Human African Trypanosomiasis (HAT) is a vector-borne disease transmitted by the bite of the tsetse fly that results in high human morbidity and mortality. The propagation of the disease has been linked to environmental factors, and understanding the vector’s habitat is vital to its control. There is no HAT vaccine, but biological control of the vector has been successful in reducing HAT incidence. However, in recent years the disease has re-emerged and spread. Due to insufficient knowledge of HAT endemic foci, the disease management remains challenging. To achieve effective deployment of control strategies, accurate knowledge of the spatial distribution of the HAT vector is vital. The current study is based in Nigeria, and looks at part of Delta State, and a part of Jigawa State, in which HAT has been identified. The work utilizes remote sensing satellite imaging and fuzzy logic to develop a HAT vector habitat classification scheme, to explore the dynamics of HAT propagation. The goal was to develop a surveillance methodology to identify factors that influence HAT epidemiology. Land cover and ancillary data were integrated to classify HAT vector habitat using geospatial-fuzzy multicriteria analysis. The work highlights the significance of geospatial techniques where epidemiological data are limited, for improving understanding of HAT. This study helped distinguish HAT vector habitat into different zones (breed, feed and rest), which allowed the direction and magnitude of HAT, a n d factors influencing propagation to be determined. This helped identify ‘HAT priority intervention areas’. The study findings suggested propagation of HAT resulted from suitability of water bodies, shrub and less-dense forest for the HAT vector, and continued exposure of human populations to these land cover classes. Overlapping of HAT vector habitat zones within built-up areas was also a cause. The study also found that HAT propagation was multidirectional, and that this may have been influenced by landscape characteristics. This novel approach can also be used in other part of Nigeria as well as adapted to investigate other diseases. In conclusion, the HAT vector habitat classification scheme is a transparent tool for policy makers for identifying vulnerable and at risk areas.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:667703 |
| Date | January 2014 |
| Creators | Akiode, Olukemi Adejoke |
| Contributors | Oduyemi, Kehinde |
| Publisher | Abertay University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://rke.abertay.ac.uk/en/studentTheses/9419b401-6604-4530-9938-57ab03234e67 |
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