Lymphatic filariasis in Luangwa District, South-East Zambia

BACKGROUND: Past case reports and recent data from LF mapping surveys indicate that LF occurs in Zambia, but no studies have been carried out to document its epidemiology and health implications. The present study assessed infection, disease, transmission and human perception aspects of LF in an endemic area of Luangwa District, South-East Zambia, as a background for planning and implementation of control. METHODS: Two neighbouring rural communities were registered and a questionnaire survey undertaken. Clinical examination, and sampling of blood for circulating filarial antigens (CFA; marker of adult worm infection) and antibodies to Bm14 antigen (marker of exposure to transmission), were carried out during the daytime. Blood from CFA positive individuals was examined for microfilariae (mf) at night. Vector surveys were carried out in selected households, using light traps. RESULTS: 985 individuals aged ≥ 1 year were registered. The CFA prevalence increased with age from 1.2% in age group 1–14 years to 20.6% in age group 50+ years (overall 8.6%). Wuchereria bancrofti mf were identified in 10.9% of CFA positive individuals (corresponding to a community prevalence of 0.9%). Prevalence and intensity of Bm14 antibodies were much higher in individuals ≥ 30 years than in younger individuals (57.2 vs. 19.3%; 0.594 vs. 0.241 OD-values). Elephantiasis and hydrocele were well known clinical manifestations in the area, but only one case of hydrocele was detected in the study population. Identified potential vectors were Anopheles funestus and An. gambiae. CONCLUSION: The study confirmed that LF was endemic in the study communities, but infection and disease prevalence was low. Several indications, including a marked recent decline in CFA prevalence, suggest that transmission in the area is on the decrease, perhaps because of intensive application of malaria control measures targeting the Anopheles vectors. It is recommended that mass drug administration is initiated to accelerate this positive trend of decline in LF transmission in the area

Mapping the Geographical Distribution of Lymphatic Filariasis in Zambia

<div><p>Background</p><p>Past case reports have indicated that lymphatic filariasis (LF) occurs in Zambia, but knowledge about its geographical distribution and prevalence pattern, and the underlying potential environmental drivers, has been limited. As a background for planning and implementation of control, a country-wide mapping survey was undertaken between 2003 and 2011. Here the mapping activities are outlined, the findings across the numerous survey sites are presented, and the ecological requirements of the LF distribution are explored.</p><p>Methodology/Principal findings</p><p>Approximately 10,000 adult volunteers from 108 geo-referenced survey sites across Zambia were examined for circulating filarial antigens (CFA) with rapid format ICT cards, and a map indicating the distribution of CFA prevalences in Zambia was prepared. 78% of survey sites had CFA positive cases, with prevalences ranging between 1% and 54%. Most positive survey sites had low prevalence, but six foci with more than 15% prevalence were identified. The observed geographical variation in prevalence pattern was examined in more detail using a species distribution modeling approach to explore environmental requirements for parasite presence, and to predict potential suitable habitats over unsurveyed areas. Of note, areas associated with human modification of the landscape appeared to play an important role for the general presence of LF, whereas temperature (measured as averaged seasonal land surface temperature) seemed to be an important determinant of medium-high prevalence levels.</p><p>Conclusions/significance</p><p>LF was found to be surprisingly widespread in Zambia, although in most places with low prevalence. The produced maps and the identified environmental correlates of LF infection will provide useful guidance for planning and start-up of geographically targeted and cost-effective LF control in Zambia.</p></div

Overview of study sites, and the numbers, positivity for circulating filarial antigens (CFA), ages and gender ratios of examined volunteers.

<p>Only volunteers with a valid CFA test result are included (tests of 229 volunteers produced invalid results).</p><p>* Milenge East 7 & Changwe Lungo.</p><p>** Mulanga-Chibesakunda.</p><p>*** Mukandankunda-Ishindi.</p><p>**** Silembe Kalambwe-Imenda.</p><p>***** Nalikwanda–Singonda.</p

Properties and sources of the remotely sensed and other environmental predictors used to model LF prevalence in Zambia.

1<p>Moderate Resolution Imaging Spectroradiometer (MODIS); available at <a href="https://lpdaac.usgs.gov/" target="_blank">https://lpdaac.usgs.gov/</a> (accessed February 2012).</p>2<p>Global Land Cover Network (GLCN); available at <a href="http://www.glcn.org/databases/lc_gc-africa_en.jsp" target="_blank">http://www.glcn.org/databases/lc_gc-africa_en.jsp</a> (accessed February 2012).</p>3<p>World Clim - Global Climate data, available at <a href="http://www.worldclim.org/" target="_blank">http://www.worldclim.org/</a> (accessed February 2012).</p>4<p>United States Geological Services (USGS) Digital Elevation Model (DEM) available at: <a href="http://eros.usgs.gov/" target="_blank">http://eros.usgs.gov/</a> (accessed February 2012).</p>5<p>Socioeconomic Data and Applications Center, available at <a href="http://sedac.ciesin.columbia.edu/data/set/wildareas-v2-human-influence-index-geographic" target="_blank">http://sedac.ciesin.columbia.edu/data/set/wildareas-v2-human-influence-index-geographic</a>. (accessed February 2012).</p

Map resulting from the overlay of the thresholded versions of the maps in Figure 4.

<p>The map depicts areas of predicted presence of ≥15% CFA prevalence (brown), ≥5% CFA prevalence (orange+brown) and areas where no or <5% CFA is predicted to be present (light yellow).</p

Response curves illustrating the relationship of MaxEnt predicted probability of occurrence to environmental variables.

<p>The values shown on the y-axis is the predicted probability of suitable conditions, as given by the logistic output format, with only the particular predictor variable used to develop the MaxEnt model. (a) The figure shows the relationship between the Human Influence Index and the predicted probability of occurrence of CFA≥5% (model 1), (b) depicts the relationship between day-time land surface temperature in the rainy season (LSTday (rainy)) and the probability of LF as modeled by model 2 (CFA≥15%), (c) shows the relationships between day-time land surface temperature in the hot-dry season (LSTnight (hot-dry) and the probability of LF occurrence as modeled by model 1 and 2, respectively, and (d) shows the relationship between the distance to nearest surface water bodies and the probability of occurrence of LF as modeled by model 1 and model 2, respectively.</p

Summary statistics of jackknife test of environmental variable importance, evaluation measures, and maximum training sensitivity plus specificity threshold results for MaxEnt model 1 (sites with CFA≥5%) and model 2 (sites with CFA prevalence ≥15%).

<p>Only the 7 predictors that were ranked in the top three of at least one of the two models are included. The top three predictors for each model are highlighted in bold.</p><p>*LST; Land Surface Temperature.</p><p>**NDVI; Normalized Difference vegetation Index.</p><p>***AUC; the area under the Receiver Operating Characteristic curve (and standard deviation).</p><p>**** CORprev is the Pearsons product moment correlation between model logistic probability and the measured CFA prevalence at survey sites.</p

Maps of the MaxEnt predicted distributions of CFA prevalence categories.

<p>(A) The heatmap values represent the relative probabilities of presence of LF with at least 5%, CFA prevalence (model 1). (B) The heatmap represent the predicted relative probability of presence of LF with at least 15% CFA prevalence (model 2).</p