BackgroundThe prevalence of infection with the three common soil-transmitted helminths (i.e. Ascaris lumbricoides, Trichuris trichiura, and hookworm) in Bolivia is among the highest in Latin America. However, the spatial distribution and burden of soil-transmitted helminthiasis are poorly documented.MethodsWe analysed historical survey data using Bayesian geostatistical models to identify determinants of the distribution of soil-transmitted helminth infections, predict the geographical distribution of infection risk, and assess treatment needs and costs in the frame of preventive chemotherapy. Rigorous geostatistical variable selection identified the most important predictors of A. lumbricoides, T. trichiura, and hookworm transmission.ResultsResults show that precipitation during the wettest quarter above 400 mm favours the distribution of A. lumbricoides. Altitude has a negative effect on T. trichiura. Hookworm is sensitive to temperature during the coldest month. We estimate that 38.0%, 19.3%, and 11.4% of the Bolivian population is infected with A. lumbricoides, T. trichiura, and hookworm, respectively. Assuming independence of the three infections, 48.4% of the population is infected with any soil-transmitted helminth. Empirical-based estimates, according to treatment recommendations by the World Health Organization, suggest a total of 2.9 million annualised treatments for the control of soil-transmitted helminthiasis in Bolivia.ConclusionsWe provide estimates of soil-transmitted helminth infections in Bolivia based on high-resolution spatial prediction and an innovative variable selection approach. However, the scarcity of the data suggests that a national survey is required for more accurate mapping that will govern spatial targeting of soil-transmitted helminthiasis control.
The distribution of hookworm in schistosomiasis-endemic areas in Brazil was mapped based on climate suitability. Known biological requirements of hookworm were fitted to data in a monthly long-term normal climate grid (18 x 18 km) using geographical information systems. Hookworm risk models were produced using the growing degree day (GDD) water budget (WB) concept. A moisture-adjusted model (MA-GDD) was developed based on accumulation of monthly temperatures above a base temperature of 15 °C (below which there is no lifecycle progression of Necator americanus) conditional on concurrent monthly values (rain/potential, evapotranspiration) of over 0.4. A second model, designated the gradient index, was calculated based on the monthly accumulation of the product of GDD and monthly WB values (GDD x WB). Both parameters had a significant positive correlation to hookworm prevalence. In the northeastern part of Brazil (the Caatinga), low hookworm prevalence was due to low soil moisture content, while the low prevalence in southern Brazil was related to low mean monthly temperatures. Both environmental temperature and soil moisture content were found to be important parameters for predicting the prevalence of N. americanus.
Visceral leishmaniasis (VL) is a neglected tropical disease transmitted by Lutzomyia longipalpis, a sand fly widely distributed in Brazil. Despite efforts to strengthen national control programs reduction in incidence and geographical distribution of VL in Brazil has not yet been successful; VL is in fact expanding its range in newly urbanized areas. Ecological niche models (ENM) for use in surveillance and response systems may enable more effective operational VL control by mapping risk areas and elucidation of eco-epidemiologic risk factors. ENMs for VL and Lu. longipalpis were generated using monthly WorldClim 2.0 data (30-year climate normal, 1-km spatial resolution) and monthly soil moisture active passive (SMAP) satellite L4 soil moisture data. SMAP L4 Global 3-hourly 9-km EASE-Grid Surface and Root Zone Soil Moisture Geophysical Data V004 were obtained for the first image of day 1 and day 15 (0:00-3:00 hour) of each month. ENM were developed using MaxEnt software to generate risk maps based on an algorithm for maximum entropy. The jack-knife procedure was used to identify the contribution of each variable to model performance. The three most meaningful components were used to generate ENM distribution maps by ArcGIS 10.6. Similar patterns of VL and vector distribution were observed using SMAP as compared to WorldClim 2.0 models based on temperature and precipitation data or water budget. Results indicate that direct Earth-observing satellite measurement of soil moisture by SMAP can be used in lieu of models calculated from classical temperature and precipitation climate station data to assess VL risk.
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