A SPATIAL DISTRIBUTION MODELING OF WEST NILE FEVER VECTORS IN THE GENUS CULEX IN THE HORN OF AFRICA
| dc.contributor.advisor | Dr. Fufa Abunna , Dr. Samson Leta | |
| dc.contributor.author | Tsega, Berhe | |
| dc.date.accessioned | 2019-12-19T08:57:01Z | |
| dc.date.accessioned | 2023-11-08T11:32:59Z | |
| dc.date.available | 2019-12-19T08:57:01Z | |
| dc.date.available | 2023-11-08T11:32:59Z | |
| dc.date.issued | 2019-06 | |
| dc.description.abstract | Many species under Culex mosquito are common vectors for West Nile Virus (WNV) and distribution of this disease is influenced by biological and physical variations. Spatial modeling of arbovirus mosquito in East African countries becomes influential due to increased frequency outbreaks and emergence. A study on a spatial distribution modeling of the West Nile Fever Vector in Ethiopia was conducted from May 2018 to June 2019. The collected Culex (Cx) species were Cx. pipiens (38.5%), Cx. univitattus (29.1%), Cx. antennatus (11.6%), Cx. quinquefasciatus (11%) and other Culex species (10.3%), potential vector species for WNV. WNV isolation was performed using Conventional one step reverse transcriptase-PCR (RT-PCR) with specific primer-WNV-F2 and WNV-Rev2. Occurrence data was obtained from Global Biodiversity Information Facility (GBIF) website and field sampling was also done in Mid Rift Valley and Southern Ethiopia. The models were created with a set of environmental predictors including climatic data, topographical, land cover, human, and livestock population count. Individual models and ensemble prediction was made using R package Biomod2. With individual models, overall average models agreed in predicting probability Culex occurrence highly contributed by soil type (49%) and precipitation (46.5%) but land cover had lowest contribution (13%). In individual models evaluation resulted eight of the total 10 models proved reliable estimations on True skills statistics (TSS≥0.8) with highest value were GLM (TSS=0.932), MARS (TSS=0.925) and RF (TSS=0.919) but result of SRE and MAXENT was found with poor TSS. An ensemble model evaluated using TSS metrics among the 30 models, the ensemble model included TSS ≥0.8. Soil type (37%) and precipitation (31.5%) were with high contribution but solar radiation (5.5%) had lowest contrition. Visualization of predicted probability occurrence of Culex showed high probability of occurrence in Oromia followed by SNNP region. Vector distribution varied from location to location depending to on their environmental preferences. Therefore, further investigation was essential on modeling of spatial and temporal situation of both vector and the disease. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/20428 | |
| dc.language.iso | en | en_US |
| dc.subject | Culex | en_US |
| dc.subject | Occurrence | en_US |
| dc.subject | Spatial modeling | en_US |
| dc.title | A SPATIAL DISTRIBUTION MODELING OF WEST NILE FEVER VECTORS IN THE GENUS CULEX IN THE HORN OF AFRICA | en_US |
| dc.type | Thesis | en_US |
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