Ecological niche modelling of bank voles in Western Europe

Investigation on risk factors of haemorrhagic fever with renal syndrome (HFRS) in Xuancheng City in Anhui Province, Mainland China

Haemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a major public health concern in both developed and developing countries. China is the most severe endemic country in the world, constituting 90% of the cases. Although the incidence of HFRS has substantively decreased in most areas of China, HFRS has rebounded remarkably in some epidemic areas. Xuancheng is one of these areas. In this study, we collected the case data reported recently in Xuancheng and designed a 1:3 case-control study. The Chi-square test, univariate and multivariate logistic regression analysis were performed. In all cases, farmers made up the highest proportion of occupations. And there were 20 variables with statistical significance including indoor hygienic conditions; the surrounding environment; whether bitten by rats at work and other criteria. In addition, exposure to rodents and rats bites is a high-risk factor for HFRS. Rodent density was calculated at 20.9% (159/760), the virus carrier rate was 9.4% (15/159) and the index of rats with a virus was about 2.0%. Exposure to rodents and insect bites is also high-risk factors for HFRS among local residents in Xuancheng. More importantly, during the flood years, the increased density of rodents led to an increased risk of human exposure to rodents. As our statistical analysis proves, targeted strategies should be developed and implemented to reduce the incidence of local diseases in the future.

Hemorrhagic fever with renal syndrome with secondary hemophagocytic lymphohistiocytosis in West China: a case report

Background

Hemophagocytic lymphohistiocytosis (HLH) is a life-threatening disease characterized by an excessive systemic inflammatory response, which can be classified as primary HLH (pHLH) and secondary HLH (sHLH). Viruses are the primary pathogens causing sHLH. Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by hantaviruses. Its main characteristics include fever, circulatory collapse with hypotension, hemorrhage, and acute kidney injury. The case of HFRS presented with sHLH is very rare in clinic. We reported the HFRS inducing by Hantaan virus (HTNV) presented with sHLH as the first case in Shaanxi province of west China.

Case presentation

A case of HFRS in 69-year-old Chinese woman, which had persistent fever, cytopenia, coagulopathy, ferritin significantly increased, hepatosplenomegaly and superficial lymphadenopathy. The hemophagocytosis was found in bone marrow, which was consistent with the characteristics of the HLH. The patient recovered completely after timely comprehensive treatments.

Conclusions

HTNV should be considered as one of the underlying viruses resulting in hemophagocytosis, and if occurs, the early diagnosis and rapid therapeutic intervention are very important to the prognosis of sHLH.

Identifying the patterns and drivers of Puumala hantavirus enzootic dynamics using reservoir sampling

Hantaviruses are zoonotic hemorrhagic fever viruses for which prevention of human spillover remains the first priority in disease management. Tailored intervention measures require an understanding of the drivers of enzootic dynamics, commonly inferred from distorted human incidence data. Here, we use longitudinal sampling of approximately three decades of Puumala orthohantavirus (PUUV) evolution in isolated reservoir populations to estimate PUUV evolutionary rates, and apply these to study the impact of environmental factors on viral spread. We find that PUUV accumulates genetic changes at a rate of ∼10⁻⁴ substitutions per site per year and that land cover type defines the dispersal dynamics of PUUV, with forests facilitating and croplands impeding virus spread. By providing reliable short-term PUUV evolutionary rate estimates, this work facilitates the evaluation of spatial risk heterogeneity starting from timed phylogeographic reconstructions based on virus sampling in its animal reservoir, thereby side-stepping the need for difficult-to-collect human disease incidence data.

Importance of Remotely-Sensed Vegetation Variables for Predicting the Spatial Distribution of African Citrus Triozid (Trioza erytreae) in Kenya

Citrus is considered one of the most important fruit crops globally due to its contribution to food and nutritional security. However, the production of citrus has recently been in decline due to many biological, environmental, and socio-economic constraints. Amongst the biological ones, pests and diseases play a major role in threatening citrus quantity and quality. The most damaging disease in Kenya, is the African citrus greening disease (ACGD) or Huanglongbing (HLB) which is transmitted by the African citrus triozid (ACT), Trioza erytreae. HLB in Kenya is reported to have had the greatest impact on citrus production in the highlands, causing yield losses of 25% to 100%. This study aimed at predicting the occurrence of ACT using an ecological habitat suitability modeling approach. Specifically, we tested the contribution of vegetation phenological variables derived from remotely-sensed (RS) data combined with bio-climatic and topographical variables (BCL) to accurately predict the distribution of ACT in citrus-growing areas in Kenya. A MaxEnt (maximum entropy) suitability modeling approach was used on ACT presence-only data. Forty-seven (47) ACT observations were collected while 23 BCL and 12 RS covariates were used as predictor variables in the MaxEnt modeling. The BCL variables were extracted from the WorldClim data set, while the RS variables were predicted from vegetation phenological time-series data (spanning the years 2014–2016) and annually-summed land surface temperature (LST) metrics (2014–2016). We developed two MaxEnt models; one including both the BCL and the RS variables (BCL-RS) and another with only the BCL variables. Further, we tested the relationship between ACT habitat suitability and the surrounding land use/land cover (LULC) proportions using a random forest regression model. The results showed that the combined BCL-RS model predicted the distribution and habitat suitability for ACT better than the BCL-only model. The overall accuracy for the BCL-RS model result was 92% (true skills statistic: TSS = 0.83), whereas the BCL-only model had an accuracy of 85% (TSS = 0.57). Also, the results revealed that the proportion of shrub cover surrounding citrus orchards positively influenced the suitability probability of the ACT. These results provide a resourceful tool for precise, timely, and site-specific implementation of ACGD control strategies.

Ecological Niche Modeling of Risk Factors for H7N9 Human Infection in China

China was attacked by a serious influenza A (H7N9) virus in 2013. The first human infection case was confirmed in Shanghai City and soon spread across most of eastern China. Using the methods of Geographic Information Systems (GIS) and ecological niche modeling (ENM), this research quantitatively analyzed the relationships between the H7N9 occurrence and the main environmental factors, including meteorological variables, human population density, bird migratory routes, wetland distribution, and live poultry farms, markets, and processing factories. Based on these relationships the probability of the presence of H7N9 was predicted. Results indicated that the distribution of live poultry processing factories, farms, and human population density were the top three most important determinants of the H7N9 human infection. The relative contributions to the model of live poultry processing factories, farms and human population density were 39.9%, 17.7% and 17.7%, respectively, while the maximum temperature of the warmest month and mean relative humidity had nearly no contribution to the model. The paper has developed an ecological niche model (ENM) that predicts the spatial distribution of H7N9 cases in China using environmental variables. The area under the curve (AUC) values of the model were greater than 0.9 (0.992 for the training samples and 0.961 for the test data). The findings indicated that most of the high risk areas were distributed in the Yangtze River Delta. These findings have important significance for the Chinese government to enhance the environmental surveillance at multiple human poultry interfaces in the high risk area.

Ecological Model to Predict Potential Habitats of Oncomelania hupensis, the Intermediate Host of Schistosoma japonicum in the Mountainous Regions, China

Background

Schistosomiasis japonica is a parasitic disease that remains endemic in seven provinces in the People’s Republic of China (P.R. China). One of the most important measures in the process of schistosomiasis elimination in P.R. China is control of Oncomelania hupensis, the unique intermediate host snail of Schistosoma japonicum. Compared with plains/swamp and lake regions, the hilly/mountainous regions of schistosomiasis endemic areas are more complicated, which makes the snail survey difficult to conduct precisely and efficiently. There is a pressing call to identify the snail habitats of mountainous regions in an efficient and cost-effective manner.

Methods

Twelve out of 56 administrative villages distributed with O. hupensis in Eryuan, Yunnan Province, were randomly selected to set up the ecological model. Thirty out of the rest of 78 villages (villages selected for building model were excluded from the villages for validation) in Eryuan and 30 out of 89 villages in Midu, Yunnan Province were selected via a chessboard method for model validation, respectively. Nine-year-average Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) as well as Digital Elevation Model (DEM) covering Eryuan and Midu were extracted from MODIS and ASTER satellite images, respectively. Slope, elevation and the distance from every village to its nearest stream were derived from DEM. Suitable survival environment conditions for snails were defined by comparing historical snail presence data and remote sensing derived images. According to the suitable conditions for snails, environment factors, i.e. NDVI, LST, elevation, slope and the distance from every village to its nearest stream, were integrated into an ecological niche model to predict O. hupensis potential habitats in Eryuan and Midu. The evaluation of the model was assessed by comparing the model prediction and field investigation. Then, the consistency rate of model validation was calculated in Eryuan and Midu Counties, respectively.

Results

The final ecological niche model for potential O. hupensis habitats prediction comprised the following environmental factors, namely: NDVI (≥ 0.446), LST (≥ 22.70°C), elevation (≤ 2,300 m), slope (≤ 11°) and the distance to nearest stream (≤ 1,000 m). The potential O. hupensis habitats in Eryuan distributed in the Lancang River basin and O. hupensis in Midu shows a trend of clustering in the north and spotty distribution in the south. The consistency rates of the ecological niche model in Eryuan and Midu were 76.67% and 83.33%, respectively.

Conclusions

The ecological niche model integrated with NDVI, LST, elevation, slope and distance from every village to its nearest stream adequately predicted the snail habitats in the mountainous regions.

Schistosomiasis japonica is a parasitic disease caused by the infection of Schistosoma japonicum. Oncomelania hupensis, serving as the unique intermediate host of S. japonicum, has a distribution highly correlated with schistosomiasis epidemic. At present, elimination of O. hupensis is still an important target for disease control in the People’s Republic of China. In mountainous regions, compared with two other endemic regions, snails are hard to detect due to the complicated environmental conditions and poor transportation systems. In this study, we developed an ecological niche model to predict the potential habitats of O. hupensis using remote sensing data including vegetation index, land surface temperature, elevation, slope and the distance from every village to its nearest stream. Validation of the approach was performed in two counties with similar ecological conditions in Yunnan Province, P.R. China. Results revealed a model with a good consistency rate of 76.67% and 83.33% for the two counties, respectively. The model holds promise for snail surveillance in mountainous regions.

Effects of Climate and Rodent Factors on Hemorrhagic Fever with Renal Syndrome in Chongqing, China, 1997-2008

China has the highest global incidence of hemorrhagic fever with renal syndrome (HFRS), constituting 90% of the cases in the world. Chongqing, located in the Three Gorges Reservoir Region, has been experiencing differences in the occurrence of HFRS from 1997 to 2008. The current study was designed to explore the effects of climate and rodent factors on the transmission of HFRS in Chongqing. Data on monthly HFRS cases, rodent strains, and climatic factors were collected from 1997 to 2008. Spatio-temporal analysis indicated that most HFRS cases were clustered in central Chongqing and that the incidence of HFRS decreased from 1997 to 2008. Poisson regression models showed that temperature (with lagged months of 0 and 5) and rainfall (with 2 lagged months) were key climatic factors contributing to the transmission of HFRS. A zero-inflated negative binomial model revealed that rodent density was also significantly associated with the occurrence of HFRS in the Changshou district. The monthly trend in HFRS incidence was positively associated with rodent density and rainfall and negatively associated with temperature. Possible mechanisms are proposed through which construction of the dam influenced the incidence of HFRS in Chongqing. The findings of this study may contribute to the development of early warning systems for the control and prevention of HFRS in the Three Gorges Reservoir Region.

Climate Variability and the Occurrence of Human Puumala Hantavirus Infections in Europe: A Systematic Review

Hantaviruses are distributed worldwide and are transmitted by rodents. In Europe, the infection usually manifests as a mild form of haemorrhagic fever with renal syndrome (HFRS) known as nephropathia epidemica (NE), which is triggered by the virus species Puumala. Its host is the bank vole (Myodes glareolus). In the context of climate change, interest in the role of climatic factors for the disease has increased. A systematic review was conducted to investigate the association between climate variability and the occurrence of human Puumala hantavirus infections in Europe. We performed a literature search in the databases MEDLINE, EMBASE and Web of Science. Studies that investigated Puumala virus infection and climatic factors in any European country with a minimum collection period of 2 years were included. The selection of abstracts and the evaluation of included studies were performed by two independent reviewers. A total of 434 titles were identified in the databases, of which nine studies fulfilled the inclusion criteria. The majority of studies were conducted in central Europe (Belgium, France and Germany), while only two came from the north (Sweden) and one from the south (Bosnia). Strong evidence was found for a positive association between temperature and NE incidence in central Europe, while the evidence for northern Europe so far appears insufficient. Results regarding precipitation were contradictory. Overall, the complex relationships between climate and hantavirus infections need further exploration to identify specific health risks and initiate appropriate intervention measures in the context of climate change.

Identification of factors influencing the Puumala virus seroprevalence within its reservoir in aMontane Forest Environment

Puumala virus (PUUV) is a major cause of mild to moderate haemorrhagic fever with renal syndrome and is transmitted by the bank vole (Myodes glareolus). There has been a high cumulative incidence of recorded human cases in South-eastern Germany since 2004 when the region was first recognized as being endemic for PUUV. As the area is well known for outdoor recreation and the Bavarian Forest National Park (BFNP) is located in the region, the increasing numbers of recorded cases are of concern. To understand the population and environmental effects on the seroprevalence of PUUV in bank voles we trapped small mammals at 23 sites along an elevation gradient from 317 to 1420m above sea level. Generalized linear mixed effects models(GLMEM) were used to explore associations between the seroprevalence of PUUV in bank voles and climate and biotic factors. We found that the seroprevalence of PUUV was low (6%–7%) in 2008 and 2009, and reached 29% in 2010. PUUV seroprevalence was positively associated with the local species diversity and deadwood layer, and negatively associated with mean annual temperature, mean annual solar radiation, and herb layer. Based on these findings, an illustrative risk map for PUUV seroprevalence prediction in bank voles was created for an area of the national park. The map will help when planning infrastructure in the national park (e.g., huts, shelters, and trails).