Relationship between local presence and density of Aedes aegypti eggs with dengue cases: a spatial analysis approach

Applicability of the Mexican ovitrap system for Aedes vector surveillance in Colombia

Ovitraps can detect Aedes vectors at an early stage and can serve as an alarm indicator for outbreak prediction. This study aimed to summarize the available literature about the ovitrap system and to determine its feasibility, required resources and costs when installing and maintaining this vector surveillance system in the municipality of Los Patios, Colombia. A scoping review to assess the role of ovitraps as a tool for Aedes vector surveillance was conducted. The subsequent fieldwork consisted of mapping the municipality, manufacturing, and installing 40 ovitraps in 10 blocks, revising them weekly for 4 weeks by two half-time employed vector control technicians, and carrying out a cost analysis. A total of 38 studies were included in this review showing that ovitraps had a better performance than other entomological surveillance methods and a positive correlation with other entomological and disease variables. From the field results over 4 weeks, a high proportion of positive ovitraps (80%, 90%, 75%, 97.5%) and positive blocks (100%) as well as a good acceptance by house owners (76.9%), were identified. Operational indicators such as average installation time of the ovitraps (10h15 m), weekly reading and reinstallation (on average 7h27 m) and the cost of the intervention (COL$1,142,304.47/US$297) were calculated. Literature shows that ovitraps are sensitive to detect the presence of Aedes mosquitoes, providing data efficiently and timely for outbreak prediction. The field testing showed it is an affordable and feasible method in the context of a Colombian municipality and similar endemic areas.

Spatial association of Aedes aegypti with dengue fever hotspots in an endemic region

Background and objective

Dengue is a vector-borne viral disease usually transmitted by Aedes mosquitoes. Around the world, the relationship between local vector density and frequency of dengue cases is being explored and needs further evidence. This study aimed to analyze the potential spatial relationships between the dengue vector (Aedes aegypti) and dengue cases in the megacity of Bangladesh during the 2019 dengue outbreak.

Methods

Vector density measures were used to estimate spatial associations with dengue case distribution. Location was determined for 364 dengue cases who were admitted to Dhaka Medical College Hospital over a period of 4 months. Data were collected using a semi-structured questionnaire, and prior consent was ensured before participation. The Moran global index, Getis-Ord Gi∗, ordinary least squares regression, geographically weighted regression and count data regression methods were used for spatial analysis.

Results

We found that dengue case distribution was not associated with immature Aedes aegypti mosquito (larvae) density across the city. The relationship between larval density measured by the Breteau Index (BI) and House Index (HI) with dengue cases was nonstationary and not statistically significant.

Conclusion

The location of dengue cases appears to be unrelated to vector distribution and vector density. These findings should prompt the search for other transmission risk factors.

Data-driven computational intelligence applied to dengue outbreak forecasting: a case study at the scale of the city of Natal, RN-Brazil

Dengue is recognized as a health problem that causes significant socioeconomic impacts throughout the world, affecting millions of people each year. A commonly used method for monitoring the dengue vector is to count the eggs that Aedes aegypti mosquitoes have laid in spatially distributed ovitraps. Given this approach, the present study uses a database collected from 397 ovitraps allocated across the city of Natal, RN—Brazil. The Egg Density Index for each neighborhood was computed weekly, over four complete years (from 2016 to 2019), and simultaneously analyzed with the dengue case incidence. Our results illustrate that the incidence of dengue is related to the socioeconomic level of the neighborhoods in the city of Natal. A deep learning algorithm was used to predict future dengue case incidence, either based on the previous weeks of dengue incidence or the number of eggs present in the ovitraps. The analysis reveals that ovitrap data allows earlier prediction (four to six weeks) compared to dengue incidence itself (one week). Therefore, the results validate that the quantification of Aedes aegypti eggs can be valuable for the early planning of public health interventions.

Aedes Albopictus (Diptera: Culicidae) Susceptibility Status to Agrochemical Insecticides Used in Durian Planting Systems in Southern Thailand

High rates of dengue morbidity occur in southern Thailand. The intensive application of insecticides in orchards could affect not only agricultural insect pests, but also nontarget mosquitoes or beneficial insects. In this study, the type and quantity of insecticides commonly used across durian plantations in southern Thailand were characterized, along with the population density of Aedes albopictus (Skuse) (Diptera: Culicidae). Our primary aim was to determine the susceptibility status of field-derived Ae. albopictus to typical application concentrations of four agrochemical insecticides; cypermethrin, chlorpyrifos, carbaryl, and imidacloprid. Mosquito eggs were collected from durian cultivation sites in five provinces in southern Thailand and used to generate adults for susceptibility tests. The cultivation sites were categorized into three groups based on insecticide application: intensive application of insecticides, low application of insecticides, and no application of insecticides. Twenty ovitraps were deployed for at least three consecutive days at each study site to collect mosquito eggs and to determine Ae. albopictus population density. WHO tube assays were used to determine the susceptibility of adult mosquitoes derived from field-collected eggs to selected insecticides. This represents the first report of the susceptibility status of Ae. albopictus from durian orchards in southern Thailand to agrochemical insecticides. Results showed complete susceptibility of these Ae. albopictus to chlorpyrifos, but reduced mortality following exposure to λ-cyhalothrin, carbaryl, and imidacloprid, which is suggestive of the development of resistance. These findings provide new insights into the status of insecticide susceptibility in Ae. albopictus populations, with important implications for mosquito and mosquito-borne disease control in Thailand.

Spatial analysis of dengue incidence and Aedes aegypti ovitrap surveillance in Belo Horizonte, Brazil

OBJECTIVES

Understanding the intra-urban spatial dynamics of Aedes aegypti and dengue transmission is important to effectively guide vector control. Ovitraps are a sensitive, cost-effective vector surveillance tool, yet few longitudinal studies have evaluated ovitrap indices and dengue occurrence. We aimed to assess the spatial patterns of dengue incidence and Ae. aegypti ovitrap positivity index (OPI) over time and to examine the spatial relationship between these two variables.

METHODS

This study used 12 years (2007-2018) of dengue case records and biweekly Ae. aegypti ovitrap data in Belo Horizonte, Brazil. We aggregated data by year and health centre catchment area (n = 152) and used both univariate and bivariate global Moran's I statistic and LISA to evaluate spatial clustering.

RESULTS

Annual dengue incidence ranged from 18 to 6262/100 000 residents and displayed spatial autocorrelation in 10/12 years, with shifting areas of high incidence. Annual OPI ranged from 35.7 to 47.6% and was clustered in all study years, but unlike dengue had consistent spatial patterns over time. Bivariate analysis found both positive (6/12 years) and negative (1/12 years) spatial associations between the two variables.

CONCLUSIONS

Low detected presence of Ae. aegypti was not a limiting factor in dengue transmission. However, stable spatial distribution of OPI suggests that certain areas may have persistent breeding sites. Future research should identify factors related to persistent Ae. aegypti hotspots to better guide vector management. Vector control efforts should be paired with additional data on population immunity, circulating serotypes and urban factors to better predict and control outbreaks.

The Mosquito, the Virus, the Climate: An Unforeseen Réunion in 2018

The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and led to the dengue outbreak in early 2018. A stage-structured model was run using observed temperature and rainfall data to simulate the life cycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias-corrected subseasonal forecasts to determine if the event could have been forecast up to 4 weeks in advance. With unseasonably warm temperatures remaining above 25°C, along with large tropical-cyclone-related rainfall events accumulating 10-15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although subseasonal forecasts of rainfall for the December-January period in Réunion are skillful up to 4 weeks in advance, the outbreak could only have been forecast 2 weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state-of-the-art subseasonal climate forecasts to produce actionable subseasonal dengue predictions. To the best of the authors' knowledge, this is the first time subseasonal forecasts have been used this way.