Environmental risk factors for haemorrhagic fever with renal syndrome in a French new epidemic area

Viel, Jean-François; Lefebvre, A.; Marianneau, Philippe; Joly, Daniel; Giraudoux, Patrick; Upegui, Erika; Tordo, Noël; Hoën, Bruno

doi:10.1017/s0950268810002062

Cited by 24 publications

(24 citation statements)

References 28 publications

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“…Genotype I includes strains from the Philippines, Thailand, Vietnam, Myanmar, Malaysia, Sri Lanka, and India (Cecilia et al, 2011; Dash et al, 2011). The India G11337 strain, which was isolated in 1961 and is therefore one of the oldest DENV-4 strains sampled, is genetically distinct and basal to other isolates of this clade.…”

Section: Resultsmentioning

confidence: 99%

Genetic and phenotypic characterization of sylvatic dengue virus type 4 strains

et al. 2012

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Four serotypes of dengue virus (DENV 1-4) currently circulate between humans and domestic/peridomestic Aedes mosquitoes, resulting in 100 million infections per year. All four serotypes emerged, independently, from sylvatic progenitors transmitted among non-human primates by arboreal Aedes mosquitoes. This study investigated the genetic and phenotypic changes associated with emergence of human DENV-4 from its sylvatic ancestors. Analysis of complete genomes of 3 sylvatic and 4 human strains revealed high conservation of both the 5′- and 3′-untranslated regions but considerable divergence within the open reading frame. Additionally, the two ecotypes did not differ significantly in replication dynamics in cultured human liver (Huh-7), monkey kidney (Vero) or mosquito (C6/36) cells, although significant inter-strain variation within ecotypes was detected. These findings are in partial agreement with previous studies of DENV-2, where human strains produced a larger number of progeny than sylvatic strains in human liver cells but not in monkey or mosquito cells.

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Section: Resultsmentioning

confidence: 99%

Genetic and phenotypic characterization of sylvatic dengue virus type 4 strains

et al. 2012

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“…The majority of epidemiologic or wildlife studies that incorporate remotely sensed data for vegetation monitoring have used spectral vegetation indices such as the Normalized Difference Vegetation Index, a vegetation greenness measure based on the contrast between red (absorbed by green plants) and infrared (reflected by green plants) reflected energy (Boone et al, 2000; Viel et al, 2006; Glass et al, 2007; Luis et al, 2009; Cao et al, 2011). We were interested in testing whether rodent dynamics are linked with variability in vegetation biomass and abundance, rather than vegetation phenology or greenness, and so chose to use remotely sensed GPP to estimate terrestrial vegetation production and resource availability at our study sites.…”

Section: Methodsmentioning

confidence: 99%

Prediction of Peromyscus Maniculatus (Deer Mouse) Population Dynamics in Montana, Usa, Using Satellite-Driven Vegetation Productivity and Weather Data

Loehman

Elias

Douglass

et al. 2012

Journal of Wildlife Diseases

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Deer mice (Peromyscus maniculatus) are the main reservoir host for Sin Nombre virus, the primary etiologic agent of hantavirus pulmonary syndrome in North America. Sequential changes in weather and plant productivity (trophic cascades) have been noted as likely catalysts of deer mouse population irruptions, and monitoring and modeling of these phenomena may allow for development of early-warning systems for disease risk. Relationships among weather variables, satellite-derived vegetation productivity, and deer mouse populations were examined for a grassland site east of the Continental Divide and a sage-steppe site west of the Continental Divide in Montana, USA. We acquired monthly deer mouse population data for mid-1994 through 2007 from long-term study sites maintained for monitoring changes in hantavirus reservoir populations, and we compared these with monthly bioclimatology data from the same period and gross primary productivity data from the Moderate Resolution Imaging Spectroradiometer sensor for 2000–06. We used the Random Forests statistical learning technique to fit a series of predictive models based on temperature, precipitation, and vegetation productivity variables. Although we attempted several iterations of models, including incorporating lag effects and classifying rodent density by seasonal thresholds, our results showed no ability to predict rodent populations using vegetation productivity or weather data. We concluded that trophic cascade connections to rodent population levels may be weaker than originally supposed, may be specific to only certain climatic regions, or may not be detectable using remotely sensed vegetation productivity measures, although weather patterns and vegetation dynamics were positively correlated.

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“…Some of the most affected regions were located close to the Swiss border [11,12]. While Italy, which shares a border with the south of Switzerland, reported no cases of hantavirus infection between 2005 and 2010 [4], in Austria, a country neighbouring Switzerland to the east, moderate numbers of PUUV infections were reported until 2011, with an increase in the number of human cases in 2012 in provinces bordering Slovenia [13].…”

Section: Introductionmentioning

confidence: 99%

Seroprevalence of hantavirus infections in Switzerland in 2009: difficulties in determining prevalence in a country with low endemicity

et al. 2013

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In several European countries, diagnosis of nephropathia epidemica, a mild form of haemorrhagic fever with renal syndrome (HFRS) caused by Puumalavirus infection, has increased over the past 10-20 years. In Switzerland, despite its geographical proximity to regions with epidemic outbreaks in Germany and France, infections are detected only sporadically. To estimate the actual prevalence and potential risk factors of human hantavirus infections in Switzerland, a seroepidemiological study was performed in 2009 on serum samples from 4,559 blood donors and 1,810 military personnel. Sera were screened using commercial Puumala IgG and hantavirus IgG enzyme-linked immunosorbent assays indicating a seroprevalence of 1% and 9%, respectively. Subsequently, the samples were analysed by immunofluorescence assay and immunoblot assay, showing a much lower prevalence, of 0.4% and 0.3%, respectively. Two of the serum samples achieved an 80% reduction in plaque-forming units in a neutralisation test. Statistical evaluation of questionnaires only identified an association of age (above 50 years) with hantavirus seropositivity when adjusted for sex (odds ratio: 2.36; 95% confidence interval: 1.10-5.05). This study provides baseline data (0.3-0.4%) for future monitoring of hantavirus seroprevalence in Switzerland and highlights the challenges in estimating the seroprevalence of these viruses in a country with very low endemicity.

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Environmental risk factors for haemorrhagic fever with renal syndrome in a French new epidemic area

Cited by 24 publications

References 28 publications

Genetic and phenotypic characterization of sylvatic dengue virus type 4 strains

Genetic and phenotypic characterization of sylvatic dengue virus type 4 strains

Prediction of Peromyscus Maniculatus (Deer Mouse) Population Dynamics in Montana, Usa, Using Satellite-Driven Vegetation Productivity and Weather Data

Seroprevalence of hantavirus infections in Switzerland in 2009: difficulties in determining prevalence in a country with low endemicity

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