Abstract
Historically, Jiangxi province has had the largest HFRS burden in China. However, thus far, the comprehensive understanding of the spatiotemporal distributions of HFRS is limited in Jiangxi. In this study, seasonal decomposition analysis, spatial autocorrelation analysis, and space–time scan statistic analyses were performed to detect the spatiotemporal dynamics distribution of HFRS cases from 2005 to 2018 in Jiangxi at the county scale. The epidemic of HFRS showed the characteristic of bi-peak seasonality, the primary peak in winter (November to January) and the second peak in early summer (May to June), and the amplitude and the magnitude of HFRS outbreaks have been increasing. The results of global and local spatial autocorrelation analysis showed that the HFRS epidemic exhibited the characteristic of highly spatially heterogeneous, and Anyi, Fengxin, Yifeng, Shanggao, **g’an and Gao’an county were hot spots areas. A most likely cluster, and two secondary likely clusters were detected in 14-years duration. The higher risk areas of the HFRS outbreak were mainly located in Jiangxi northern hilly state, spreading to Wuyi mountain hilly state as time advanced. This study provided valuable information for local public health authorities to design and implement effective measures for the control and prevention of HFRS.
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Introduction
Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne infectious disease caused by hantaviruses in the Bunyaviridae family1. Transmission of hantavirus to humans occurs via inhalation of aerosolized viral particles present in the urine, feces, and saliva excreted into the environment by rodents infected with it2. In China, the major causative agents of HFRS are Hantaan virus (HTNV) and Seoul virus (SEOV), whose natural rodents hosts are respectively striped field mice (A. agrarius) and Norway rats (R. norvegicus)3,4. So far, China remains the most endemic country, and there were more than 11,000 HFRS cases reported annually from 2016 to 20185.
Jiangxi province, which is located in the southern bank of the middle and lower reaches of the Yangzi River, is one of the most serious HFRS endemic areas of China. Since the first case of HFRS was reported in Pengze county in 1961, the HFRS epidemic has rapidly spread to 6 counties in the 1960s, 39 counties in the 1970s, 65 counties in the 1980s, and 88 counties in the 1990s. The number of HFRS cases has also risen sharply, and reached a peak in 1985, with an incidence of 21/100,000 persons. The epidemic of HFRS has expanded throughout the central and northern Jiangxi and reached Ningdu county, Ganzhou city, in the south6. Jiangxi currently remains one of the provinces with the highest HFRS incidence during recent years according to the national HFRS surveillance data11,12,14,15,16,17,18,19. However, the dynamics spatiotemporal distributions of HFRS in Jiangxi have not yet been explored systematically. So this study aims to explore the dynamics of spatiotemporal distributions based on the case surveillance data from 2005 to 2018 at the county scale in Jiangxi, and providing valuable scientific support for HFRS monitoring and control.
Materials and methods
Study areas
Jiangxi (24°29′14″–30°04′44″ N, 113°34′36″–118°28′58″ E) lies in southeastern China, with an approximate area of 16.5 thousand km2, and population of 44.56 million in 2010, including 11 cities and 100 counties (Fig. 1). Jiangxi belongs to a humid subtropical climate, with annual rainfall, annual average temperature, and annual average sunshine ranging from 1,341 to 1,943 mm, 16.2 to 19.7 °C, 1,473 to 2,077 h, respectively20.
The location of the study area. (A) Location of Jiangxi province, in China. (B) Administrative division of the study area(1. Donghu; 2. ** towards Poyang lake, which has formed a huge basin opening to the north20. In historical literatures, Jiangxi was often divided into three zoogeographic regions and five zoogeographic states: Jiangxi northern plain region (including the plain state bordering on rivers and lakes and Jiangxi northern hilly state), Jiangxi central mountainous hilly region (including Wuyi mountainous hilly state and Wugong mountainous hilly state), and Jiangxi southern mountainous region (including Jiangxi southern mountainous state) (Fig. 1).
Data source
Reported daily HFRS data for the period of 2005 to 2018 were extracted from CISDCP in the Chinese Center for Disease Control and Prevention (China CDC). The gathered information about individual HFRS cases included the age, occupation onset and confirmation date, case category, and residential address. The diagnosis of HFRS cases referred to the ‘Diagnostic criteria for epidemic hemorrhagic fever’ (WS278–2008) of China (https://www.nhc.gov.cn/wjw/s9491/200802/39043.shtml). HFRS cases were aggregated and geocoded to the corresponding county in ArcGIS (Version 10.4, ESRI Inc., Redlands, CA, USA). The base map was acquired from the geospatial data cloud (https://www.gscloud.cn/). The population size in every county was issued by the National Bureau of Statistics of the People’s Republic of China (https://www.stats.gov.cn/tjsj/ndsj/). Clinically diagnosed and laboratory-confirmed cases were included in our study. And 148 cases were excluded due to invalid addresses (incomplete, incorrect or outside study area) or suspected cases.
Spatiotemporal cluster analysis
A seasonal-trend decomposition of time series analysis was performed to explore the various characteristics of periodicity and seasonality in R software (Version 3.1 AT&T BellLaboratories, Auckland, New Zealand). A global spatial autocorrelation analysis and a Local Indicators of Spatial Association (LISA) analysis were conducted in ArcGIS software (Version 10.4, ESRI Inc., Redlands, CA, USA) to visualize the global and local spatial clustering of HFRS cases in Jiangxi from 2005 to 2018. Global Moran’s I Index (ranged from − 1 to 1) was used to analyze global spatial autocorrelation. Moran’s Index = 0 implied a random spatial distribution. Moran’s I Index < 0 implied a dispersing spatial distribution, and Moran’s I Index > 0 implied a clustering spatial distribution. Local Moran’s I was calculated to explore significant hot spots (High–High), cold spots (Low–Low), and outliers (High–Low and Low–High)21. A Kulldorff’s spatiotemporal scan statistical analysis was used to identify the spatiotemporal clusters of HFRS cases in Jiangxi in SaTScan Software (Version 9.4, Martin Kulldorff, National Cancer Institute, Bethesda, MD, USA)22. The discrete Poisson probability model by a circular window with a radius was used for scanning. The maximum of the spatial and temporal size were all defined as 25%. A P < 0.05 was considered to be significant.
The maps were made in ArcGIS software (Version 10.4, ESRI Inc., Redlands, CA, USA).
Ethics approval
Ethical approval for the research was granted by the Chinese Center for Disease Control and Prevention Ethics Committee (No. 2012CB955504). This study didn’t collect patients’ samples, and the data obtained from the China Information System for Disease Control and Prevention (CISDCP) were anonymized so that subjects could not be identified. Therefore, the ethics committee agreed that no informed consent was needed from patients. All methods in our study were used in accordance with the relevant guidelines and regulations.
Results
Descriptive statistics
A total of 7,203 HFRS cases with a case fatality rate of 1.34%, were reported in Jiangxi from 2005 to 2018. The annual case number ranged from 335 in 2009 to 683 in 2018, and presented a total uptrend during the 14-year period. Male cases were 4,950 (68.7%), and the male-to-female ratio (not significant) ranged from 2.9:1 in 2008 to 1.9:1 in 2018. A total of 74.4% of HFRS cases occurred in individuals aged from 16 to 60 years old, and different age group ratios of different years were significantly different (χ2 = 217.0, p = 0.000). The majority of HFRS cases were farmers (67.2%), followed by students (8.4%). Different occupational ratios of different years existed significant differences (χ2 = 180.7, p = 0.000) (Table 1).
The cumulative number of HFRS cases in each county ranged from 0 to 1,060, among which Shanggao county had the highest annual number of 284 cases. The cumulative incidence rate of HFRS varied between counties (Fig. 2). The top ten counties with the highest HFRS incidence rates were Shanggao (324.46/100,000), Yifeng (290.46/100,000), An’yi (135.41/100,000), Gao’an (120.87/100,000), Fengxin (88.40/100,000), Qianshan (66.46/100,000), Hengfeng (63.47/100,000), Yushan (58.96/100,000) and ** countries. Water Sci. Technol. 63, 1899–1905. https://doi.org/10.2166/wst.2011.413 (2011)." href="/article/10.1038/s41598-020-70761-0#ref-CR42" id="ref-link-section-d220679008e2734">42. All the above factors in the region provided human beings with fewer opportunities for exposure to rodent hosts.
Some limitations should be considered when interpreting our findings. Firstly, the bias could exist in this study because the HFRS cases did not differentiate HTNV from SEOV infections, and came from the passive surveillance system called CISDCP. Secondly, social factors and urbanization level might have an important impact on the epidemic process of HFRS but were not included in the analysis due to data unavailable. Finally, specific species of rodent populations were not characterized in our study area.
In conclusion, this study has analyzed the spatiotemporal characteristics of HFRS comprehensively in Jiangxi from 2005 to 2018. We found that HFRS cases were aggregated in Jiangxi northern hilly state, spreading to Wuyi mountain hilly state as time advanced. Therefore, more interventions should be implemented for the prevention and control of HFRS in the future, including animal hosts surveillance, causative agents detection, medical training, and health promotion. Most importantly, further research efforts should be undertaken to explore the potentially influential factors and etiological surveillance in the next step to provide more scientific evidence for the prevention and control of HFRS.
Data availability
All data involved in the study are available from Q. Liu and S.E.C.
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Acknowledgements
This study was supported by the National Science and Technology Major Project (No. 2017ZX10303404005, URLs: https://www.nmp.gov.cn/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank all the doctors and staff who have collected and reported HFRS cases.
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All authors have approved the final version of the manuscript, and have significant contributions to the work. S.Y., Y.G., X.L., and Q. Liu conceived the idea for this study, performed the statistical analysis, and contributed to the first draft and final version of this paper. C.Y.Y, X.Q. L., Y.Q.L., S.E.C. were responsible for data collection, data interpretation, and manuscript review. S.M. and Y.J.Y participated in revising the study.
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Yang, S., Gao, Y., Liu, X. et al. Spatiotemporal dynamics of hemorrhagic fever with renal syndrome in Jiangxi province, China. Sci Rep 10, 14291 (2020). https://doi.org/10.1038/s41598-020-70761-0
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DOI: https://doi.org/10.1038/s41598-020-70761-0
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