Background
Methods
Experimental insects
Experimental setting and recording system
Recording session procedures
Objective 1—mosquito appearance frequency on the net
Objective 2—determinants of hole encounter frequency
Objective 3—determinants of hole passage
Analysis of videos
Data analysis
Results
General
Objective 1
Objective 2
Model | Coefficient (b) |
p value | R2
|
---|---|---|---|
y = a + b × length | 3.05E−04 | <0.001 | 0.644 |
y = a + b × width | 9.99E−04 | <0.001 | 0.300 |
y = a + b × perimeter | 1.46E−04 | <0.001 | 0.746 |
y = a + b × area | 8.99E−06 | <0.001 | 0.857 |
Objective 3
Width (mm) | Length (mm) | # encounters | # passages | Prop’n passages |
---|---|---|---|---|
Sides, rectangular | ||||
6 | 8 | 76 | 0 | 0.00 |
10 | 53 | 0 | 0.00 | |
25 | 131 | 2 | 0.02 | |
210 | 100 | 2 | 0.02 | |
11 | 11 | 112 | 10 | 0.09 |
15 | 15 | 26 | 6 | 0.23 |
85 | 120 | 41 | 0.34 | |
120 | 53 | 20 | 0.38 | |
210 | 24 | 8 | 0.33 | |
17 | 19 | 43 | 12 | 0.28 |
20 | 32 | 87 | 34 | 0.43 |
40 | 71 | 34 | 0.48 | |
113 | 56 | 28 | 0.50 | |
35 | 84 | 102 | 56 | 0.55 |
152 | 81 | 49 | 0.60 | |
210 | 77 | 49 | 0.64 | |
60 | 82 | 70 | 45 | 0.64 |
120 | 69 | 50 | 0.72 | |
210 | 13 | 8 | 0.62 | |
Roof, rectangular | ||||
4 | 6 | 68 | 0 | 0.00 |
6 | 6 | 147 | 0 | 0.00 |
8 | 314 | 9 | 0.03 | |
13 | 165 | 7 | 0.04 | |
21 | 90 | 9 | 0.10 | |
25 | 170 | 17 | 0.10 | |
40 | 53 | 5 | 0.09 | |
60 | 56 | 4 | 0.07 | |
77 | 140 | 9 | 0.06 | |
148 | 63 | 4 | 0.06 | |
8 | 13 | 234 | 21 | 0.09 |
38 | 30 | 2 | 0.07 | |
60 | 45 | 9 | 0.20 | |
11 | 13 | 202 | 35 | 0.17 |
38 | 31 | 4 | 0.13 | |
59 | 83 | 38 | 0.46 | |
80 | 46 | 16 | 0.35 | |
13 | 17 | 136 | 62 | 0.46 |
40 | 72 | 27 | 0.38 | |
160 | 118 | 45 | 0.38 | |
15 | 17 | 117 | 29 | 0.25 |
40 | 63 | 18 | 0.29 | |
60 | 69 | 32 | 0.46 | |
76 | 55 | 22 | 0.40 | |
160 | 52 | 23 | 0.44 | |
21 | 22 | 103 | 48 | 0.47 |
40 | 77 | 36 | 0.47 | |
60 | 66 | 29 | 0.44 | |
77 | 61 | 33 | 0.54 | |
160 | 95 | 39 | 0.41 | |
30 | 30 | 70 | 49 | 0.70 |
60 | 94 | 51 | 0.54 | |
80 | 37 | 26 | 0.70 |
Base (mm) | Av. width (mm) | # encounters | # passages | Prop’n passages |
---|---|---|---|---|
Side, triangular, 210 mm | ||||
25 | 15 | 68 | 19 | 0.28 |
36 | 21 | 42 | 17 | 0.41 |
80 | 42 | 90 | 49 | 0.54 |
Diameter (mm) | Length (mm) | # encounters | # passages | Prop’n passages |
---|---|---|---|---|
Side, round | ||||
8 | NA | 43 | 2 | 0.04 |
35 | NA | 120 | 61 | 0.51 |
40 | NA | 153 | 90 | 0.59 |
70 | NA | 43 | 31 | 0.72 |
Model | Coefficient (b) | p value | R2
|
---|---|---|---|
Roof, rectangular holes | |||
y = a + b × length | 1.445E−03 | 0.07856 | 0.0673 |
y = a + b × width | 2.514E−02 | <0.001 | 0.8122 |
y = a + b × ln (width) | 3.434E−01 | <0.001 | 0.8621 |
y = a + b × perimeter | 9.759E−04 | 0.0103 | 0.1678 |
y = a + b × area | 1.643E−04 | <0.001 | 0.3920 |
Side, rectangular holes | |||
y = a + b × length | 1.479E−03 | 0.0476 | 0.1650 |
y = a + b × width | 1.134E−02 | <0.001 | 0.7187 |
y = a + b × ln (width) | 3.020E−01 | <0.001 | 0.9256 |
y = a + b × perimeter | 8.557E−04 | 0.00705 | 0.3176 |
y = a + b × area | 5.312E−05 | <0.001 | 0.5075 |
Side, triangular holes | |||
y = a + b × mean width | 0.009 | 0.21 | 0.89 |
y = a + b × ln (mean width) | 2.430E−01 | 0.14 | 0.95 |
Side, round holes | |||
y = a + b × diameter | 3.192E−01 | 0.0025 | 0.99 |
y = a + b × ln (diameter) | 3.192E−01 | 0.0025 | 0.99 |
Discussion
Objective 1—activity levels
Objective 2—hole encounter
Objective 3—hole passage
Entry risk model
Objective 1
Objective 2
Objective 3
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The tool presented here is based on experiments with colonized An. gambiae and has not been validated with wild An. gambiae. In addition, the tool may need to be adjusted for other vector species since they may exert different pressure patterns on the net. See, for instance, net distribution results for Anopheles albimanus [11].
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As previously stated, the tool calculates the hourly mean number of entries expected for a net that is under constant attack throughout the hour by one mosquito (i.e. each time the hypothetical modelled mosquito enters the net it is instantly replaced by another outside the net).
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Entry risk scores can be expressed for any time period by multiplying the values from the spreadsheet for hourly risk by the number of hours.
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Risk scores can be expressed for more than one mosquito attacking the net by multiplying the values from the tool by the number of attacking mosquitoes.
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Risk scores for any number of mosquitoes present outside the net for any number of hours can be calculated by combining the previous two measures.
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The maximum hole length or width that can meaningfully be entered in each row of the spreadsheet is 300 mm (30 cm) because all values in the model are based on sampling units of 30 cm × 30 cm. Holes longer than 300 mm can be handled by dividing them between rows in the spreadsheet. For example, a hole 400 mm long could be entered as two holes in successive lines, one with a length of, for instance, 250 mm and the other with a length of 150 mm.
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Portions of holes that span more than one FA should be apportioned accordingly and the components’ dimensions should be entered into the appropriate parts of the spreadsheet.
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Holes with a width of 5 mm or less are considered by the model to be impassable and will not affect the net score.
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Because people using bed nets in real-life are not likely to sleep just in the middle of the net or remain still and because nets often accommodate more than one person at a time, the model as presented takes a cautious approach by scoring all roof holes as though they are in FA1.
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Bed nets in normal use hang and sag in various ways not reflected by these idealized nets. This will likely affect mosquitoes as they fly along the net surfaces and interact with holes and damaged areas. Describing and accounting for these effects may lead to improvements to this tool but these are outside the scope of the present study,
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The tool assumes the net is a perfect sink for mosquitoes and does not attempt to account for mosquitoes leaving it.
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Because all experiments were done in still air which allowed the host odour plume to rise vertically (see Sutcliffe and Colborn [14]), the tool may not accurately model situations where there are significant cross drafts or air turbulence that disrupt or re-direct host odour plumes. While this may be an important consideration in some settings, the ‘still air’ condition is common; for instance, very low night time air flows (less than 0.1 m/s) have been measured in many rural houses in Africa and southeast Asia [15].
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These studies were done with untreated nets and provide a baseline for determining how much entry risk is further reduced for treated nets. A full answer to this question will require further research but a preliminary estimate is possible. Parker et al. [13] saw little or no mosquito activity 20–25 min after mosquito (susceptible An. gambiae) release into a tent housing a fully-charged PermaNet 2.0 net. Based on flight activity reduction alone this would translate to an hourly entry risk reduction over the untreated net prediction of 70% or more since hole encounter and hole entry are both events that require the mosquito to be active. Despite insecticide effects, it has been shown experimentally that people sleeping under holed treated nets may be bitten by insecticide-susceptible mosquitoes even though the mosquitoes are eventually killed by net contact (e.g. [16, 17]).
Implications for bed net damage assessment
Hole location
Hole size
pHI size class | Size class diameters (mm) | Modelled riska
| Risk range | |||||
---|---|---|---|---|---|---|---|---|
Minimum | Mid-range | Maximum | Minimum | Mid-range | Maximum | Within classification | Mid-range to mid-range | |
Smaller than thumb | 5b
| 12.5 | 20 | 0.002 | 0.044 | 0.141 | 70.5× | NA |
Thumb-fist | 20 | 60 | 100 | 0.141 | 2.074 | 6.711 | 47.6× | 47.1× |
Fist-head | 100 | 175 | 250 | 6.711 | 20.286 | 41.180 | 6.1× | 9.8× |
Larger than head | 250 | 300c
| NA | 41.180 | 59.177 | NA | ≫1.4× | 2.9× |