Ecological Drivers of Mansonella perstans Infection in Uganda and Patterns of Co-endemicity with Lymphatic Filariasis and Malaria

Abstract

Background: Mansonella perstans is a widespread, but relatively unknown human filarial parasite transmitted by Culicoides biting midges. Although it is found in many parts of sub-Saharan Africa, only few studies have been carried out to deepen the understanding of its ecology, epidemiology, and health consequences. Hence, knowledge about ecological drivers of the vector and parasite distribution, integral to develop spatially explicit models for disease prevention, control, and elimination strategies, is limited.

Methodology: We analyzed data from a comprehensive nationwide survey of M. perstans infection conducted in 76 schools across Uganda in 2000-2003, to identify environmental drivers. A suite of Bayesian geostatistical regression models was fitted, and the best fitting model based on the deviance information criterion was utilized to predict M. perstans infection risk for all of Uganda. Additionally, we investigated co-infection rates and co-distribution with Wuchereria bancrofti and Plasmodium spp. infections observed at the same survey by mapping geographically overlapping areas.

Principal findings: Several bioclimatic factors were significantly associated with M. perstans infection levels. A spatial Bayesian regression model showed the best fit, with diurnal temperature range, normalized difference vegetation index, and cattle densities identified as significant covariates. This model was employed to predict M. perstans infection risk at non-sampled locations. The level of co-infection with W. bancrofti was low (0.3%), due to limited geographic overlap. However, where the two infections did overlap geographically, a positive association was found.

Conclusions/significance: This study presents the first geostatistical risk map for M. perstans in Uganda. We confirmed a widespread distribution of M. perstans, and identified important potential drivers of risk. The results provide new insight about the ecologic preferences of this otherwise poorly known filarial parasite and its Culicoides vector species in Uganda, which might be relevant for other settings in sub-Saharan Africa.

Fig 1. School survey locations and observed prevalence of M. perstans microfilaremia in Uganda.

Fig 2. Observed proportional distribution of mono- and co-infections (yellow) with M. perstans (green) and W. bancrofti filariasis (red).

Data from 11,606 pupils aged 5–19 years in 76 schools in Uganda (2000–2003).

Fig 3. Geostatistical model-based predicted mean prevalence of Mansonella perstans in school-aged children in Uganda.

Smooth map of the predicted mean prevalence of M. perstans (a), and the corresponding map of the standard deviations of the predictions (b), highlighting areas of high/low uncertainty associated with the model predictions.

Fig 4. Maps of the predicted geographic co-distribution of M. perstans and W. bancroftibased on A) a 10% prevalence threshold, and B) a 5% prevalence threshold.

The predicted areas are based on surveys of Ugandan school-aged children in 2000–2003 and Bayesian geostatistical model predictions of each (single) parasite infection. Predicted areas of high risk malaria (Plasmodium spp. infection prevalence >50%) is shown in hatch as an overlay.