Ovitrap Surveillance of Aedes aegypti and Aedes albopictus in Dengue Endemic Areas in Keramat and Shah Alam, Selangor in 2016

A, Noor Afizah; Ak, Mohd Arif; Wa, Nazni; Hl, Lee

doi:10.31436/imjm.v17i3.243

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…A surveillance system effectivity using ovitraps as a dengue vector control method has been proved in several countries. In Malaysia, surveillance using ovitraps in identified dengue hotspot areas shows a positive correlation between the ovitrap index (OI) and dengue cases [ 56 , 57 , 58 ]. Vector surveillance using an ovitrap followed by early detection and environmental awareness has been proved to help improve mosquito-borne disease transmission in Taiwan [ 59 , 60 ].…”

Section: Discussionmentioning

confidence: 99%

Potential Way to Develop Dengue Virus Detection in Aedes Larvae as an Alternative for Dengue Active Surveillance: A Literature Review

Rachmawati,

Ekawardhani,

Fauziah

et al. 2024

TropicalMed

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The burden of dengue has emerged as a serious public health issue due to its impact on morbidity, mortality, and economic burden. Existing surveillance systems are inadequate to provide the necessary data for the prompt and efficient control of dengue. Passive surveillance of dengue cases may lead to underreporting and delayed mitigation responses. Improved dengue control program requires sensitive and proactive methods for early detection of dengue. We collected and reviewed existing research articles worldwide on detecting dengue virus in Aedes species larvae. Searches were conducted in PUBMED and Google Scholar, including all the studies published in English and Bahasa Indonesia. Twenty-nine studies were included in this review in terms of assay used, positivity rate, and dengue serotype detected. The presence of dengue virus in immature mosquitoes was mostly detected using reverse transcription PCR (RT-PCR) in pooled larvae. In one study, dengue virus was detected in larvae from laboratory-infected mosquitoes using enzyme-linked immunosorbent assay (ELISA). The positivity rate of dengue virus detection ranged from 0 to 50% in field-caught larvae. Although various methods can detect the dengue virus, further research encourages the use of low-cost and less laborious methods for active surveillance of dengue in larvae.

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Section: Discussionmentioning

confidence: 99%

Potential Way to Develop Dengue Virus Detection in Aedes Larvae as an Alternative for Dengue Active Surveillance: A Literature Review

Rachmawati,

Ekawardhani,

Fauziah

et al. 2024

TropicalMed

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“…The effectiveness of the ovitrap surveillance system in improving dengue vector management has been evaluated in Taiwan [ 14 , 19 , 27 ], Malaysia [ 23 , 29 , 30 , 35 – 37 ], Trinidad [ 38 ], and the Philippines [ 39 ]. Our results indicated that the monthly average PHI, OI, and ODI values were significantly correlated with the monthly total local dengue incidence.…”

Section: Discussionmentioning

confidence: 99%

Ovitrap surveillance of dengue vector mosquitoes in Bandung City, West Java Province, Indonesia

et al. 2021

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Larval surveillance is the central approach for monitoring dengue vector populations in Indonesia. However, traditional larval indices are ineffective for measuring mosquito population dynamics and predicting the dengue transmission risk. We conducted a 14-month ovitrap surveillance. Eggs and immature mosquitoes were collected on a weekly basis from an urban village of Bandung, namely Sekejati. Ovitrap-related indices, namely positive house index (PHI), ovitrap index (OI), and ovitrap density index (ODI), were generated and correlated with environmental variables, housing type (terraced or high-density housing), ovitrap placement location (indoor or outdoor; household or public place), and local dengue cases. Our results demonstrated that Aedes aegypti was significantly predominant compared with Aedes albopictus at each housing type and ovitrap placement location. Ovitrap placement locations and rainfall were the major factors contributing to variations in PHI, OI, and ODI, whereas the influences of housing type and temperature were subtle. Indoor site values were significantly positively correlated to outdoor sites’ values for both OI and ODI. OI and ODI values from households were best predicted with those from public places at 1- and 0-week lags, respectively. Weekly rainfall values at 4- and 3-week lags were the best predictors of OI and ODI for households and public places, respectively. Monthly mean PHI, OI, and ODI were significantly associated with local dengue cases. In conclusion, ovitrap may be an effective tool for monitoring the population dynamics of Aedes mosquitoes, predicting dengue outbreaks, and serving as an early indicator to initiate environmental clean-up. Ovitrap surveillance is easy for surveyors if they are tasked with a certain number of ovitraps at a designated area, unlike the existing larval surveillance methodology, which entails identifying potential breeding sites largely at the surveyors’ discretion. Ovitrap surveillance may reduce the influence of individual effort in larval surveillance that likely causes inconsistency in results.

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Multivariate spatio-temporal approach to identify vulnerable localities in dengue risk areas using Geographic Information System (GIS)

Withanage

Gunawardana

Viswakula

et al. 2021

Sci Rep

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Dengue is one of the most important vector-borne infection in Sri Lanka currently leading to vast economic and social burden. Neither a vaccine nor drug is still not being practiced, vector controlling is the best approach to control disease transmission in the country. Therefore, early warning systems are imminent requirement. The aim of the study was to develop Geographic Information System (GIS)-based multivariate analysis model to detect risk hotspots of dengue in the Gampaha District, Sri Lanka to control diseases transmission. A risk model and spatial Poisson point process model were developed using separate layers for patient incidence locations, positive breeding containers, roads, total buildings, public places, land use maps and elevation in four high risk areas in the district. Spatial correlations of each study layer with patient incidences was identified using Kernel density and Euclidean distance functions with minimum allowed distance parameter. Output files of risk model indicate that high risk localities are in close proximity to roads and coincide with vegetation coverage while the Poisson model highlighted the proximity of high intensity localities to public places and possibility of artificial reservoirs of dengue. The latter model further indicate that clustering of dengue cases in a radius of approximately 150 m in high risk areas indicating areas need intensive attention in future vector surveillances.

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Ovitrap Surveillance of Aedes aegypti and Aedes albopictus in Dengue Endemic Areas in Keramat and Shah Alam, Selangor in 2016

Cited by 3 publications

References 3 publications

Potential Way to Develop Dengue Virus Detection in Aedes Larvae as an Alternative for Dengue Active Surveillance: A Literature Review

Potential Way to Develop Dengue Virus Detection in Aedes Larvae as an Alternative for Dengue Active Surveillance: A Literature Review

Ovitrap surveillance of dengue vector mosquitoes in Bandung City, West Java Province, Indonesia

Multivariate spatio-temporal approach to identify vulnerable localities in dengue risk areas using Geographic Information System (GIS)

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