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Mapping hotspots of malaria transmission from pre-existing hydrology, geology and geomorphology data in the pre-elimination context of Zanzibar, United Republic of Tanzania.

Hardy A, Mageni Z, Dongus S, Killeen G, Macklin MG, Majambare S, Ali A, Msellem M, Al-Mafazy AW, Smith M, Thomas C - Parasit Vectors (2015)

Bottom Line: Previous studies have relied on surface topographic wetness to indicate hydrological potential for vector breeding sites, but this is unsuitable for karst (limestone) landscapes such as Zanzibar where water flow, especially in the dry season, is subterranean and not controlled by surface topography.We examine the relationship between dry and wet season spatial patterns of diagnostic positivity rates of malaria infection amongst patients reporting to health facilities on Unguja, Zanzibar, with the physical geography of the island, including land cover, elevation, slope angle, hydrology, geology and geomorphology in order to identify transmission hot spots using Boosted Regression Trees (BRT) analysis.Specifically, high infection rates in the central and southeast regions of the island coincide with outcrops of hard dense limestone which cause locally elevated water tables and the location of dolines (shallow depressions plugged with fine-grained material promoting the persistence of shallow water bodies).

View Article: PubMed Central - PubMed

Affiliation: Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK. ajh13@aber.ac.uk.

ABSTRACT

Background: Larval source management strategies can play an important role in malaria elimination programmes, especially for tackling outdoor biting species and for eliminating parasite and vector populations when they are most vulnerable during the dry season. Effective larval source management requires tools for identifying geographic foci of vector proliferation and malaria transmission where these efforts may be concentrated. Previous studies have relied on surface topographic wetness to indicate hydrological potential for vector breeding sites, but this is unsuitable for karst (limestone) landscapes such as Zanzibar where water flow, especially in the dry season, is subterranean and not controlled by surface topography.

Methods: We examine the relationship between dry and wet season spatial patterns of diagnostic positivity rates of malaria infection amongst patients reporting to health facilities on Unguja, Zanzibar, with the physical geography of the island, including land cover, elevation, slope angle, hydrology, geology and geomorphology in order to identify transmission hot spots using Boosted Regression Trees (BRT) analysis.

Results: The distribution of both wet and dry season malaria infection rates can be predicted using freely available static data, such as elevation and geology. Specifically, high infection rates in the central and southeast regions of the island coincide with outcrops of hard dense limestone which cause locally elevated water tables and the location of dolines (shallow depressions plugged with fine-grained material promoting the persistence of shallow water bodies).

Conclusions: This analysis provides a tractable tool for the identification of malaria hotspots which incorporates subterranean hydrology, which can be used to target larval source management strategies.

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Related in: MedlinePlus

Observed hotspots of malaria infection and probability of malaria infection hotspots predicted from a BRT model using variables summarising the physical geography of Unguja, Zanzibar for (A) the wet season and (B) the dry season. White areas are where probability of malaria infection hotspot was predicted to be −1 to 0.
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Fig7: Observed hotspots of malaria infection and probability of malaria infection hotspots predicted from a BRT model using variables summarising the physical geography of Unguja, Zanzibar for (A) the wet season and (B) the dry season. White areas are where probability of malaria infection hotspot was predicted to be −1 to 0.

Mentions: Predicted maps of malaria hotspot probability are shown in Figure 7. Predictions for both the wet and dry seasons indicate similar patterns, with an increase in predicted hotspots in the south of the island and the northeast also demonstrating potential for hotspot occurrence. Primarily, hotspots are concentrated in areas with steep slopes close to dolines. The model follows observed hotspots for most locations across the island, although some apparent false negatives occur. For instance, hotspots occur at Fumba on northwest coast and Donge Vijibweni in the far north of the island (see Figure 2 for locations) but are not predicted by the model. Some false positives also occur, particularly in areas with steep coastal cliffs, such as Pwani, where slope angle has a high influence on both the wet and dry season BRT models.Figure 7


Mapping hotspots of malaria transmission from pre-existing hydrology, geology and geomorphology data in the pre-elimination context of Zanzibar, United Republic of Tanzania.

Hardy A, Mageni Z, Dongus S, Killeen G, Macklin MG, Majambare S, Ali A, Msellem M, Al-Mafazy AW, Smith M, Thomas C - Parasit Vectors (2015)

Observed hotspots of malaria infection and probability of malaria infection hotspots predicted from a BRT model using variables summarising the physical geography of Unguja, Zanzibar for (A) the wet season and (B) the dry season. White areas are where probability of malaria infection hotspot was predicted to be −1 to 0.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4307680&req=5

Fig7: Observed hotspots of malaria infection and probability of malaria infection hotspots predicted from a BRT model using variables summarising the physical geography of Unguja, Zanzibar for (A) the wet season and (B) the dry season. White areas are where probability of malaria infection hotspot was predicted to be −1 to 0.
Mentions: Predicted maps of malaria hotspot probability are shown in Figure 7. Predictions for both the wet and dry seasons indicate similar patterns, with an increase in predicted hotspots in the south of the island and the northeast also demonstrating potential for hotspot occurrence. Primarily, hotspots are concentrated in areas with steep slopes close to dolines. The model follows observed hotspots for most locations across the island, although some apparent false negatives occur. For instance, hotspots occur at Fumba on northwest coast and Donge Vijibweni in the far north of the island (see Figure 2 for locations) but are not predicted by the model. Some false positives also occur, particularly in areas with steep coastal cliffs, such as Pwani, where slope angle has a high influence on both the wet and dry season BRT models.Figure 7

Bottom Line: Previous studies have relied on surface topographic wetness to indicate hydrological potential for vector breeding sites, but this is unsuitable for karst (limestone) landscapes such as Zanzibar where water flow, especially in the dry season, is subterranean and not controlled by surface topography.We examine the relationship between dry and wet season spatial patterns of diagnostic positivity rates of malaria infection amongst patients reporting to health facilities on Unguja, Zanzibar, with the physical geography of the island, including land cover, elevation, slope angle, hydrology, geology and geomorphology in order to identify transmission hot spots using Boosted Regression Trees (BRT) analysis.Specifically, high infection rates in the central and southeast regions of the island coincide with outcrops of hard dense limestone which cause locally elevated water tables and the location of dolines (shallow depressions plugged with fine-grained material promoting the persistence of shallow water bodies).

View Article: PubMed Central - PubMed

Affiliation: Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, UK. ajh13@aber.ac.uk.

ABSTRACT

Background: Larval source management strategies can play an important role in malaria elimination programmes, especially for tackling outdoor biting species and for eliminating parasite and vector populations when they are most vulnerable during the dry season. Effective larval source management requires tools for identifying geographic foci of vector proliferation and malaria transmission where these efforts may be concentrated. Previous studies have relied on surface topographic wetness to indicate hydrological potential for vector breeding sites, but this is unsuitable for karst (limestone) landscapes such as Zanzibar where water flow, especially in the dry season, is subterranean and not controlled by surface topography.

Methods: We examine the relationship between dry and wet season spatial patterns of diagnostic positivity rates of malaria infection amongst patients reporting to health facilities on Unguja, Zanzibar, with the physical geography of the island, including land cover, elevation, slope angle, hydrology, geology and geomorphology in order to identify transmission hot spots using Boosted Regression Trees (BRT) analysis.

Results: The distribution of both wet and dry season malaria infection rates can be predicted using freely available static data, such as elevation and geology. Specifically, high infection rates in the central and southeast regions of the island coincide with outcrops of hard dense limestone which cause locally elevated water tables and the location of dolines (shallow depressions plugged with fine-grained material promoting the persistence of shallow water bodies).

Conclusions: This analysis provides a tractable tool for the identification of malaria hotspots which incorporates subterranean hydrology, which can be used to target larval source management strategies.

Show MeSH
Related in: MedlinePlus