Lymphatic filariasis in Nigeria; micro-stratification overlap mapping (MOM) as a prerequisite for cost-effective resource utilization in control and surveillance

Abstract

Background: Nigeria has a significant burden of lymphatic filariasis (LF) caused by the parasite Wuchereria bancrofti. A major concern to the expansion of the LF elimination programme is the risk of serious adverse events (SAEs) associated with the use of ivermectin in areas co-endemic with Loa filariasis. To better understand this, as well as other factors that may impact on LF elimination, we used Micro-stratification Overlap Mapping (MOM) to highlight the distribution and potential impact of multiple disease interventions that geographically coincide in LF endemic areas and which will impact on LF and vice versa.

Methodology/principal findings: LF data from the literature and Federal Ministry of Health (FMoH) were collated into a database. LF prevalence distributions; predicted prevalence of loiasis; ongoing onchocerciasis community-directed treatment with ivermectin (CDTi); and long-lasting insecticidal mosquito net (LLIN) distributions for malaria were incorporated into overlay maps using geographical information system (GIS) software. LF was prevalent across most regions of the country. The mean prevalence determined by circulating filarial antigen (CFA) was 14.0% (n = 134 locations), and by microfilaria (Mf) was 8.2% (n = 162 locations). Overall, LF endemic areas geographically coincided with CDTi priority areas, however, LLIN coverage was generally low (<50%) in areas where LF prevalence was high or co-endemic with L. loa.

Conclusions/significance: The extensive database and series of maps produced in this study provide an important overview for the LF Programme and will assist to maximize existing interventions, ensuring cost effective use of resources as the programme scales up. Such information is a prerequisite for the LF programme, and will allow for other factors to be included into planning, as well as monitoring and evaluation activities given the broad spectrum impact of the drugs used.

Figure 1. Map of Nigeria and its geopolitical zones.

North Central - Benue, FCT, Kogi, Kwara, Nasarawa, Niger, Plateau. North East - Adamawa, Bauchi, Borno, Gombe, Taraba, Yobe. North West - Kaduna, Katsina, Kano, Kebbi, Sokoto, Jigawa,, Zamfara. South East - Abia, Anambra, Ebonyi, Enugu, Imo. South - Akwa-Ibom, Bayelsa, Cross-River, Delta, Edo, Rivers. South West - Ekiti, Lagos, Osun, Ondo, Ogun, Oyo. Note: Elevation data based on ETOPO2 global 2-minute gridded resolution from National Oceanic and Atmospheric Administration (NOAA) available from ESRI Redland, CA.

Figure 2. LF prevalence data, endemicity status and disease data.

a. CFA and Mf data. b. LF endemicity. c. Disease data. Note: Data source for CFA, MF prevalence (2a) and disease (2c) data available in Table S1. LF endemicity map (2c) developed by FMoH.

Figure 3. LF prevalence data pre-MDA and post-MDA.

a. Pre-MDA CFA (n = 68). b. Post-MDA CFA (n = 66). c. Pre-MDA Mf (n = 124). d. Post-MDA Mf (n = 38). Note: Data source for CFA, MF prevalence available in Table S1.

Figure 4. LF prevalence overlapping loiasis areas.

a. CFA prevalence and loiasis. b. Mf prevalence and loiasis. c. LF endemicity and loiasis. d. Close up of LF and loiasis overlap. Note: Loiaisis endemicity based on eye worm history map determined from RAPLOA surveys published by Zouré et al. 2011 . Three levels of loiasis shaded green <20%, yellow 20–40% and dark brown >40% highlight the extent of geographical overlap between CFA (4a) and MF (4b) prevalence data points available in Table S1. Figure 4c shows loiasis overlap with LF endemicity map developed by the FMoH, and the medium to high risk loiasis areas (yellow and dark brown shading) of the south eastern region is shown close-up in 4d. The small localized high risk loiasis area (dark brown) geographically coincides with areas classified as LF non-endemic (solid green).

Figure 5. LF prevalence and intervention distribution overlap.

a. CDTi treatment (ivermectin). b. CDTi and LF. c. CDTI and loaisis. d. LLIN coverage. e. LLINs and LF. f. LLINs and loiasis. Note: Data source for CDTi (5a) based on WHO-APOC Country profile – Nigeria (shaded grey) and for LLIN coverage (5d) based on Malaria Indicator Survey (shaded blue) to highlight the geographical overlap with CFA and Mf data prevalence points from Table S1(5b and 5e) and loiasis map by Zouré et al. 2011 (5c and 5f) respectively.