‘Repel all biters’: an enhanced collection of endophilic Anopheles gambiae and Anopheles arabiensis in CDC light-traps, from the Kagera Region of Tanzania, in the presence of a combination mosquito net impregnated with piperonyl butoxide and permethrin

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Abstract

Background

Mosquito nets containing synergists designed to overcome metabolic resistance mechanisms in vectors have been developed. These may enhance excitability in the mosquitoes and affect how they respond to CDC light-traps. Investigating the behaviour of vectors of disease in relation to novel mosquito nets is, therefore, essential for the design of sampling and surveillance systems.

Methods

In an initial experiment in Muleba, Tanzania, nine bedrooms from three housing clusters were sampled. CDC light-traps were operated indoors next to occupied untreated nets (UTN), Olyset ^® long lasting insecticidal net (LLIN) and Olyset Plus ^® LLIN containing piperonyl butoxide (PBO) synergist. Nets were rotated daily between the nine rooms over nine nights. A further series of experiments using the nets on alternate nights in a single room was undertaken during the short rains. Anopheles gambiae s.l. were collected in CDC light-traps, a window-trap and Furvela tent-trap. Anopheles gambiae s.l. were identified to species by polymerase chain reaction (PCR).

Results

In the initial experiment 97.7% of the 310 An. gambiae s.l. were An. gambiae s.s., the remainder being Anopheles arabiensis. The number of mosquitoes collected from 81 light-trap collections was greater in the presence of an Olyset [density rate ratio 1.81, 95% CI (1.22–2.67), p = 0.003] relative to an UTN. In a second experiment, in the wet season 84% of the 180 An. gambiae s.l. identified were An. arabiensis. The number of An. gambiae s.l. collected from a light-trap compared to a tent-trap was significantly higher when an Olyset Plus net was used compared to an UTN. Survival of the mosquitoes in the window trap was not reduced by the use of an Olyset Plus net in the bedroom relative to an Olyset net.

Conclusion

Mosquitoes entering bedrooms, even those susceptible to pyrethroids, were not killed by contact with an Olyset Plus LLIN. The enhanced numbers of An. gambiae or An. arabiensis collected in light-traps when a treated net is used requires further experimentation and may be because of a heightened escape reaction on the part of the mosquito.

Related collections

Most cited references 24

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The molecular basis of insecticide resistance in mosquitoes.

Janet Hemingway, Nicola J Hawkes, Lynn McCarroll … (2004)

Insecticide resistance is an inherited characteristic involving changes in one or more insect gene. The molecular basis of these changes are only now being fully determined, aided by the availability of the Drosophila melanogaster and Anopheles gambiae genome sequences. This paper reviews what is currently known about insecticide resistance conferred by metabolic or target site changes in mosquitoes.

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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.

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Indoor Residual Spraying in Combination with Insecticide-Treated Nets Compared to Insecticide-Treated Nets Alone for Protection against Malaria: A Cluster Randomised Trial in Tanzania

Philippa West, Natacha Protopopoff, Alexandra Wright … (2014)

Introduction In the past decade, insecticide-treated net (ITN) distribution has been scaled up across Africa in line with the Abuja Declaration in 2000 [1]. The percentage of households that owned at least one ITN in Africa increased from 3% in 2000 to 54% in 2013. The World Health Organization (WHO) policy that ITNs should be provided to everyone in malaria risk areas (universal coverage) [2] has been adopted by 34 of the 44 malaria endemic countries in Africa [3]. Indoor residual spraying (IRS) of houses, the second major vector control tool used to prevent malaria, has similarly been scaled up. The proportion of at-risk populations protected by IRS increased from less than 5% in 2005 to 8% in 2012 [3]. As a result of the increase in the deployment of these preventive tools and the increased availability and use of artemisinin-based combination therapies, malaria-related mortality fell by 45% between 2000 and 2012 in Africa, but there remained an estimated 165 million cases and 562,000 deaths due to malaria in 2012 [3]. In an attempt to reduce the malaria burden further, a number of countries have chosen to use ITNs and IRS in combination. Fifty-seven countries, 31 of which are in Africa, use both IRS and ITNs, in at least some areas [3]. Applying ITNs and IRS in the same area can increase the proportion of individuals who are protected by at least one intervention or, more optimally, may provide additional protection for those protected by both interventions compared to those receiving one method alone [4]–[7]. Since the cost of implementing both IRS and universal coverage of ITNs is much greater than the cost of implementing only one of the interventions [8], it is important to know what extra protection is gained by adding a second intervention, to help national malaria control programmes and international funding agencies such as the President's Malaria Initiative (PMI) and the Global Fund to Fight AIDS, Tuberculosis and Malaria make decisions that are based on evidence of likely impacts and costs. This is particularly significant now, since it is estimated that global funding for malaria is less than half of what is needed to attain universal coverage of malaria vector control, i.e., access to either ITNs or IRS [9]. It is unclear from current evidence whether combined use of ITNs and IRS provides an additional benefit compared to using either intervention alone, and whether this will be similar across transmission settings [4]–[7],[10],[11]. A recent trial in Benin found no added benefit to using IRS in combination with ITNs compared to ITNs alone [10]. However, this trial had a relatively small sample size, and its findings may be applicable to only a particular transmission setting in west Africa [12]. To help define future malaria control policy in Africa, the PMI decided to sponsor an independent two-arm cluster randomised controlled trial (CRT) to compare the protective effectiveness of IRS in combination with high coverage of ITNs with high coverage of ITNs alone for malaria transmission control. Tanzania has a high malaria disease burden, with a national average of 9% of children under 5 y being infected with malaria parasites [13]. Malaria control activities have been scaled up nationally since 2005 [14]–[16]. A universal coverage campaign (UCC) primarily funded by the Global Fund to Fight AIDS, Tuberculosis and Malaria distributed long-lasting insecticidal nets (LLINs) free of charge in 2011 to top up coverage from previous distributions [14],[15],[17]. IRS, funded by the PMI, commenced in 2007 in two districts of Kagera Region, in northwest Tanzania, and has since been extended to cover 18 districts [18]. Because IRS is costly and logistically intensive [8],[19], there is an urgent need to know whether it is necessary to continue with IRS after an ITN UCC has been successfully completed. The trial was carried out in 109 rural villages in Muleba District (1°45′S 31°40′E), Kagera Region [20],[21]. The study area includes 68,108 households at an altitude ranging from 1,100 to 1,600 m above sea level. Rainfall occurs in two seasons: the “short rains” in October–December (average monthly rainfall 160 mm) and the “long rains” in March–May (average monthly rainfall 300 mm) [22], with malaria transmission occurring throughout the year and peaking after the rainy seasons [23]. Annual rounds of IRS with the pyrethroid lambda-cyhalothrin (ICON 10CS, Syngenta) were conducted between 2007 and 2011 in Muleba District, i.e., in the entire study area. The predominant malaria vectors are Anopheles gambiae s.s. and An. arabiensis [24]. Tests of mosquito susceptibility using standard WHO bioassays showed resistance to pyrethroids in An. gambiae s.s. in 2011 [24]. As a result, IRS policy was changed to use the carbamate insecticide bendiocarb (Ficam 80% wettable powder, Bayer) by the PMI in 2012. Methods Ethics and Community Sensitisation The trial was approved by the ethics review committees of the Kilimanjaro Christian Medical College, the Tanzanian National Institute for Medical Research, and the London School of Hygiene and Tropical Medicine. Written informed consent was obtained from all respondents. Prior to the baseline surveys, village and hamlet leaders were invited to sensitisation sessions conducted by district health officers. The trial was registered with ClinicalTrials.gov (registration number NCT01697852) in September 2012. The trial was not registered earlier because the authors were not aware of journal requirements for prospective registration. All authors have affirmed that any trials they are involved in on the same or a related drug or intervention are registered. An accurate summary of the trial's results has been submitted to ClinicalTrials.gov. Study Design A CRT was conducted, comparing the Plasmodium falciparum prevalence rate (PfPR) in children 0.5–14 y old between communities targeted to receive both high-coverage IRS and high coverage of ITNs (ITN+IRS arm) and communities targeted for high coverage of ITNs only (standard-care control arm). Secondary outcomes were moderate/severe anaemia (haemoglobin <8 g/dl) in children under 5 y old and entomological inoculation rate (EIR) due to An. gambiae s.l. Power calculations showed that 25 clusters per study arm were required, with 80 children per cluster, to give 80% power to detect a true absolute difference in PfPR of at least 3% between study arms (relative difference 31%) with 5% significance (two-sided), based on an expected prevalence in the ITN only arm of 9% (PfPR in first baseline survey). The between-cluster coefficient of variation (k) was calculated as 0.25 from the first pre-randomisation baseline survey [25]. Each cluster consisted of at least one village and was divided into a core surveillance area consisting of at least 200 houses and approximately 1 km radius, where the surveys were conducted, and an outer buffer zone, 1 km in width, which also received the allocated treatment but in which no outcome monitoring was done. Villages were eligible for inclusion in the study if they were within daily commuting distance for survey work and had been sprayed with IRS in the baseline year. All clusters received LLINs from the UCC in 2011. Twenty-five clusters were randomly allocated to receive IRS, in addition to ITNs, using restricted randomisation to limit potential imbalance between study arms [25]. Baseline surveys provided data on seven criteria for which the study arms were balanced by constraining the randomisation (Table 1). 200,000 random allocations were generated. Mean values for each arm were calculated from cluster summaries for each of the seven restriction variables; 25,119 randomisations fulfilled the restriction criteria and were therefore eligible. These allocations were tested for independence between any two clusters. The large number of acceptable allocations, of which one was randomly selected, ensured that the restriction did not affect the validity of inference. There was no evidence of dependence between any pair of clusters [25],[26]. 10.1371/journal.pmed.1001630.t001 Table 1 Restriction variables for randomisation and realisation of balance between the study arms. Variable Maximum Difference in Means between Study Armsa ITN Arma ITN+IRS Arma Actual Difference PfPRb in February–March 2011c 3% 9.9% 9.3% 0.5% PfPR in June–July 2011d 3% 22.4% 19.6% 2.7% Housing densitye 20 HH/km2 165.1 HH/km2 152.6 HH/km2 12.5 HH/km2 Mean elevation 50 m 1,364.8 m 1,330.7 m 34.1 m ITN usaged , f 5% 35.0% 30.4% 4.6% Adequate LLIN ownershipe , g 5% 61.3% 56.3% 5.0% Clusters with entomological surveillance Count of 2 20 clusters 20 clusters 0 clusters a Means for each study arm were calculated from cluster summaries. b PfPR from RDTs. c Recorded in baseline survey 1(February–March 2011). d Recorded in baseline survey 2 (June–July 2011) after the UCC. e Housing density in surveillance area of clusters. f Net used the night before the survey in all age groups. g Percentage of households with at least one LLIN per two people. HH, household. Interventions Households in the study area with children aged under 5 y received LLINs from a national distribution campaign in 2009 [16]. In 2011, the district health authority, supported by Mennonite Economic Development Associates, completed a UCC that distributed 144,000 LLINs (Olyset, Sumitomo Chemicals) to the population of Muleba District, including all study clusters. The campaign aimed to top up net coverage, so that every sleeping place had one ITN. After the UCC, 91% of households owned at least one ITN, and 58% of households owned enough ITNs to cover all their sleeping places [20]. Spraying was conducted by RTI International on behalf of PMI in the ITN+IRS study arm. The interior walls of each dwelling were sprayed with the carbamate insecticide bendiocarb (Ficam 80% wettable powder, Bayer) at 400 mg/m2 between December 2011 and January 2012 (round 1), and between April and May 2012 (round 2). Spray rounds were timed to precede the peak in malaria cases that normally occurs at the end of each rainy season, taking into account the relatively short residual duration of bendiocarb. Bendiocarb is a carbamate insecticide recommended by WHO for IRS [27],[28]. It is one of the few insecticides evaluated and approved by the WHO Pesticide Evaluation Scheme that has the potential to control pyrethroid-resistant mosquitoes, is odour-free, and is safe to house occupants at the recommended application rate [27]. Before obtaining WHO approval, all IRS insecticides are subject to risk assessment by WHO toxicologists [29]. Bendiocarb is an acetylcholinesterase inhibitor, but no serious adverse effects due to bendiocarb IRS have been reported in the recent medical literature. Surveys Three post-intervention cross-sectional household surveys were undertaken in 2012 (see Figure 1). Survey A (23 February–31 March) was after the short rainy season and 2 mo after the first spray round. Survey B (25 June–31 July) was after the long rainy season, 6 mo after the first spray round, and 2 mo after the second spray round. Survey C (25 October–4 December) was 6 mo after the second spray round and 10 mo after the first. Baseline surveys were conducted in 2011 during the same periods as surveys A and B. 10.1371/journal.pmed.1001630.g001 Figure 1 Study timetable. Surveys 1 and 2 are baseline surveys. Surveys A, B, and C are post-intervention. For each survey, 80 households were randomly selected in the core area of each cluster. Households were eligible for the study if they had children aged 0.5–14 y. Any child aged 0.5–14 y was eligible to be included in the study. Up to three children per household were randomly selected for testing. Allowing for ineligible households, absence on the day of the survey, and refusals at the household and individual level, it was estimated that this would provide on average 80 children for testing per cluster. The household head or another responsible adult from the household was interviewed, after seeking written informed consent. Data on IRS coverage, bed net ownership and usage, demographics of household members, and other household characteristics were gathered using an adapted version of the standard Malaria Indicator Survey [30]. Selected children were tested on the following day for malaria parasites using a rapid diagnostic test (RDT) (CareStart [Pan] Malaria, DiaSys) and had haemoglobin levels measured using HemoCue Hb 201+ (Aktiebolaget Leo Diagnostics). Individuals testing positive by RDT were treated with artemether/lumefantrine (Artefan 20/120, Ajanta Pharma) following national treatment guidelines. Entomological surveillance was carried out in the core surveillance areas of a subset of 40 of the 50 clusters from April 2011 to December 2012. For one night of each month US Centers for Disease Control and Prevention light traps for mosquito collections were set up in eight randomly selected houses in each cluster (320 houses per month). Anopheles mosquitoes collected were identified to species using a simplified morphological key adapted from Gillies and Coetzee [31]. A sub-sample of An. gambiae s.l. individuals were tested using real-time PCR TaqMan assay to distinguish between the two sibling species An. gambiae s.s. and An. arabiensis [32]. Mosquitoes were also tested for P. falciparum sporozoites (P. falciparum circumsporozoite protein) using ELISA [33]. Statistical Analysis Statistical analysis was done in Stata 12 (Statacorp) and R version 2.13.1 (R Foundation for Statistical Computing). The odds of PfPR and moderate/severe anaemia for individuals were compared between study arms in intention-to-treat (ITT) analysis using logistic regression. Mean haemoglobin was compared between the study arms using linear regression. A robust variance estimator was used to calculate standard errors to adjust for within-cluster correlation of responses (Stata survey commands, first-order Taylor-series linearization method) [34],[35]. PfPR was considered as P. falciparum alone or mixed infections as detected by the RDT. The overall odds ratio (OR) for the three surveys combined was calculated accounting for survey. An adjusted Wald test was performed to test whether there was evidence for effect modification between study arm and survey round. A sensitivity analysis was conducted excluding one cluster from the ITN only arm that mistakenly received IRS, to assess the impact of this protocol violation on the results of ITT analysis. Because of the wide variation in cluster-level estimates of PfPR at baseline, an OR for ITN+IRS versus ITN alone was calculated adjusting for baseline PfPR. A secondary per-protocol analysis was performed, in which individuals from the ITN+IRS arm who used an ITN and lived in a house sprayed in the most recent round of IRS were compared to individuals who used an ITN in the ITN only arm. The cluster that violated the protocol was excluded from the per-protocol analysis. The monthly EIR was calculated as the daily EIR found during the one night collection multiplied by the number of days in the month. Mean EIRs were compared between study arms using negative binomial regression and adjusting for within-cluster correlation. Results At baseline, PfPR, anaemia, ITN ownership, ITN usage, and mean EIR per month (Table 2) were similar in the two study arms. PfPR in children aged 6 mo to 14 y old was 9.3% (95% CI 5.9%–14.5%) after the short rains (survey A, February–March) and 22.8% (95% CI 17.3%–29.4%) after the long rains (survey B, June–July). Anaemia in children 0.5–4 y was 6.2% (95% CI 4.5%–8.5%) after the long rains. 10.1371/journal.pmed.1001630.t002 Table 2 Baseline characteristics of individuals and households by study arm, Muleba District, 2011. Characteristic ITN Only ArmPercent [95% CI] (n) ITN+IRS ArmPercent [95% CI] (n) PfPR in March 2011a , b , c 10.3 [5.2–19.3] (2,487) 8.4 [4.5–15.3] (2,655) PfPR in July 2011a , b , d 24.6 [17.0–34.3] (2,121) 21.0 [13.8–30.5] (2,185) Moderate/severe anaemiaa , d , e 6.4 [3.9–10.2] (785) 6.1 [4.1–8.9] (841) Mean haemoglobin (g/dl)a , d , 10.6 [10.4–10.9] (785) 10.6 [10.4–10.9] (841) ITN use in all age groupsa , d , f 53.3 [48.2–58.3] (6,755) 58.2 [53.8–62.5] (6,913) Households with adequate ITNsd , g , h 54.5 [49.5–59.5] (1,243) 62.3 [57.3–67.1] (1,250) Households with ≥1 ITNd , g 88.9 [86.0–91.3] (1,248) 92.6 [90.8–94.0] (1,251) Households received IRS in 2011c , g , i 94.4 [91.3–96.5] (1,598) 95.5 [93.5–96.9] (1,640) Mean An. gambiae mosquitoes per house per nightg , j 3.1 [1.0–9.6] (1,055) 2.2 [0.5–9.1] (1,120) Sporozoite ratea , k 1.1 [0.8–1.4] (1,359) 2.0 [1.4–2.8] (1,466) Mean EIR/monthl 1.1 [0.4–2.8] 1.3 [0.4–4.4] a Calculated from individual-level data. b PfPR from RDTs. c Recorded in baseline survey 1 (February–March 2011). d Baseline survey 2 (June–July 2011) after the UCC. e Haemoglobin <8 g/dl. f Reported sleeping under an ITN the night previous to the survey. g Calculated from household-level data. h At least one ITN per sleeping place. i Approximately 1 mo after spraying. j Arithmetic mean. k Proportion of mosquitoes positive for P. falciparum sporozoites. l Number of infective bites per month. Of the 2,000 houses selected in each study arm for each post-intervention survey, 20% to 24% had no children between 0.5 and 14 y old (were ineligible), 13% to 18% were vacant on the day of survey, fewer than 1% refused to participate, and 55% to 61% participated in the survey (Figure 2). Of the children selected for RDT, 81%–84% were tested. Post-intervention IRS coverage reported by householders was 92.1% after the first spray round and 89.5% after the second (Table 3). 10.1371/journal.pmed.1001630.g002 Figure 2 Trial profile for study households and children in the ITN only and ITN+IRS study arms. Survey A = 2 mo after first intervention spray. Survey B = 6 mo after first intervention spray and 2 mo after second intervention spray. Survey C = 10 mo after first intervention spray and 6 mo after second intervention spray. *No children 0.5–14 y old. 1Dwelling vacant for survey duration. 2Includes not found (91.0%), not visited (2.4%), and missing data (6.6%). 3Households (HH) that were included and where children attended for testing. 10.1371/journal.pmed.1001630.t003 Table 3 IRS coverage, ITN ownership, and ITN usage in the intervention year, Muleba District, 2012. Survey Arm Reported IRS CoverageaPercent [95% CI] (n b) Adequate ITN OwnershipcPercent [95% CI] (n b) ≥1 ITN OwneddPercent [95% CI] (n b) ITN UseePercent [95% CI] (n f) Survey A ITN only 3.3 [1.8–5.9] (1,177) 52.2 [47.8–56.5] (1,178) 85.8 [83.7–87.7] (1,177) 46.6 [41.7–51.6] (2,193) ITN+IRS 92.1 [88.4–94.7] (1,215) 57.2 [53.6–60.7] (1,215) 89.0 [87.1–90.6] (1,216) 53.0 [47.5–58.3] (2,349) Survey B ITN only 5.2 [1.3–18.6] (1,094) 51.6 [47.0–56.0] (1,094) 82.5 [78.7–85.7] (1,096) 40.7 [34.7–47.0] (2,045) ITN+IRS 89.5 [84.0–93.2] (1,138) 57.4 [54.0–60.9] (1,142) 88.2 [85.7–90.3] (1,142) 44.1 [39.2–49.2] (2,207) Survey C ITN only 13.0 [6.6–24.1] (1,165) 52.8 [47.6–58.0] (1,168) 78.2 [74.3–81.6] (1,170) 36.0 [29.8–42.6] (2,101) ITN+IRS 89.3 [83.6–93.2] (1,209) 56.8 [51.7–61.8] (1,211) 83.8 [79.9–87.1] (1,211) 36.1 [31.0–41.5] (2,303) Survey A = 2 mo after first intervention spray. Survey B = 6 mo after first intervention spray and 2 mo after second intervention spray. Survey C = 10 mo after first intervention spray and 6 mo after second intervention spray. a Reported spray status of household in the spray round preceding the survey. b Households. c Percentage of households with sufficient ITNs for at least one per sleeping place. d Percentage of households with at least one ITN. e Percentage of study children that reported sleeping under an ITN the night previous to the survey. ITN usage in all age groups was very similar to ITN use in the study children. f Individuals. In the intervention year, the percentage of houses with sufficient ITNs for each sleeping place remained stable over successive surveys and was similar between study arms (range 52%–57%; Table 3). 82.2% and 87.0% of households owned at least one ITN in the ITN only arm and the ITN+IRS arm, respectively (all surveys combined), with weak evidence that the percentage of households that owned at least one ITN was lower in the ITN only arm, and that it decreased from survey A to survey C in both arms (Table 3). ITN usage in children was similar between study arms but declined from 50% in survey A to 36% in survey C. The primary outcome PfPR was lower in the ITN+IRS arm than in the ITN only arm in all three surveys in the intervention year (Table 4). For all three surveys combined, the overall OR was 0.43 (95% CI 0.19–0.97), with weak evidence that the intervention effect differed between surveys (interaction p = 0.08). The strongest effect was observed in survey B (OR 0.33, 95% CI 0.15–0.75), which was conducted at the peak of malaria transmission after the long rains, 6 mo after the first IRS and 2 mo after the second IRS. The evidence for an effect was weaker in survey A (OR 0.51, 95% CI 0.24–1.09), conducted shortly after the first IRS round, and in survey C (OR 0.48, 95% CI 0.18–1.24), conducted several months after the main transmission season and 6 mo after last spray round. The range of cluster-specific estimates for PfPR was 0% to 92% in the ITN only arm and 0% to 68% in the ITN+IRS arm. The sensitivity analysis showed that excluding the cluster from the ITN only arm that had received IRS did not affect the results of the ITT analysis (Table S1). The overall OR for all three surveys combined was very similar after adjusting for baseline PfPR, OR = 0.41, but the precision of the estimate was increased (95% CI 0.29–0.59, p<0.0001). 10.1371/journal.pmed.1001630.t004 Table 4 PfPR in children 0.5–14 y old in the ITN only and ITN+IRS arms (intention to treat) in survey A, B, and C, Muleba District, Tanzania, 2012. Survey Arm PfPRaPercent [95% CI] (n) OR [95% CI], p-Value Survey A ITN only 23.6 [15.4–34.2] (2,191) 1.00 ITN+IRS 13.6 [8.3–21.4] (2,342) 0.51 [0.24–1.09], p = 0.082 Survey B ITN only 30.5 [20.2–43.4] (2,033) 1.00 ITN+IRS 12.7 [7.4–21.0] (2,204) 0.33 [0.15–0.75], p = 0.009 Survey C ITN only 24.5 [14.2–38.9] (2,091) 1.00 ITN+IRS 13.4 [7.3–23.4] (2,285) 0.48 [0.18–1.24], p = 0.127 All three surveys combined ITN only 26.1 [16.7–38.4] (6,315) 1.00 ITN+IRS 13.3 [7.9–21.5] (6,831) 0.43 [0.19–0.97], p = 0.043b Survey A = 2 mo after first intervention spray. Survey B = 6 mo after first intervention spray and 2 mo after second intervention spray. Survey C = 10 mo after first intervention spray and 6 mo after second intervention spray. a PfPR from RDTs. b Adjusted for survey. Prevalence of moderate to severe anaemia in children under 5 y old, a secondary outcome, was lower in the ITN+IRS arm in all post-intervention surveys, but the difference was statistically significant only in survey B (Table 5). Mean haemoglobin was higher in children under 5 y old in the ITN+IRS arm than in the ITN only arm in all three surveys. The evidence for an effect was greatest in survey B (0.49 g/dl, 95% CI 0.10–0.89, p = 0.016), with a non-significant result in survey A (0.28 g/dl, 95% CI −0.02 to 0.59, p = 0.065) and survey C (0.36 g/dl, 95% CI −0.02 to 0.73, p = 0.060). 10.1371/journal.pmed.1001630.t005 Table 5 Anaemia and mean haemoglobin in children under 5+IRS arms (intention to treat), for survey A, B, and C, Muleba District, Tanzania, 2012. Survey Arm Anaemia Prevalencea Mean Haemoglobin (g/dl) Percent [95% CI] (n) OR [95% CI], p-Value Mean [95% CI] (n) Difference [95% CI], p-Value Survey A ITN only 6.0 [4.1–8.7] (815) 1.00 10.6 [10.4–10.8] (815) ITN+IRS 3.9 [2.5–6.2] (864) 0.64 [0.34–1.19], p = 0.155 10.9 [10.7–11.1] (864) 0.28 [−0.02 to 0.59], p = 0.065 Survey B ITN only 4.7 [2.6–8.6] (737) 1.00 10.9 [10.6–11.2] (737) ITN+IRS 2.2 [1.3–3.6] (784) 0.44 [0.20–1.01], p = 0.053 11.4 [11.2–11.6] (784) 0.49 [0.10 to 0.89], p = 0.016 Survey C ITN only 3.2 [1.8–5.7] (739) 1.00 10.8 [10.6–11.1] (739) ITN+IRS 2.6 [1.6–4.4] (831) 0.81 [0.37–1.77], p = 0.590 11.2 [11.0–11.4] (831) 0.36 [−0.02 to 0.73], p = 0.060 All three surveys combined ITN only 4.7 [3.2–6.9] (2,291) 1.00 10.8 [10.5–11.0] (2,291) ITN+IRS 2.9 [2.0–4.3] (2,479) 0.62 [0.34–1.10], p = 0.102b 11.2 [11.0–11.3] (2,479) 0.37 [0.07 to 0.68], p = 0.017b Survey A = 2 mo after first intervention spray. Survey B = 6 mo after first intervention spray and 2 mo after second intervention spray. Survey C = 10 mo after first intervention spray and 6 mo after second intervention spray. a Prevalence of moderate/severe anaemia (haemoglobin <8 g/dl). b Adjusted for survey. Mean EIR per month, a secondary outcome, was 0.22 in the ITN+IRS arm and 1.26 in the ITN only arm (rate ratio = 0.17, 95% CI 0.03–1.08, p = 0.059; Table 6). 10.1371/journal.pmed.1001630.t006 Table 6 Mean number of An. gambiae mosquitoes per household, sporozoite rate, and EIR in the ITN only and ITN+IRS arms during the post-intervention period, Muleba District, Tanzania, 2011–2012. Arm Mean or Percent [95% CI] (n)a Effect [95% CI], p-Value Mean b An. gambiae per house per night ITN only 1.7 [0.5–6.4] (1,892) ITN+IRS 0.4 [0.1–1.4] (1,893) Rate ratio = 0.23 [0.04–1.44], p = 0.113 Sporozoite rate c ITN only 2.5 [2.1–3.1] (3,059) ITN+IRS 1.8 [0.5–6.2] (717) OR = 0.72 [0.21–2.53], p = 0.600 Mean EIR/month d ITN only 1.3 [0.3–4.6] ITN+IRS 0.2 [0.1–0.8] Rate ratio = 0.17 [0.03–1.08], p = 0.059 a Data are mean [95% CI] (number of houses) for mean An. gambiae per house per night and percent [95% CI] (number of An. gambiae) for sporozoite rate. b Arithmetic mean. c Proportion of mosquitoes positive for P. falciparum sporozoites. d Number of infective bites per month. The between-cluster coefficient of variation (k) was 0.20, 0.28, and 0.26 in the three post-intervention surveys, respectively. For each survey, k was similar in the two arms. For all surveys, per-protocol analysis showed statistically significant evidence for a protective effect of the combined intervention on PfPR (survey A: OR 0.39, 95% CI 0.18–0.81; survey B: OR 0.21, 95% CI 0.09–0.49; and survey C: OR 0.27, 95% CI 0.10–0.73; Table 7). 10.1371/journal.pmed.1001630.t007 Table 7 Per-protocol analysis of PfPR in children 0.5–14 y old and anaemia in children under 5 y old in surveys A, B, and C. Survey Arm PrevalencePercent [95% CI] (n) OR [95% CI], p-Value Pf PR a Survey A ITNb 26.7 [17.5–38.6] (954) 1.00 ITN+IRSc 12.3 [7.8–18.9] (1,142) 0.39 [0.18–0.81], p = 0.013 Survey B ITNb 35.5 [23.2–50.2] (782) 1.00 ITN+IRSc 10.2 [5.7–17.7] (892) 0.21 [0.09–0.49], p = 0.001 Survey C ITNb 29.4 [16.7–46.4] (707) 1.00 ITN+IRSc 10.1 [5.4–18.2] (770) 0.27 [0.10–0.73], p = 0.011 Anaemia d Survey A ITNb 5.9 [3.5–9.7] (390) 1.00 ITN+IRSc 3.8 [1.8–7.5] (453) 0.62 [0.25–1.55], p = 0.301 Survey B ITNb 5.4 [2.2–12.5] (295) 1.00 ITN+IRSc 1.9 [0.8–4.1] (374) 0.33 [0.10–1.12], p = 0.076 Survey C ITNb 4.0 [2.2–7.0] (303) 1.00 ITN+IRSc 2.3 [1.0–5.0] (305) 0.57 [0.21–1.55], p = 0.264 Muleba, Tanzania, 2012; analysis restricted to ITN users in both study arms. Survey A = 2 mo after first intervention spray. Survey B = 6 mo after first intervention spray and 2 mo after second intervention spray. Survey C = 10 mo after first intervention spray and 6 mo after second intervention spray. a PfPR from RDTs. b ITN used by the individual the night preceding the survey in the ITN only arm. c ITN used by the individual the night preceding the survey, and household with IRS in the ITN+IRS arm. One cluster that was allocated to be in the ITN only arm but received IRS in the second spray round was excluded from this analysis. d Prevalence of moderate/severe anaemia (haemoglobin <8 g/dl). Discussion This is the first randomised trial to our knowledge that provides evidence that IRS, when used in combination with ITNs, can give significant added protection against malarial infection compared to ITN use alone. There was also some evidence that anaemia prevalence was lower in communities with the combination. Exposure to infectious mosquito bites was about one-sixth in communities with the combined intervention compared to those in the ITN only arm. Two rounds of IRS with bendiocarb were conducted to overcome the short residual activity of the insecticide [27],[36] and to ensure that there was active ingredient on the walls of sprayed homes throughout the transmission season. IRS coverage in the ITN+IRS arm was high at approximately 90% in both spray rounds, which would have optimised its effectiveness [37]. On the other hand, whilst 85% of households owned at least one ITN, use of ITNs was modest, declining to 36% by the end of the study. The low usage of ITNs means that the addition of IRS may have simply protected those who were not using an ITN, thus compensating for low ITN usage rather than offering additional protection to net users. This interpretation is contradicted by the results of a per-protocol analysis, which excluded those not using ITNs, showing strong evidence that ITN users whose houses were sprayed were additionally protected by IRS. The estimated reduction in PfPR associated with the combination of interventions was greater in the per-protocol analysis than in the ITT analysis in each survey. Per-protocol analysis excludes non-compliers (for IRS and ITN) and therefore may have been influenced by confounders. It is likely that the observed overall effect of the intervention combination was a result of both IRS protecting those not using ITNs, and IRS additionally protecting ITN users. A potential negative impact of the combination of interventions is that having their house sprayed may encourage some residents to stop sleeping under an ITN. This was not observed in this study; ITN usage was similar between the villages with and without IRS in each post-intervention survey. ITN usage and ownership was slightly higher at baseline in the ITN+IRS arm compared to the ITN only arm, but the 95% confidence intervals for these estimates overlapped. This non-significant difference could have led to a slight overestimation of the effect size. PfPR was slightly lower at baseline in the ITN+IRS arm compared to the ITN only arm, but the effect size did not change after adjusting for PfPR at baseline. This suggests that baseline PfPR was not confounding the relationship between study arm and PfPR (the outcome). In the baseline year, malaria prevalence was higher in June–July after the long rainy season than in February–March after the short rains. In the intervention year, the prevalence similarly increased in June–July (survey B) in the ITN only arm, but prevalence in the ITN+IRS arm remained low, suggesting IRS and ITNs in combination prevented the seasonal increase in infections. The added protective effect of IRS peaked in the second survey, at the height of transmission after the long rains. This was probably the optimal time for the insecticide to reduce the abundance of the mosquito population (N. Protopopoff, personal communication) and thus to observe the impact of IRS on the prevalence of malarial infections. The limited residual activity of bendiocarb IRS has been shown to reduce its protective effectiveness 3–5 mo after spraying, which probably accounts for the loss of added benefit seen in the third survey, which was 6 mo after the last spray round at the beginning of the short rains [27],[36]. Implementing IRS with long-lasting insecticide formulations might be necessary to maintain the effectiveness of the combination throughout the year. Alternatively, the time between IRS rounds could be reduced, but this would considerably raise the cost of the combined intervention [38]. The secondary outcomes anaemia and EIR also pointed to added protection being provided by the combination of IRS and ITNs, but the evidence for these endpoints was weaker. The combination intervention was associated with higher haemoglobin levels in children under 5 y, particularly at the peak of the transmission season. The study had been powered to show a difference in the primary outcome (PfPR), and therefore may have been underpowered for these secondary outcomes. Nevertheless, the results for all outcomes are consistent. One of the limitations of this study is that clinical incidence of malaria could not be recorded in addition to infection prevalence because recording of confirmed malaria cases was unreliable because of stock-outs of RDTs at health facilities. Implementing both IRS and universal coverage of ITNs is obviously considerably more costly than ITNs alone. Estimating the cost-effectiveness of the combination compared to ITNs alone was beyond the scope of this particular research. Although IRS is known to be highly cost-effective [8],[39]–[43], the marginal cost per case averted through using IRS in combination with ITNs should ideally be assessed in future studies. This is particularly important in light of the funding gap that has been identified for meeting the demand for universal coverage of vector control for populations in malaria endemic regions [3]. Previous studies have investigated the combined use of multiple vector control methods versus one method alone, but the results have been inconsistent [4],[44]–[47]. The only published trial data are from a 28-cluster, four-arm CRT carried out in Benin that compared (1) targeted coverage of LLINs (pregnant women and children only), (2) universal coverage of LLINs, (3) targeted coverage of LLINs combined with bendiocarb IRS, and (4) universal coverage of LLINs combined with bendiocarb-treated wall linings [10]. The study found no difference in malaria incidence, geometric mean parasite density, or mosquito abundance between any of the study arms. The lack of any evidence of an added benefit of the combined interventions over the use of LLINs alone has to be viewed against the modest sample size, and hence potentially low power of this trial [12], and the lack of a comparator arm with universal coverage of ITNs. There are a number of differences between the Benin trial and the current study that may have contributed to the discordant results. In the Benin trial, the interval between IRS rounds was 8 mo, whereas it was only 4 mo in the current study, as IRS was timed according to the seasonal peaks in cases, and taking account of its short residual duration on walls. The first two cross-sectional surveys for the current trial were timed to coincide with the seasonal peaks in cases and were only 2 mo after each IRS round, whereas in Benin the cases were recorded at 6-wk intervals for 18 mo, so that the measured effect of the additional IRS may include a period when the insecticide, which is known to have a short residual duration, was no longer effective. In the Benin trial, LLINs were given only to target groups in the reference arm and in the study arm with IRS, whereas in the current trial ITNs were distributed to all age groups. Large CRTs have recently been conducted in the Gambia [48],[49] and in Sudan [50] comparing villages with IRS and LLINs to villages with only LLINs, but the results have not yet been published. Evidence of an added benefit from the combination intervention compared to IRS or ITNs alone has been shown in a number of observational studies [4],[45],[47],[51]–[55]. For example, children 2–14 y old consistently received added personal protection from using nets in addition to IRS on the island of Bioko, Equatorial Guinea (OR 0.71, 95% CI 0.59–0.86), and in Zambezia, Mozambique (OR 0.63, 95% CI 0.50–0.79) [4],[36]. In Pakistan, nets provided added protection against P. vivax and P. falciparum in refugee camps where IRS was conducted [56]. However, other studies observed no additional benefit from the combination compared to one intervention alone [46],[57],[58]. One interpretation of these divergent conclusions is that if the intervention present in both study arms is compromised or poorly implemented, the second method compensates for the deficiency of the first, providing apparent added protection that would otherwise not be seen. On the other hand, if the reference arm intervention is well implemented and efficacious in both study arms, there may be little or no scope for additional protection by a second intervention. ITN usage in the present trial was moderate, and hence the IRS protected many people who were not using a net in the ITN+IRS arm, whilst non-users in the ITN only arm remained unprotected. Any community or “mass effect” of ITNs on mosquito population size would have been limited because of the low community net usage. Therefore, the protective effect of ITNs in this study was possibly suboptimal. In Bioko, ITNs provided personal protection in the presence of IRS that was rendered only partially effective by moderate coverage (77%–79%) and use of an insecticide that did not outlast the long malaria season [36],[51]. Protopopoff et al. reported that in Burundi there was no additional reduction in infection prevalence in children from adding LLINs to IRS because high coverage (90%) of IRS had already reduced the sporozoite rate to a level where nets had no further impact [57]. In Sao Tome, where the IRS programme was poorly implemented, with low coverage and long intervals between spray rounds, there was an additional benefit from using ITNs and IRS compared to IRS alone [47]. However, on the neighbouring island of Principe, where IRS coverage was high (85%) and implemented on schedule, there was no added protection from ITNs in combination with IRS compared to IRS alone [46],[47]. Insecticide resistance may be another reason why differences have been seen for the effectiveness of the combination of IRS and ITNs, resulting in either an apparent “added” effect of the second effective intervention, if the first was ineffective due to insecticide resistance, or no added effect if the second intervention was ineffective due to insecticide resistance. In the study area of this trial, there was evidence for high levels of resistance to pyrethroids in An. gambiae s.s. The epidemiological impact of pyrethroid resistance on the effectiveness of ITNs is currently not known [59]. However, if the effectiveness of the ITNs was compromised [24] because of insecticide resistance, this would have enhanced our estimate of the additional benefit of non-pyrethroid IRS. If pyrethroid-treated nets were to be rendered partially ineffective in the presence of resistance, there would be a compelling case for combining ITNs with non-pyrethroid IRS. An experimental hut trial in an area of Tanzania where the main vector is An. arabiensis found that if ITNs were used, the addition of IRS using insecticides with high irritancy such as dichlorodiphenyltrichloroethane (DDT) or lambda-cyhalothrin did not increase mosquito mortality or repel mosquitoes from the house [11]. However, the addition of IRS using pirimiphos-methyl, an organophosphate that has high toxicity and low irritancy, did increase mosquito mortality. These findings underscore that the interaction between the two interventions is complex and that the added protective effect will be dependent on the feeding and resting behaviours of particular malaria vectors, on the type of IRS insecticide used, on the susceptibility of local vectors to each of the insecticides in the combination, and on ITN usage [5]–[7],[11]. As a result, added protection may not be observed in all situations. A systematic review of all the trial results estimating the effectiveness of the combination of ITNs and IRS should be undertaken once the results of the trials in Sudan and the Gambia are available. Nevertheless, this trial provides encouraging evidence for an additional benefit from applying IRS in combination with ITNs compared to ITNs alone. To our knowledge it is the first CRT to do so. The added protection from the supplementary use of IRS may in the case of bendiocarb be limited to only a few months, raising the question of whether residual insecticides of short duration are cost-effective when used in combination with ITNs. This study was conducted as an effectiveness study and not an efficacy study. The LLINs were distributed by a national UCC and therefore represented a real-life malaria control programme, including the challenges faced in achieving high coverage and usage of ITNs. In conclusion, national malaria control programmes should consider implementing IRS in combination with ITNs if local ITN strategies alone are insufficiently effective and cannot be improved. A key consideration would be the additional cost of providing the combined intervention. Given the inconsistent trial evidence and the unproven generalisability of the findings of all studies that have investigated this question, it would be prudent for malaria control programmes implementing the two methods simultaneously to monitor the impact and cost-effectiveness of the combination to verify whether the additional resources have the desired effect. Supporting Information Checklist S1 CONSORT checklist. (DOCX) Click here for additional data file. Table S1 Pf PR in children 0.5–14 y old in the ITN only and ITN+IRS arms (intention to treat) excluding the cluster that violated the protocol, in survey A, B, and C, Muleba District, Tanzania, 2012. (DOCX) Click here for additional data file.

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Corey LeClair:

ORCID: http://orcid.org/0000-0001-5441-9921

+255653634609 , corey_leclair@hotmail.com

Judith Cronery: judithrubalila@gmail.com

Enock Kessy: kessyenock@gmail.com

Elsa V. E. Tomás: erzeliatomas@yahoo.com.br

Yohannes Kulwa: yohannes.kulwa@gmail.com

Franklin W. Mosha: fwmosha@gmail.com

Mark Rowland: mark.rowland@lshtm.ac.uk

Natacha Protopopoff: nprotopopoff@gmail.com

J. Derek Charlwood: jdcharlwood@gmail.com

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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): 15 August 2017

Publication date PMC-release: 15 August 2017

Publication date Collection: 2017

Volume: 16

Electronic Location Identifier: 336

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[1 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Department of Disease Control, , London School of Hygiene and Tropical Medicine, ; London, UK

[2 ]ISNI 0000 0004 0648 0439, GRID grid.412898.e, , Kilimanjaro Christian Medical University College, ; Moshi, Tanzania

[3 ]MOZDAN, Morrumbene, Mozambique

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Corey LeClair http://orcid.org/0000-0001-5441-9921

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Publisher ID: 1972

DOI: 10.1186/s12936-017-1972-z

PMC ID: 5558705

PubMed ID: 28810872

SO-VID: f6aaeaef-ba60-4c40-85ce-84230c48565c

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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.

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Date received : 26 April 2017

Date accepted : 4 August 2017

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Funded by: DFID/MRC/Wellcome Trust

Award ID: MR/L004437/1

Award Recipient : Mark Rowland

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ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: light-trap,mosquito,sampling,long lasting insecticidal nets,resistance,piperonyl butoxide,surveillance,anopheles gambiae,anopheles

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ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: light-trap, mosquito, sampling, long lasting insecticidal nets, resistance, piperonyl butoxide, surveillance, anopheles gambiae, anopheles

‘Repel all biters’: an enhanced collection of endophilic Anopheles gambiae and Anopheles arabiensis in CDC light-traps, from the Kagera Region of Tanzania, in the presence of a combination mosquito net impregnated with piperonyl butoxide and permethrin

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The molecular basis of insecticide resistance in mosquitoes.

The Impact of Pyrethroid Resistance on the Efficacy of Insecticide-Treated Bed Nets against African Anopheline Mosquitoes: Systematic Review and Meta-Analysis

Indoor Residual Spraying in Combination with Insecticide-Treated Nets Compared to Insecticide-Treated Nets Alone for Protection against Malaria: A Cluster Randomised Trial in Tanzania

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