Maximum entropy modeling risk of anthrax in the Republic of Kazakhstan

Abdrakhmanov, Sarsenbay; Mukhanbetkaliyev, Yersyn Y.; Korennoy, Fedor I.; Sultanov, Akhmetzhan A.; Kadyrov, Ablaikhan; Кushubaev, Dosym B; Bakishev, None Temirlan

doi:10.1016/j.prevetmed.2017.06.003

Cited by 23 publications

(29 citation statements)

References 23 publications

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“…The method is widely used for: (i) modelling the potential range of distribution of a species; and, (ii) modelling the potential area of distribution of the disease based on the assumption of its coincidence with the pathogen's geographical range. Examples of the latter approach are studies by Peterson et al and Rose and Wall on viral diseases [53,54]; Du et al on myasis [55]; Abdrakhmanov et al [56,57]; Mwakapej et al [58] on anthrax. A conceptual review of the application of the MaxEnt method in biogeography is given in [59].…”

Section: Geospatial Analysismentioning

confidence: 99%

Re-introduction of vivax malaria in a temperate area (Moscow region, Russia): a geographic investigation

Mironova

Shartova

Beljaev

et al. 2020

Malar J

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Background: Between 1999 and 2008 Russia experienced a flare-up of transmission of vivax malaria following its massive importation with more than 500 autochthonous cases in European Russia, the Moscow region being the most affected. The outbreak waned soon after a decrease in importation in mid-2000s and strengthening the control measures. Compared with other post-eradication epidemics in Europe this one was unprecedented by its extension and duration. Methods: The aim of this study is to identify geographical determinants of transmission. The degree of favourability of climate for vivax malaria was assessed by measuring the sum of effective temperatures and duration of season of effective infectivity using data from 22 weather stations. For geospatial analysis, the locations of each of 405 autochthonous cases detected in Moscow region have been ascertained. A MaxEnt method was used for modelling the territorial differentiation of Moscow region according to the suitability of infection re-emergence based on the statistically valid relationships between the distribution of autochthonous cases and environmental and climatic factors. Results: In 1999-2004, in the beginning of the outbreak, meteorological conditions were extremely favourable for malaria in 1999, 2001 and 2002, especially within the borders of the city of Moscow and its immediate surroundings. The greatest number of cases occurred at the northwestern periphery of the city and in the adjoining rural areas. A significant role was played by rural construction activities attracting migrant labour, vegetation density and landscape division. A cutoff altitude of 200 m was observed, though the factor of altitude did not play a significant role at lower altitudes. Most likely, the urban heat island additionally amplified malaria re-introduction. Conclusion: The malariogenic potential in relation to vivax malaria was high in Moscow region, albeit heterogeneous. It is in Moscow that the most favourable conditions exist for vivax malaria re-introduction in the case of a renewed importation. This recent event of large-scale re-introduction of vivax malaria in a temperate area can serve as a case study for further research.

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Section: Geospatial Analysismentioning

confidence: 99%

Re-introduction of vivax malaria in a temperate area (Moscow region, Russia): a geographic investigation

Mironova

Shartova

Beljaev

et al. 2020

Malar J

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“…For this end, the risk levels were integrated by municipal districts by determining the average value within each district (the maximum of three values was taken for rabies). Thereafter, the obtained values were ranked in accordance with Table 4 (Abdrakhmanov et al 2016(Abdrakhmanov et al , 2017. The zoning results are presented the form of risk maps for each disease.…”

Section: Generalization Of Risk Levels Within Administrative Areasmentioning

confidence: 99%

“…This paper was initiated to generalize the methodology of zoning of the RK according to the degree of risk of rabies and anthrax outbreaks (Abdrakhmanov et al 2016(Abdrakhmanov et al , 2017. Given the natural focal nature of both studied diseases, the zoning was carried out using the mathematical-geographic method for modelling environmental niches (ENM) with optimization by the principle of maximum entropy (MaxEnt).…”

Section: Introductionmentioning

confidence: 99%

Zoning of the republic of Kazakhstan as to the risk of natural focal diseases in animals: the case of rabies and anthrax

Abdrakhmanov

Mukhanbetkaliyev

Korennoy

et al. 2020

GES

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Rabies and anthrax, being natural focal diseases, are characterized by the ability to persist in areas with a certain combination of environmental factors without human intervention. These infections annually cause sporadic outbreaks in domestic, livestock and wild animals in the Republic of Kazakhstan (RK) receiving close attention of the veterinary service. In particular, targeted mass vaccination and surveillance are conducted, which requires zoning of the country according to the exposure to the diseases.This paper presents a zoning approach based on the estimation of suitability to the study diseases using the Environmental Niche Modelling method. Retrospective data on animal rabies outbreaks in the RK for 2003-2014, as well as data on anthrax burial sites for 1933-2014 were used. The following environmental factors were treated as potential explanatory variables: 1) a set of climate data derived variables BIOCLIM; 2) altitude above the sea level; 3) land cover type; 4) the maximum green vegetation fraction and 5) soil type.The modelling outcomes for both diseases indicate elevated risks along the northern and southeastern borders of the RK that not only follows the distribution of historic disease cases, but also accounts for potentially suitable environmental conditions. To comply with the requirements of the veterinary service, gridded risk maps were converted into categorical maps by averaging risk values within municipal districts and ranking according to four categories: low, medium, high, and very high.The maps obtained may be used as recommendations to the veterinary service as a basis for developing regionspecific anti-epizootic measures.

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“…In addition, MaxEnt generates response curves of each continuous predictor essential in interpreting model performance (van Gils, Conti, Ciaschetti, & Westinga, ; van Gils, Westinga, Carafa, Antonucci, & Ciaschetti, ). MaxEnt has become the SDM tool of choice for animal distribution studies, including wild boar (Bosch, Mardones, Pérez, Torre, & Muñoz, ), bear (van Gils et al, ) and anthrax (Abdrakhmanov et al., ). Furthermore, MaxEnt provided a robust response independently of a number of selected variables of 5 or lower (Navarro‐Cerrillo, Hernández‐Bermejo, & Hernández‐Clemente, ; van Gils et al, ).…”

Section: Introductionmentioning

confidence: 99%

High probability areas for ASF infection in China along the Russian and Korean borders

Fekede

Gils

Huang³

et al. 2019

Transbound Emerg Dis

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Summary African swine fever (ASF) is a transcontinental, contagious, fatal virus disease of pig with devastating socioeconomic impacts. Interaction between infected wild boar and domestic pig may spread the virus. The disease is spreading fast from the west of Eurasia towards ASF‐free China. Consequently, prediction of the distribution of ASF along the Sino‐Russian‐Korean borders is urgent. Our area of interest is Northeast China. The reported ASF‐locations in 11 contiguous countries from the Baltic to the Russian Federation were extracted from the archive of the World Organization for Animal Health from July 19, 2007 to March 27, 2017. The locational records of the wild boar were obtained from literature. The environmental predictor variables were downloaded from the WorldClim website. Spatial rarefication and pair‐wise geographic distance comparison were applied to minimize spatial autocorrelation of presence points. Principal component analysis (PCA) was used to minimize multi‐collinearity among predictor variables. We selected the maximum entropy algorithm for spatial modelling of ASF and wild boar separately, combined the wild boar prediction with the domestic pig census in a single map of suids and overlaid the ASF with the suids map. The accuracy of the models was assessed by the AUC. PCA delivered five components accounting for 95.7% of the variance. Spatial autocorrelation was shown to be insignificant for both ASF and wild boar records. The spatial models showed high mean AUC (0.92 and 0.97) combined with low standard deviations (0.003 and 0.006) for ASF and wild boar, respectively. The overlay of the ASF and suids maps suggests that a relatively short sector of the Sino‐Russian border has a high probability entry point of ASF at current conditions. Two sectors of the Sino‐Korean border present an elevated risk.

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Maximum entropy modeling risk of anthrax in the Republic of Kazakhstan

Cited by 23 publications

References 23 publications

Re-introduction of vivax malaria in a temperate area (Moscow region, Russia): a geographic investigation

Re-introduction of vivax malaria in a temperate area (Moscow region, Russia): a geographic investigation

Zoning of the republic of Kazakhstan as to the risk of natural focal diseases in animals: the case of rabies and anthrax

High probability areas for ASF infection in China along the Russian and Korean borders

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