| Literature DB >> 19796380 |
Abdisalan M Noor1, Viola C Kirui, Simon J Brooker, Robert W Snow.
Abstract
BACKGROUND: The scaling of malaria control to achieve universal coverage requires a better understanding of the population sub-groups that are least protected and provide barriers to interrupted transmission. Here we examine the age pattern of use of insecticide treated nets (ITNs) in Africa in relation to biological vulnerabilities and the implications for future prospects for universal coverage.Entities:
Mesh:
Year: 2009 PMID: 19796380 PMCID: PMC2761895 DOI: 10.1186/1471-2458-9-369
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Summary of national households surveys with data on ITN use among all age-groups in African countries where national surveys reported information on all ages: countries are ranked from highest to lowest based on the proportion of individuals of all ages who slept under an ITN the night prior to survey.
| Kenya | MIS | 2007 | June-July | 200 | 6,854 | 31,297 | 5,483 | 22.5 | 39.2 | 38.9 | |
| Tanzania | AIS/MIS | 2007-8 | October-February | 475 | 8,497 | 41,871 | 5,948 | 18.8 | 32.3 | 29.4 | |
| Zambia | DHS | 2007 | April-October | 319 | 7,164 | 35,562 | 8,486 | 24.9 | 29.1 | 23.9 | |
| Mali | DHS | 2006 | April-September | 408 | 12,998 | 73,685 | 15,621 | 25.2 | 27.3 | 21.2 | |
| Benin | DHS | 2006 | July-November | 750 | 17,511 | 90,650 | 12,790 | 10.3 | 19.7 | 14.1 | |
| Senegal | MIS | 2006 | November-December | 150 | 3,063 | 30,199 | 3,998 | 21.7 | 16.2 | 13.2 | |
| Angola | MIS | 2006-7 | November-April | 120 | 2,599 | 14,399 | 1,040 | 10.9 | 17.7 | 13.0 | |
| Djibouti | MIS | 2008-9 | December-February | 156 | 3,603 | 22,373 | 1,802 | 17.6 | 19.9 | 13.0 | |
| Sudan | MIS | 2005 | October | 143 | 2,460 | 10,639 | 1,194 | 4.8 | 15.4 | 11.3 | |
| Rwanda | DHS | 2005 | February-July | 462 | 10,272 | 47,851 | 4,498 | 4.2 | 13.6 | 9.4 | |
| Uganda | DHS | 2006 | May-October | 368 | 8,870 | 45,439 | 3,291 | 5.8 | 9.6 | 7.2 | |
| Namibia | DHS | 2006-7 | October-March | 500 | 9,200 | 42,633 | 2,562 | 8 | 11.1 | 6.0 | |
| Niger | DHS | 2006 | January-June | 345 | 7,660 | 47,964 | 2,633 | 12.8 | 8.7 | 5.5 | |
| DRC | DHS | 2007 | May-August | 300 | 8,886 | 48,291 | 2,567 | 1.9 | 7.7 | 5.3 | |
| Zimbabwe | DHS | 2005-6 | August-March | 400 | 9,285 | 40,805 | 929 | 2.5 | 3.0 | 3.3 | |
| Ethiopia | DHS | 2005 | April-August | 540 | 13,721 | 67,539 | 589 | 0.3 | 2.3 | 1.5 | |
| Guinea | DHS | 2005 | February-June | 297 | 6,282 | 38,182 | 409 | 0.2 | 1.4 | 1.1 | |
| Swaziland | DHS | 2006-7 | July-February | 275 | 4,843 | 22,143 | 86 | 1.2 | 0.7 | 0.4 | |
AIS = AIDS Indicator Survey; DRC = Democratic Republic of Congo; ITN = Insecticide Treated Net (a bed net treated with an insecticide the last six months prior to survey or a long lasting insecticidal net); DHS = Demographic and Health Survey; MIS = Malaria Indicator Survey.
Figure 1Graphs of percentage of sample population sleeping under ITN the night before survey, overall and by gender, against the number of persons enumerated in each age category (left) and pie charts of the proportion of projected 2007 population who did not sleep under ITN by age category (right) in: A) group 1: countries where ≥ 20% of the sample population slept under ITN (Kenya, Tanzania, Zambia, Mali); B) group 2: countries where 10-<20% of the sample population slept under ITN (Benin, Senegal, Angola, Djibouti, Sudan); C) group 3 - countries where<10% of the sample population slept under ITN (Rwanda, Uganda, Namibia, Niger, DRC, Zimbabwe, Ethiopia, Guinea, Swaziland). Pink, blue and black lines on the graphs represent the percentage female, male and total sample population sleeping under ITN the night before survey respectively.
A summary of ITN use among individuals of ages < 5 years; 5-19 years; 20-44 years; and ≥45 years and the estimated number of persons (millions) in each age group NOT protected with ITN in 2007: countries are ranked from highest to lowest based on the proportion of individuals of all ages who slept under an ITN the night prior to survey.
| Kenya | 6.32 (39.2) | 3.80 | 14.14 (30.0) | 9.90 | 12.91 (43.5) | 7.29 | 4.46 (35.5) | 2.87 |
| Tanzania | 7.34 (32.3) | 4.97 | 15.61(21.5) | 12.25 | 13.25 (32.5) | 8.94 | 5.22 (26.2) | 3.82 |
| Zambia | 2.23 (29.1) | 1.58 | 4.81 (16.4) | 4.02 | 3.83 (29.6) | 2.70 | 1.48 (26.8) | 1.08 |
| Mali | 2.15 (27.3) | 1.56 | 4.77 (15.1) | 4.05 | 4.07 (24.8) | 3.06 | 1.43 (23.3) | 1.10 |
| Benin | 1.41 (19.7) | 1.13 | 3.12 (10.6) | 2.79 | 2.74 (17.2) | 2.27 | 1.13 (10.4) | 1.01 |
| Senegal | 1.99 (16.2) | 1.67 | 4.59 (11.3) | 4.07 | 3.97 (13.5) | 3.43 | 1.37 (14.4) | 1.17 |
| Angola | 3.14 (17.7) | 2.58 | 6.81 (7.5) | 6.30 | 5.55 (15.7) | 4.68 | 2.07 (13.6) | 1.79 |
| Djibouti | 0.11 (19.9) | 0.09 | 0.30 (11.8) | 0.26 | 0.30 (12.7) | 0.27 | 0.13 (10.3) | 0.11 |
| Sudan | 5.80 (15.4) | 4.90 | 14.69 (9.2) | 13.34 | 13.95 (11.5) | 12.34 | 6.06 (9.5) | 5.48 |
| Rwanda | 1.61 (13.6) | 1.39 | 3.56 (5.0) | 3.38 | 3.21 (13.8) | 2.77 | 1.13 (6.9) | 1.05 |
| Uganda | 6.00 (9.6) | 5.42 | 12.52 (4.4) | 11.97 | 9.18 (10.4) | 8.23 | 3.04 (6.4) | 2.85 |
| Namibia | 0.27 (11.1) | 0.24 | 0.76 (4.3) | 0.72 | 0.75 (6.8) | 0.70 | 0.31 (4) | 0.30 |
| Niger | 2.97 (8.7) | 2.71 | 5.52 (4.2) | 5.28 | 4.11 (6.2) | 3.85 | 1.63 (3.7) | 1.57 |
| DRC | 11.64 (7.7) | 10.75 | 24.69 (3.2) | 23.90 | 18.92 (6.9) | 17.61 | 7.33 (4.4) | 7.01 |
| Zimbabwe | 1.71 (3.0) | 1.66 | 5.01 (1.7) | 4.92 | 4.23 (4.7) | 4.03 | 1.60 (3.0) | 1.55 |
| Ethiopia | 13.08 (2.3) | 12.78 | 30.37 (1) | 30.07 | 24.82 (1.9) | 24.35 | 10.52 (0.9) | 10.42 |
| Guinea | 1.61 (1.4) | 1.59 | 3.58 (0.7) | 3.56 | 3.11 (1.5) | 3.06 | 1.36 (0.9) | 1.35 |
| Swaziland | 0.16 (0.7) | 0.16 | 0.46 (0.1) | 0.46 | 0.38 (0.7) | 0.38 | 0.15 (0.1) | 0.15 |
Figure 2Graph showing the prevalence of infection (red line) among individuals of all ages in the Coast province of Kenya prior to scaled ITN delivery [31]and the proportion of the population sleeping under an insecticide treated net (green line) in 2007 after the national free mass campaign of 2006 [32]. The graph illustrates that in Kenya the national ITNs scaling-up strategies have been sub-optimal in terms of targeting the populations aged 5-19 years (shaded grey), the age-group in which pre-intervention parasite prevalence was at its peak.