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Ecological niche modeling as a tool for prediction of the potential geographic distribution of Bacillus anthracis spores in Tanzania.
Mwakapeje, Elibariki R; Ndimuligo, Sood A; Mosomtai, Gladys; Ayebare, Samuel; Nyakarahuka, Luke; Nonga, Hezron E; Mdegela, Robinson H; Skjerve, Eystein.
Afiliación
  • Mwakapeje ER; Epidemiology and Diseases Control Section, Ministry of Health, Community Development, Gender, Elderly and Children, Dar es Salaam, Tanzania; Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania; Faculty of Veterinary Medicine, Norwegian Universit
  • Ndimuligo SA; Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway. Electronic address: soodan@student.matnat.uio.no.
  • Mosomtai G; Earth Observation Unit, International Centre for Insect Physiology and Ecology, Nairobi, Kenya. Electronic address: gmosomtai@icipe.org.
  • Ayebare S; Climate and Biodiversity Unit, Wildlife Conservation Society, Bronx, New York, USA. Electronic address: sayebare@wcs.org.
  • Nyakarahuka L; Department of Biosecurity, Ecosystems and Veterinary Public Health, Makerere University, Kampala, Uganda. Electronic address: n3luke@covab.mak.ac.ug.
  • Nonga HE; Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania. Electronic address: hezron@sua.ac.tz.
  • Mdegela RH; Department of Veterinary Medicine and Public Health, Sokoine University of Agriculture, Morogoro, Tanzania. Electronic address: rmdegela@sua.ac.tz.
  • Skjerve E; Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Oslo, Norway. Electronic address: eystein.skjerve@nmbu.no.
Int J Infect Dis ; 79: 142-151, 2019 Feb.
Article en En | MEDLINE | ID: mdl-30521941
ABSTRACT

INTRODUCTION:

Anthrax is caused by the spore-forming, Gram-positive bacterium Bacillus anthracis. The aim of this study was to predict the potential distribution of B. anthracis in Tanzania and produce epidemiological evidence for the management of anthrax outbreaks in the country.

METHODS:

The Maxent algorithm was used to predict areas at risk of anthrax outbreaks based on the occurrence and environmental data in Arusha and Kilimanjaro regions; the model was later transferred to predict the entire country. Seventy percent of the occurrence data were used to train the model, while 30% were used for model evaluation.

RESULTS:

Four regions of northern Tanzania are predicted to have a high risk for anthrax outbreaks, while the southern and western regions had low-risk areas. Soil type (56.5%), soil pH (23.7%), and isothermally (10.4%) were the most important variables for the model prediction, and the most significant soil types were solonetz, fluvisols, and lithosols.

CONCLUSIONS:

A strong risk level across districts of the Tanzania mainland was identified in this study. A total of 18 districts in Tanzania Mainland are predicted to be at very high risk of an anthrax outbreak occurrence. These findings are important for policymakers to effectively mount targeted control measures for anthrax outbreaks in Tanzania.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacillus anthracis / Ecosistema / Carbunco Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans País/Región como asunto: Africa Idioma: En Revista: Int J Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2019 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Bacillus anthracis / Ecosistema / Carbunco Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans País/Región como asunto: Africa Idioma: En Revista: Int J Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2019 Tipo del documento: Article