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      An improved mosquito electrocuting trap that safely reproduces epidemiologically relevant metrics of mosquito human-feeding behaviours as determined by human landing catch

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          Reliable quantification of mosquito host—seeking behaviours is required to determine the efficacy of vector control methods. For malaria, the gold standard approach remains the risky human landing catch (HLC). Here compare the performance of an improved prototype of the mosquito electrocuting grid trap (MET) as a safer alternative with HLC for measuring malaria vector behaviour in Dar es Salaam, Tanzania.


          Mosquito trapping was conducted at three sites within Dar es Salaam representing a range of urbanicity over a 7-month period (December 2012–July 2013, 168 sampling nights). At each site, sampling was conducted in a block of four houses, with two houses being allocated to HLC and the other to MET on each night of study. Sampling was conducted both indoors and outdoors (from 19:00 to 06:00 each night) at all houses, with trapping method (HLC and MET) being exchanged between pairs of houses at each site using a crossover design.


          The MET caught significantly more Anopheles gambiae sensu lato than the HLC, both indoors (RR [95 % confidence interval (CI)]) = 1.47 [1.23–1.76], P < 0.0001 and outdoors = 1.38 [1.14–1.67], P < 0.0001). The sensitivity of MET compared with HLC did not detectably change over the course of night for either An. gambiae s.l. (OR [CI]) = 1.01 [0.94–1.02], P = 0.27) or Culex spp. (OR [CI]) = 0.99 [0.99–1.0], P = 0.17) indoors and declined only slightly outdoors: An. gambiae s.l. (OR [CI]) = 0.92 [0.86–0.99], P = 0.04), and Culex spp. (OR [CI]) = 0.99 [0.98–0.99], P = 0.03). MET-based estimates of the proportions of mosquitoes caught indoors ( P i ) or during sleeping hours ( P fl ), as well as the proportion of human exposure to bites that would otherwise occurs indoors (π i ), were statistically indistinguishable from those based on HLC for An. gambiae s.l. (P = 0.43, 0.07 and 0.48, respectively) and Culex spp. (P = 0.76, 0.24 and 0.55, respectively).


          This improved MET prototype is highly sensitive tool that accurately quantifies epidemiologically-relevant metrics of mosquito biting densities, behaviours and human exposure distribution.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12936-016-1513-1) contains supplementary material, which is available to authorized users.

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          Most cited references 110

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          A general and simple method for obtainingR2from generalized linear mixed-effects models

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            The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015

            Since the year 2000, a concerted campaign against malaria has led to unprecedented levels of intervention coverage across sub-Saharan Africa. Understanding the effect of this control effort is vital to inform future control planning. However, the effect of malaria interventions across the varied epidemiological settings of Africa remains poorly understood owing to the absence of reliable surveillance data and the simplistic approaches underlying current disease estimates. Here we link a large database of malaria field surveys with detailed reconstructions of changing intervention coverage to directly evaluate trends from 2000 to 2015 and quantify the attributable effect of malaria disease control efforts. We found that Plasmodium falciparum infection prevalence in endemic Africa halved and the incidence of clinical disease fell by 40% between 2000 and 2015. We estimate that interventions have averted 663 (542–753 credible interval) million clinical cases since 2000. Insecticide-treated nets, the most widespread intervention, were by far the largest contributor (68% of cases averted). Although still below target levels, current malaria interventions have substantially reduced malaria disease incidence across the continent. Increasing access to these interventions, and maintaining their effectiveness in the face of insecticide and drug resistance, should form a cornerstone of post-2015 control strategies.
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              Identification of single specimens of the Anopheles gambiae complex by the polymerase chain reaction.

              A ribosomal DNA-polymerase chain reaction (PCR) method has been developed for species identification of individuals of the five most widespread members of the Anopheles gambiae complex, a group of morphologically indistinguishable sibling mosquito species that includes the major vectors of malaria in Africa. The method, which is based on species-specific nucleotide sequences in the ribosomal DNA intergenic spacers, may be used to identify both species and interspecies hybrids, regardless of life stage, using either extracted DNA or fragments of a specimen. Intact portions of a mosquito as small as an egg or the segment of one leg may be placed directly into the PCR mixture for amplification and analysis. The method uses a cocktail of five 20-base oligonucleotides to identify An. gambiae, An. arabiensis, An. quadriannnulatus, and either An. melas in western Africa or An. melas in eastern and southern Africa.

                Author and article information

                +255686997298 ,
                Malar J
                Malar. J
                Malaria Journal
                BioMed Central (London )
                13 September 2016
                13 September 2016
                : 15
                : 1
                [1 ]Environmental Health and Ecological Sciences Thematic Group, Coordination Office, Ifakara Health Institute, PO Box 78373, Kiko Avenue, Mikocheni, Dar es Salaam, United Republic of Tanzania
                [2 ]College of Medical, Veterinary and Life Sciences, Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, UK
                [3 ]Bioelectronics Unit, University of Glasgow, Graham Kerr Building, Glasgow, G12 8QQ UK
                [4 ]Vector Biology Department, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA UK
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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 ( applies to the data made available in this article, unless otherwise stated.

                Funded by: European Union Seventh Framework Programme
                Award ID: FP7/2007-2013
                Funded by: FundRef, Wellcome Trust;
                Award ID: 102368/Z/13/Z
                Award Recipient :
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                © The Author(s) 2016


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