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      The evidence for improving housing to reduce malaria: a systematic review and meta-analysis

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          Abstract

          Background

          The global malaria burden has fallen since 2000, sometimes before large-scale vector control programmes were initiated. While long-lasting insecticide-treated nets and indoor residual spraying are highly effective interventions, this study tests the hypothesis that improved housing can reduce malaria by decreasing house entry by malaria mosquitoes.

          Methods

          A systematic review and meta-analysis was conducted to assess whether modern housing is associated with a lower risk of malaria than traditional housing, across all age groups and malaria-endemic settings. Six electronic databases were searched to identify intervention and observational studies published from 1 January, 1900 to 13 December, 2013, measuring the association between house design and malaria. The primary outcome measures were parasite prevalence and incidence of clinical malaria. Crude and adjusted effects were combined in fixed- and random-effects meta-analyses, with sub-group analyses for: overall house type (traditional versus modern housing); screening; main wall, roof and floor materials; eave type; ceilings and elevation.

          Results

          Of 15,526 studies screened, 90 were included in a qualitative synthesis and 53 reported epidemiological outcomes, included in a meta-analysis. Of these, 39 (74 %) showed trends towards a lower risk of epidemiological outcomes associated with improved house features. Of studies assessing the relationship between modern housing and malaria infection ( n = 11) and clinical malaria ( n = 5), all were observational, with very low to low quality evidence. Residents of modern houses had 47 % lower odds of malaria infection compared to traditional houses (adjusted odds ratio (OR) 0°53, 95 % confidence intervals (CI) 0°42–0°67, p < 0°001, five studies) and a 45–65 % lower odds of clinical malaria (case–control studies: adjusted OR 0°35, 95 % CI 0°20–0°62, p <0°001, one study; cohort studies: adjusted rate ratio 0°55, 95 % CI 0°36–0°84, p = 0°005, three studies). Evidence of a high risk of bias was found within studies.

          Conclusions

          Despite low quality evidence, the direction and consistency of effects indicate that housing is an important risk factor for malaria. Future research should evaluate the protective effect of specific house features and incremental housing improvements associated with socio-economic development.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12936-015-0724-1) contains supplementary material, which is available to authorized users.

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          Most cited references27

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          Effect of two different house screening interventions on exposure to malaria vectors and on anaemia in children in The Gambia: a randomised controlled trial.

          House screening should protect people against malaria. We assessed whether two types of house screening--full screening of windows, doors, and closing eaves, or installation of screened ceilings--could reduce house entry of malaria vectors and frequency of anaemia in children in an area of seasonal malaria transmission. During 2006 and 2007, 500 occupied houses in and near Farafenni town in The Gambia, an area with low use of insecticide-treated bednets, were randomly assigned to receive full screening, screened ceilings, or no screening (control). Randomisation was done by computer-generated list, in permuted blocks of five houses in the ratio 2:2:1. Screening was not treated with insecticide. Exposure to mosquitoes indoors was assessed by fortnightly light trap collections during the transmission season. Primary endpoints included the number of female Anopheles gambiae sensu lato mosquitoes collected per trap per night. Secondary endpoints included frequency of anaemia (haemoglobin concentration <80 g/L) and parasitaemia at the end of the transmission season in children (aged 6 months to 10 years) who were living in the study houses. Analysis was by modified intention to treat (ITT), including all randomised houses for which there were some outcome data and all children from those houses who were sampled for haemoglobin and parasitaemia. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN51184253. 462 houses were included in the modified ITT analysis (full screening, n=188; screened ceilings, n=178; control, n=96). The mean number of A gambiae caught in houses without screening was 37.5 per trap per night (95% CI 31.6-43.3), compared with 15.2 (12.9-17.4) in houses with full screening (ratio of means 0.41, 95% CI 0.31-0.54; p<0.0001) and 19.1 (16.1-22.1) in houses with screened ceilings (ratio 0.53, 0.40-0.70; p<0.0001). 755 children completed the study, of whom 731 had complete clinical and covariate data and were used in the analysis of clinical outcomes. 30 (19%) of 158 children from control houses had anaemia, compared with 38 (12%) of 309 from houses with full screening (adjusted odds ratio [OR] 0.53, 95% CI 0.29-0.97; p=0.04), and 31 (12%) of 264 from houses with screened ceilings (OR 0.51, 0.27-0.96; p=0.04). Frequency of parasitaemia did not differ between intervention and control groups. House screening substantially reduced the number of mosquitoes inside houses and could contribute to prevention of anaemia in children. Medical Research Council.
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            Multiple-Insecticide Resistance in Anopheles gambiae Mosquitoes, Southern Côte d’Ivoire

            Targeting the mosquito vector is the most effective way to prevent malaria transmission; worldwide, this method accounts for more than half of malaria control expenditures ( 1 , 2 ). During the past decade, increased use of insecticide-treated bed nets and indoor residual spraying have made a pivotal contribution toward decreasing the number of malaria cases ( 1 ). However, these gains are threatened by the rapid development and spread of insecticide resistance among major malaria vectors in Africa ( 3 ). To keep vector resistance from undermining control programs, insecticide-resistance management strategies must reduce the current overreliance on pyrethroids. These compounds are used widely for indoor residual spraying and uniquely for insecticide-treated bed nets. However, having a limited number of insecticides available for malaria vector control restricts options for effective insecticide resistance management. Only 4 classes of insecticide, which share 2 modes of action, are approved by the World Health Organization (WHO). A mutation at a single target site can result in mosquito resistance to DDT and pyrethroids or to organophosphates and carbamates. Furthermore, mosquitoes can express multiple insecticide-resistance mechanisms ( 4 ). For example, in several populations of the major malaria vector in Africa, Anopheles gambiae s.l. mosquitoes, mutations in the DDT/pyrethroid target site, known as knockdown resistance (kdr) alleles, have been found in conjunction with resistance alleles of the acetylcholinesterase gene (Ace-1R ), the target site of organophosphates and carbamates ( 5 ). To date, however, these cases of multiple-insecticide resistance have been restricted by the relatively low prevalence of organophosphate/carbamate resistance and the limited effect that kdr mutations alone have on pyrethroid-based interventions ( 6 ). We report a population of An. gambiae mosquitoes from a rice-growing area of southern Côte d’Ivoire that have high frequencies of kdr and Ace-1R alleles and unprecedentedly high levels of phenotypic resistance to all insecticide classes available for malaria control. The Study During May–September 2011, mosquito larvae were collected in irrigated rice fields surrounding Tiassalé, southern Côte d’Ivoire (5°52′47′′N; 4°49′48′′W) and reared to adults in insectaries on a diet of MikroMin (Tetra, Melle, Germany) fish food. A total of 1,571 adult female An. gambiae s.l. mosquitoes, 3–5 days of age, were exposed to 1 of 5 insecticides (0.1% bendiocarb, 1.0% fenitrothion, 0.75% permethrin, 0.05% deltamethrin, 4% DDT) or a control papers for 1 hour, according to standard WHO procedures ( 7 ). Mosquito deaths were recorded 24 hours later. DNA was extracted from individual mosquitoes according to the LIVAK method ( 8 ), and a subsample of 500 mosquitoes were all found to be the M molecular form of An. gambiae s.s. by using the SINE-PCR method ( 9 ). The target site mutation G119S in the Ace-1 gene (Ace-1R ) and L1014F and L1014S kdr mutations were screened by using restriction fragment length polymorphism ( 10 ) or TaqMan assays ( 11 ), respectively. According to WHO criteria, An. gambiae mosquitoes from Tiassalé are resistant to all insecticide classes, and resistance is extremely prevalent; more than two thirds of mosquitoes survived the diagnostic dose for 4 of the 5 insecticides tested (Table 1). To assess the level of resistance, we exposed the Tiassalé population and a susceptible laboratory population of An. gambiae (Kisumu) mosquitoes to the pyrethroid deltamethrin or the carbamate bendiocarb for a range of exposure times and assessed deaths 24 hours later (Technical Appendix). We found an unexpectedly strong resistance phenotype to the 2 insecticides (Figure 1, Figure 2). For deltamethrin, 4 hours of exposure were required to kill 50% (median lethal time, [LT50]); in comparison, the LT50 for the susceptible Kisumu strain was <2 minutes (resistance ratio = 138) (Technical Appendix). Similarly, the LT50 for bendiocarb was nearly 5 hours for the Tiassalé strain yet <12 minutes for the susceptible strain (resistance ratio = 24) (Technical Appendix). Table 1 Prevalence of insecticide resistance in Anopheles gambiae mosquitoes, M form, from Tiassalé, Côte d’Ivoire, 2011 Insecticide No. tested* No. dead % Dead (95% CI) Permethrin 288 69 24.0 (19.1–29.3) Deltamethrin 282 90 31.9 (26.5–37.7) DDT 306 25 8.2 (5.4–11.8) Fenitrothion 296 219 74.0 (68.6–78.9) Bendiocarb 299 37 12.4 (8.9–16.6) *Measured by death within 24 h, after 1h exposure to each insecticide. All mosquitoes were resistant according to World Health Organization classification (<80% dead) ( 7 ). Figure 1 Time-mortality curve for wild-caught Anopheles gambiae mosquitoes from Tiassalé, southern Côte d’Ivoire, exposed to deltamethrin (median time to death = 248 minutes). Logistic regression line was fitted to time-response data by using SigmaPlot version 11.0 (www.sigmaplot.com). R2 = 0.96. Error bars indicate SEM. Figure 2 Time-mortality curve for wild-caught Anopheles gambiae mosquitoes from Tiassalé, southern Côte d’Ivoire, exposed to bendiocarb (median time to death = 286 minutes). Logistic regression line was fitted to time-response data by using SigmaPlot version 11.0 (www.sigmaplot.com). R2 = 0.88. Error bars indicate SEM. To investigate the causes of this resistance, we screened a subset of mosquitoes for the target site mutations, kdr 1014F and 1014S. Only the 1014F kdr mutation was detected, and this resistance allele was found at high frequency (83%). There was a significant association between presence of the 1014F kdr allele and ability to survive exposure to DDT but not to either pyrethroid (Table 2). In contrast, the Ace-1R allele was strongly associated with survival after exposure to bendiocarb and fenitrothion (Table 2). Table 2 Association between genotype and mosquito survival after insecticide exposure* Insecticide No. tested Status No. No. per genotype Frequency† Odds ratio§ p value LL LF FF 1014F‡ DDT 73 Alive 48 2 7 39 88.5 4 0.02 Dead 25 2 10 13 72 Permethrin 88 Alive 44 1 12 31 84.1 1.23 0.82 Dead 44 3 12 29 79.5 Deltamethrin 89 Alive 45 1 12 32 84.4 0.82 0.86 Dead 44 2 9 33 85.2 GG GS SS 119S¶ Bendiocarb 86 Alive 49 0 49 0 50 100 0.40 × 10–12 Dead 37 25 12 0 16.2 Fenitrothion 100 Alive 50 0 50 0 50 1,176 0 Dead 50 48 2 0 2 *F and L represent mutant resistant alleles (phenylalanine) and wild-type alleles (leucine), respectively; S and G represent mutant resistant alleles (serine) and wild-type alleles (glycine), respectively. No resistant homozygotes GG were found among the 186 mosquitoes genotyped for Ace-1R by restriction fragment length polymorphism (a subset of 48 was further screened by using the TaqMan assay; congruence between the 2 methods was 100%).
†The frequencies were calculated for each insecticide and mosquito status (alive/dead) after exposure.
‡1014F represent the kdr frequencies.
§Genotypic odds ratios (ORs) are shown because these exceed allelic ORs for DDT (recessive model), bendiocarb, and fenitrothion (both overdominant models), and are similar for permethrin and deltamethrin. For bendiocarb and fenitrothion absence of GG genotypes in the “Alive” group means that ORs are infinity, therefore ORs are shown if one GG was present. F and L represent mutant resistant alleles (phenylalanine) and wild-type alleles (leucine), respectively; S and G represent mutant resistant alleles (serine) and wild-type alleles.
¶119S represents the Ace-1R frequencies. Conclusions Pyrethroid resistance in An. gambiae mosquitoes was first reported from Côte d’Ivoire in 1993 ( 12 ); carbamate resistance was detected in the 1990s ( 13 ). Nevertheless, ≈2 decades later, it is surprising and worrying to find complete resistance to all insecticides tested, particularly—for deltamethrin and bendiocarb—at such high levels. Resistance mechanisms seem to be varied. Ace-1R is strongly associated with organophosphate and carbamate resistance, and the absence of 119S homozygotes might be attributable to the high fitness cost of the Ace-1R allele in the absence of insecticide ( 14 ). Presence of the 1014F kdr allele alone does not confer the ability to survive diagnostic doses of pyrethroids; thus, alternative mechanisms must be responsible for the high-level pyrethroid resistance in this population. The selective pressures responsible for this intense multiple-insecticide resistance in Tiassalé mosquitoes are unclear. There is a high coverage of insecticide-treated bed nets, but this coverage does not differ from that in other parts of the continent, and indoor residual spraying has not been conducted in this region. Use of insecticides in agriculture has been linked to resistance in malaria vectors. This use is perhaps the most likely explanation in this district of intense commercial production of rice, cocoa, and coffee. Whatever the cause, the implications of this resistance scenario for malaria control are severe. With no new classes of insecticides for malaria control anticipated until 2020 at the earliest ( 15 ), program managers have few options available when confronted with multiple-insecticide resistance. Assessing the effect of pyrethroid resistance on the efficacy of insecticide-treated bed nets is complex because of the poorly understood associations between net integrity, insecticide content, net usage, and net efficacy. Nevertheless, resistance levels, such as those reported here, combined with continual selection pressure will inevitably lead to suboptimal mosquito control by use of insecticide-treated bed nets and indoor residual spraying. If unchecked, this resistance could spread rapidly and threaten the fragile gains that have been made in reducing malaria across Africa. Technical Appendix Time-mortality curve for Anopheles gambiae mosquitoes, Kisumu strain, exposed to deltamethrin and bendiocarb, and time-death data for adult female A. gambiae s.s. mosquitoes, Tiassalé strain, and standard susceptible colony Kisumu 24 hours after exposure to bendiocarb or deltamethrin.
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              Effect of expanded insecticide-treated bednet coverage on child survival in rural Kenya: a longitudinal study

              Summary Background The potential of insecticide-treated bednets (ITNs) to contribute to child survival has been well documented in randomised controlled trials. ITN coverage has increased rapidly in Kenya from 7% in 2004 to 67% in 2006. We aimed to assess the extent to which this investment has led to improvements in child survival. Methods A dynamic cohort of about 3500 children aged 1–59 months were enumerated three times at yearly intervals in 72 rural clusters located in four districts of Kenya. The effect of ITN use on mortality was assessed with Poisson regression to take account of potential effect-modifying and confounding covariates. Findings 100 children died over 2 years. Overall mortality rates were much the same in the first and second years of the study (14·5 per 1000 person-years in the first year and 15·4 per 1000 person-years in the second). After adjustment for age, time period, and a number of other possible confounding variables, ITN use was associated with a 44% reduction in mortality (mortality rate ratio 0·56, 95% CI 0·33–0·96; p=0·04). This level of protection corresponds to about seven deaths averted for every 1000 ITNs distributed. Interpretation A combined approach of social marketing followed by mass free distribution of ITNs translated into child survival effects that are comparable with those seen in previous randomised controlled trials.
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                Author and article information

                Contributors
                lucy.tusting@lshtm.ac.uk
                mippolito@jhu.edu
                barbara.willey@lshtm.ac.uk
                immo.kleinschmidt@lshtm.ac.uk
                gdorsey@medsfgh.ucsf.edu
                goslingr@globalhealth.ucsf.edu
                s.w.lindsay@durham.ac.uk
                Journal
                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                1475-2875
                9 June 2015
                9 June 2015
                2015
                : 14
                : 209
                Affiliations
                [ ]Department of Disease Control, London School of Hygiene & Tropical Medicine, London, WC1E 7HT UK
                [ ]Department of Medicine, Division of Infectious Diseases, Johns Hopkins University School of Medicine, 1830 Building Room 450B, 600 North Wolfe Street, Baltimore, MD 21287 USA
                [ ]Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
                [ ]Department of Medicine, University of California, San Francisco, CA 94143 USA
                [ ]Global Health Group, University of California, San Francisco, CA 94105 USA
                [ ]School of Biological and Biomedical Sciences, Durham University, Durham, DH1 3LE UK
                Article
                724
                10.1186/s12936-015-0724-1
                4460721
                26055986
                8ec7b991-dd89-4e05-ae08-5ac5ce12a939
                © Tusting et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 12 January 2015
                : 6 May 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Infectious disease & Microbiology
                malaria,plasmodium falciparum,vector,anopheles gambiae,house,eaves,socio-economic

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