Integrated risk mapping and landscape characterisation of lymphatic filariasis and loiasis in South West Nigeria.

Nigeria has the heaviest burden of lymphatic filariasis (LF) in sub-Saharan Africa, which is caused by the parasite and transmitted by mosquitoes. LF is targeted for elimination and the national programme is scaling up mass drug administration (MDA) across the country to interrupt transmission. However, in some regions the co-endemicity of the filarial parasite (loiasis) is an impediment due to the risk of severe adverse events (SAEs) associated with the drug ivermectin. To better understand factors influencing LF elimination in loiasis areas, this study conducted a cross-sectional survey on the prevalence and co-distribution of the two infections, and the potential demographic, landscape, human movement, and intervention-related risk factors at a micro-level in the South West zone of Nigeria. In total, 870 participants from 10 communities on the fringe of a meso-endemic loiasis area of Osun State were selected. LF prevalence was measured by clinical assessment and using the rapid immunochromatographic test (ICT) to detect antigen. Overall LF prevalence was low with ICT positivity ranging from 0 to 4.7%, with only 1 hydrocoele case identified. Males had significantly higher ICT positivity than females (3.2% vs 0.8%). Participants who did not sleep under a bed net had higher ICT positivity (4.0%) than those who did (1.3%). ICT positivity was also higher in communities with less tree coverage/canopy height (2.5-2.8%) than more forested areas with greater tree coverage/canopy height (0.9-1.0%). In comparison, loiasis was determined using the rapid assessment procedure for loiasis (RAPLOA), and found in all 10 communities with prevalence ranging from 1.4% to 11.2%. No significant difference was found by participants' age or sex. However, communities with predominately shrub land (10.4%) or forested land cover (6.2%) had higher prevalence than those with mosaic vegetation/croplands (2.5%). Satellite imagery showed denser forested areas in higher loiasis prevalence communities, and where low or no ICT positivity was found. Only one individual was found to be co-infected. GPS tracking of loiasis positive cases and controls also highlighted denser forested areas within higher loiasis risk communities and the sparser land cover in lower-risk communities. Mapping LF-loiasis distributions against landscape characteristics helped to highlight the micro-heterogeneity, identify potential SAE hotspots, and determine the safest and most appropriate treatment strategy.