Evidence of Spatial Clustering Distribution Patterns of Malaria in Epe, Lagos, Nigeria

Investigation of the spatial distribution patterns of malaria with the goal of detecting intense transmission areas and clustering is prerequisite to planning an effective targeted malaria intervention. Parasitological sampling was done in settlements in Epe and Orimedu, Lagos, Nigeria. Blood samples were collected from 360 participants with georeferenced residences, selected through multistage systematic sampling technique. Each study area was delineated into 3 Malaria Risk Zones (MRZs), namely; Very High (V-MRZ), High (H-MRZ) and low (L-MRZ), according to distances of 500m, 1000m and 1500m respectively away from perennial water bodies. Clustering and Outlier analysis was carried out to generate predictive malaria risk maps. Overall malaria prevalence was 32.2%., being significantly higher in Orimedu (52.6%) than Epe (47.4%), p<005. Prevalence was 28%, 32% and 50% in the VH-MRZ, High-MRZ and L-MRZ respectively in Epe. H-MRZ accounted for the highest prevalence (67%), in Orimedu, followed by the V-MRZ (39%) while the L-MRZ was uninhabited. Malaria clustering was detected in Uraka, Iberikodo and Sagidan settlements in Epe (Moran’s Index = 062, p<005) but not in Orimedu. The multiple distinct malaria risk zones coupled with the characteristic steep topographic may be responsible for forcing malaria to localize and cluster in Epe compared to Orimedu.

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Publication Details

Journal
Epidemiology International Journal
Published
2024-11-04
DOI
https://doi.org/10.23880/eij-16000283
Primary Topic
COVID-19 epidemiological studies
Type
article
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article

Evidence of Spatial Clustering Distribution Patterns of Malaria in Epe, Lagos, Nigeria

Abdulrahman BB, Adesola AH
Epidemiology International Journal
COVID-19 epidemiological studies
article

Evidence of Spatial Clustering Distribution Patterns of Malaria in Epe, Lagos, Nigeria

Abdulrahman BB, Adesola AH
article en

Abstract

Investigation of the spatial distribution patterns of malaria with the goal of detecting intense transmission areas and clustering is prerequisite to planning an effective targeted malaria intervention. Parasitological sampling was done in settlements in Epe and Orimedu, Lagos, Nigeria. Blood samples were collected from 360 participants with georeferenced residences, selected through multistage systematic sampling technique. Each study area was delineated into 3 Malaria Risk Zones (MRZs), namely; Very High (V-MRZ), High (H-MRZ) and low (L-MRZ), according to distances of 500m, 1000m and 1500m respectively away from perennial water bodies. Clustering and Outlier analysis was carried out to generate predictive malaria risk maps. Overall malaria prevalence was 32.2%., being significantly higher in Orimedu (52.6%) than Epe (47.4%), p<005. Prevalence was 28%, 32% and 50% in the VH-MRZ, High-MRZ and L-MRZ respectively in Epe. H-MRZ accounted for the highest prevalence (67%), in Orimedu, followed by the V-MRZ (39%) while the L-MRZ was uninhabited. Malaria clustering was detected in Uraka, Iberikodo and Sagidan settlements in Epe (Moran’s Index = 062, p<005) but not in Orimedu. The multiple distinct malaria risk zones coupled with the characteristic steep topographic may be responsible for forcing malaria to localize and cluster in Epe compared to Orimedu.

Epidemiology International JournalVol. 8(4)
Openalex Percentile: Top 73%
COVID-19 epidemiological studies
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Evidence of Spatial Clustering Distribution Patterns of Malaria in Epe, Lagos, Nigeria — Abdulrahman BB, Adesola AH · Epidemiology International Journal (2024) | TGRS Research Map | TGRS