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Geo-spatial hotspots of hemorrhagic fever with renal syndrome and genetic characterization of Seoul variants in Beijing, China.

ABSTRACT: BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China, and has extended from rural areas to cities recently. Beijing metropolis is a novel affected region, where the HFRS incidence seems to be diverse from place to place. METHODOLOGY/PRINCIPAL FINDINGS: The spatial scan analysis based on geographical information system (GIS) identified three geo-spatial "hotspots" of HFRS in Beijing when the passive surveillance data from 2004 to 2006 were used. The Relative Risk (RR) of the three "hotspots" was 5.45, 3.57 and 3.30, respectively. The Phylogenetic analysis based on entire coding region sequence of S segment and partial L segment sequence of Seoul virus (SEOV) revealed that the SEOV strains circulating in Beijing could be classified into at least three lineages regardless of their host origins. Two potential recombination events that happened in lineage #1 were detected and supported by comparative phylogenetic analysis. The SEOV strains in different lineages and strains with distinct special amino acid substitutions for N protein were partially associated with different spatial clustered areas of HFRS. CONCLUSION/SIGNIFICANCE: Hotspots of HFRS were found in Beijing, a novel endemic region, where intervention should be enhanced. Our data suggested that the genetic variation and recombination of SEOV strains was related to the high risk areas of HFRS, which merited further investigation.

SUBMITTER: Zuo SQ

PROVIDER: S-EPMC3019113 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Geo-spatial hotspots of hemorrhagic fever with renal syndrome and genetic characterization of Seoul variants in Beijing, China.

Zuo Shu-Qing SQ Fang Li-Qun LQ Zhan Lin L Zhang Pan-He PH Jiang Jia-Fu JF Wang Li-Ping LP Ma Jia-Qi JQ Wang Bing-Cai BC Wang Ri-Min RM Wu Xiao-Ming XM Yang Hong H Cao Zhi-Wei ZW Cao Wu-Chun WC

PLoS neglected tropical diseases 20110111 1

<h4>Background</h4>Hemorrhagic fever with renal syndrome (HFRS) is highly endemic in mainland China, and has extended from rural areas to cities recently. Beijing metropolis is a novel affected region, where the HFRS incidence seems to be diverse from place to place.<h4>Methodology/principal findings</h4>The spatial scan analysis based on geographical information system (GIS) identified three geo-spatial "hotspots" of HFRS in Beijing when the passive surveillance data from 2004 to 2006 were used ...[more]

PMID: 21264354

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Project description:Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused mainly by two hantaviruses in China: Hantaan virus and Seoul virus. Environmental factors can significantly affect the risk of contracting hantavirus infections, primarily through their effects on rodent population dynamics and human-rodent contact. We aimed to clarify the environmental risk factors favoring rodent-to-human transmission to provide scientific evidence for developing effective HFRS prevention and control strategies. The 10-year (2006-2015) field surveillance data from the rodent hosts for hantavirus, the epidemiological and environmental data extracted from satellite images and meteorological stations, rodent-to-human transmission rates and impacts of the environment on rodent community composition were used to quantify the relationships among environmental factors, rodent species and HFRS occurrence. The study included 709 cases of HFRS. Rodent species in Chenzhou, a hantavirus hotspot, comprise mainly Rattus norvegicus, Mus musculus, R. flavipectus and some other species (R. losea and Microtus fortis calamorum). The rodent species played different roles across the various land types we examined, but all of them were associated with transmission risks. Some species were associated with HFRS occurrence risk in forest and water bodies. R. norvegicus and R. flavipectus were associated with risk of HFRS incidence in grassland, whereas M. musculus and R. flavipectus were associated with this risk in built-on land. The rodent community composition was also associated with environmental variability. The predictive risk models based on these significant factors were validated by a good-fit model, where: cultivated land was predicted to represent the highest risk for HFRS incidence, which accords with the statistics for HFRS cases in 2014-2015. The spatial heterogeneity of HFRS disease may be influenced by rodent community composition, which is associated with local environmental conditions. Therefore, future work should focus on preventing HFRS is moist, warm environments.

Project description:BackgroundHemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China.MethodsThe annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables.ResultsA distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51).ConclusionThe temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang.

Dataset Information

Geo-spatial hotspots of hemorrhagic fever with renal syndrome and genetic characterization of Seoul variants in Beijing, China.

Publications

Geo-spatial hotspots of hemorrhagic fever with renal syndrome and genetic characterization of Seoul variants in Beijing, China.

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