Predicting and Validating Malaria Vulnerability in Rural Kwara State, Nigeria: A Geospatial - Clinical Laboratory Approach

Abstract

Background: Geographical Information System (GIS) establish relationship or link between vector borne diseases and associated environmental factors thereby providing explanation for the spatial distribution pattern, possible causes of diseases outbreak and implication on the community. We hypothesized, if GIS data could correlates with laboratory-based quantitative assessment of malaria prevalence pattern in rural Kwara State, Nigeria. This work focuses on utilization of GIS hardware, software to map, predict, communicate risk, in some selected geographic area and was substantiated with determination of malaria prevalence with RDTs and Giemsa Microscopy. Methods: Garmin GPS was used to capture the coordinates (Lat/Long) of 6 selected settlements and overlaid with a geo-referenced satellite image in the study area. A total of One hundred and thirty five (135) vulnerable individuals were diagnosed for Malaria with light Olympus microscope and rapid diagnostic kit. Data were entered and analyzed using R-Package for Statistical Computing and Graphics. Results: Apodu and Elemere had the highest malaria vulnerability index within 300m radius and the vulnerability index increases as one move away from the center of the settlement. The possible explanation for this high vulnerability could be the presence of pond/lake in Apodu. This is a good breeding site for mosquito couple with dense vegetation as one move from the centre of the settlements. Unlike Apodu, Gbugudu was at highest risk at 100 m buffer (60%) but the vulnerability index decreases as one move away from the settlement centre. The absence of thick vegetation and presence numerous cultivated farmlands on the eastern part could have been responsible for this observation. The RDT results revealed 37% malaria prevalance in all three communities combined while Light microscopy recorded 48% positivity rate. However, with Light microscopy, Apodu community had a higher infected to non-infected persons' ratio at 58.7% to 41.3% than Gbugudu and Elemere, both of which showed lower prevalence rates at 30.3% and 46.2% respectively. Conclusions: Findings of this study showed dense vegetation and ponds within Apodu, Elemere and Malete centres serves a good breeding site for mosquito coupled with dense vegetation was responsible for the high vulnerability index at these areas. Settlements within 1 km radius around KWASU campus recorded lower index possibly due to low vegetation. Results from this study indicate that the degree of malaria parasitaemia in the three settlement correlates directly with the remote sensing data. Funding Statement: Oluwasogo A Olalubi was a recipient of Tertiary Education (Tetfund) Institution Research Grant No:KWASUTETFUND/2016ABUJA/1/31. Declaration of Interests: No competing interests were disclosed. Ethics Approval Statement: All aspects of the study were approved by Kwara State University Research Committee and Ethical Review Board. Verbal and written Informed consent was obtained from all the community leaders/respondents in the three major settlement screened. They were assured of voluntary participation,confidentiality of their test results and responses and the opportunity to withdraw at any time withoutprejudice in line with the Helsinki Declaration was emphasized (World Medical Association, 2001).