SPATIAL DISTRIBUTION OF LYMPHATIC FILARIASIS IN CROSS RIVER STATE, NIGERIA: A GEOGRAPHICAL INFORMATION SYSTEMS (GIS) STUDY

Iniodu George; Davison Mbere-obong

doi:10.29121/granthaalayah.v4.i12.2016.2398

Authors

Ukpong, Iniodu George Department of Biological Sciences, Cross River University of Technology, Calabar, Nigeria
John, Davison Mbere-obong Department of Biological Sciences, Cross River University of Technology, Calabar, Nigeria

DOI:

https://doi.org/10.29121/granthaalayah.v4.i12.2016.2398

Keywords:

Lympatic Filariasis, GIS, Spatial Distribution, Incidence, Wuchereria Bancrofti, Cross River State

Abstract [English]

Effective control efforts on Lymphatic filariasis (LF) are hindered by paucity of reliable data on spatial distribution of the disease. Aim: This study was aimed at mapping and describing the transmission pattern of lymphatic filariasis in order to identify high risk zones of infection in Cross River State (CRS), to guide intervention programmes. Method: An 8-year case record (2006-2013) of Lymphatic filariasis in the 18 local government areas (LGAs) of CRS was mapped using geographical information system, (GIS); employing the graduated colour map with natural break classification method. Thematic (LF incidence) maps generated in ArcView 3.1 were overlaid on vegetation and natural drainage maps of the state. Data on seasonal incidence were mapped through aggregation of attribute data (LF cases) by months. Data analysis was through thematic mapping and descriptive statistics. Results: Thematic maps displayed spatial variation in the distribution of LF in the state; showing Ogoja LGA with highest incidence (61.25%) of the 800 reported cases; Ikom, the lowest; 1(0.125%) and zero case in 7 LGAs. There were no visually remarkable patterns to suggest strong influence of vegetation and natural drainage on transmission. Greater proportion (82.12%) of cases was recorded in the dry season. Conclusion: The study has produced prevalence map of LF in the state, which could guide intervention programmes; and has also revealed paucity of data at the disposal of healthcare authorities, a situation that could hinder large scale intervention. Findings identify poor health-seeking behavior of the population and poor disease surveillance strategies in the state. Community health education, strengthening of public health apparatus and interventions through mass drug administration and integrated vector control, are recommended.

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