Spatial and Seasonal Patterns of Indoor-Resting Mosquitoes Across the Sudan and Sahel Savannah Zones of Bauchi State Nigeria
DOI:
https://doi.org/10.54987/jebat.v9i1.210Keywords:
Anopheles gambiae complex, Entomological surveillance, Indoor-resting mosquitoes, Malaria vectors, Pyrethrum spray catchAbstract
Indoor mosquito abundance varies across ecological settings and seasons and can provide useful surveillance information for malaria-vector control. This study conducted a secondary spatial and temporal analysis of previously collected indoor mosquito surveillance data from Bauchi State, Nigeria, with emphasis on ecological-zone and local-government-area patterns. The analysis used the LGA-level and monthly observations available from a previous pyrethrum spray catch (PSC) survey covering nine LGAs and 270 rooms. The available dataset contained 6,935 adult mosquitoes, including 2,841 Anopheles gambiae sensu lato. Four LGAs were classified within the Sudan savannah and five within the Sahel savannah. Descriptive frequencies, percentages and reconstructed monthly index summaries were used. Because original room-level replicate observations were unavailable for this secondary analysis, no new inferential tests were performed. Bauchi LGA contributed the largest adult mosquito catch (1,200; 17.3%), whereas Dambam contributed the smallest (506; 7.3%). Anopheles gambiae sensu lato represented 41.0% of all adult mosquitoes. Its proportional contribution ranged from 21.9% in Jama’are to 59.9% in Dambam. The monthly reported indices showed recurrent increases during June–August and generally lower values during parts of the late dry season. The mean reported monthly index was 2.52 in the Sudan-zone LGAs and 2.04 in the Sahel-zone LGAs in the reconstructed summary. The available surveillance data demonstrate spatial heterogeneity in indoor mosquito abundance and substantial variation in the contribution of Anopheles gambiae sensu lato across Bauchi State. The findings support continued geographically distributed surveillance, particularly around the rainy season. Because the present analysis is based on aggregate secondary data, the observed patterns should be interpreted as descriptive rather than causal or inferential.
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