OBJECTIVES: To examine whether housing interventions were effective in reducing mosquito densities in homes and the impact on the incidence of mosquito-borne diseases.
METHODS: In this systematic review and meta-analysis, we searched 16 online databases, including NIH PubMed, CINAHL Complete, LILACS, Ovid MEDLINE, and Cochrane Central Register of Controlled Trials for randomized trials published from database inception to June 30, 2020. The primary outcome was the incidence of any mosquito-borne diseases. Secondary outcomes encompassed entomological indicators of the disease transmission. I2 values were used to explore heterogeneity between studies. A random-effects meta-analysis was used to assess the primary and secondary outcomes, with sub-group analyses for type of interventions on home environment, study settings (rural, urban, or mixed), and overall house type (traditional or modern housing).
RESULTS: The literature search yielded 4,869 articles. After screening, 18 studies were included in the qualitative review, of which nine were included in the meta-analysis. The studies enrolled 7,200 households in Africa and South America, reporting on malaria or dengue only. The type of home environmental interventions included modification to ceilings and ribbons to close eaves, screening doors and windows with nets, insecticide-treated wall linings in homes, nettings over gables and eaves openings, mosquito trapping systems, metal-roofed houses with mosquito screening, gable windows and closed eaves, and prototype houses using southeast Asian designs. Pooled analysis depicted a lower risk of mosquito-borne diseases in the housing intervention group (OR = 0.68; 95% CI = 0.48 to 0.95; P = 0.03). Subgroup analysis depicted housing intervention reduced the risk of malaria in all settings (OR = 0.63; 95% CI = 0.39 to 1.01; P = 0.05). In urban environment, housing intervention was found to decrease the risk of both malaria and dengue infections (OR = 0.52; 95% CI = 0.27 to 0.99; P = 0.05).Meta-analysis of pooled odds ratio showed a significant benefit of improved housing in reducing indoor vector densities of both Aedes and Anopheles (OR = 0.35; 95% CI = 0.23 to 0.54; P<0.001).
CONCLUSIONS: Housing intervention could reduce transmission of malaria and dengue among people living in the homes. Future research should evaluate the protective effect of specific house features and housing improvements associated with urban development.
Methods: Males were fed one of two diets in this study: experimental extract of Eurycoma longifolia (MSAs) and sugar only (MSOs). Differences in life span, courtship latency, copulation activity and mating success were examined between the two groups.
Results: No deaths occurred among MSA and MSO males. Life span of MSOs was similar to that of MSAs. The courtship latency of MSAs was shorter than that of MSOs (P<0.01). MSAs had greater copulation success than MSOs (P<0.001). In all female treatments, MSAs mated more than MSOs, but the differences in rate were significant only in the highest female density (P<0.05). In MSAs, mating success varied significantly with female density (P<0.01), with the 20-female group (P<0.01) having the lowest rate. Single MSA had better mating success at the two lowest female densities. In MSOs, there were no significant differences in mating success rate between the different female densities.
Interpretation & conclusions: Our results suggested that the herbal aphrodisiac, E. longifolia, stimulated the sexual activity of Ae. aegypti and may be useful for improving the mating competitiveness of sterile males, thus improving SIT programmes.
METHODS: Malaria disease incidence rates by active case detection in cohorts of children, and indicators of insecticide resistance in local vectors were monitored in each of approximately 300 separate locations (clusters) with high coverage of malaria vector control over multiple malaria seasons. Phenotypic and genotypic resistance was assessed annually. In two countries, Sudan and India, clusters were randomly assigned to receive universal coverage of ITNs only, or universal coverage of ITNs combined with high coverage of IRS. Association between malaria incidence and insecticide resistance, and protective effectiveness of vector control methods and insecticide resistance were estimated, respectively.
RESULTS: Cohorts have been set up in all five countries, and phenotypic resistance data have been collected in all clusters. In Sudan, Kenya, Cameroon and Benin data collection is due to be completed in 2015. In India data collection will be completed in 2016.
DISCUSSION: The paper discusses challenges faced in the design and execution of the study, the analysis plan, the strengths and weaknesses, and the possible alternatives to the chosen study design.
METHODS: Anopheles gambiae (s.l.) mosquitoes were identified to species level using PCR techniques. Standard WHO insecticide susceptibility bioassays were carried out to detect resistance to deltamethrin (0.05%), DDT (4%) and bendiocarb (0.1%). TaqMan assays were performed on random samples of deltamethrin-resistant phenotyped and pyrethrum spray collected individuals to determine Vgsc-1014 knockdown resistance mutations.
RESULTS: Anopheles arabiensis accounted for 99.9% of any anopheline species collected across all sites. Bioassay screening indicated that mosquitoes remained susceptible to bendiocarb but were resistance to deltamethrin and DDT in all areas. There were significant increases in deltamethrin resistance over the four years, with overall mean percent mortality to deltamethrin declining from 81.0% (95% CI: 77.6-84.3%) in 2011 to 47.7% (95% CI: 43.5-51.8%) in 2014. The rate of increase in phenotypic deltamethrin-resistance was significantly slower in the LLIN + IRS arm than in the LLIN-only arm (Odds ratio 1.34; 95% CI: 1.02-1.77). The frequency of Vgsc-1014F mutation varied spatiotemporally with highest frequencies in Galabat (range 0.375-0.616) and New Halfa (range 0.241-0.447). Deltamethrin phenotypic-resistance correlated with Vgsc-1014F frequency.
CONCLUSION: Combining LLIN and IRS, with different classes of insecticide, may delay pyrethroid resistance development, but the speed at which resistance develops may be area-specific. Continued monitoring is vital to ensure optimal management and control.