Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software.
Burkholderia pseudomallei (Bp), causing melioidosis, is becoming a major global public health concern. It is highly endemic in Southeast Asia (SEA) and Northern Australia and is persisting beyond the established areas of endemicity. This study aimed to determine the environmental variables that woul...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS Neglected Tropical Diseases |
| Online Access: | https://doi.org/10.1371/journal.pntd.0012684 |
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| author | Jose Francis V Abrantes Zenn Ashley P Cariño Hozeo Luis S Mercado Fatima N Vicencio Gio Ray S Sosa Miguel Angelo M Habaña Nikki Heherson A Dagamac |
| author_facet | Jose Francis V Abrantes Zenn Ashley P Cariño Hozeo Luis S Mercado Fatima N Vicencio Gio Ray S Sosa Miguel Angelo M Habaña Nikki Heherson A Dagamac |
| author_sort | Jose Francis V Abrantes |
| collection | DOAJ |
| description | Burkholderia pseudomallei (Bp), causing melioidosis, is becoming a major global public health concern. It is highly endemic in Southeast Asia (SEA) and Northern Australia and is persisting beyond the established areas of endemicity. This study aimed to determine the environmental variables that would predict the most suitable ecological niche for this pathogenic bacterium in SEA by maximum entropy (MaxEnt) modeling. Systematic review and meta-analysis of data for melioidosis were obtained from public databases such as PubMed, Harmonized World Soil (HWSD) and WorldClim. The potential map showing the environmental layers was processed by ArcGIS, and the prediction for the probability of habitat suitability using MaxEnt software (version 3·4·4) and ENMeval R-based modeling tools was utilized to generate the distribution map with the best-fit model. Both bioclimatic and edaphic predictors were found to be the most important niche-determining environmental variables affecting the geographical distribution of Bp. The highest probability of suitability was predicted in areas with mean temperature of the wettest quarter at ≥26°C, annual precipitation of <2300 mm and Acrisol soil type. Combining those significantly influential variables, our predictive modeling generated a potential distribution map showing the concentration of areas and its location names with high suitability for Bp presence. The predicted distribution of Bp is extensive in the mainland part of SEA. This can be used to draw appropriate measures to safeguard public health and address the true disease burden of melioidosis in the region under the current climate scenario. |
| format | Article |
| id | doaj-art-78872b3f7dc9401dbc0f8b88c953828c |
| institution | Kabale University |
| issn | 1935-2727 1935-2735 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Neglected Tropical Diseases |
| spelling | doaj-art-78872b3f7dc9401dbc0f8b88c953828c2025-02-05T05:33:28ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352025-01-01191e001268410.1371/journal.pntd.0012684Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software.Jose Francis V AbrantesZenn Ashley P CariñoHozeo Luis S MercadoFatima N VicencioGio Ray S SosaMiguel Angelo M HabañaNikki Heherson A DagamacBurkholderia pseudomallei (Bp), causing melioidosis, is becoming a major global public health concern. It is highly endemic in Southeast Asia (SEA) and Northern Australia and is persisting beyond the established areas of endemicity. This study aimed to determine the environmental variables that would predict the most suitable ecological niche for this pathogenic bacterium in SEA by maximum entropy (MaxEnt) modeling. Systematic review and meta-analysis of data for melioidosis were obtained from public databases such as PubMed, Harmonized World Soil (HWSD) and WorldClim. The potential map showing the environmental layers was processed by ArcGIS, and the prediction for the probability of habitat suitability using MaxEnt software (version 3·4·4) and ENMeval R-based modeling tools was utilized to generate the distribution map with the best-fit model. Both bioclimatic and edaphic predictors were found to be the most important niche-determining environmental variables affecting the geographical distribution of Bp. The highest probability of suitability was predicted in areas with mean temperature of the wettest quarter at ≥26°C, annual precipitation of <2300 mm and Acrisol soil type. Combining those significantly influential variables, our predictive modeling generated a potential distribution map showing the concentration of areas and its location names with high suitability for Bp presence. The predicted distribution of Bp is extensive in the mainland part of SEA. This can be used to draw appropriate measures to safeguard public health and address the true disease burden of melioidosis in the region under the current climate scenario.https://doi.org/10.1371/journal.pntd.0012684 |
| spellingShingle | Jose Francis V Abrantes Zenn Ashley P Cariño Hozeo Luis S Mercado Fatima N Vicencio Gio Ray S Sosa Miguel Angelo M Habaña Nikki Heherson A Dagamac Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software. PLoS Neglected Tropical Diseases |
| title | Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software. |
| title_full | Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software. |
| title_fullStr | Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software. |
| title_full_unstemmed | Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software. |
| title_short | Identification of Environmental Determinants Involved in the Distribution of Burkholderia pseudomallei in Southeast Asia using MaxEnt software. |
| title_sort | identification of environmental determinants involved in the distribution of burkholderia pseudomallei in southeast asia using maxent software |
| url | https://doi.org/10.1371/journal.pntd.0012684 |
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