Volume 11, Number 9—September 2005
Research
Malaria Attributable to the HIV-1 Epidemic, Sub-Saharan Africa
Table 2
Country† | Urban, % | Population at risk for malaria, by intensity of transmission, % |
HIV-1 prevalence in adults, % |
Malaria incidence/1,000 py‡ |
Malaria deaths/1,000 py‡ |
||||
---|---|---|---|---|---|---|---|---|---|
Low or unstable | High | National§ | Urban-rural ratio¶ | Increase due to HIV, % | Increase due to HIV, % | ||||
Angola | 34 | 53 | 46 | 3.9 | 1.6# | 291 | 1.2 | 1.8 | 4.2 |
Benin | 42 | 0 | 100 | 1.9 | 1.8 | 434 | 0.4 | 2.4 | 1.4 |
Botswana | 49 | 13 | 0 | 37.3 | 1.0 | 3.5 | 28.0 | 0.028 | 114.4 |
Burkina Faso | 17 | 0 | 100 | 4.2 | 3.1 | 538 | 0.8 | 3.1 | 2.9 |
Burundi | 9 | 64 | 21 | 6.0 | 3.6 | 209 | 2.4 | 1.4 | 8.6 |
Cameroon | 49 | 24 | 74 | 6.9 | 1.7 | 317 | 1.9 | 1.8 | 6.5 |
Central African Republic | 41 | 0 | 100 | 13.5 | 1.2 | 419 | 3.2 | 2.3 | 11.3 |
Chad | 24 | 14 | 86 | 4.8 | 1.3 | 451 | 1.1 | 2.6 | 4.1 |
Congo | 65 | 0 | 100 | 4.9 | 1.6# | 380 | 1.1 | 2.1 | 3.8 |
Côte d'Ivoire | 44 | 0 | 100 | 7.0 | 2.1 | 402 | 1.6 | 2.2 | 5.2 |
Democratic Republic of the Congo | 30 | 10 | 85 | 4.2 | 1.6 | 423 | 0.9 | 2.4 | 3.3 |
Equatorial Guinea | 48 | 2 | 97 | 11.6 | 1.6# | 401 | 2.5 | 2.3 | 8.50 |
Eritrea | 19 | 83 | 16 | 2.5 | 1.6# | 197 | 1.3 | 1.4 | 4.2 |
Ethiopia | 16 | 50 | 14 | 4.4 | 4.8 | 142 | 1.7 | 1.0 | 5.9 |
Gabon | 81 | 0 | 96 | 8.1 | 1.9 | 287 | 1.9 | 1.5 | 6.0 |
Gambia | 31 | 0 | 100 | 1.2 | 0.7 | 429 | 0.3 | 2.3 | 1.0 |
Ghana | 36 | 2 | 98 | 3.1 | 1.2 | 401 | 0.8 | 2.1 | 2.6 |
Guinea | 28 | 1 | 99 | 3.2 | 1.6# | 468 | 0.7 | 2.6 | 2.2 |
Guinea-Bissau | 32 | 0 | 100 | 3.8 | 1.6# | 480 | 0.7 | 2.7 | 2.7 |
Kenya | 33 | 57 | 21 | 6.7 | 1.8 | 164 | 2.9 | 1.1 | 10.4 |
Liberia | 45 | 0 | 100 | 5.9 | 1.6# | 437 | 1.1 | 2.5 | 4.0 |
Madagascar | 30 | 36 | 60 | 1.7 | 0.7 | 327 | 0.4 | 1.9 | 1.3 |
Malawi | 15 | 22 | 77 | 14.2 | 1.6# | 435 | 3.5 | 2.6 | 13.3 |
Mali | 30 | 10 | 90 | 1.9 | 1.5 | 464 | 0.4 | 2.7 | 1.5 |
Mauritania | 58 | 59 | 41 | 0.6 | 1.6# | 221 | 0.2 | 1.4 | 0.72 |
Mozambique | 32 | 4 | 96 | 12.2 | 1.2 | 437 | 2.8 | 2.4 | 10.3 |
Namibia | 31 | 8 | 0 | 21.3 | 1.3 | 2.3 | 14.5 | 0.018 | 52.4 |
Niger | 21 | 11 | 89 | 1.2 | 3.2 | 496 | 0.2 | 2.9 | 0.8 |
Nigeria | 44 | 1 | 99 | 5.4 | 1.1 | 420 | 1.2 | 2.3 | 4.3 |
Rwanda | 6 | 60 | 7 | 5.1 | 3.6** | 129 | 2.6 | 0.9 | 8.9 |
Senegal | 47 | 3 | 97 | 0.8 | 1.1 | 395 | 0.2 | 2.2 | 0.65 |
Sierra Leone | 37 | 0 | 100 | 1.8 | 1.6# | 440 | 0.4 | 2.5 | 1.4 |
Somalia | 28 | 96 | 3 | 0.7 | 1.6# | 148 | 0.4 | 1.1 | 1.3 |
South Africa | 57 | 15 | 0 | 21.5 | 1.3 | 3.5 | 17.0 | 0.028 | 62.1 |
Sudan | 36 | 42 | 56 | 2.3 | 1.6# | 281 | 0.7 | 1.7 | 2.5 |
Swaziland | 26 | 69 | 0 | 38.8 | 1.6# | 21 | 26.1 | 0.17 | 107.0 |
Tanzania | 32 | 21 | 75 | 8.8 | 2.7 | 372 | 2.0 | 2.1 | 7.4 |
Togo | 33 | 0 | 100 | 4.1 | 2.6 | 445 | 0.9 | 2.5 | 3.0 |
Uganda | 14 | 20 | 73 | 4.1 | 1.9 | 437 | 1.1 | 2.6 | 4.1 |
Zambia | 40 | 16 | 83 | 16.5 | 2.1 | 396 | 3.6 | 2.3 | 14.0 |
Zimbabwe | 35 | 54 | 0 | 24.6 | 1.2 | 16 | 16.7 | 0.128 | 61.9 |
Average†† | 34 | 23 | 67 | 6.9 | 2.0 | 320 | 1.3 | 1.8 | 4.9 |
Median | 33 | 14 | 85 | 4.8 | 1.6 | 396 | 1.2 | 2.2 | 4.2 |
*Malaria incidence and deaths denote estimates in the absence of HIV, all age groups combined. Abbreviations: /1,000py = per 1,000 person-years.
†Excluded from analysis were the following small countries: Lesotho and the islands The Seychelles, Reunion, Comoros and Mauritius, which are at negligible malaria risk, and Sao Tome & Principe and Cape Verde, which may be subject to stable malaria transmission but whose transmission intensity has not been precisely characterized in the Malaria Risk in Africa model.
‡Calculated by using country-specific age distributions.
§Estimates by UNAIDS/World Health Organization (WHO) for end of 2003 (28).
¶From estimates by UNAIDS/WHO for end of 2003 or from national household surveys (11). Same ratios assumed for children as for adults.
#In the absence of reliable urban/rural data, we applied the median urban/rural ratio across countries with urban and rural data.
**In the absence of specific urban and rural data, the estimate for neighboring Burundi, which was judged to be similar in HIV epidemiology, was applied.
††Weighted according to population size, except for the increases in malaria incidence and deaths due to HIV-1, which are weighted according to the absolute number of malaria cases and deaths in each country.
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