Table 2.

Summary of analyzed geographical areas, vectors, environmental factors and main findings of studies dealing with malaria.

	Geographical area	Vector	Analyzed environmental factors	Affected by climate change	Changes in prevalence or incidence due to climate change	Expansion due to climate change	First author (year of publication)
	Main findings
	East [Kenia)	Anopheles spp	Average temperature increase	Yes	Increases	No	19,
	An increase of 1ºC has been registered over the last 30 years, which coincides with an increase in malaria outbreaks
	East [Kenia]	Anopheles spp	Average temperature increase	Uncertain	Uncertain	Uncertain	17,
	Parasitary development may be underestimated under cold conditions if only average monthly temperatures are taken into account. On the contrary, under warm weather conditions it may be overestimated
	East [Kenia]	Anopheles spp	Variations in rainfall patterns, altitude changes	Yes	Decreases	No	42,
	Decreasing trends in malaria at both low and high altitudes. Increases in rainfall increment significantly malaria incidence
	East [Kenia]	Anopheles spp	Average temperature variations	No	Decreases	No	45,
	Predicted relative increases in the larvarian development rate due to climate change are smaller since water temperature does not increase
	East [Kenia]	Anopheles spp	Average temperature increase, variations in diurnal temperature	No	Increases	No	18,
	If diurnal temperature range increases, extrinsic incubation period sensitivity decreases. Relative effects of average temperature increases are smaller than predicted if daily temperature fluctuations are taken into account
	East [Tanzania]	Anopheles gambiae, Anopheles stephensi	Average temperature increase	No	Decreases	No	44,
	After mosquito exposure to different temperatures (27ºC optimal temperature, 30ºC and 33ºC future projections] and diurnal variability (0,6–9ºC), it is verified that average temperature increases induce a decrease in oocyte prevalence and intensity and sporozoite prevalence
	East (Tanzania)	Anopheles spp	Average temperature increase, increased rainfall	Yes	Increases	Uncertain	[32]
	32–33ºC endemic transmission frame. Effects of rainfall are more unpredictable and difficult to quantify
	East (Tanzania)	Anopheles spp	Average temperature increase, increased rainfall	Yes	Increases	Yes	[33]
	Extinction depends more on rainfall than on temperature. Optimal temperature for endemic transmission and progress into previously free zones: 32–33ºC. In 2080, with 4–5ºC increases, Rukwa and Kigoma (near Democratic Republic of Congo). Southern Morogoro, Iringa, Ruvuma and Mtwara near Malawi and Mozambique will be affected
	East [Kenia, Uganda, Rwanda, Burundi)	Anopheles gambiae	Average temperature increase	Yes	Increases	Yes	20,
	Temperature changes significantly amplified by mosquito population dynamics
	East [Ethiopia]	Anopheles spp	Average temperature increase, increased altitude	Yes	Increases	Yes	37,
	Increases in temperature extend spatial distribution to higher altitudes
	East [Ethiopia, Kenia, Uganda]	Anopheles spp	Average temperature increase, increased rainfall	Yes	Increases	No	41,
	Significant changes in climatic variability coincide with increased magnitude and frequency of malaria epidemics since 1989
	South, East and West	Anopheles gambiae, Anopheles arabiensis	Average temperature increase	Yes	Increases	Yes	34,
	Future malaria suitability will decrease in Western Africa and Sahel due to increases in average annual temperatures and will increase in Eastern and Southern Africa because of 1.5–2.7ºC increases
	West [Niger, Benin and Mali]	Anopheles gambiae	Average temperature variations, increased rainfall	Uncertain	Increases	Yes	24,
	If tropical meteorological data from Benin were applied on the Niger Sahel, mosquito abundance will increase, whereas it may decrease with Malian data
	Africab	Anopheles spp	Average temperature increase, diminished rainfall	Yes	Increases	Yes	27,
	Current occurrence is restricted by deserts and highlands, epidemics in the Sahel and some Highland regions. Future projections show a decrease in most tropical areas in Africa due to increasing temperatures and decreasing annual rainfall. Increasing epidemics in southern Sahel. Increasing intensity in Eastern Africa and Highland areas
	Africab	Anopheles gambiae	Net effect of climate change	Yes	Uncertain	Yes	35,
	All year transmission suitable areas shift from Central and Western Africa to Uganda, Angola, Gabon and Cameroon. High season transmission [4–8 months] expands into Southern Africa and Madagascar
	Africab	Anopheles gambiae, Anopheles arabiensis	Average temperature increase, variations in summer and Winter rainfall	Yes	Increases	Yes	39,
	Shift toward Southern and Eastern Africa. Western and Central Africa might lose suitability for both Anopheles species
	Africab	Anopheles gambiae, Anopheles arabiensis	Average temperature increase, variations in rainfall patterns	Yes	Increases	Yes	40,
	Anopheles gambiae expansion toward Angola, Burundi, Comoro Islands, Ethiopia, Kenia, Malawi, Mali, South Africa, Tanzania, Zambia; and of Anopheles arabiensis toward Angola Botswana, Burundi, Democratic Republic of Congo, Djibouti, Ethiopia, Kenia, Malawi, Namibia, Rwanda, South Africa, Sudan, Swaziland, Gambia, Uganda, Zimbabwe with 2ºC temperature increase in all Africa and changes in rainfall patterns. 0.1ºC increases lead to expansion of Anopheles gambiae toward Angola, Cameroon, Ethiopia, Guinea, Mozambique, Niger, Sierra Leona, South Africa, Uganda, Zambia and Zimbabwe.
	Worldwidea	Anopheles spp	Net effect of climate change	Yes	Increases	No	47,
	Increase in malaria in East African highlands, South Africa, central Angola and the Madagascar plateau. Decreases in tropical areas, including Western Africa. Net increase of suitability and population at risk, but with uncertainties
	Worldwidea	Anopheles spp	Net effect of climate change, climate trends since 1900	Yes	Decreases	No	28,
	Future effects are smaller than those observed since 1900. Contradiction between observed and predicted effects

^aPredictive models that analyze disease incidence at worldwide level.

^bPredictive models that analyze disease incidence throughout the whole African continent.