A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan
Abstract Background Rift Valley fever (RVF) is a zoonotic viral vector-borne disease that affects both animals and humans and leads to severe economic consequences. RVF outbreaks are triggered by a favorable environment and flooding, which enable mosquitoes to proliferate and spread the virus furthe...
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| Format: | Article |
| Language: | English |
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BMC
2019-11-01
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| Series: | Tropical Medicine and Health |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s41182-019-0178-1 |
| _version_ | 1818929591868194816 |
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| author | Rania Salah Eldien Bashir Osama Ahmed Hassan |
| author_facet | Rania Salah Eldien Bashir Osama Ahmed Hassan |
| author_sort | Rania Salah Eldien Bashir |
| collection | DOAJ |
| description | Abstract Background Rift Valley fever (RVF) is a zoonotic viral vector-borne disease that affects both animals and humans and leads to severe economic consequences. RVF outbreaks are triggered by a favorable environment and flooding, which enable mosquitoes to proliferate and spread the virus further. RVF is endemic to Africa and has spread to Saudi Arabia and Yemen. There is great concern that RVF may spread to previously unaffected geographic regions due to climate change. We aimed to better understand the spatiotemporal pattern of the 2007 RVF outbreak at the human–animal–environment interface and to determine environmental factors that may have effects on RVF occurrence in Gezira state, Sudan. Materials and methods We compiled epidemiological, environmental, and spatiotemporal data across time and space using remote sensing and a geographical information system (GIS). The epidemiological data included 430 RVF human cases as well as human and animal population demographic data for each locality. The cases were collected from 41 locations in Gezira state. The environmental data represent classified land cover during 2007, the year of the RVF outbreak, and the average of the Normalized Difference Vegetation Index (NDVI) for 6 months of 2007 is compared with those of 2010 and 2014, when there was no RVF outbreak. To determine the effect of the environmental factors such as NDVI, soil type, and RVF case’s location on the Blue Nile riverbank on RVF incidence in Gezira state, a multilevel logistic regression model was carried out. Results We found that the outbreak in Gezira state occurred as a result of interaction among animals, humans, and the environment. The multilevel logistic regression model (F = 43,858, df = 3, p = 0.000) explained 23% of the variance in RVF incidence due to the explanatory variables. Notably, soil type (β = 0.613, t = 11.284, p = 0.000) and NDVI (β = − 0.165, t = − 3.254, p = 0.001) were the explanatory environmental factors that had significant effects on RVF incidence in 2007 in Gezira state, Sudan. Conclusions Precise remote sensing and the GIS technique, which rely on environmental indices such as NDVI and soil type that are satellite-derived, can contribute to establishing an early warning system for RVF in Sudan. Future preparedness and strengthening the capacity of regional laboratories are necessary for early notification of outbreaks in animals and humans. |
| first_indexed | 2024-12-20T03:47:15Z |
| format | Article |
| id | doaj.art-06d8f171ebe14377baf2f19261114661 |
| institution | Directory Open Access Journal |
| issn | 1349-4147 |
| language | English |
| last_indexed | 2024-12-20T03:47:15Z |
| publishDate | 2019-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Tropical Medicine and Health |
| spelling | doaj.art-06d8f171ebe14377baf2f192611146612022-12-21T19:54:34ZengBMCTropical Medicine and Health1349-41472019-11-0147111010.1186/s41182-019-0178-1A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central SudanRania Salah Eldien Bashir0Osama Ahmed Hassan1Animal Health Directorate, General Directorate of Animal Health and Epizootic Diseases Control, Ministry of LivestockThe Centre for Global Health, Department of Community Medicine and Global Health, Faculty of Medicine, University of OsloAbstract Background Rift Valley fever (RVF) is a zoonotic viral vector-borne disease that affects both animals and humans and leads to severe economic consequences. RVF outbreaks are triggered by a favorable environment and flooding, which enable mosquitoes to proliferate and spread the virus further. RVF is endemic to Africa and has spread to Saudi Arabia and Yemen. There is great concern that RVF may spread to previously unaffected geographic regions due to climate change. We aimed to better understand the spatiotemporal pattern of the 2007 RVF outbreak at the human–animal–environment interface and to determine environmental factors that may have effects on RVF occurrence in Gezira state, Sudan. Materials and methods We compiled epidemiological, environmental, and spatiotemporal data across time and space using remote sensing and a geographical information system (GIS). The epidemiological data included 430 RVF human cases as well as human and animal population demographic data for each locality. The cases were collected from 41 locations in Gezira state. The environmental data represent classified land cover during 2007, the year of the RVF outbreak, and the average of the Normalized Difference Vegetation Index (NDVI) for 6 months of 2007 is compared with those of 2010 and 2014, when there was no RVF outbreak. To determine the effect of the environmental factors such as NDVI, soil type, and RVF case’s location on the Blue Nile riverbank on RVF incidence in Gezira state, a multilevel logistic regression model was carried out. Results We found that the outbreak in Gezira state occurred as a result of interaction among animals, humans, and the environment. The multilevel logistic regression model (F = 43,858, df = 3, p = 0.000) explained 23% of the variance in RVF incidence due to the explanatory variables. Notably, soil type (β = 0.613, t = 11.284, p = 0.000) and NDVI (β = − 0.165, t = − 3.254, p = 0.001) were the explanatory environmental factors that had significant effects on RVF incidence in 2007 in Gezira state, Sudan. Conclusions Precise remote sensing and the GIS technique, which rely on environmental indices such as NDVI and soil type that are satellite-derived, can contribute to establishing an early warning system for RVF in Sudan. Future preparedness and strengthening the capacity of regional laboratories are necessary for early notification of outbreaks in animals and humans.http://link.springer.com/article/10.1186/s41182-019-0178-1Rift Valley feverOne HealthRemote sensingGeographical information systemNormalized Difference Vegetation IndexSoil type |
| spellingShingle | Rania Salah Eldien Bashir Osama Ahmed Hassan A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan Tropical Medicine and Health Rift Valley fever One Health Remote sensing Geographical information system Normalized Difference Vegetation Index Soil type |
| title | A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan |
| title_full | A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan |
| title_fullStr | A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan |
| title_full_unstemmed | A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan |
| title_short | A One Health perspective to identify environmental factors that affect Rift Valley fever transmission in Gezira state, Central Sudan |
| title_sort | one health perspective to identify environmental factors that affect rift valley fever transmission in gezira state central sudan |
| topic | Rift Valley fever One Health Remote sensing Geographical information system Normalized Difference Vegetation Index Soil type |
| url | http://link.springer.com/article/10.1186/s41182-019-0178-1 |
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