| Literature DB >> 19656399 |
Martha Betson1, Musa Jawara, Taiwo Samson Awolola.
Abstract
BACKGROUND: Vector control is an effective way of reducing malaria transmission. The main vector control methods include the use of insecticide-treated bed nets and indoor residual spraying (IRS). Both interventions rely on the continuing susceptibility of Anopheles to a limited number of insecticides. However, insecticide resistance, in particular pyrethroid-DDT cross-resistance, is a challenge facing malaria vector control in Africa because pyrethroids represent the only class of insecticides approved for treating bed nets and DDT is commonly used for IRS. Here baseline data are presented on the insecticide susceptibility levels of malaria vectors prior to The Gambian indoor residual spraying intervention programme.Entities:
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Year: 2009 PMID: 19656399 PMCID: PMC3224992 DOI: 10.1186/1475-2875-8-187
Source DB: PubMed Journal: Malar J ISSN: 1475-2875 Impact factor: 2.979
Figure 1Map of The Gambia showing the location of the larval collection sites. Pie charts indicate relative proportions of An. gambiae s.s., An. arabiensis and An. melas found at each site. On the map green represents the Western Division, pink the North Bank Division, yellow the Lower River Division, red the Central River Division and light green the Upper River Division.
Number of Anopheles gambiae s.l. mosquitoes tested and percentage mortality observed in insecticide susceptibility tests.
| Study site | Variable | DDT | Insecticide Permethrin | Deltamethrin |
|---|---|---|---|---|
| No. exposed | 160 | 150 | 155 | |
| No. dead (%) | 160 (100) | 150 (100) | 155 (100) | |
| 95% CI$ | 97.8, 100 | 97.6, 100 | 97.6, 100 | |
| % alive | NA† | NA | NA | |
| No. exposed | 80 | 63 | 66 | |
| No. dead (%) | 57 (71.3) | 56 (88.9) | 61 (92.4) | |
| 95% CI | 60.0, 80.8 | 78.4, 95.4 | 83.2, 97.5 | |
| % alive | 100 | 85.7 | 75.0 | |
| No. exposed | 78 | 76 | 81 | |
| No. dead (%) | 71 (91.0) | 72 (94.7) | 75 (92.6) | |
| 95% CI | 82.4, 96.3 | 87.1, 98.5 | 84.6, 97.2 | |
| % alive | 100 | 75.0 | 83.3 | |
| No. exposed | 22 | 18 | 22 | |
| No. dead (%) | 21 (95.5) | 16 (88.9) | 22 (100) | |
| 95% CI | 77.2, 99.9 | 65.3, 98.6 | 84.6, 100 | |
| % alive | 100 | 50 | NA | |
| No. exposed | 38 | 41 | 38 | |
| No. dead (%) | 38 (100) | 40 (97.6) | 37 (97.4) | |
| 95% CI | 84.6, 100 | 92.5, 100 | 91.9, 100 | |
| % alive | NA | 100 | NA | |
| No. exposed | 22 | 19 | 20 | |
| No. dead (%) | 22 (100) | 19 (100) | 20 (100) | |
| 95% CI | 84.6, 100 | 82.4, 100 | 83.2, 100 | |
| % alive | NA | NA | NA |
$ 95% confidence interval calculated by the exact method
* % of surviving mosquitoes which were An. arabiensis. Other surviving mosquitoes were An. gambiae s.s.
† NA = not applicable/available
Figure 2Knockdown rate of unfed female . from Brikama (A), Essau (B), Farafenni (C), Mansakonko (D), Kuntaur (E) and Basse (F) exposed to pyrethroid and DDT treated papers.
Knockdown times (KDTs) for Anopheles gambiae s.l. in The Gambia after exposure to different insecticides.
| Insecticide | Study site | KDT | KDT | |
|---|---|---|---|---|
| Brikama | 166 | 26.1 (17.0–34.1) | 68.3 (67.9–148.9) | |
| Essau | 80 | 46.1 (42.4–50.8) | 126.6 (102.1–174.3) | |
| Farafenni | 80 | 28.7 (26.3–30.8) | 63.9 (56.9–75.1) | |
| Mansakonko | 22 | 30.1 (25.5–34.2) | 64.3 (53.1–92.3) | |
| Kuntaur | 39 | 22.7 (20.1–25.1) | 47.0 (41.2–56.7) | |
| Basse | 25 | 28.6 (24.6–32.5) | 67.5 (55.4–93.4) | |
| Brikama | 150 | 27.6 (21.6–31.8) | 52.3 (47.8–74.7) | |
| Essau | 63 | 14.3 (10.9–17.3) | 85.0 (64.5–132.0) | |
| Farafenni | 76 | 6.9$ | 54.7$ | |
| Mansakonko | 18 | 15.0 (10.9–18.6) | 42.6 (33.6–63.2) | |
| Kuntaur | 41 | 1.0* | 17.2* | |
| Basse | 19 | 9.2 (5.2–11.8) | 21.9 (16.9–40.7) | |
| Brikama | 155 | 25.1 (17.1–32.1) | 67.8 (64.0–131.4) | |
| Essau | 66 | 10.8 (9.4–12.0) | 21.7 (18.9–26.7) | |
| Farafenni | 88 | 8.3 (6.6–9.6) | 18.7 (16.2–23.6) | |
| Mansakonko | 22 | 5.6* | 16.8* | |
| Kuntaur | 38 | 3.3 (0.2–6.8) | 24.3 (16.8–50.6) | |
| Basse | 20 | 16.3 (12.7–19.5) | 41.3 (33.9–55.8) |
@ Total number of mosquitoes exposed to each insecticide.
# 95% confidence limits
$ The linear log-time probit model is not a good fit to the data in this case. Therefore the estimates of KD50 and KD95 are unlikely to be accurate and the confidence limits could not be estimated
* Lower and upper confidence limits could not be estimated due to large g value [25]