Table 3.

Estimated change in the number of malaria cases due to climate change in the past 20 years ^(a).

	Average annual cases per 1,000 people (1990–2000)	Cases Elasticity (%)		Computed change in number of cases per 1,000 people under under observed climate change past 20 years	Equivalent percentage change per 1,000 people
		to 1 º C change in Temp.	to 1% change in Precip.
Algeria	0.01	155.25	2.38	0.00	0.33
Benin	86.53	23.93	−0.50	−8.81	−0.10
Botswana	31.05	1.78	−0.02	0.23	0.01
Burkina	60.99	19.92	−0.66	−3.99	−0.07
Burundi	168.53	14.30	0.16	2.17	0.01
Central Afr. Rep.	32.36	−27.73	10.89	10.32	0.32
Chad	45.14	0.87	−0.15	−0.12	0.00
Cote d'Ivoire	55.56	183.91	−13.69	8.25	0.15
Djibouti	9.73	143.36	4.63	16.67	1.71
Egypt	0.00	132.28	1.13	0.00	0.72
Ethiopia	6.19	−46.19	−84.68	−32.22	−5.21
Ghana	120.89	34.86	−1.85	−7.35	−0.06
Guinea	67.27	−12.44	−12.25	−62.18	−0.92
Malawi	381.81	10.47	−3.08	81.22	0.21
Mali	27.40	11.59	−0.01	0.64	0.02
Mauritania	62.29	21.94	0.31	4.35	0.07
Morocco	0.01	313.46	9.85	0.01	1.10
Niger	96.78	14.84	0.23	7.38	0.08
Rwanda	165.90	30.98	−2.90	2.54	0.02
South Africa	0.51	3.89	0.11	0.00	0.00
Sudan	228.75	29.16	−1.34	−18.33	−0.08
Togo	112.28	8.37	−0.23	−4.43	−0.04
Uganda	92.24	4.39	−0.32	2.23	0.02
Tanzania	302.68	1.97	0.00	1.19	0.00
Zimbabwe	98	12.65	−0.53	2.68	0.03

^(a)The formula used to calculate the projected cases is based on the definition of elasticity. Let the elasticity value of the number malaria cases with respect to 1 °C change in temperature be a% and the elasticity value of the number of malaria cases with respect to 1% change in precipitation be b%. If the projected change in temperature in degree Celsius c^o is and the projected change in precipitation is expressed in percentage as d%, then knowing the current number of malaria cases average m, the projected number of malaria cases is calculated as p = m × (a × c + b × d)/100.