Modeling the environmental suitability for Bacillus anthracis in the Qinghai Lake Basin, China

Arotolu, Temitope Emmanuel; Wang, Haoning; Lv, JiaNing; Shi, Kun; Gils, Hein van; Huang, Liang; Wang, Xiaolong

doi:10.1371/journal.pone.0275261

Cited by 5 publications

(5 citation statements)

References 49 publications

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“…Suppression of unnecessary loading and rotation of factor pattern of variables was used to retain predictors for subsequent analysis in MaxEnt. Next, the least contributing and high standard deviation (SD) 20,21 variables were eliminated stepwise and using the MaxEnt model 21,22 . Finally, variance inflation factor (VIF) 23,24 analysis was conducted to evaluate the multicollinearity among predictors after the reduction 25 .…”

Section: Methodsmentioning

confidence: 99%

“…Next, the least contributing and high standard deviation (SD) 20,21 variables were eliminated stepwise and using the MaxEnt model. 21,22 Finally, variance inflation factor (VIF) 23,24 analysis was conducted to evaluate the multicollinearity among predictors after the reduction. 25 A VIF value below 10 indicates low and acceptable multicollinearity.…”

Section: Spatial Distribution Model Analysismentioning

confidence: 99%

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Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

Han,

Gao,

Xin

et al. 2024

Journal of Medical Virology

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The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick‐borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high‐risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work.

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Section: Methodsmentioning

confidence: 99%

Section: Spatial Distribution Model Analysismentioning

confidence: 99%

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

Han,

Gao,

Xin

et al. 2024

Journal of Medical Virology

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“…The collinearity among environmental variables was assessed using the variance inflation factor (VIF) to avoid overfitting the model. A VIF value low 10 indicates that multicollinearity is acceptable [28].…”

Section: Data Collection and Preprocessing For Maxentmentioning

confidence: 99%

The Geographical Coexist of the Migratory Birds, Ticks, and Nairobi Sheep Disease Virus May Potentially Contribute to the Passive Spreading of Nairobi Sheep Disease

Kim,

Wang,

Cha

et al. 2023

Transboundary and Emerging Diseases

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Nairobi sheep disease (NSD) is a hemorrhagic vector-borne disease of small ruminants caused by the Nairobi sheep disease virus (NSDV), also known as Ganjam virus (GV). NSDV and GV refer to the same virus. The NSDV has been identified in East Africa, India, Sri Lanka, and China, and NSDV vector ticks can be carried by birds. There is few research on the mechanism of the global cycle and spillover of NSDV. Based on the prediction of the high probability distribution areas of NSD by the maximum entropy model (MaxEnt), the possible passive transport routes of NSDV vector ticks by migratory birds were simulated for further evaluation. The transmission probability of NSDV vector ticks by migrating birds was calculated using evaluations of the parasitism intensity of ticks on migratory birds at start points, the flying burden of parasitized birds, and the attachment coefficient of ticks on birds during migration. A total of 31 potential transport routes were predicted, which, through interaction with each other, constitute a spreading network for NSDV. Seven species of migratory birds were predicted as intra or interregional carriers. Our study first provides measurable support for estimating the possibility of passive migration of NSDV vector ticks by migratory birds that may be potential carriers of ticks and proposes a transmission mechanism between all known natural foci and potential natural foci. These findings highlight the necessity of cooperation in the management of the NSDV in all known and potential natural foci located in different countries, with the aim of blocking global circulation in a cost-effective way. Furthermore, these findings may also contribute to the prevention of other similar diseases.

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“…We used the setting of the natural break with a maximum distance of 40 km and a minimum of 5 km [12]. Collinearity among environmental variables was assessed using the principal component analysis (PCA) and variance inflation factors (VIFs) [3]. Multicollinearity may violate statistical assumptions and may alter model predictions [23].…”

Section: Preprocessing Of Spatial Modelling Datamentioning

confidence: 99%

Estimating the spatial distribution of African swine fever outbreak in China by combining four regional-level spatial models

YAO,

ZHAI,

WANG

et al. 2023

J. Vet. Med. Sci.

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The outbreaks of African Swine Fever (ASF) in China are ongoing, and the inadequate management of the pig supply chain is criticized. In the past four years, a series of preventive and control measures have been supplied national wide, while the outbreaks have not been terminated. This suggests the existing animal disease management at the district level may not be appropriate to control ASF under the current situation of the ASF outbreak in China. It is urgent to further describe real distribution areas of ASF in China. In this study, we combined four regional-scale models to predict the risk distribution of ASF in mainland China and identify risk factors related to ASF outbreaks. The results showed that the four regional-scale models were more accurate in predicting the ASF outbreaks than the nationwide scale model. The four regional-scale models identified the potential risk factors associated with ASF outbreaks, such as population density, pig density, land cover, temperature, and elevation factors. Moreover, seven clusters with high potential risk of ASF outbreaks were identified. Then, based on the results, we proposed more suitable prevention and control plans for ASF, which can assist the implementation of transport management policies within and between risk clusters.

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Modeling the environmental suitability for Bacillus anthracis in the Qinghai Lake Basin, China

Cited by 5 publications

References 49 publications

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China

The Geographical Coexist of the Migratory Birds, Ticks, and Nairobi Sheep Disease Virus May Potentially Contribute to the Passive Spreading of Nairobi Sheep Disease

Estimating the spatial distribution of African swine fever outbreak in China by combining four regional-level spatial models

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