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The impact of temperature on insecticide toxicity against the malaria vectors Anopheles arabiensis and Anopheles funestus
research-article
Author(s):
Katey D. Glunt
1 ,
Shüné V. Oliver
2
,
3 ,
Richard H. Hunt
2
,
3 ,
Krijn P. Paaijmans
1
,
4
,
Publication date (Electronic):
2 April 2018
Journal:
Malaria Journal
Publisher:
BioMed Central
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Abstract
Background
It is anticipated that malaria elimination efforts in Africa will be hampered by increasing resistance to the limited arsenal of insecticides approved for use in public health. However, insecticide susceptibility status of vector populations evaluated under standard insectary test conditions can give a false picture of the threat, as the thermal environment in which the insect and insecticide interact plays a significant role in insecticide toxicity.
Methods
The effect of temperature on the expression of the standard WHO insecticide resistance phenotype was examined using Anopheles arabiensis and Anopheles funestus strains: a susceptible strain and the derived resistant strain, selected in the laboratory for resistance to DDT or pyrethroids. The susceptibility of mosquitoes to the pyrethroid deltamethrin or the carbamate bendiocarb was assessed at 18, 25 or 30 °C. The ability of the pyrethroid synergist piperonyl-butoxide (PBO) to restore pyrethroid susceptibility was also assessed at these temperatures.
Results
Temperature impacted the toxicity of deltamethrin and bendiocarb. Although the resistant An. funestus strain was uniformly resistant to deltamethrin across temperatures, increasing temperature increased the resistance of the susceptible An. arabiensis strain. Against susceptible An. funestus and resistant An. arabiensis females, deltamethrin exposure at temperatures both lower and higher than standard insectary conditions increased mortality. PBO exposure completely restored deltamethrin susceptibility at all temperatures. Bendiocarb displayed a consistently positive temperature coefficient against both susceptible and resistant An. funestus strains, with survival increasing as temperature increased.
Conclusions
Environmental temperature has a marked effect on the efficacy of insecticides used in public health against important African malaria vectors. Caution must be exercised when drawing conclusions about a chemical’s efficacy from laboratory assays performed at only one temperature, as phenotypic resistance can vary significantly even over a temperature range that could be experienced by mosquitoes in the field during a single day. Similarly, it might be inappropriate to assume equal efficacy of a control tool over a geographic area where local conditions vary drastically. Additional studies into the effects of temperature on the efficacy of insecticide-based interventions under field conditions are warranted.
Related collections
Most cited references31
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Insecticide Resistance in African Anopheles Mosquitoes: A Worsening Situation that Needs Urgent Action to Maintain Malaria Control.
Hilary Ranson, Natalie Lissenden (2016)
Malaria control is reliant on insecticides to control the mosquito vector. As efforts to control the disease have intensified, so has the selection pressure on mosquitoes to develop resistance to these insecticides. The distribution and strength of this resistance has increased dramatically in recent years and now threatens the success of control programs. This review provides an update on the current status of resistance to the major insecticide classes in African malaria vectors, considers the evidence that this resistance is already compromising malaria control efforts, and looks to the future to highlight some of the new insecticide-based tools under development and the challenges in ensuring they are most effectively deployed to manage resistance.
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Malaria morbidity and pyrethroid resistance after the introduction of insecticide-treated bednets and artemisinin-based combination therapies: a longitudinal study.
Jean-François Trape, Adama Tall, Nafissatou Diagne … (2011)
Substantial reductions in malaria have been reported in several African countries after distribution of insecticide-treated bednets and the use of artemisinin-based combination therapies (ACTs). Our aim was to assess the effect of these policies on malaria morbidity, mosquito populations, and asymptomatic infections in a west African rural population. We did a longitudinal study of inhabitants of Dielmo village, Senegal, between January, 2007, and December, 2010. We monitored the inhabitants for fever during this period and we treated malaria attacks with artesunate plus amodiaquine. In July, 2008, we offered longlasting insecticide (deltamethrin)-treated nets (LLINs) to all villagers. We did monthly night collections of mosquitoes during the whole study period, and we assessed asymptomatic carriage from cross-sectional surveys. Our statistical analyses were by negative binomial regression, logistic regression, and binomial or Fisher exact test. There were 464 clinical malaria attacks attributable to Plasmodium falciparum during 17,858 person-months of follow-up. The incidence density of malaria attacks averaged 5·45 (95% CI 4·90-6·05) per 100 person-months between January, 2007, and July, 2008, before the distribution of LLINs. Incidence density decreased to 0·41 (0·29-0·55) between August, 2008, and August, 2010, but increased back to 4·57 (3·54-5·82) between September and December, 2010--ie, 27-30 months after the distribution of LLINs. The rebound of malaria attacks were highest in adults and children aged 10 years or older: 45 (63%) of 71 malaria attacks recorded in 2010 compared with 126 (33%) of 384 in 2007 and 2008 (p<0·0001). 37% of Anopheles gambiae mosquitoes were resistant to deltamethrin in 2010, and the prevalence of the Leu1014Phe kdr resistance mutation increased from 8% in 2007 to 48% in 2010 (p=0·0009). Increasing pyrethroid resistance of A gambiae and increasing susceptibility of older children and adults, probably due to decreasing immunity, caused the rebound and age shift of malaria morbidity. Strategies to address the problem of insecticide resistance and to mitigate its effects must be urgently defined and implemented. Institut de Recherche pour le Développement and the Pasteur Institute of Dakar. Copyright © 2011 Elsevier Ltd. All rights reserved.
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The Impact of Pyrethroid Resistance on the Efficacy of Insecticide-Treated Bed Nets against African Anopheline Mosquitoes: Systematic Review and Meta-Analysis
Clare Strode, Sarah Donegan, Paul Garner … (2014)
Introduction The World Health Organization (WHO) estimates that there were 655,000 malaria deaths in 2010, with 86% occurring in children under 5 y [1]. Malaria deaths are declining with the massive scaling up of control measures, of which insecticide-treated bed nets (ITNs) are a major component. ITNs reduce deaths in children [2] and provide personal protection to the user, and at scale they provide community-wide protection by reducing the number of infective mosquitoes in the vicinity where ITNs are used [3],[4]. Between 2008 and 2010, 254 million ITNs were supplied to countries in sub-Saharan Africa, and the proportion of African households in possession of a net rose from 3% in 2000 to 50% by 2010 [5]. Nets, when in good condition and used correctly, are effective, simple to use, easy to deliver to rural communities, and cost-effective when used in highly endemic malarious areas [6]. On account of their low mammalian toxicity, speed of action, and high insecticidal activity, pyrethroids [7] are the only insecticide class recommended by the WHO for use in ITNs [8]. ITNs are effective with the African vectors Anopheles gambiae s.s. and An. funestus in part because these species are endophagic (feed indoors) and endophilic (rest indoors after feeding). Aside from their insecticidal activity, pyrethroids also exert an excito-repellency effect, which can lead to fewer mosquitoes entering a home (deterrence) where ITNs are used, or can cause disrupted blood feeding and premature exit of mosquitoes from the home (induced exophily) [9]. Because of the excito-repellency property of ITNs, these nets retain their personal protection properties for users even after the nets become holed [10]. The emergence and spread of insecticide resistance to all four classes of public health insecticides (pyrethroids, organochlorines, organophosphates, and carbamates) threatens the effectiveness of ITNs and indoor residual house spraying. Currently, 27 countries in sub-Saharan Africa have reported pyrethroid resistance in Anopheles vectors [11]. The real figure could very well be higher, as a lack of in-country resistance monitoring prevents accurate assessment. Because of their pyrethroid dependency, ITNs are especially vulnerable to insecticide resistance, as unlike indoor residual house spraying there are no readily available alternative insecticides. To prevent amplifying pyrethroid resistance, the WHO recommends that pyrethroid insecticides should not be used for indoor residual house spraying in areas with high long-lasting insecticide-treated bed net (LLIN) coverage [1]. In a recent study the extensive deployment and use of LLINs was blamed in part for selecting resistance in Anopheles vectors in Senegal, where malaria morbidity also increased [12]. The threat of resistance has led the WHO and members of the Roll Back Malaria Partnership to produce the “Global Plan for Insecticide Resistance Management in Malaria Vectors”, which stresses the urgency with which this problem needs to be addressed [13]. Insecticide resistance takes multiple forms: target-site resistance, metabolic resistance, and cuticular resistance. Target-site resistance to pyrethroids in An. gambiae and An. arabiensis is underpinned by a non-silent point mutation (either L1014F or L1014S) in the sodium channel gene, which is referred to as the knock-down resistance (kdr) genotype [14],[15]. Target-site resistance prevents the successful binding of the insecticide molecule to sodium channels on the nerve membranes. Metabolic resistance is caused by the activity of three large multi- gene families (cytochrome P450s, glutathione transferases, and carboxylesterases) that are able to metabolise or sequester the insecticide, thereby preventing it from reaching its target [16]. It is becoming clear that the cytochrome P450s are responsible for the majority of cases of metabolic resistance, with a secondary role for the glutathione transferases [17]–[20]. There is also preliminary evidence that cuticular resistance may be a contributing factor, but this aspect requires further analysis [17],[18],[21]. As pyrethroids and the organochlorine insecticide DDT target the sodium channel protein, cross-resistance to both insecticides is common. There is evidence that phenotypic resistance and kdr frequency have increased following the introduction of ITNs in some areas [22],[23], which could nullify the effectiveness of ITNs [24]. Policy makers and researchers debate whether these various forms of resistance are having an impact on the effectiveness of ITNs in malaria control. We carried out a systematic review of all relevant studies on human outcomes, but it became clear very quickly that there was an almost total absence of evidence to draw any conclusions on the impact of pyrethroid resistance on the efficacy of nets in decreasing disease transmission. So we turned to entomological studies: evidence of an effect of resistance on mosquitoes could be indicative of resistance having an impac on disease transmission. Our objective is to assess the effects of insecticide resistance in African anopheline mosquitoes on ITNs in terms of entomological outcomes in precise laboratory assays (cone tests), in laboratory tests with animals (tunnel tests), and in field trials with human volunteers as the attractants. Methods Inclusion Criteria Study design We included laboratory tests (cone tests and tunnel tests) and field trials using experimental huts (see Box 1 for details of types of studies included). Box 1. Types of Studies Included Cone Test Methods: Studies in the laboratory in which mosquitoes are placed inside a plastic cone that is attached to a net for three minutes; after net exposure the mosquitoes are placed in a holding container while entomological outcomes are measured [25]. Outcomes: Mosquito mortality after 24 h, percentage knock-down at 60 min, and time to 50% or 95% knock-down. Advantages: Researchers can standardise confounding variables, such as mosquito species, sex, age, and blood feeding status. The number of mosquitoes used in the test is standardised. Tunnel Test Methods: Studies in a laboratory, using animal bait, such as a guinea pig, placed at one end of a specially constructed tunnel. A fixed number of mosquitoes are released at the other end of the tunnel, and they must pass through a holed ITN or UTN to reach the animal bait. The following morning, both live and dead mosquitoes, blood fed and non-blood fed, are collected and counted from both sides of the holed net. Live mosquitoes are monitored for a further 24 h to assess delayed mortality [25]. Outcomes: Deterrence (not passed through net), blood feeding, and mosquito mortality. Advantages: As for cone test. Field Trials Methods: Studies in areas where mosquitoes breed. Volunteers sleep in experimental huts for a specific period under an ITN or an UTN, with one hut per person. The huts are identical in construction, and incorporate exit traps to catch wild mosquitoes entering and exiting the hut prematurely. Each morning of the trial, both live and dead mosquitoes, blood fed and non-blood fed, are collected and counted from both inside the hut and the exit traps. Live mosquitoes are monitored for a further 24 h to assess delayed mortality. Volunteers and nets are randomly allocated to huts at the start of the trial and are usually rotated to avoid bias. Often huts are cleaned between rotations to avoid cross-contamination of huts from the different treatment arms [25]. Outcomes: Deterrence, blood feeding, mosquito mortality, and induced exophily. Advantages: Given that this method assesses the response of wild mosquitoes to human volunteers, it is a more realistic representation of how effective ITNs are in terms of entomological outcomes, compared with laboratory methods. Mosquito population Included African malaria vectors were An. gambiae, An. arabiensis, or An. funestus. We included laboratory studies that used established laboratory-colonised strains of mosquitoes with known resistance phenotype or genotype. Experimental hut study trials were included if they measured the resistance status of the wild mosquito populations at the time of the study by bioassays with our without kdr genotyping. Intervention We included studies that compared an ITN (conventionally treated bed net [CTN] or a LLIN) versus an untreated bed net (UTN). The CTNs (which require dipping into insecticide and which also require retreatment at least once a year) must have been impregnated with a WHO-recommended pyrethroid with the recommended formulation and dose (see Table 1 for recommended impregnation regimens). The LLINs (which are factory-treated nets where the insecticide is incorporated within or bound around the net fibres) must have had either interim or full recommendation from the WHO (see Table 2 for recommended LLINs). 10.1371/journal.pmed.1001619.t001 Table 1 WHO-recommended pyrethroids for treatment of CTNs for vector control. Pyrethroid Formulation Dosagea Alpha-cypermethrin SC 10% 20–40 Cyfluthrin EW 5% 50 Deltamethrin SC 1%; WT 25%; WT 25%+binderK-ob 15–25 Etofenprox EW 10% 200 Lambda-cyhalothrin CS 2.5% 10–15 Permethrin EC 10% 200–500 a Milligrams of active ingredient per square metre of netting. b K-O Tab 1-2-3. CS, capsule suspension; EC, emulsifiable concentrate; EW, emulsion, oil in water; SC, suspension concentrate; WT, water dispersible tablet. 10.1371/journal.pmed.1001619.t002 Table 2 WHO-recommended LLINs for vector control. Product Name Product Type Status of WHO Recommendation DawaPlus 2.0 Deltamethrin coated on polyester Interim Duranet Alpha-cypermethrin incorporated into polyethylene Interim Interceptor Alpha-cypermethrin coated on polyester Full LifeNet Deltamethrin incorporated into polypropylene Interim MAGNet Alpha-cypermethrin incorporated into polyethylene Interim Netprotect Deltamethrin incorporated into polypropylene Interim Olyset Permethrin incorporated into polypropylene Full OlysetPlus Permethrin and piperonyl butoxide incorporated into polyethylene Interim PermaNet 2.0 Deltamethrin coated on polyester Full PermaNet 2.5 Deltamethrin coated on polyester with strengthened border Interim PermaNet 3.0 Combination: deltamethrin coated on polyester with strengthened border (side panels) and deltamethrin and piperonyl butoxide incorporated into polyethylene (roof) Interim Royal Sentry Alpha-cypermethrin incorporated into polyethylene Interim Yorkool LN Deltamethrin coated on polyester Full Outcomes Included outcomes were blood feeding, mosquito mortality, deterrence (reduction in the number of mosquitoes found in experimental huts), induced exophily (number of mosquitoes found in the exit trap of experimental huts), not passed though net (measure of deterrence in tunnel test), percent knock-down at 60 min, time to 50% knock-down, and time to 95% knock-down [25] (Table 3). 10.1371/journal.pmed.1001619.t003 Table 3 Measured outcomes appropriate for the different types of study. Outcome Description Laboratory Methods Field Method: Experimental Hut Trial Cone Test Tunnel Test Blood feeding A measure of the number of mosquitoes that have fed within a hut or in a tunnel during a lab test. Indicates how effective an ITN is in protecting the person sleeping under it (personal protection). √ √ Mosquito mortality Measured as the number of mosquitoes killed following exposure to an ITN or UTN, either immediate death or delayed death (24 h following exposure). Measured as a proportion of the total number of mosquitoes found within a hut or placed in tunnel/cone during a lab test. Indicates how effective an ITN is at directly killing mosquitoes. √ √ √ Induced exophily Measured as the proportion of mosquitoes found in exit traps, which indicates an attempt to prematurely exit the hut. Indicates how effective an ITN is in protecting the person sleeping under the net (personal protection). √ Deterrence A reduction in the number of mosquitoes entering a hut using an ITN relative to the number of mosquitoes found in a control hut using an UTN. Indicates how effective an ITN is in protecting the person sleeping under the net (personal protection). √ Not pass through net Equivalent to deterrence in hut trials; measured as the number of mosquitoes that do not pass through a holed ITN to reach an animal bait relative to an UTN in a control test. Indicates the potential effectiveness an ITN could have in protecting the person sleeping under the net. √ Knock-down at 60 min The number of mosquitoes that are knocked down (the inability of a mosquito to fly or stand) within 60 min following exposure to a net. √ Time to 50% knock-down The time taken to knock down 50% of mosquitoes used in the test. √ Time to 95% knock-down The time taken to knock down 95% of mosquitoes used in the test. √ Search Strategy The search period was from 1 January 1980 to 17 May 2013 or later. We searched the following databases for relevant studies: MEDLINE (from 1 January 1980 to 31 December 2013) and Cochrane Central Register of Controlled Trials, Science Citation Index Expanded, Social Sciences Citation Index, African Index Medicus, and CAB Abstracts (from 1 January 1980 to 17 May 2013). There was no language restriction (see Table S1 for the search terms used). We also searched the following conference proceedings: First MIM Pan-African Malaria Conference, Senegal, 6–9 January 1997; Second MIM Pan-African Malaria Conference, South Africa, 15–19 March 1999; Third MIM Pan-African Malaria Conference, Tanzania, 17–22 November 2002; Fourth MIM Pan-African Malaria Conference, Cameroon, 13–18 November 2005; Fifth MIM Pan-African Malaria Conference, Nairobi, 2–6 November 2009; American Society of Tropical Medicine and Hygiene 59th Annual Meeting, Atlanta, Georgia, 3–7 November 2010; American Society of Tropical Medicine and Hygiene 60th Annual Meeting, Philadelphia, Pennsylvania, 4–8 December 2011; and American Society of Tropical Medicine and Hygiene 61st Annual Meeting, Atlanta, Georgia, 11–15 November 2012. Study Selection Two authors (C. S. and A. A. E.) independently screened the search results for potentially relevant studies and retrieved the corresponding full articles. C. S. and A. A. E. independently assessed the articles for eligibility using a standardised form (Table S2). Discrepancies between the eligibility results were resolved by discussion. Study investigators were contacted for clarification if the eligibility of a particular study was unclear. Multiple publications from the same study were identified, and if eligible, the original study was taken forward for inclusion. Data Extraction C. S. and A. A. E. independently extracted data from all included studies into a data extraction form. Missing or unclear outcome data were requested from the study investigators. For dichotomous outcomes for the ITN and UTN groups, the number of mosquitoes experiencing the outcome and the total number of mosquitoes were extracted (Tables S3–S5). For continuous outcomes, we extracted the mean and standard deviation when possible. For deterrence, the total number of mosquitoes was extracted for the ITN and UTN groups. A sub-sample of 10% of the studies was randomly selected to assess the performance of the duplicate extraction processes by C. S. and A. A. E. Differences between the two extraction processes were examined, and no serious discrepancies were found. The data extracted by C. S. were used in all analyses. Stratification of Resistance The WHO classifies mosquitoes as susceptible to insecticides if, after exposure to a diagnostic dose, there is ≥98% mortality, and as resistant to insecticides if there is ≤90% mortality; mortality between 97% and 90% requires the confirmation of resistance genes for mosquitoes to be classified as resistant [26]. Characterisation of resistance across studies was not consistent, as some studies used bioassays, others used kdr genotyping, and some used a combination of both. We therefore developed a composite classification system to allow us to categorise the insecticide resistance status of mosquitoes in three broad groups (low, moderate, and high), based on phenotypic resistance measured using bioassay mortality data and/or kdr frequency (Table 4). The alleles for kdr are presented as a frequency or percentage. 10.1371/journal.pmed.1001619.t004 Table 4 Stratification of mosquito resistance constructed for this study based on either percent mortality from WHO bioassay data and/or kdr frequency. Resistance Status Percent Bioassay Mortality kdr Frequency (Percent) High 80 (high kdr) 80 (high mortality) 80% (L1014F) Not stated Y Y N N Darriet 1998 (YFO)b [32] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) CTN permethrin 500 mg/m2, 225 holes No High 15.9% (permethrin 0.25%) >80% (L1014F) Not stated Y Y N N Etang 2004 (Kisumu) [43] An. gambiae s.s. (Kisumu, lab strain) CTN permethrin 500 mg/m2 No Low Not stated Not stated Not stated Y Y N N Etang 2004 (OC-Lab) [43] An. gambiae (lab strain) CTN permethrin 500 mg/m2 No Unclear Not stated Not stated Elevated P450 activity Y Y N N Fane 2012 [47] An. gambiae s.s. (Kisumu, lab strain) CTN alpha-cypermethrin 40 mg/m2 No Low Not stated Not stated Not stated Y N Y Y Gimnig 2005 (Kisumu)a [45] An. gambiae s.s. (Kisumu, lab strain) LLIN Olyset No Low Not stated Not stated Not stated Y Y N N Gimnig 2005 (Kisumu)b [45] An. gambiae s.s. (Kisumu, lab strain) CTN K-O Tab 1-2-3 deltamethrin 25 mg/m2 No Low Not stated Not stated Not stated Y Y N N Hodjati 1999 (KWA 1 d) [44] An. gambiae s.s. (KWA, lab strain) CTN permethrin 500 mg/m2 No Low Not stated Not stated Not stated Y N Y N Hodjati 1999 (KWA 10 d) [44] An. gambiae s.s. (KWA, lab strain) CTN permethrin 500 mg/m2 No Low Not stated Not stated Not stated Y N Y N Hodjati 1999 (KWA 10 d fed) [44] An. gambiae s.s. (KWA, lab strain) CTN permethrin 500 mg/m2 No Low Not stated Not stated Not stated Y N Y N Hodjati 1999 (RSP 1 d) [44] An. gambiae s.s. (RSP, lab strain) CTN permethrin 500 mg/m2 No High Not stated Not stated Not stated Y N Y N Hodjati 1999 (RSP 10 d) [44] An. gambiae s.s. (RSP, lab strain) CTN permethrin 500 mg/m2 No High Not stated Not stated Not stated Y N Y N Hodjati 1999 (RSP 10 d fed) [43] An. gambiae s.s. (RSP, lab strain) CTN permethrin 500 mg/m2 No High Not stated Not stated Not stated Y N Y N Mahama 2007 (Kisumu) [46] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 2.0 No Low Not stated Not stated Not stated Y N Y Y Mahama 2007 (VKPR) [46] An. gambiae s.s. (VKPR, lab strain) LLIN PermaNet 2.0 No High Not stated Not stated Not stated Y N Y Y Malima 2009 (cone) [37] An. gambiae s.s. (Muheza, Tanzania, wild population) CTN deltamethrin 25 mg/m2 No Low 100% (permethrin 0.75%) Not stated Not stated Y Y N N Koudou 2011 (Kisumu)a [42] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 3.0 No Low Not stated Not stated Not stated Y Y N N Koudou 2011 (Kisumu)b [42] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 3.0 Yes Low Not stated Not stated Not stated Y Y N N Koudou 2011 (Kisumu)c [42] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 2.0 No Low Not stated Not stated Not stated Y Y N N Koudou 2011 (Kisumu)d [42] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 2.0 Yes Low Not stated Not stated Not stated Y Y N N Koudou 2011 (Kisumu)e [42] An. gambiae s.s. (Kisumu, lab strain) CTN deltamethrin 25 mg/m2 Yes Low Not stated Not stated Not stated Y Y N N Koudou 2011 (YFO)a [42] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) LLIN PermaNet 3.0 No High 10.6% (deltamethrin 0.05%) >80% (L1014F) Not stated Y Y N N Koudou 2011 (YFO)b [42] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) LLIN PermaNet 3.0 Yes High 10.6% (deltamethrin 0.05%) >80% (L1014F) Not stated Y Y N N Koudou 2011 (YFO)c [42] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) LLIN PermaNet 2.0 No High 10.6% (deltamethrin 0.05%) >80% (L1014F) Not stated Y Y N N Koudou 2011 (YFO)d [42] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) LLIN PermaNet 2.0 Yes High 10.6% (deltamethrin 0.05%) >80% (L1014F) Not stated Y Y N N Koudou 2011 (YFO)e [42] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) CTN deltamethrin 25 mg/m2 Yes High 10.6% (deltamethrin 0.05%) >80% (L1014F) Not stated Y Y N N Malima 2008 (cone)a [36] An. gambiae s.s. (Kisumu, lab strain) LLIN Olyset No Low Not stated Not stated Not stated Y Y N N Malima 2008 (cone)b [36] An. gambiae s.s. (Kisumu, lab strain) CTN alpha-cypermethrin 20 mg/m2 No Low Not stated Not stated Not stated Y Y N N Okia 2013 (Kisumu)a [4] An. gambiae s.s. (Kisumu, lab strain) LLIN Olyset No Low 100% (permethrin 0.75%), 100% (deltamethrin 0.05%) Not stated Not stated Y N N N Okia 2013 (Kisumu)b [4] An. gambiae s.s. (Kisumu, lab strain) LLIN Interceptor No Low 100% (permethrin 0.75%), 100% (deltamethrin 0.05%) Not stated Not stated Y N N N Okia 2013 (Kisumu)c [4] An. gambiae s.s. (Kisumu, lab strain) LLIN Netprotect No Low 100% (permethrin 0.75%), 100% (deltamethrin 0.05%) Not stated Not stated Y N N N Okia 2013 (Kisumu)d [4] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 2.0 No Low 100% (permethrin 0.75%), 100% (deltamethrin 0.05%) Not stated Not stated Y N N N Okia 2013 (Kisumu)e [4] An. gambiae s.s. (Kisumu, lab strain) LLIN PermaNet 3.0 No Low 100% (permethrin 0.75%), 100% (deltamethrin 0.05%) Not stated Not stated Y N N N Okia 2013 (Kanugu)a [4] An. gambiae s.s. (Kanugu, Uganda, wild population) LLIN Olyset No Moderate 68% (permethrin 0.75%), 97% (deltamethrin 0.05%) 36.7% (L1014S) Not stated Y N N N Okia 2013 (Kanugu)b [4] An. gambiae s.s. (Kanugu, Uganda, wild population) LLIN Interceptor No Moderate 68% (permethrin 0.75%), 97% (deltamethrin 0.05%) 36.7% (L1014S) Not stated Y N N N Okia 2013 (Kanugu)c [4] An. gambiae s.s. (Kanugu, Uganda, wild population) LLIN Netprotect No Moderate 68% (permethrin 0.75%), 97% (deltamethrin 0.05%) 36.7% (L1014S) Not stated Y N N N Okia 2013 (Kanugu)d [4] An. gambiae s.s. (Kanugu, Uganda, wild population) LLIN PermaNet 2.0 No Moderate 68% (permethrin 0.75%), 97% (deltamethrin 0.05%) 36.7% (L1014S) Not stated Y N N N Okia 2013 (Kanugu)e [4] An. gambiae s.s. (Kanugu, Uganda, wild population) LLIN PermaNet 3.0 No Moderate 68% (permethrin 0.75%), 97% (deltamethrin 0.05%) 36.7% (L1014S) Not stated Y N N N Okia 2013 (Lira)a [4] An. gambiae s.s. (Lira, Uganda, wild population) LLIN Olyset No Moderate 60% (permethrin 0.75%), 71% (deltamethrin 0.05%) 33.5% (L1014S) Not stated Y N N N Okia 2013 (Lira)b [4] An. gambiae s.s. (Lira, Uganda, wild population) LLIN Interceptor No Moderate 60% (permethrin 0.75%), 71% (deltamethrin 0.05%) 33.5% (L1014S) Not stated Y N N N Okia 2013 (Lira)c [4] An. gambiae s.s. (Lira, Uganda, wild population) LLIN Netprotect No Moderate 60% (permethrin 0.75%), 71% (deltamethrin 0.05%) 33.5% (L1014S) Not stated Y N N N Okia 2013 (Lira)d [4] An. gambiae s.s. (Lira, Uganda, wild population) LLIN PermaNet 2.0 No Moderate 60% (permethrin 0.75%), 71% (deltamethrin 0.05%) 33.5% (L1014S) Not stated Y N N N Okia 2013 (Lira)e [4] An. gambiae s.s. (Lira, Uganda, wild population) LLIN PermaNet 3.0 No Moderate 60% (permethrin 0.75%), 71% (deltamethrin 0.05%) 33.5% (L1014S) Not stated Y N N N Okia 2013 (Tororo)a [4] An. gambiae s.s. (Tororo, Uganda, wild population) LLIN Olyset No Moderate 53% (permethrin 0.75%), 66% (deltamethrin 0.05%) 35.4% (L1014S) Not stated Y N N N Okia 2013 (Tororo)b [4] An. gambiae s.s. (Tororo, Uganda, wild population) LLIN Interceptor No Moderate 53% (permethrin 0.75%), 66% (deltamethrin 0.05%) 35.4% (L1014S) Not stated Y N N N Okia 2013 (Tororo)c [4] An. gambiae s.s. (Tororo, Uganda, wild population) LLIN Netprotect No Moderate 53% (permethrin 0.75%), 66% (deltamethrin 0.05%) 35.4% (L1014S) Not stated Y N N N Okia 2013 (Tororo)d [4] An. gambiae s.s. (Tororo, Uganda, wild population) LLIN PermaNet 2.0 No Moderate 53% (permethrin 0.75%), 66% (deltamethrin 0.05%) 35.4% (L1014S) Not stated Y N N N Okia 2013 (Tororo)e [4] An. gambiae s.s. (Tororo, Uganda, wild population) LLIN PermaNet 3.0 No Moderate 53% (permethrin 0.75%), 66% (deltamethrin 0.05%) 35.4% (L1014S) Not stated Y N N N Okia 2013 (Wakiso)a [4] An. gambiae s.s. (Wakiso, Uganda, wild population) LLIN Olyset No Moderate 90% (permethrin 0.75%), 94% (deltamethrin 0.05%) 36.6% (L1014S) Not stated Y N N N Okia 2013 (Wakiso)b [4] An. gambiae s.s. (Wakiso, Uganda, wild population) LLIN Interceptor No Moderate 90% (permethrin 0.75%), 94% (deltamethrin 0.05%) 36.6% (L1014S) Not stated Y N N N Okia 2013 (Wakiso)c [4] An. gambiae s.s. (Wakiso, Uganda, wild population) LLIN Netprotect No Moderate 90% (permethrin 0.75%), 94% (deltamethrin 0.05%) 36.6% (L1014S) Not stated Y N N N Okia 2013 (Wakiso)d [4] An. gambiae s.s. (Wakiso, Uganda, wild population) LLIN PermaNet 2.0 No Moderate 90% (permethrin 0.75%), 94% (deltamethrin 0.05%) 36.6% (L1014S) Not stated Y N N N Okia 2013 (Wakiso)e [4] An. gambiae s.s. (Wakiso, Uganda, wild population) LLIN PermaNet 3.0 No Moderate 90% (permethrin 0.75%), 94% (deltamethrin 0.05%) 36.6% (L1014S) Not stated Y N N N Okumu 2012a [6] An. arabiensis (colony established from wild population) LLIN Icon Life No Low 100% (DDT 4%), >90% (pyrethroids) Not stated Not stated Y N N N Okumu 2012b [6] An. arabiensis (colony established from wild population) LLIN Olyset No Low 100% (DDT 4%), >90% (pyrethroids) Not stated Not stated Y N N N Okumu 2012c [6] An. arabiensis (colony established from wild population) LLIN PermaNet 2.0 No Low 100% (DDT 4%), >90% (pyrethroids) Not stated Not stated Y N N N Winkler 2012a [48] An. gambiae s.s. (Kisumu, lab strain) CTN Icon Maxx lambda-cyhalothrin (polyethylene net) No Low Not stated Not stated Not stated Y N N N Winkler 2012b [48] An. gambiae s.s. (Kisumu, lab strain) CTN Icon Maxx lambda-cyhalothrin (polyester net) No Low Not stated Not stated Not stated Y N N N KD, percent knock-down at 60 min; KDT50, time to knock-down of 50% of the mosquitoes; KDT95, time to knock-down of 95% of the mosquitoes; MM, mosquito mortality; OC-Lab, OCEAC Laboratory strain; YFO, Yaokoffikro. Fifty-seven comparisons used An. gambiae s.s. mosquitoes, whilst three were of An. arabiensis. Overall, 29 comparisons used laboratory-reared mosquito strains (Kisumu, VKPR, OC-Lab, KWA, and RSP strains), and 28 comparisons used wild field-caught mosquitoes from Yaokoffikro (Côte d'Ivoire), Muheza (Tanzania), and localities in Uganda. Three comparisons used recently colonised An. arabiensis mosquitoes that were originally collected from the Ulanga District of Tanzania. Based on the reported WHO bioassay percent mortalities and kdr frequencies, 28 comparisons were carried out with mosquitoes with low resistance, 20 comparisons with moderately resistant mosquitoes, and 11 comparisons with highly resistant mosquitoes; resistance was unclear for one comparison. Only one comparison measured metabolic resistance. For the risk of bias assessment, all comparisons reported comparability of ITN and UTN mosquito groups, but it was unclear in all studies whether observers were blinded (Table S6). No comparison reported incomplete outcome data. Fifteen comparisons reported raw data for ITN and UTN groups, the remaining 45 did not. Tunnel tests The 11 included tunnel test studies made 20 comparisons. UTNs were compared against unwashed CTNs and LLINs. Characteristics for each comparison are given in Table 8. All comparisons used An. gambiae mosquitoes (the number of mosquitoes used varied from 200 to 592). Three comparisons used wild field-caught mosquitoes from Yaokoffikro (Côte d'Ivoire) and Muheza (Tanzania) in their assessment, whilst 17 comparisons used laboratory-reared mosquito strains (Kisumu, VKPR, Kisumu/VKPR hybrids, Tola, and Kou strains). Based on the reported WHO bioassay percent mortalities and kdr frequencies, 12 comparisons were carried out with mosquitoes with low resistance, six comparisons used highly resistant mosquitoes, and resistance was moderate for two comparisons. No comparison measured metabolic resistance. 10.1371/journal.pmed.1001619.t008 Table 8 Study characteristics of the included tunnel tests. Study Mosquito Species (Strain/Origin) Intervention (All versus UTN) Net Washed Resistance Status Resistance Testing Measured Outcomes Bioassay Percent Mortality (Insecticide) kdr Frequency (Mutation) Metabolic Resistance MM BF NPT Chandre 2000 (L1 Kisumu) [29] An. gambiae s.s. (Kisumu, lab strain) CTN permethrin 250 mg/m2 No Low 98% (permethrin 0.25%) Not stated Not stated Y Y Y Chandre 2000 (L1 Kou) [29] An. gambiae (Kou, lab strain) CTN permethrin 250 mg/m2 No High 0% (permethrin 0.25%) 100% (L1014F) Not stated Y Y Y Chandre 2000 (L1 Tola) [29] An. gambiae s.s. (Tola, lab strain) CTN permethrin 250 mg/m2 No High Not stated 100% (L1014F) Not stated Y Y Y Chandre 2000 (L2 Kisumu) [29] An. gambiae s.s. (Kisumu, lab strain) CTN permethrin 500 mg/m2 No Low 98% (permethrin 0.25%) Not stated Not stated Y Y N Chandre 2000 (L2 YFO)a [29] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) CTN permethrin 250 mg/m2 No High Not stated 94.4% (L1014F) Not stated Y Y N Chandre 2000 (L2 YFO)b [29] An. gambiae s.s. (Yaokoffikro, Côte d'Ivoire, wild population) CTN permethrin 500 mg/m2 No High Not stated 94.4% (L1014F) Not stated Y Y N Corbel 2004 (Kisumu/VKPR hybrid)a [30] An. gambiae (Kisumu/VKPR hybrid, lab strain) CTN permethrin 250 mg/m2 No Moderate Not stated RS (frequency not stated) Not stated Y Y N Corbel 2004 (Kisumu/VKPR hybrid)b [30] An. gambiae (Kisumu/VKPR hybrid, lab strain) CTN permethrin 500 mg/m2 No Moderate Not stated RS (frequency not stated) Not stated Y Y N Corbel 2004 (Kisumu)a [30] An. gambiae s.s. (Kisumu, lab strain) CTN permethrin 250 mg/m2 No Low Not stated Not stated Not stated Y Y N Corbel 2004 (Kisumu)b [30] An. gambiae s.s. (Kisumu, lab strain) CTN permethrin 500 mg/m2 No Low Not stated Not stated Not stated Y Y N Corbel 2004 (VKPR)a [30] An. gambiae s.s. (VKPR, lab strain) CTN permethrin 250 mg/m2 No High Not stated RR (frequency not stated) Not stated Y Y N Corbel 2004 (VKPR)b [30] An. gambiae s.s. (VKPR, lab strain) CTN permethrin 500 mg/m2 No High Permethrin resistant RR (frequency not stated) Not stated Y Y N Malima 2008a [36] An. gambiae s.s. (Kisumu, lab strain) CTN alpha-cypermethrin 20 mg/m2 No Low 100% (deltamethrin 0.05%), 100% (permethrin 0.75%) absent Not stated Y Y Y Malima 2008b [36] An. gambiae s.s. (Kisumu, lab strain) LLIN Olyset No Low 100% (permethrin 0.75%) Not stated Not stated Y Y Y Malima 2009 (tunnel) [37] An. gambiae s.s. (Muheza, Tanzania, wild population) CTN deltamethrin 25 mg/m2 No Low 100% (permethrin 0.75%) Not stated Not stated Y Y Y Oxborough 2009a [40] An. gambiae s.s. (Kisumu, lab strain) CTN deltamethrin 25 mg/m2 (on polyester nets) No Low Not stated Not stated Not stated Y Y Y Oxborough 2009b [40] An. gambiae s.s. (Kisumu, lab strain) CTN deltamethrin 25 mg/m2 (on polyethylene nets) No Low Not stated Not stated Not stated Y Y Y Oxborough 2009c [40] An. gambiae s.s. (Kisumu, lab strain) CTN deltamethrin 25 mg/m2 (on cotton nets) No Low Not stated Not stated Not stated Y Y Y Oxborough 2009d [40] An. gambiae s.s. (Kisumu, lab strain) CTN deltamethrin 25 mg/m2 (on nylon nets) No Low Not stated Not stated Not stated Y Y Y BF, blood fed; MM, mosquito mortality; NPT, not passed through net; RR, homozygous for the kdr allele; RS, heterozygous for the kdr allele. For the risk of bias assessment, 16 comparisons reported comparability of ITN and UTN mosquito groups, whilst comparability was unclear in four comparisons (Table S7). It was unclear in all studies whether observers were blinded. No comparison reported incomplete outcome data. Sixteen comparisons reported raw data for ITN and UTN groups, the remaining four did not. Experimental hut field trials The 24 included hut studies made 56 comparisons (Table 9). 20 comparisons used field sites in Côte D'Ivoire, 14 in Tanzania, 11 in Benin, six in Burkina Faso, and five in Cameroon. Most comparisons (41 of 56) were of An. gambiae mosquitoes, 12 were of An. arabiensis, and three were of An. funestus. Two comparisons used laboratory-reared strains (Kisumu). Based on the reported WHO bioassay percent mortalities and kdr frequencies, 26 comparisons were carried out with mosquitoes with low resistance, 21 comparisons used highly resistant mosquitoes, and resistance was moderate for nine comparisons. Two comparisons measured metabolic resistance. 10.1371/journal.pmed.1001619.t009 Table 9 Study characteristics of the included experimental hut trials. Study Study Location Study Start Date Duration (Nights) Mosquito Species (Strain/Origin) Intervention (All versus UTN) Net Washed Resistance Status Resistance Testing Measured Outcomes WHO Bioassay Percent Mortality (Insecticide) kdr Frequency (L1014F Mutation) Metabolic Resistance D BF IE MM Asidi 2005a [28] Yaokoffikro field station, Côte d'Ivoire 15 August 2002 33 An. gambiae s.s. CTN lambda-cyalothrin 18 mg/m2 No High NS >90%a NS Y Y Y Y Asidi 2005b [28] Yaokoffikro field station, Côte d'Ivoire 15 August 2002 33 An. gambiae s.s. CTN lambda-cyalothrin 18 mg/m2 Yes High NS >90%a NS Y Y Y Y Chandre 2000 (Kisumu)a [29] Yaokoffikro field station, Côte d'Ivoire NS NS An. gambiae s.s. (Kisumu, lab strain) CTN deltamethrin 25 mg/m2 No Low 98.6% (permethrin 0.25%) NS NS Y Y N Y Chandre 2000 (Kisumu)b [29] Yaokoffikro field station, Côte d'Ivoire NS NS An. gambiae s.s. (Kisumu, lab strain) CTN permethrin 500 mg/m2 No Low 98.6% (permethrin 0.25%) NS NS Y Y N Y Chandre 2000 (YFO)a [29] Yaokoffikro field station, Côte d'Ivoire NS NS An. gambiae s.s. (Yaokoffikro, wild population) CTN deltamethrin 25 mg/m2 No High NS 94.40% NS Y Y N Y Chandre 2000 (YFO)b [29] Yaokoffikro field station, Côte d'Ivoire NS NS An. gambiae s.s. (Yaokoffikro, wild population) CTN permethrin 500 mg/m2 No High NS 94.40% NS Y Y N Y Corbel 2004a [30] CREC field station, Cotonou, Benin NS NS An. gambiae s.s. (M form) CTN permethrin 500 mg/m2 No Moderate NS 78.80% NS Y Y Y Y Corbel 2004b [30] CREC field station, Cotonou, Benin NS NS An. gambiae s.s. (M form) CTN permethrin 250 mg/m2 No Moderate NS 63.40% NS Y Y Y Y Corbel 2010 (Benin)a [31] Malanville, Benin NS NS An. gambiae s.s. (S form) LLIN PermaNet 2.0 No Low 85% (deltamethrin 0.05%) 16% NS Y Y Y Y Corbel 2010 (Benin)b [31] Malanville, Benin NS NS An. gambiae s.s. (S form) LLIN PermaNet 2.0 Yes Low 85% (deltamethrin 0.05%) 16% NS Y Y Y Y Corbel 2010 (Benin)c [31] Malanville, Benin NS NS An. gambiae s.s. (S form) LLIN PermaNet 3.0 No low 85% (deltamethrin 0.05%) 16% NS Y Y Y Y Corbel 2010 (Benin)d [31] Malanville, Benin NS NS An. gambiae s.s. (S form) LLIN PermaNet 3.0 Yes Low 85% (deltamethrin 0.05%) 16% NS Y Y Y Y Corbel 2010 (Benin)e [31] Malanville, Benin NS NS An. gambiae s.s. (S form) CTN deltamethrin 25 mg/m2 Yes Low 85% (deltamethrin 0.05%) 16% NS Y Y Y Y Corbel 2010 (BFaso)a [31] Valleé du Kou, Burkina Faso NS NS An. gambiae s.s. (15% M form/85% S form) LLIN PermaNet 2.0 No High 23% (deltamethrin 0.05%) >80% NS Y Y Y Y Corbel 2010 (BFaso)b [31] Valleé du Kou, Burkina Faso NS NS An. gambiae s.s. (15% M form/85% S form) LLIN PermaNet 2.0 Yes High 23% (deltamethrin 0.05%) >80% NS Y Y Y Y Corbel 2010 (BFaso)c [31] Valleé du Kou, Burkina Faso NS NS An. gambiae s.s. (15% M form/85% S form) LLIN PermaNet 3.0 No High 23% (deltamethrin 0.05%) >80% NS Y Y Y Y Corbel 2010 (BFaso)d [31] Valleé du Kou, Burkina Faso NS NS An. gambiae s.s. (15% M form/85% S form) LLIN PermaNet 3.0 Yes High 23% (deltamethrin 0.05%) >80% NS Y Y Y Y Corbel 2010 (BFaso)e [31] Valleé du Kou, Burkina Faso NS NS A An. gambiae s.s. (15% M form/85% S form) CTN deltamethrin 25 mg/m2 Yes High 23% (deltamethrin 0.05%) >80% NS Y Y Y Y Corbel 2010 (Cameroon)a [30] Pitoa, Cameroon NS NS An. arabiensis (95%), An. gambiae s.s. (5%) (S form) LLIN PermaNet 2.0 No Moderate 70% (deltamethrin 0.05%) 80% NS Y Y Y Y Ngufor 2011 (80 holes) [39] Akron, Benin NS NS An. gambiae s.s. LLIN deltamethrin 55 mg/m2, 80 holes in the net No High NS >80% NS Y Y Y Y Okumu 2013 (dry season)a [9] Ulanga District, Tanzania NS NS An. arabiensis LLIN Olyset No Low 100% (DDT), 95.5% (deltamethrin), 95.2% (permethrin), 90.2% (lambda-cyhalothrin) NS NS Y Y Y Y Okumu 2013 (dry season)b [9] Ulanga District, Tanzania NS NS An. arabiensis LLIN PermaNet 2.0 No Low 100% (DDT), 95.5% (deltamethrin), 95.2% (permethrin), 90.2% (lambda-cyhalothrin) NS NS Y Y Y Y Okumu 2013 (dry season)c [9] Ulanga District, Tanzania NS NS An. arabiensis LLIN Icon Life No Low 100% (DDT), 95.5% (deltamethrin), 95.2% (permethrin), 90.2% (lambda-cyhalothrin) NS NS Y Y Y Y Okumu 2013 (wet season)a[9] Ulanga District, Tanzania NS NS An. arabiensis LLIN Olyset No Low 100% (DDT), 95.5% (deltamethrin), 95.2% (permethrin), 90.2% (lambda-cyhalothrin) NS NS Y Y Y Y Okumu 2013 (wet season)b [9] Ulanga District, Tanzania NS NS An. arabiensis LLIN PermaNet 2.0 No Low 100% (DDT), 95.5% (deltamethrin), 95.2% (permethrin), 90.2% (lambda-cyhalothrin) NS NS Y Y Y Y Okumu 2013 (wet season)c [9] Ulanga District, Tanzania NS NS An. arabiensis LLIN Icon Life No Low 100% (DDT), 95.5% (deltamethrin), 95.2% (permethrin), 90.2% (lambda-cyhalothrin) NS NS Y Y Y Y Oxborough 2013 [49] KCMUC field station, Tanzania NS NS An. arabiensis CTN alpha-cypermethrin 25 mg/m2 No Moderate 58% (lambda-cyhalothrin 0.05%), 76% (permethrin 0.75%), 100% (DDT 4%), 100% (fenitrothrion 1%) 0% (L1014F), 0% (L1014S)b NS Y Y Y Y Tungu 2010a [41] Muheza, Tanzania NS NS An. gambiae s.s. LLIN PermaNet 2.0 No Low 100% (deltamethrin 0.05%) NS NS Y Y Y Y Tungu 2010b [41] Muheza, Tanzania NS NS An. gambiae s.s. LLIN PermaNet 2.0 Yes Low 100% (deltamethrin 0.05%) NS NS Y Y Y Y Tungu 2010c [41] Muheza, Tanzania NS NS An. gambiae s.s. LLIN PermaNet 3.0 No Low 100% (deltamethrin 0.05%) NS NS Y Y Y Y Tungu 2010d [41] Muheza, Tanzania NS NS An. gambiae s.s. LLIN PermaNet 3.0 Yes Low 100% (deltamethrin 0.05%) NS NS Y Y Y Y Tungu 2010e [41] Muheza, Tanzania NS NS An. gambiae s.s. CTN deltamethrin 25 mg/m2 Yes Low 100% (deltamethrin 0.05%) NS NS Y Y Y Y Djenontin 2010 [34] Valleé du Kou, Burkina Faso NS NS An. gambiae s.s. (M form) LLIN PermaNet 2.0 No High NS 92% NS Y Y Y Y a In mosquitoes from control huts (mosquitoes from the test huts were not screened). b Oxborough et al. [49] was the only study that tested for L104F and for L104S, but found no mutations for either. BF, blood fed; BFaso, Burkina Faso; CREC, Entomological Research Centre of Cotonou; D, deterrence; IE, induced exophily; KCMUC, Kilimanjaro Christian Medical University College; M.ville, Malanville; MM, mosquito mortality; NS, not stated; YFO, Yaokoffikro. For the risk of bias assessment, no comparisons reported comparability of ITN and UTN mosquito groups or blinded collectors of mosquitoes or the sleepers (Table S8). Forty-eight of the 56 comparisons reported raw data for ITN and UTN groups. It was unclear in 16 comparisons as to whether nets were randomly allocated to huts at the start of the study. Overall, 41 comparisons rotated ITNs, eight did not, and seven did not report rotation. Fifty comparisons rotated sleepers, whilst it was unclear as to whether the remaining comparisons rotated the sleepers between huts. Table 10 displays the rigor of implementation assessment of each hut trial in terms of particular study design characteristics. Standardisation across studies both in terms of the experimental design and reporting was not consistent. Of the 16 comparisons that compared a washed net, 12 washed the net in accordance with the WHO protocol, one did not wash the net using WHO procedures, and it was unclear whether the remaining three had followed WHO procedures. Seven of the 56 comparisons cleaned the huts before the study, whereas 25 comparisons cleaned the huts after each rotation; the remaining comparisons were unclear regarding when the huts were cleaned. Overall, 38 of the 56 comparisons tested the ITNs before the study, 32 comparisons tested the ITNs on completion of the study, and 22 comparisons tested the nets chemically; the remaining comparisons did not test the nets. Outcomes were not measured on male mosquitoes in 30 of the 56 comparisons, but were measured in the remaining 26 comparisons. 10.1371/journal.pmed.1001619.t010 Table 10 Assessment of “rigor” for experimental hut trials. Study Wash Procedurea Huts Cleanedb ITNs Tested Male Mosquitoes Excluded from Study Resistance Testing of Mosquitoesf Before Study After Each Rotation Before Studyc End of Studyd Chemicallye Bioassays kdr Number Genotyped Statedg Metabolic Resistance Asidi 2005a [28] n/a Yes Unclear No No No Yes No Yes No No Asidi 2005b [28] No Yes Unclear No No No Yes No Yes No No Chandre 2000 (Kisumu)a [29] n/a Unclear Unclear Yes No No Yes Yes No No No Chandre 2000 (Kisumu)b [29] n/a Unclear Unclear Yes No No Yes Yes No No No Chandre 2000 (YFO)a [29] n/a Unclear Unclear Yes No No Yes No Yes No No Chandre 2000 (YFO)b [29] n/a Unclear Unclear Yes No No Yes No Yes No No Corbel 2004a [30] n/a Unclear Unclear No No No Yes No Yes Yes No Corbel 2004b [30] n/a Unclear Unclear No No No Yes No Yes Yes No Corbel 2010 (Benin)a [31] n/a Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Benin)b [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Benin)c [31] n/a Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Benin)d [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Benin)e [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (BFaso)a [31] n/a Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (BFaso)b [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (BFaso)c [31] n/a Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (BFaso)d [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (BFaso)e [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Cameroon)a [31] n/a Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Cameroon)b [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Cameroon)c [31] n/a Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Cameroon)d [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Corbel 2010 (Cameroon)e [31] Yes Unclear Unclear Yes Yes Yes No Yes Yes No No Darriet 1998a [32] n/a Unclear Yes No Yes No No Yes No n/a No Darriet 1998b [32] n/a Unclear Yes No Yes No No Yes No n/a No Darriet 2000 [33] n/a Unclear Unclear No No No Yes Yes No n/a No Fanello 1999a [35] n/a Unclear Unclear No No Yes No No Yes Yes No Fanello 1999b [35] n/a Unclear Unclear No No Yes No No Yes Yes No Koudou 2011a [42] n/a Yes Yes Yes Yes No Yes Yes No n/a No Koudou 2011b [42] n/a Yes Yes Yes Yes No Yes Yes No n/a No Koudou 2011c [42] Yes Yes Yes Yes Yes No Yes Yes No n/a No Koudou 2011d [42] Yes Yes Yes Yes Yes No Yes Yes No n/a No Koudou 2011e [41] Yes Yes Yes Yes Yes No Yes Yes No n/a No Malima 2008 (funestus)a [36] n/a Unclear Yes Yes No No Yes Yes No n/a No Malima 2008 (funestus)b [36] n/a Unclear Yes Yes No No Yes Yes No n/a No Malima 2008 (gambiae)a [36] n/a Unclear Yes Yes No No Yes Yes No n/a No Malima 2008 (gambiae)b [36] n/a Unclear Yes Yes No No Yes Yes No n/a No Malima 2009 (funestus) [37] n/a Unclear Yes Yes Yes No Yes Yes No n/a No Malima 2009 (gambiae) [37] n/a Unclear Yes Yes Yes No Yes Yes No n/a No N'Guessan 2007 (Cotonou) [38] n/a Unclear Unclear Yes Yes No Yes Yes Yes Yes Yes N'Guessan 2007 (M.ville) [38] n/a Unclear Unclear Yes Yes No Yes Yes Yes Yes Yes Ngufor 2011 (6 holes) [39] n/a Unclear Unclear No No No Yes No Yes Yes No Ngufor 2011 (80 holes) [39] n/a Unclear Unclear No No No Yes No Yes Yes No Okumu 2013 (dry season)a [9] n/a Unclear Yes No No No No Yes No n/a No Okumu 2013 (dry season)b [9] n/a Unclear Yes No No No No Yes No n/a No Okumu 2013 (dry season)c [9] n/a Unclear Yes No No No No Yes No n/a No Okumu 2013 (wet season)a [9] n/a Unclear Yes No No No No Yes No n/a No Okumu 2013 (wet season)b [9] n/a Unclear Yes No No No No Yes No n/a No Okumu 2013 (wet season)c [9] n/a Unclear Yes No No No No Yes No n/a No Oxborough 2013 [49] n/a Unclear Yes No No No No Yes Yes Yes No Tungu 2010a [41] n/a Unclear Yes Yes Yes Yes Yes Yes No n/a No Tungu 2010b [41] Unclear Unclear Yes Yes Yes Yes Yes Yes No n/a No Tungu 2010c [41] n/a Unclear Yes Yes Yes Yes Yes Yes No n/a No Tungu 2010d [41] Unclear Unclear Yes Yes Yes Yes Yes Yes No n/a No Tungu 2010e [41] Unclear Unclear Yes Yes Yes Yes Yes Yes No n/a No Djenontin 2010 [34] n/a Unclear Unclear Yes Yes No Yes No Yes Yes No a Nets washed in accordance with WHO standardised protocol [24]. n/a indicates the net was unwashed. b Huts cleaned and ventilated before the start of the study and after each rotation of net to prevent cross-contamination of insecticide. c Bioassays using laboratory-reared mosquito populations conducted on ITNs before the study to ensure that impregnation of nets has been performed correctly. d Bioassays using laboratory-reared mosquito populations conducted on ITNs at the end of the study to measure the residual activity. e Chemical analysis of ITNs to ensure the correct dosage of insecticide is present. f Resistance status of mosquito populations assessed using bioassay to measure the level of phenotypic resistance, kdr genotyping to measure the frequency of the L1014F or L1014S mutation, and metabolic resistance testing, which can be carried out using synergists, biochemical enzyme analysis, or gene expression profiling. g n/a indicates kdr was not measured. BFaso, Burkina Faso; M.ville, Malanville; n/a, not applicable; YFO, Yaokoffikro. Characterisation of resistance was not consistent across studies. Seventeen comparisons measured phenotypic resistance using bioassays complemented with kdr genotyping in the mosquito populations under investigation. Bioassays on their own were used in 27 comparisons, whilst 11 comparisons were performed on mosquitoes for which only kdr genotyping was used. Characterisation of metabolic resistance was reported in just two studies, where the authors also measured phenotypic resistance and kdr. For those studies which screened for kdr, ten stated the number of mosquitoes that had been genotyped. Relationship between Resistance and Entomological Outcomes Cone tests Forty-seven cone test comparisons reported mosquito mortality (21 low, 20 moderate, and five high resistance and one unclear) (Figure S1). Mortality was very low in the untreated net group, and the risk of mosquito mortality is much higher using ITNs as compared with UTNs regardless of resistance. The study-specific RDs showed huge variability within all three categories of resistance. The meta-analytic results showed that the difference in mortality risk using ITNs as compared with UTNs decreased as resistance increased. Nevertheless, mortality risk was significantly higher for ITNs compared to UTNs regardless of resistance: with low resistance, the difference in risk of mortality is 0.86 (95% CI 0.72 to 1.01; 4,626 mosquitoes, 21 comparisons; I 2 = 100%, 95% CI 100% to 100%); in the case of moderate resistance the difference in risk is 0.71 (95% CI 0.53 to 0.88; 5,760 mosquitoes, 20 comparisons; I 2 = 100%, 95% CI 100% to 100%); with high resistance, the difference in risk is 0.56 (95% CI 0.17 to 0.95; 784 mosquitoes, five comparisons; I 2 = 99%, 95% CI 99% to 100%). The test for subgroup differences did not demonstrate a difference in the RD between high, medium, and low resistance subgroups (p = 0.12, I 2 = 49%, 95% CI 23% to 66%). A further 12 comparisons (seven low resistance, five high) presented data that could not be combined in meta-analysis (Table 11). 10.1371/journal.pmed.1001619.t011 Table 11 Results from cone tests comparing LLIN or CTN versus UTN for mosquito mortality and knock-down at 60 min. Study Intervention (All versus UTN) Net Washed Mosquito Species (Strain) Resistance Status Mosquito Mortality Knock-Down at 60 min ITN (Percent) UTN (Percent) RD ITN (Percent) UTN (Percent) RD Koudou 2011 (Kisumu)a [42] LLIN PermaNet 3.0 No An. gambiae s.s. (Kisumu) Low 99 0 0.99 98 0 0.98 Koudou 2011 (Kisumu)b [42] LLIN PermaNet 3.0 Yes An. gambiae s.s. (Kisumu) Low 99 0 0.99 98 0 0.98 Koudou 2011 (Kisumu)c [42] LLIN PermaNet 2.0 No An. gambiae s.s. (Kisumu) Low 100 0 1 99 0 0.99 Koudou 2011 (Kisumu)d [42] LLIN PermaNet 2.0 Yes An. gambiae s.s. (Kisumu) Low 99 0 0.99 97 0 0.97 Koudou 2011 (Kisumu)e [42] CTN deltamethrin 25 mg/m2 Yes An. gambiae s.s. (Kisumu) Low 95 0 0.95 95 0 0.95 Malima 2008 (cone)a [36] LLIN Olyset No An. gambiae s.s. (Kisumu) Low 99 0 0.99 75 0 0.75 Malima 2008 (cone)b [36] CTN alpha-cypermethrin 20 mg/m2 No An. gambiae s.s. (Kisumu) Low 84 0 0.84 88 0 0.88 Koudou 2011 (YFO)a [42] LLIN PermaNet 3.0 No An. gambiae s.s. (Yaokoffikro wild population) High 48 0 0.48 77 0 0.77 Koudou 2011 (YFO)b [42] LLIN PermaNet 3.0 Yes An. gambiae s.s. (Yaokoffikro wild population) High 95 0 0.95 95 0 0.95 Koudou 2011 (YFO)c [42] LLIN PermaNet 2.0 No An. gambiae s.s. (Yaokoffikro wild population) High 42 0 0.42 84 0 0.84 Koudou 2011 (YFO)d [42] LLIN PermaNet 2.0 Yes An. gambiae s.s. (Yaokoffikro wild population) High 82 0 0.82 90 0 0.9 Koudou 2011 (YFO)e [42] CTN deltamethrin 25 mg/m2 Yes An. gambiae s.s. (Yaokoffikro wild population) High 8 0 0.08 17 0 0.17 YFO, Yaokoffikro. Nine comparisons reported percentage knock-down at 60 min (six low resistance, two high, one unclear; Figure S2). In mosquitoes with low resistance, the risk of being knocked down is significantly higher using ITNs as compared with UTNs, but with high resistance, there is no difference between ITNs and UTNs. A significant difference is detected between the meta-analytic results for mosquitoes with low, unclear, and high resistance (p 0.90, which is close to fixation, is unlikely to revert rapidly, we cannot rule out the migration of mosquito populations or other confounding factors that could dramatically influence mosquito populations and/or resistance profiles over time. In terms of interpreting the patterns, this has to be done with care, given the variability of the results. Reduced killing of mosquitoes with increasing resistance in tunnel and hut studies raises concerns. Feeding preferences of mosquitoes can be plastic [60], and there is evidence that anthropogenic species such as An. gambiae and An. funestus can switch to feeding on cattle to obtain a blood meal in the presence of pyrethroid-treated materials [61],[62]. So, although the personal protection properties of ITNs (i.e., prevention of blood feeding and induced exophily) are still maintained, there is still the risk that if different hosts are available, mosquitoes could adapt their feeding preferences and thereby maintain large population sizes. If LLIN coverage is lowered, nets become badly damaged, are inappropriately used, are sold on, or are used less over time (all of which are realistic scenarios) [63], the reduced killing of resistant mosquitoes, which may have obtained a blood meal elsewhere, could be a cause for concern. Inconsistency between studies in relation to study design, execution, and reporting format across all experimental hut trials is an obstacle in addressing the relationship between resistance and ITN efficacy confidently. There are no clear guidelines for measuring ITN efficacy against resistant mosquitoes. As a consequence, the studies do not easily lend themselves to meta-analysis, and so it is difficult to generate a consensus. It is likely that the effects of resistance on some outcomes may be moderate or small, but the lack of standardisation means the methodological differences between studies obscure any detection or coherent synthesis between studies. So, if this field of research aims to identify generalisable findings, then researchers need to consider how best to measure the dependent and independent variables so that the results are more comparable. Our concern with this lack of transparency and standardisation, and the need for improved reporting, echoes recent calls [64] for research to be better planned, co-ordinated, and of higher quality. With such gaps and lack of standardisation in the primary studies, it could be argued that current research represents inefficient use of scarce resources of the scientific community as a whole. Based on the studies included in this meta-analysis, ITNs remain at least somewhat effective against African anopheline mosquitoes even when resistance has developed. However, whether ITNs remain effective against resistant mosquitoes cannot be definitively addressed whilst the execution and reporting of field studies and the profiling of resistance in mosquito populations is inadequate and inconsistent. Ideally, phenotypic resistance, target-site resistance, and metabolic resistance testing should all be applied to mosquito populations in the vicinity of the hut trial. If this is not feasible, then a combination of either phenotypic and target-site resistance testing or target-site and metabolic resistance testing should be performed. Authors should make it clear in their reporting if they have omitted to test for any of the three categories of resistance highlighted above. It is also imperative that resistance is measured at the time of the study rather than relying on retrospective data. International agreement is needed for standardised methods for measuring the impact of resistance on ITNs before conclusive statements about the effect of resistance can be made. In order to initiate dialogue about the standardisation of methods and reporting we have generated a list of criteria that need to be addressed based on the experience of this review (Box 2). It is important that policy makers and non-governmental organizations plan vector control strategies and purchase ITNs based on the best available data. Box 2. Considerations for Experimental Hut Study Design and Reporting Resistance Testing of Mosquito Populations: Reporting Information Required Phenotypic resistance: doses of insecticide tested, exposure times to insecticide, total number of mosquitoes tested, total number of mosquitoes killed Target-site resistance: type of mutation screened for (i.e., L1014F or L104S), associated kdr allele frequencies Metabolic resistance: identification of genes or enzyme class implicated in conferring resistance Study Design Reporting Criteria: Reporting Requirement Study start date: date Study duration: number of nights Mosquito species present at location: species name and molecular form Nets randomly allocated to huts at start of trial: yes or no Nets rotated between huts during trial: yes or no Sleepers rotated between huts during trial: yes or no Washing of nets: wash procedure provided Huts cleaned between rotations: yes or no Observers collecting mosquitoes blinded to intervention: yes or no Sleepers blinded to intervention: yes or no Male mosquitoes used in the analysis: excluded or included Raw data for measured outcomes: provided Raw data for UTNs: provided Supporting Information Figure S1 Forest plot for cone tests comparing LLIN or CTN versus UTN for mosquito mortality. (EPS) Click here for additional data file. Figure S2 Forest plot for cone tests comparing LLIN or CTN versus UTN for knock-down at 60 min. (EPS) Click here for additional data file. Figure S3 Forest plot for tunnel tests comparing LLIN or CTN versus UTN for mosquito mortality. (EPS) Click here for additional data file. Figure S4 Forest plot for tunnel tests comparing LLIN or CTN versus UTN for blood feeding. (EPS) Click here for additional data file. Figure S5 Forest plot for tunnel tests comparing LLIN or CTN versus UTN for not passed though net. (EPS) Click here for additional data file. Figure S6 Funnel plot for mosquito mortality for cone tests. (EPS) Click here for additional data file. Figure S7 Funnel plot for percentage knock-down at 60 min for cone tests. (EPS) Click here for additional data file. Figure S8 Funnel plot for blood feeding for tunnel tests. (EPS) Click here for additional data file. Figure S9 Funnel plot for mosquito mortality for tunnel tests. (EPS) Click here for additional data file. Figure S10 Funnel plot for deterrence for tunnel tests. (EPS) Click here for additional data file. Figure S11 Funnel plot for blood feeding for experimental hut trials. (EPS) Click here for additional data file. Figure S12 Funnel plot for mosquito mortality for experimental hut trials. (EPS) Click here for additional data file. Figure S13 Funnel plot for induced exophily for experimental hut trials. (EPS) Click here for additional data file. Figure S14 Forest plot for sensitivity analysis for blood feeding in hut studies where ITNs were randomly allocated to huts. (PDF) Click here for additional data file. Figure S15 Forest plot for sensitivity analysis for mosquito mortality in hut studies where ITNs were randomly allocated to huts. (PDF) Click here for additional data file. Figure S16 Forest plot for sensitivity analysis for induced exophily in hut studies where ITNs were randomly allocated to huts. (PDF) Click here for additional data file. Figure S17 Forest plot for sensitivity analysis for blood feeding in hut studies where ITNs were rotated between huts. (PDF) Click here for additional data file. Figure S18 Forest plot for sensitivity analysis for mosquito mortality in hut studies where ITNs were rotated between huts. (PDF) Click here for additional data file. Figure S19 Forest plot for sensitivity analysis for induced exophily in hut studies where ITNs were rotated between huts. (PDF) Click here for additional data file. Figure S20 Forest plot for sensitivity analysis for blood feeding in hut studies where sleepers were rotated between huts. (PDF) Click here for additional data file. Figure S21 Forest plot for sensitivity analysis for mosquito mortality in hut studies where sleepers were rotated between huts. (PDF) Click here for additional data file. Figure S22 Forest plot for sensitivity analysis for induced exophily in hut studies where sleepers were rotated between huts. (PDF) Click here for additional data file. Protocol S1 Protocol for the impact of pyrethroid resistance on the efficacy of insecticide treated bed nets against anopheline mosquitoes: systematic review. (DOCX) Click here for additional data file. Table S1 Search terms for electronic databases. (XLSX) Click here for additional data file. Table S2 Example of the form used to assess the eligibility of each study based on the inclusion criteria. (XLSX) Click here for additional data file. Table S3 Example of the form used for data extraction for cone tests. (XLSX) Click here for additional data file. Table S4 Example of the form used for data extraction for tunnel tests. (XLSX) Click here for additional data file. Table S5 Example of the form used for data extraction for experimental hut trials. (XLSX) Click here for additional data file. Table S6 Risk of bias assessment for the included cone tests. (XLSX) Click here for additional data file. Table S7 Risk of bias assessment for the included tunnel tests. (XLSX) Click here for additional data file. Table S8 Risk of bias assessment for the included experimental hut trials. (XLSX) Click here for additional data file. Table S9 Summary of sensitivity analysis for hut studies with low risk of bias. (XLSX) Click here for additional data file.
Author and article information
Contributors
Krijn P. Paaijmans: krijnpaaijmans@gmail.com
Journal
Journal ID (nlm-ta): Malar J
Journal ID (iso-abbrev): Malar. J
Title:
Malaria Journal
Publisher:
BioMed Central
(London
)
ISSN
(Electronic):
1475-2875
Publication date
(Electronic):
2
April
2018
Publication date PMC-release: 2
April
2018
Publication date Collection: 2018
Volume: 17
Electronic Location Identifier: 131
Affiliations
[1
]ISNI 0000 0000 9635 9413, GRID grid.410458.c, ISGlobal, Barcelona Ctr. Int. Health Res. (CRESIB), , Hospital Clínic - Universitat de Barcelona, ; Barcelona, Spain
[2
]ISNI 0000 0004 0630 4574, GRID grid.416657.7, Centre for Emerging Zoonotic and Parasitic Diseases, , National Institute for Communicable Diseases, ; Johannesburg, South Africa
Article
Publisher ID: 2250DOI: 10.1186/s12936-018-2250-4
PMC ID: 5879579
PubMed ID: 29606123
SO-VID: 0eb95d33-6f8c-45cc-bb62-fff7f379d896
Copyright © © The Author(s) 2018
License:
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
History
Date
received
: 25
October
2017
Date
accepted
: 24
February
2018
Categories
Subject:
Research
Custom metadata
issue-copyright-statement © The Author(s) 2018
ScienceOpen disciplines: Infectious disease & Microbiology
Data availability:
ScienceOpen disciplines: Infectious disease & Microbiology