Geoscience Reference
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forecast is also supported by limited observations in four high-altitude sites in East
Africa where increases in malaria have been reported and then present and past
conditions compared using 95-year climate records. Looking at the combination
of required temperature, rainfall, humidity and number of months suitable for P.
falciparum , conditions have not changed significantly either over the 95-year period
or in the two decades of malaria increase (Hay et al., 2002). In short, there is a natural
variation in the disease in addition to anything that might be connected with climate
change.
Does this mean that there will be no future health impacts from malaria due to
climate change? Certainly not. Notwithstanding surprises, the distribution of malaria
will change but it may not result in huge increases in numbers of cases due to
climate change alone, although the places where infections take place are likely to
alter. However, climate change in combination with other factors, such as continued
increasing international mobility, might result in sporadic localised outbreaks in parts
of Western Europe and North America. By the end of the 21st century malaria might
be found in some parts of mid South America, parts of southern Africa and further
east of its existing range in Asia. Equally, parts of mid South America, eastern
Africa, eastern India and parts of east Asia that are presently suitable for malaria
may become unsuitable. Consequently, the deployment of anti-malaria measures will
need modifying.
Here climate change science is set to help. The marked increase in sophistication
of computer models of the global climate, especially their regional-level spin-offs,
are beginning to be used to develop forecast systems of malaria outbreaks. (Here, as
elsewhere in this topic, the term model means a mathematical simulation as opposed
to how epidemiologists sometimes use the word as a simple correlation or statistical
relationship between two things; Palmer, 2006.) One such system has already had
practical success in semi-arid Botswana, adding up to 4 months' extra lead time in
advance of existing warnings of outbreaks. It predicts regional climate patterns about
6 months in advance. In Botswana the rainy season, hence the malaria season, begins
in December but health officials have to wait until February or March before they can
make an accurate assessment. The new model enables them to make the prediction
months before the rainy season starts (Thomson et al., 2006).
Then again, some non-climatic factors can aggravate matters. For example,
Anopheles pesticide resistance was first noticed in the 1950s and resistance to
chloroquine (an anti-malaria pharmaceutical) was first seen in the 1960s and has
become an increasing problem since. Evidence of resistance to the modern anti-
infective drugs atovaquone and proguanil was noted in 2003. In China artemisinin-
based combination drugs derived from the sweet wormwood plant ( Artemisa annua )
have yet to encounter resistance and they are increasingly being used in Africa. Con-
sequently, demand for these drugs is rising but even with them the evolution of resist-
ance will continue to be of concern, so increasing dependence on artemisinin-based
pharmaceuticals. Indeed, in 2004 the WHO announced a shortage of artemisinin-
based combination drugs and forecast a demand of 10 million treatment courses,
predicting that this would rise to 60 million in 2005 (WHO, 2004).
Finally there is the question of how long artemisinin-based drugs will continue
to avoid resistance by malaria parasites. One option to delay the onset of resistance
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