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

Abstract

Objectives To analyze the relationship between the occurrence of dengue and ovitrap positivity and dengue egg density in two Amazonas municipalities (Brazil) in 2016. Methods We performed a case‐control study using secondary data from the dengue fever surveillance system. Ovitraps distributed regularly in the urban area of two cities were used to monitor the presence of the vector. The relationship between egg positivity, egg density and the location of dengue cases was evaluated using two approaches as follows: (i) based on the result of the nearest neighbour ovitrap and (ii) based on the results of the set of ovitraps within the influence area of 300 m from the location of each case and control. Results During the study period, 229 confirmed cases of dengue fever were reported in Tabatinga and 89 cases in Itacoatiara. In this study, we found that the positivity of ovitraps was related to the occurrence of dengue in Tabatinga and Itacoatiara. An association between egg density of Ae. aegypti and dengue occurrence was also observed in Itacoatiara. The temporal lags for ovitrap positivity measurements were predominantly 15 or 30 days. A dengue association for egg density for a 15‐day time lag was detected for one of the case‐control approaches. Conclusions The location of dengue cases is related to ovitrap egg positivity, while a less evident possible association may exist for egg density. This indicates that these traps could be used to improve vector control actions.

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

“…Additionally, while the effects of environmental factors, such as rainfall and temperature, on dengue have been well established, the relationship between vector proliferation and dengue incidence is not well understood (Bowman et al, 2014) and the limited number of studies to date have produced somewhat contradictory results (de Albuquerque et al, 2018; de Melo et al, 2012; Degener et al, 2014; Liyanage et al, 2019; Pessanha et al, 2014). One potential reason suggested is that most dengue risk factors are likely to exhibit spatial dependence, and this spatial dependence should be considered in further research (Scott & Morisson, 2003; Vargas et al, 2015).…”

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

“…We used the smallest level of aggregation that included observations for every spatial unit, as there were not ovitraps in every census tract. Future research could use point data for analyses [41] and should continue to consider the significance of different spatial scales in vector surveillance.…”

“…Analyses using the database of dengue cases were constrained by certain limitations, including the use of a passive surveillance system which could result in underreporting; a case definition which includes laboratory‐confirmed and clinically diagnosed cases, which could result in misdiagnosis; and the use of a patient’s home address as the presumed site of infection. Despite these common limitations [16, 17, 41], we believe the data reflect general disease patterns due to the long period of observation and the well‐established dengue surveillance programme in this city [8]. In addition, ovitraps do not account for alternative available breeding sites and so we did not examine abundance indices in our spatial analysis.…”

“…Similar definitions have been used to study dengue incidence in Belo Horizonte [8, 40]. The eight‐week difference was chosen as a conservative estimate of the temporal lag between egg indices and dengue incidence [41, 42]. This definition aligned the beginning of the study year with the annual nadir, or lowest value, of each variable and allowed us to capture the entire seasonal curve in a single year.…”

Knowledge discovery and dengue forecasting applied in a four-year dataset collected at Natal/RN – Brazil

“…Counting the eggs deposited in spatially distributed ovitraps can serve as a proxy for levels of Aedes infestation, and allows determining geographic distribution, density and seasonality of the vector [7]. Although ovitrap are not a direct measurement for adult mosquito density, this method represent a good estimator [6] [8].…”