AIMS: This systematic review aims to determine the factors associated with mosquito control among construction workers.
METHODS: Primarily, articles related to factors associated with mosquito control among construction workers were collected from two different online databases (ScienceDirect and EBSCOhost). Two independent reviewers were assigned to screen the titles and abstracts of the collected data, stored in Microsoft Excel, against the inclusion and exclusion criteria. Afterwards, the quality of the included articles was critically assessed using the Mixed Method Appraisal Tool (MMAT). Of the 171 articles identified, 4 were included in the final review.
RESULTS: Based on the thorough evaluation, mosquito-related knowledge, practical mosquito prevention measures, and Larval Source Management (LSM) were identified as vital factors associated with mosquito control among construction workers. The significant association between mosquito-related knowledge and control practices indicates higher knowledge linked to effective practices, particularly among female workers and those who were recently infected with malaria. Concurrently, there were notable challenges regarding sustainable preventive measures and larval control methods in construction settings.
CONCLUSION: Implementing effective mosquito control, including knowledge and practice on mosquito control together with vector control, is highly required to suppress the expanding mosquito population. It is recommended that employers provide continuous mosquito control education and training to their employees and reward them with incentives, while employees should comply with the guidelines set by their employers to ensure successful mosquito control and reduce the spread of mosquito-borne diseases in the construction industry.
Methods: We carried out fogging with Pyrethroid insecticide (Detral 2.5 EC) at 10 different sites in a forest situated in the state of Selangor, Peninsular Malaysia. Across the sites, we counted the numbers of knocked-down invertebrates and identified them based on morphology to different taxa. We constructed Bayesian hierarchical Poisson regression models to investigate the effects of fogging on: (1) a target invertebrate taxon (Diptera) 3-h post-fogging; (2) selected non-target invertebrate taxa 3-h post-fogging; and (3) an invertebrate pollinator taxon (Lepidoptera) 24-h post-fogging.
Results: A total of 1,874 invertebrates from 19 invertebrate orders were knocked down by the fogging treatment across the 10 sites. Furthermore, 72.7% of the invertebrates counted 3-h post-fogging was considered dead. Our regression models showed that given the data and prior information, the probability that fogging had a negative effect on invertebrate taxa 3-h post-fogging was 100%, with reductions to 11% of the pre-fogging count of live individuals for the target invertebrate taxon (Diptera), and between 5% and 58% of the pre-fogging count of live individuals for non-target invertebrate taxa. For the invertebrate pollinator, the probability that fogging had a negative effect 24-h post-fogging was also 100%, with reductions to 53% of the pre-fogging count of live individuals.
Discussion: Our Bayesian models unequivocally demonstrate that fogging has detrimental effects on one pollinator order and non-target invertebrate orders, especially taxa that have comparatively lower levels of chitinisation. While fogging is effective in killing the target order (Diptera), no mosquitos were found dead in our experiment. In order to maintain urban biodiversity, we recommend that health authorities and the private sector move away from persistent insecticide fogging and to explore alternative measures to control adult mosquito populations.
Methods: In this present study, two protein extractions methods were performed to analyze female Ae. aegyti proteome, via TCA acetone precipitation extraction method and a commercial protein extraction reagent CytoBusterTM. Then, protein identification was performed by LC-ESI-MS/MS and followed by functional protein annotation analysis.
Results: The CytoBusterTM reagent gave the highest protein yield with a mean of 475.90 µg compared to TCA acetone precipitation extraction showed 283.15 µg mean of protein. LC-ESI-MS/MS identified 1,290 and 890 proteins from the CytoBusterTM reagent and TCA acetone precipitation, respectively. When comparing the protein class categories in both methods, there were three additional categories for proteins identified using CytoBusterTM reagent. The proteins were related to scaffold/adaptor protein (PC00226), protein binding activity modulator (PC00095) and intercellular signal molecule (PC00207). In conclusion, the CytoBusterTM protein extraction reagent showed a better performance for the extraction of proteins in term of the protein yield, proteome coverage and extraction speed.