Addressing challenges faced by insecticide spraying for the control of dengue fever in Bangkok, Thailand: a qualitative approach

Srichan, Peeradone; Niyom, Saranath Lawpoolsri; Pacheun, Oranut; Iamsirithawon, Sopon; Chatchen, Supawat; Jones, Caroline; White, Lisa J.; Pan-ngum, Wirichada

doi:10.1093/inthealth/ihy038

Cited by 8 publications

(10 citation statements)

References 22 publications

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“…We also considered a negative binomial (NB) base distribution with overdispersion parameter to capture the variability in estimation. This gives rise to (1)…”

Section: Dengue Nowcasting Corrected For Reporting Delaymentioning

confidence: 99%

“…Dengue is a mosquito-borne infectious disease that causes a huge economic and public health burden in Thailand and other tropical countries. Across Thailand, approximately 100,000 annual cases are notified to the Bureau of Epidemiology, Thai Ministry of Public Health [1]. Dengue infection poses a major problem for public health officials in the country with epidemics occurring every 2 to 3 years.…”

Section: Introductionmentioning

confidence: 99%

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Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

et al. 2020

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Background: The ability to produce timely and accurate estimation of dengue cases can significantly impact disease control programs. A key challenge for dengue control in Thailand is the systematic delay in reporting at different levels in the surveillance system. Efficient and reliable surveillance and notification systems are vital to monitor health outcome trends and early detection of disease outbreaks which vary in space and time.Methods: Predicting the trend in dengue cases in real-time is a challenging task in Thailand due to a combination of factors including reporting delays. We present decision support using a spatiotemporal nowcasting model which accounts for reporting delays in a Bayesian framework with sliding windows. A case study is presented to demonstrate the proposed nowcasting method using weekly dengue surveillance data in Bangkok at district level in 2010. Results:The overall real-time estimation accuracy was 70.69% with 59.05% and 79.59% accuracy during low and high seasons averaged across all weeks and districts. The results suggest the model was able to give a reasonable estimate of the true numbers of cases in the presence of delayed reports in the surveillance system. With sliding windows, models could also produce similar accuracy to estimation with the whole data. Conclusions:A persistent challenge for the statistical and epidemiological communities is to transform data into evidence-based knowledge that facilitates policy making about health improvements and disease control at the individual and population levels. Improving real-time estimation of infectious disease incidence is an important technical development. The effort in this work provides a template for nowcasting in practice to inform decision making for dengue control.

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“…We also considered a negative binomial (NB) base distribution with overdispersion parameter to capture the variability in estimation. This gives rise to (1)…”

Section: Dengue Nowcasting Corrected For Reporting Delaymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

et al. 2020

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“…However, the group also recognizes that many control programmes do not have the resources to apply insecticides in an optimal manner leading to poor coverage, sub-standard operational practice (i.e. fogging outdoors in the heat of the day), and delayed responses [53]. There is no empirical evidence to link resistance-associated control failures to increased dengue, Zika or chikungunya transmission.…”

Section: Reports From Round Tablesmentioning

confidence: 99%

Second WIN International Conference on “Integrated approaches and innovative tools for combating insecticide resistance in vectors of arboviruses”, October 2018, Singapore

et al. 2019

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The past 40 years have seen a dramatic emergence of epidemic arboviral diseases transmitted primarily by mosquitoes. The frequency and magnitude of the epidemics, especially those transmitted by urban Aedes species, have progressively increased over time, accelerating in the past 10 years. To reduce the burden and threat of vector-borne diseases, the World Health Organization (WHO) has recently adopted the Global Vector Control Response (GVCR) in order to support countries in implementing effective sustainable vector control. The evidence-base to support vector control is however limited for arboviral diseases which make prioritization difficult. Knowledge gaps in the distribution, mechanisms and impact of insecticide resistance on vector control impedes the implementation of locally tailored Aedes control measures. This report summarizes the main outputs of the second international conference of the Worldwide Insecticide resistance Network (WIN) on “ Integrated approaches and innovative tools for combating insecticide resistance in arbovirus vectors ” held in Singapore, 1–3 October 2018. The aims of the conference were to review progress and achievements made in insecticide resistance surveillance worldwide, and to discuss the potential of integrated vector management and innovative technologies for efficiently controlling arboviral diseases. The conference brought together 150 participants from 26 countries.

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“…Bangkok, the capital city of Thailand, bears a considerable burden of reported cases of dengue and has year-round endemic transmission [ 26 ]. In Bangkok, dengue-confirmed cases from the hospitals are reported to the Bangkok Metropolitan Administration (BMA) and Ministry of Public Health (MoPH) via an online operating system “Epi-net” [ 27 ]. Based on this notification, intervention is activated, which is largely based on fumigation of insecticide in the patient’s household and the neighboring area within a radius of 100 m [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand

Lefebvre

Karki

Misslin

et al. 2022

IJERPH

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Dengue is the most widespread mosquito-borne viral disease of man and spreading at an alarming rate. Socio-economic inequality has long been thought to contribute to providing an environment for viral propagation. However, identifying socio-economic (SE) risk factors is confounded by intra-urban daily human mobility, with virus being ferried across cities. This study aimed to identify SE variables associated with dengue at a subdistrict level in Bangkok, analyse how they explain observed dengue hotspots and assess the impact of mobility networks on such associations. Using meteorological, dengue case, national statistics, and transport databases from the Bangkok authorities, we applied statistical association and spatial analyses to identify SE variables associated with dengue and spatial hotspots and the extent to which incorporating transport data impacts the observed associations. We identified three SE risk factors at the subdistrict level: lack of education, % of houses being cement/brick, and number of houses as being associated with increased risk of dengue. Spatial hotspots of dengue were found to occur consistently in the centre of the city, but which did not entirely have the socio-economic risk factor characteristics. Incorporation of the intra-urban transport network, however, much improved the overall statistical association of the socio-economic variables with dengue incidence and reconciled the incongruous difference between the spatial hotspots and the SE risk factors. Our study suggests that incorporating transport networks enables a more real-world analysis within urban areas and should enable improvements in the identification of risk factors.

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Addressing challenges faced by insecticide spraying for the control of dengue fever in Bangkok, Thailand: a qualitative approach

Cited by 8 publications

References 22 publications

Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

Second WIN International Conference on “Integrated approaches and innovative tools for combating insecticide resistance in vectors of arboviruses”, October 2018, Singapore

Importance of Public Transport Networks for Reconciling the Spatial Distribution of Dengue and the Association of Socio-Economic Factors with Dengue Risk in Bangkok, Thailand

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