller than those of the SARIMA (1,0,1) (2,1,0)12 model.

Conclusion

From 2005 to 2022, the incidence of HFRS in Quzhou City showed an overall downward trend, but the epidemic in high-incidence areas was still serious. In the future, the dynamics of HFRS outbreaks and host animal surveillance should be continuously strengthened in combination with the Prophet model. During the peak season, HFRS vaccination and health education are promoted with farmers as the key groups.

Case Report: Hemorrhagic Fever with Renal Syndrome Complicated by Bilateral Subdural Hematoma

Hemorrhagic fever with renal syndrome (HFRS) is an acute, natural focal disease worldwide. Bilateral subdural hematoma (BSH) is a rare occurrence in patients with HFRS. A 51-year-old man was admitted with fever, headache, lower back pain, and reduced urine volume. The patient was diagnosed with HFRS accompanied by BSH, as evidenced by IgM and IgG antibodies for hantavirus that were positive, and abnormal blood test results and computed tomographic head scan. He recovered and was discharged after symptomatic treatment. Hemorrhagic fever with renal syndrome might present rare clinical manifestations with BSH. The early identification of this condition is crucial to an improved prognosis.