Background
The environmental landscape within an area is a significant factor in determining the spatial distribution of many different disease vectors, reservoirs, intermediate hosts and parasites and, thus, also the spatial distribution of a variety of diseases, including human African trypanosomiasis (HAT; also known as sleeping sickness). These correlations can be quantified and described to allow greater understanding and highlight areas with potentially higher risks of vector or reservoir presence, disease transmission, or both [
1‐
3].
Trypanosoma brucei rhodesiense, the vector transmitted parasite subspecies which causes the fatal disease Rhodesian HAT, is reliant on the availability of suitable habitat and environmental conditions for the tsetse vector (
Glossina spp.). Due to this association with particular types of land cover, HAT (and tsetse) distributions can be correlated with landscape information that captures the distribution of potential tsetse habitats. An increased risk of Rhodesian HAT in areas close to ‘long vegetation swamp’ habitats has been detected in two recent studies [
4,
5]. Several other studies have examined tsetse populations and risk of Gambian HAT (caused by
Trypanosoma brucei gambiense) in relation to the presence of particular crop types (such as coffee or cocoa) [
6,
7], the level of human land use, disturbance of vegetation and also human movement patterns [
8‐
10].
The recent spread of Rhodesian HAT in Uganda, the only country which sustains active transmission of both
T.
b.
rhodesiense and
T.
b.
gambiense[
11], has led to increasing concern over a potential future overlap of the two forms of the disease [
12]. The north-west spread of
T.
b.
rhodesiense, which has been attributed to the movement of infected livestock (the main reservoir of the parasite in Uganda) from endemic areas, has brought areas of transmission of the two forms within 150 km of one another [
11‐
15]. Treatment protocols differ between the two forms of HAT and the current diagnostic methods available in affected areas of Uganda are not suitable for definitive sub-species differentiation. Thus, a future overlap may severely compromise treatment and increase the likelihood of treatment failures. In light of this recent spread of Rhodesian HAT, there is an urgent need for evidence-based, spatially focused control measures.
Rhodesian HAT occurs in poor, remote, rural areas with low human population densities and evidence suggests that the majority of
T.
b.
rhodesiense infections are acquired outside of the village of residence [
5,
16,
17]. Specific activities have been implicated in Rhodesian HAT acquisition such as watering livestock and collecting water or firewood, implicating the landscape profile of areas surrounding the village of residence in epidemiological risk [
16,
17]. Despite the apparent advantages of spatially targeted disease control within individual HAT foci, few attempts have been made to identify the specific locations that HAT cases acquire their infections. The majority of research focuses on the village or household of residence as the spatial entity to which epidemiological data is attached, although the analysis of this type of data will not allow the identification of areas with an elevated epidemiological risk. Laveissière
et al. [
18] proposed the use of entomological data (fly density, age and blood meals) to calculate an epidemiological risk index relating to the density of vectors and the amount of human-tsetse contact. However, the entomological surveys required for this risk index can be costly and time consuming. More recently, the identification of high risk areas for
T.
b.
gambiense transmission, to allow the implementation of targeted tsetse control, was carried out by Courtin
et al. [
10] by tracking the movements of individuals (HAT cases and controls) and characterising the epidemiological risk of different sites and activities. Another recent study (focusing on Rhodesian HAT in Uganda) investigated the significance of the proportion of different sized buffer zones (circular zones, of defined radius, centred on a point of interest) surrounding homesteads that intersected with areas of wetland for HAT acquisition. It was found that areas of wetland within 500 m to 3 km of homesteads significantly increased the risk of Rhodesian HAT with the highest significance observed between 800 and 900 m [
5].
The significance of wetland areas up to 3 km from the homestead for the risk of Rhodesian HAT indicates that transmission may occur up to 3 km away from the homestead [
5]. In addition, the average distance of daily short-distance trips (e.g. to work or to fetch water) for village residents in Uganda (the predominant population group in
T.
b.
rhodesiense endemic areas) has been estimated to range from approximately 2 km for low income households to 4 km for high income households [
19], reinforcing the hypothesis that HAT transmission occurs within approximately 3 km of the homestead. Using geo-referenced epidemiological data (i.e. data that can provide spatial information on where HAT patients live), it is possible to identify the areas in which patients will normally carry out their daily activities by creating a buffer (circular zone) around their homestead or village of residence. These “daily activity areas” can be used to represent the area in which HAT acquisition most likely occurred based on the hypothesis that transmission normally occurs within 3 km of the homestead. It also follows that the areas in which a large number of HAT patient’s daily activity areas overlap may constitute areas of elevated epidemiological risk. These are areas that individuals from a number of neighbouring villages visit regularly, with landscape features that promote a high level of interaction between tsetse, livestock reservoirs (mainly cattle) and humans, thus, encouraging a high intensity of HAT transmission. Areas with an elevated epidemiological risk should be considered as priority areas for HAT control activities, including tsetse control and livestock based interventions.
The current research aims to provide a starting point for the identification of locations with elevated transmission of Rhodesian HAT (due to high levels of contact between humans and tsetse) in comparison to other areas by combining previous findings with epidemiological and environmental data. The exploratory approach discussed above was used, combining geo-referenced Rhodesian HAT patient records (and matched controls) and information on the average daily distances travelled to identify areas with an elevated epidemiological risk in Soroti and Serere districts, Uganda, over a four year period. A classified land cover map for the area was created using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery to allow characterisation of the landscape profiles within areas of high epidemiological risk. Utilising case records geo-located to the village of residence to identify potential high transmission areas, the costs associated with the types of studies discussed above (collecting entomological data or human movement data) can be alleviated. The elevated epidemiological risk areas identified in this manner may provide a starting point for the spatial targeting of tsetse trapping activities in the study area, and can also provide additional information on the landscape profiles conducive to intense transmission of Rhodesian HAT.
Discussion
The investigation of areas with elevated risk of HAT transmission is difficult as infection normally occurs outside of the village of residence in areas where humans come into contact with tsetse [
16,
17]. The location of a HAT patient’s village of residence or homestead does not provide sufficient information to identify the areas in which an elevated epidemiological risk occurs or the landscape features contributing to this increased infection risk. The methods which have previously been used to identify high transmission risk areas (e.g. the use of entomological sampling or the tracking of human movements) are time consuming and can be costly [
10,
18]. Here, a novel method has been explored, utilising knowledge of the distance outside of the village of residence travelled by village inhabitants on an average day to identify the areas which are likely to support elevated HAT transmission. The data acquisition required for this method is less time and resource intensive than previous methods, allowing the identification of potential epidemiological risk areas with minimal field-based surveys. Consistent differences between the overlap zones of cases and controls were detected and several epidemiological risk zones identified; these areas are likely to be frequented by the residents of a number of surrounding villages (i.e. to water and graze livestock or collect firewood), and due to their particular landscapes and environmental conditions, may promote a high level of interaction between tsetse vectors, livestock and humans.
The application of buffer analysis in spatial epidemiology is not uncommon, and is typically used to include landscape features surrounding the home or village of residence in an analysis (e.g., [
4,
31]), particularly in cases where disease transmission is expected to occur outside of the home or village. However, it is unlikely that the landscape within the full buffer area contributes to the risk of disease transmission, particularly in the case of Rhodesian HAT, where transmission tends to occur in localised areas which promote increased interaction between humans, livestock and tsetse. The use of full buffer areas in these situations will dilute attempts to delineate epidemiological risk areas and will weaken correlations between the locations of cases and the occurrence of specific landscape features (e.g. specific types of land cover). By identifying areas which are within 3 km of several HAT patients’ villages (e.g. overlap areas) rather than using the full buffer areas, it is possible to select portions of the buffer which are more likely to represent an increased epidemiological risk of HAT.
An analysis of the landscape within overlap zones using a range of thresholds (based on the number of overlapping daily activity areas) illustrated consistency (across the four annual periods and with increasing threshold values) in the differences between the overlap zones for cases and controls with respect to the proportions occupied by seasonally flooding grassland and lake fringe swamp. The significantly higher proportions of these land cover classes in case overlap zones than control overlap zones correlates with the habitat requirements of Glossina fuscipes fuscipes, the primary vector within the study area (prefers riverine vegetation). These results indicate that the landscape in areas which are likely to have been frequented by HAT patients differs from the landscape in areas likely to have been frequented by controls, and is more likely to support Glossina spp. populations and, therefore, transmission of HAT. The difference in landscape between cases and controls was smaller using the full buffer areas, and in some cases the consistent trends described above were reversed. This indicates that the benchmark situation may not have adequately targeted the epidemiological risk areas and the specific landscape profiles within the selected areas may have been diluted.
Using the 99th percentile for the selection of high overlap zones, a distinct difference can be observed between the case and control zones; the high overlap areas for cases (epidemiological risk zones) moved gradually over the study period, but the high overlap areas for controls remained relatively static and close to Serere hospital. A clear temporal trend in the landscape can be observed within these high overlap zones over the four annual periods. Within the first annual period, there was no significant difference in the proportional coverage of crops and open savannah or seasonally flooding grassland or the elevation between case and control high overlap areas. No significant difference was observed for the proportion of high overlap areas that was built up and bare ground for the first or second annual periods. In subsequent years, however, the differences between case and control high overlap areas became statistically significant; there was a significantly lower proportion of the land cover classes built up and bare ground and crops and open savannah in the case high overlap zones and a significantly larger proportion of seasonally flooding grassland. In addition, the average elevation was significantly lower in case high overlap areas than controls in the second, third and fourth annual periods. For the woodland and dense savannah land cover classes, the proportion of high overlap area was larger for controls than cases for all annual periods, except for the third annual period where this pattern was reversed.
The temporal movement of the potential high transmission zones and the changing landscape profiles within these areas reflects the spatial dispersal of the disease outwards from the point of initial introduction (the livestock market) over time [
13,
32]. The landscapes within the potential high transmission zones, particularly in the third and fourth annual periods, may constitute areas with a higher risk of
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b.
rhodesiense transmission due their greater suitability for vector populations, combined with an increased amount of interaction between humans, livestock and tsetse. As the potential high transmission zones were, by definition, areas outside the village, the human population density of the areas should be low. The low population density and a lower level of human disturbance (due to less agricultural activity as evidenced by a lower proportion of the land cover class crops and open savannah) results in less disturbance of potential tsetse habitat. The presence of land cover classes which provide suitable tsetse habitat (such as seasonally flooding grassland), in combination with less human disturbance may partly explain an elevated transmission risk. In addition to the characterised landscape profiles within the epidemiological risk zones, it is likely that local factors influencing the daily movement patterns of village inhabitants from surrounding villages also play a role. For example areas of seasonally flooding grassland may be used frequently for the watering of livestock for surrounding villages, thus, increasing contact between humans, livestock and tsetse flies and promoting transmission of
T.
b rhodesiense. The accessibility of these areas may also contribute, although it has not been possible to examine such factors using the data available.
The selection of a single threshold value to allow the observation of differences between case and control high overlap zones across each of the four annual periods is not a straightforward decision. Ideally, to allow comparability between the results for each of the four annual periods, the same threshold value would be used for each. However, the varying case (and, therefore, control) numbers in each of the annual periods, in addition to spatial heterogeneity, meant that the maximum number of overlapping daily activity areas differed for cases and controls, and for each of the four annual periods. The 99th percentile was selected to give an initial illustration of the potential for this exploratory method, but future work should consider refining the threshold selection.
The information provided from this type of exploratory analysis may enable the micro-scale spatial targeting of tsetse control activities, including the employment of tsetse traps or livestock based control (treatment and restricted application [RAP] of insecticides to livestock) [
33,
34]. The implementation of spatially targeted vector control in areas where people may be at a greater risk of acquiring HAT (due to landscape features) may have a direct impact on transmission of
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b.
rhodesiense to humans at a local scale, enabling a reduction in the burden of Rhodesian HAT in the most affected communities. Localised vector control along with RAP insecticide use across larger areas (e.g. districts or sub counties) may complement one another by focusing on both the interruption of local transmission cycles and the reduction of
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b.
rhodesiense prevalence in reservoirs in a spatially hierarchical manner. The spatial targeting of traps in locations identified as having an elevated epidemiological risk has also been proposed for the control of Gambian HAT in West Africa [
10].
Acknowledgements
This study was supported by the World Health Organization (SCW, NAW), DFID Research Into Use Programme (SCW, NAW), the Medical Research Council (PMA, SCW, NAW - project G0902445; NAW, PMA – project MR/J012343/1), IKARE (SCW, NAW) and the Wellcome Trust (SCW; EMF - grant number 085308). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Competing interests
The authors declare no competing financial interests.
Authors’ contribution
The data acquisition was conducted by EMF. The study design was conceived and data analysis performed by NAW. PMA provided expertise and assistance with land cover classification and spatial data analysis. The manuscript was written by NAW and PMA, with all authors contributing to the interpretation of results and the final manuscript.