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.
METHODOLOGY/PRINCIPAL FINDINGS: Genome-wide microarray-based transcription analysis was carried out to detect the genes associated with metabolic resistance in these populations. Comparisons of the susceptible New Orleans strain to three non-exposed multiple insecticide resistant field strains; Penang, Kuala Lumpur and Kota Bharu detected 2605, 1480 and 425 differentially expressed transcripts respectively (fold-change>2 and p-value ≤ 0.05). 204 genes were commonly over-expressed with monooxygenase P450 genes (CYP9J27, CYP6CB1, CYP9J26 and CYP9M4) consistently the most up-regulated detoxification genes in all populations, indicating that they possibly play an important role in the resistance. In addition, glutathione S-transferases, carboxylesterases and other gene families commonly associated with insecticide resistance were also over-expressed. Gene Ontology (GO) enrichment analysis indicated an over-representation of GO terms linked to resistance such as monooxygenases, carboxylesterases, glutathione S-transferases and heme-binding. Polymorphism analysis of CYP9J27 sequences revealed a high level of polymorphism (except in Joho Bharu), suggesting a limited directional selection on this gene. In silico analysis of CYP9J27 activity through modelling and docking simulations suggested that this gene is involved in the multiple resistance in Malaysian populations as it is predicted to metabolise pyrethroids, DDT and bendiocarb.
CONCLUSION/SIGNIFICANCE: The predominant over-expression of cytochrome P450s suggests that synergist-based (PBO) control tools could be utilised to improve control of this major dengue vector across Malaysia.