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1.
Nature ; 516(7531): 387-90, 2014 Dec 18.
Article in English | MEDLINE | ID: mdl-25470038

ABSTRACT

During the long Sahelian dry season, mosquito vectors of malaria are expected to perish when no larval sites are available; yet, days after the first rains, mosquitoes reappear in large numbers. How these vectors persist over the 3-6-month long dry season has not been resolved, despite extensive research for over a century. Hypotheses for vector persistence include dry-season diapause (aestivation) and long-distance migration (LDM); both are facets of vector biology that have been highly controversial owing to lack of concrete evidence. Here we show that certain species persist by a form of aestivation, while others engage in LDM. Using time-series analyses, the seasonal cycles of Anopheles coluzzii, Anopheles gambiae sensu stricto (s.s.), and Anopheles arabiensis were estimated, and their effects were found to be significant, stable and highly species-specific. Contrary to all expectations, the most complex dynamics occurred during the dry season, when the density of A. coluzzii fluctuated markedly, peaking when migration would seem highly unlikely, whereas A. gambiae s.s. was undetected. The population growth of A. coluzzii followed the first rains closely, consistent with aestivation, whereas the growth phase of both A. gambiae s.s. and A. arabiensis lagged by two months. Such a delay is incompatible with local persistence, but fits LDM. Surviving the long dry season in situ allows A. coluzzii to predominate and form the primary force of malaria transmission. Our results reveal profound ecological divergence between A. coluzzii and A. gambiae s.s., whose standing as distinct species has been challenged, and suggest that climate is one of the selective pressures that led to their speciation. Incorporating vector dormancy and LDM is key to predicting shifts in the range of malaria due to global climate change, and to the elimination of malaria from Africa.


Subject(s)
Animal Migration/physiology , Anopheles/physiology , Estivation/physiology , Insect Vectors/physiology , Models, Biological , Seasons , Animals , Malaria/transmission , Population Density , Population Dynamics , Rain , Species Specificity
2.
J Med Entomol ; 51(1): 27-38, 2014 Jan.
Article in English | MEDLINE | ID: mdl-24605449

ABSTRACT

Changes in spatial distribution of mosquitoes over time in a Sahelian village were studied to understand the sources of the mosquitoes during the dry season when no larval sites are found. At that time, the sources of Anopheles gambiae Giles may be local shelters used by aestivating mosquitoes or migrants from distant populations. The mosquito distribution was more aggregated during the dry season, when few houses had densities 7- to 24-fold higher than expected. The high-density houses during the dry season differed from those of the wet season. Most high-density houses during the dry season changed between years, yet their vicinity was rather stable. Scan statistics confirmed the presence of one or two adjacent hotspots in the dry season, usually found on one edge of the village. These hotspots shifted between the early and late dry season. During the wet season, the hotspots were relatively stable near the main larval site. The locations of the hotspots in the wet season and early and late dry season were similar between years. Season-specific, stable, and focal hotspots are inconsistent with the predictions based on the arrival of migrants from distant localities during the dry season, but are consistent with the predictions based on local shelters used by aestivating mosquitoes. Targeting hotspots in Sahelian villages for vector control may not be effective because the degree of aggregation is moderate, the hotspots are not easily predicted, and they are not the sources of the population. However, targeting the dry-season shelters may be highly cost-effective, once they can be identified and predicted.


Subject(s)
Anopheles/physiology , Estivation , Animals , Female , Housing , Humans , Male , Mali , Population Density , Population Dynamics , Seasons
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