Stegomyia Indices and Risk of Dengue Transmission: A Lack of Correlation

Spatial model of Dengue Hemorrhagic Fever (DHF) risk: scoping review

BACKGROUND

Creating a spatial model of dengue fever risk is challenging duet to many interrelated factors that could affect dengue. Therefore, it is crucial to understand how these critical factors interact and to create reliable predictive models that can be used to mitigate and control the spread of dengue.

METHODS

This scoping review aims to provide a comprehensive overview of the important predictors, and spatial modelling tools capable of producing Dengue Haemorrhagic Fever (DHF) risk maps. We conducted a methodical exploration utilizing diverse sources, i.e., PubMed, Scopus, Science Direct, and Google Scholar. The following data were extracted from articles published between January 2011 to August 2022: country, region, administrative level, type of scale, spatial model, dengue data use, and categories of predictors. Applying the eligibility criteria, 45 out of 1,349 articles were selected.

RESULTS

A variety of models and techniques were used to identify DHF risk areas with an arrangement of various multiple-criteria decision-making, statistical, and machine learning technique. We found that there was no pattern of predictor use associated with particular approaches. Instead, a wide range of predictors was used to create the DHF risk maps. These predictors may include climatology factors (e.g., temperature, rainfall, humidity), epidemiological factors (population, demographics, socio-economic, previous DHF cases), environmental factors (land-use, elevation), and relevant factors.

CONCLUSIONS

DHF risk spatial models are useful tools for detecting high-risk locations and driving proactive public health initiatives. Relying on geographical and environmental elements, these models ignored the impact of human behaviour and social dynamics. To improve the prediction accuracy, there is a need for a more comprehensive approach to understand DHF transmission dynamics.

Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data

Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. In this study, we use vector indices and meteorological data as predictors to develop the ML models. We trained and validated seven ML algorithms, including an ensemble ML method, and compared their performance using the receiver operating characteristic (ROC) with the area under the curve (AUC), accuracy and F1 score. Our results show that an ensemble ML such as XG Boost, AdaBoost and Random Forest perform better than the logistics regression, Naïve Bayens, decision tree, and support vector machine (SVM), with XGBoost having the highest AUC, accuracy and F1 score. Analysis of the importance of the variables showed that the container index was the least important. By removing this variable, the ML models improved their performance by at least 6% in AUC and F1 score. Our result provides a framework for future studies on the use of predictive models in the development of an early warning system.

How habitat factors affect an Aedes mosquitoes driven outbreak at temperate latitudes: The case of the Chikungunya virus in Italy

BACKGROUND

Outbreaks of Aedes-borne diseases in temperate areas are not frequent, and limited in number of cases. We investigate the associations between habitat factors and temperature on individuals' risk of chikungunya (CHIKV) in a non-endemic area by spatially analyzing the data from the 2017 Italian outbreak.

METHODOLOGY/PRINCIPAL FINDINGS

We adopted a case-control study design to analyze the association between land-cover variables, temperature, and human population density with CHIKV cases. The observational unit was the area, at different scales, surrounding the residence of each CHIKV notified case. The statistical analysis was conducted considering the whole dataset and separately for the resort town of Anzio and the metropolitan city of Rome, which were the two main foci of the outbreak. In Rome, a higher probability for the occurrence of CHIKV cases is associated with lower temperature (OR = 0.72; 95% CI: 0.61-0.85) and with cells with higher vegetation coverage and human population density (OR = 1.03; 95% CI: 1.00-1.05). In Anzio, CHIKV case occurrence was positively associated with human population density (OR = 1.03; 95% CI: 1.00-1.06) but not with habitat factors or temperature.

CONCLUSION/SIGNIFICANCE

Using temperature, human population density and vegetation coverage data as drives for CHIKV transmission, our estimates could be instrumental in assessing spatial heterogeneity in the risk of experiencing arboviral diseases in non-endemic temperate areas.

The Potential of Surveillance Data for Dengue Risk Mapping: An Evaluation of Different Approaches in Cuba

To better guide dengue prevention and control efforts, the use of routinely collected data to develop risk maps is proposed. For this purpose, dengue experts identified indicators representative of entomological, epidemiological and demographic risks, hereafter called components, by using surveillance data aggregated at the level of Consejos Populares (CPs) in two municipalities of Cuba (Santiago de Cuba and Cienfuegos) in the period of 2010-2015. Two vulnerability models (one with equally weighted components and one with data-derived weights using Principal Component Analysis), and three incidence-based risk models were built to construct risk maps. The correlation between the two vulnerability models was high (tau > 0.89). The single-component and multicomponent incidence-based models were also highly correlated (tau ≥ 0.9). However, the agreement between the vulnerability- and the incidence-based risk maps was below 0.6 in the setting with a prolonged history of dengue transmission. This may suggest that an incidence-based approach does not fully reflect the complexity of vulnerability for future transmission. The small difference between single- and multicomponent incidence maps indicates that in a setting with a narrow availability of data, simpler models can be used. Nevertheless, the generalized linear mixed multicomponent model provides information of covariate-adjusted and spatially smoothed relative risks of disease transmission, which can be important for the prospective evaluation of an intervention strategy. In conclusion, caution is needed when interpreting risk maps, as the results vary depending on the importance given to the components involved in disease transmission. The multicomponent vulnerability mapping needs to be prospectively validated based on an intervention trial targeting high-risk areas.

Urbanization of Aedes mosquito populations and evolution of arboviral disease risk in Africa

The arboviral diseases dengue, chikungunya, and yellow fever are re-merging and gaining a foothold in Africa, with a significant threat of large outbreaks in urban areas. Although their emergence is intimately linked to the primary vector Aedes aegypti, which thrives in urban environments, the risk of these diseases remains substantially heterogeneous in different geographic areas. Range expansion of invasive mosquito species Aedes albopictus, and colonization of urban habitats by sylvatic and peridomestic Aedes vectors, are likely to alter the diseases' epidemiology. We discuss how a network of different vector species and perhaps vector subpopulations could interact with associated serotypes/genotypes/lineages of the causative viruses of these diseases potentially impacting transmission risk in urban landscapes with implications for disease surveillance and control.

Aedes Mosquito Surveillance Using Ovitraps, Sweep Nets, and Biogent Traps in the City of Yaoundé, Cameroon

Arbovirus diseases represent a significant public health problem in Cameroon and vector surveillance is a key component of prevention strategies. However, there is still not enough evidence of the efficacy of different sampling methods used to monitor Aedes mosquito population dynamic in different epidemiological settings. The present study provides data on the evaluation of ovitraps and different adult sampling methods in the city of Yaoundé and its close vicinity. Entomological surveys were carried out from February 2020 to March 2021 in two urban (Obili, Mvan), two peri-urban (Simbock, Ahala), and two rural (Lendom, Elig-essomballa) sites in the city of Yaoundé. The efficacy of three sampling methods, namely ovitraps, Biogent Sentinel trap, and sweep nets, was evaluated. Different ovitrap indices were used to assess the infestation levels across study sites; a general linear model was used to determine if there are statistical differences between positive ovitraps across ecological zones. A total of 16,264 Aedes mosquitoes were collected during entomological surveys. Ovitraps provided the highest mosquito abundance (15,323; 91.14%) and the highest species diversity. Of the five Aedes species collected, Aedes albopictus (59.74%) was the most commonly recorded in both urban and rural settings. Different Aedes species were collected in the same ovitrap. The ovitrap positivity index was high in all sites and varied from 58.3% in Obili in the urban area to 86.08% in Lendom in the rural area. The egg density index varied from 6.42 in Mvan (urban site) to 13.70 in Lendom (rural area). Adult sampling methods recorded mostly Aedes albopictus. The present study supports high infestation of Aedes species in the city of Yaoundé. Ovitraps were highly efficient in detecting Aedes distribution across study sites. The situation calls for regular surveillance and control of Aedes population to prevent sudden occurrence of outbreaks.

Increased Attraction and Stability of Beauveria bassiana-Formulated Microgranules for Aedes aegypti Biocontrol

Aedes aegypti (Linn.) incidence has increased in recent years, causing human viral diseases such as dengue, which are often fatal. Beauveria bassiana (Bals., Vuillemin) efficacy for Ae. aegypti biological control has been evidenced but it relies on host susceptibility and strain virulence. We hypothesized that B. bassiana conidia microgranular formulations (MGF) with the additives acetone, lactic acid, and sugar increase Ae. aegypti adult exposure, thus improving their biocontrol effectiveness. Beauveria bassiana strain four (BBPTG4) conidia stability was assessed after 0 d, 5 d, and 30 d storage at 25 °C ± 2 °C with additives or in MGF after 91 d of storage at 25 °C ± 2 °C or 4 °C ± 1 °C, whereas mortality was evaluated after adult exposure to MGF + conidia, using home-made traps. Additives did not show toxicity to conidia. In addition, we observed that sugar in MGF increased Ae. aegypti adults’ attraction and their viability resulted in a 3-fold reduction after 5 d and 1- to 4-fold decrease after 30 d of storage, and formulations were less attractive (p < 0.05). Conidia stability was higher on MGF regardless of the storage temperature, losing up to 2.5-fold viability after 91 d. In conclusion, BBPTG4 infected and killed Ae. aegypti, whereas MGF attracting adults resulted in 42.2% mortality, increasing fungus auto dissemination potential among infected surviving adults. It is necessary to further evaluate MGF against Ae. aegypti in the field.

Climate variability and Aedes vector indices in the southern Philippines: An empirical analysis

Background

Vector surveillance is an essential public health tool to aid in the prediction and prevention of mosquito borne diseases. This study compared spatial and temporal trends of vector surveillance indices for Aedes vectors in the southern Philippines, and assessed potential links between vector indices and climate factors.

Methods

We analysed routinely collected larval and pupal surveillance data from residential areas of 14 cities and 51 municipalities during 2013–2018 (House, Container, Breteau and Pupal Indices), and used linear regression to explore potential relationships between vector indices and climate variables (minimum temperature, maximum temperature and precipitation).

Results

We found substantial spatial and temporal variation in monthly Aedes vector indices between cities during the study period, and no seasonal trend apparent. The House (HI), Container (CI) and Breteau (BI) Indices remained at comparable levels across most surveys (mean HI = 15, mean CI = 16, mean BI = 24), while the Pupal Productivity Index (PPI) was relatively lower in most months (usually below 5) except for two main peak periods (mean = 49 overall). A small proportion of locations recorded high values across all entomological indices in multiple surveys. Each of the vector indices were significantly correlated with one or more climate variables when matched to data from the same month or the previous 1 or 2 months, although the effect sizes were small. Significant associations were identified between minimum temperature and HI, CI and BI in the same month (R2 = 0.038, p = 0.007; R2 = 0.029, p = 0.018; and R2 = 0.034, p = 0.011, respectively), maximum temperature and PPI with a 2-month lag (R2 = 0.031, p = 0.032), and precipitation and HI in the same month (R2 = 0.023, p = 0.04).

Conclusions

Our findings indicated that larval and pupal surveillance indices were highly variable, were regularly above the threshold for triggering vector control responses, and that vector indices based on household surveys were weakly yet significantly correlated with city-level climate variables. We suggest that more detailed spatial and temporal analyses of entomological, climate, socio-environmental and Aedes-borne disease incidence data are necessary to ascertain the most effective use of entomological indices in guiding vector control responses, and reduction of human disease risk.

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

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.

The dengue virus, transmitted by Aedes vectors, has been continuously spreading in tropical and subtropical countries, causing illness and fatality. Given the lack of a cost-effective dengue vaccine, the vector control approach for reducing the Aedes population remains the key method for mitigating dengue transmission. For a successful vector control program, an effective vector surveillance system is crucial for precisely predicting the spatial and temporal risk of a dengue outbreak. The ovitrap system improves data collection efficiency, aiding long-term dengue vector monitoring activities. This study is one of the few long-term dengue vector surveillance programs in Indonesia and provides compelling evidence of the need to improve the existing conventional larval surveillance system. The results demonstrated that two dengue vector mosquitoes, A. aegypti and A. albopictus, were present in the study area, and A. aegypti was more prevalent than A. albopictus. We observed an interactive relationship between ovitrap placement and rainfall in the dynamics of ovitrap-related indices; understanding this relationship allows for timely initiation of vector control and intervention strategies. We conclude that the ovitrap surveillance system is a sensitive tool for monitoring the population dynamics of Aedes vectors, predicting dengue outbreaks, and potentially improving community-based conventional larval surveillance.

Field Effectiveness of Drones to Identify Potential Aedes aegypti Breeding Sites in Household Environments from Tapachula, a Dengue-Endemic City in Southern Mexico

Aedes aegypti control programs require more sensitive tools in order to survey domestic and peridomestic larval habitats for dengue and other arbovirus prevention areas. As a consequence of the COVID-19 pandemic, field technicians have faced a new occupational hazard during their work activities in dengue surveillance and control. Safer strategies to monitor larval populations, in addition to minimum householder contact, are undoubtedly urgently needed. Drones can be part of the solution in urban and rural areas that are dengue-endemic. Throughout this study, the proportion of larvae breeding sites found in the roofs and backyards of houses were assessed using drone images. Concurrently, the traditional ground field technician's surveillance was utilized to sample the same house groups. The results were analyzed in order to compare the effectiveness of both field surveillance approaches. Aerial images of 216 houses from El Vergel village in Tapachula, Chiapas, Mexico, at a height of 30 m, were obtained using a drone. Each household was sampled indoors and outdoors by vector control personnel targeting all the containers that potentially served as Aedes aegypti breeding sites. The main results were that the drone could find 1 container per 2.8 found by ground surveillance; however, containers that were inaccessible by technicians in roofs and backyards, such as plastic buckets and tubs, disposable plastic containers and flowerpots were more often detected by drones than traditional ground surveillance. This new technological approach would undoubtedly improve the surveillance of Aedes aegypti in household environments, and better vector control activities would therefore be achieved in dengue-endemic countries.

Homogeneity and Possible Replacement of Populations of the Dengue Vectors Aedes aegypti and Aedes albopictus in Indonesia

Currently, Aedes aegypti, the principal vector of dengue virus in Indonesia, has spread throughout the archipelago. Aedes albopictus is also present. Invasion and high adaptability of the Aedes mosquitoes to all of these areas are closely related to their ecology and biology. Between June 2016 and July 2017, larval and adult mosquito collections were conducted in 43 locations in 25 provinces of Indonesia using standardized sampling methods for dengue vector surveillance. The samples collected were analyzed for polymorphism and phylogenetic relationship using the mitochondrial cox1 gene and the nuclear ribosomal internal transcribed spacer 2 (ITS2). Almost all Ae. aegypti samples collected in this study (89%) belonged to the same haplotype. A similar situation is observed with the nuclear ITS2 marker. Populations of Ae. aegypti characterized few years ago were genetically different. A closely related observation was made with Aedes albopictus for which the current populations are different from those described earlier. Ae. aegypti populations were found to be highly homogenous all over Indonesia with all samples belonging to the same maternal lineage. Although difficult to demonstrate formally, there is a possibility of population replacement. Although to a lower extent, a similar conclusion was reached with Ae. albopictus.

Assessment of Mosquito Collection Methods for Dengue Surveillance

Several methods exist to collect and assess the abundance of dengue vector mosquitoes, i.e., morning adult collection, pupal collection, ovitraps, human landing, and larval collection. Several of these methods are officially implemented to monitor mosquito density and make decisions on treatments for dengue control. This monitoring is also constrained by the need to conduct this assessment on a “one point/one day” process, meaning that once the threshold of 100 households is reached, the assessment is made, and the collectors teams move to another place, thus preventing the use of long-term sampling methods. This diversity of methods might be a source of variability and lack of statistical significance. There is also a lack of published data regarding the efficacy of these methods. Furthermore, the Stegomyia indices are shown to be not reliable for assessing the risk of dengue outbreaks. A mosquito survey was, thus, conducted in 39 locations corresponding to 15 dengue endemic provinces in Indonesia by using the different adult and larval collection methods recommended nationwide. A total of 44,675 mosquitoes were collected. The single larva method was the most efficient. Out of a total of 89 dengue-positive pools, the most frequently encountered virus was DENV2, which made up half of the positive samples, followed by DENV3 and DENV1, respectively. Factor analysis of mixed data showed that no correlation could be found between any methods and the presence of dengue virus in mosquitoes. Moreover, no correlation could be found between any methods and the incidence of dengue. There was no consistency in the efficacy of a given method from one site to another. There was no correlation between any of the parameters considered, i.e., method, incidence of dengue, location, and the presence of dengue virus in mosquitoes.

Social and environmental risk factors for dengue in Delhi city: A retrospective study

Global urbanization is leading to an inexorable spread of several major diseases that need to be stemmed. Dengue is one of these major diseases spreading in cities today, with its principal mosquito vector superbly adapted to the urban environment. Current mosquito control strategies are proving inadequate, especially in the face of such urbanisation and novel, evidence-based targeted approaches are needed. Through combined epidemiological and entomological approaches, we aimed to identify a novel sanitation strategy to alleviate the burden of dengue through how the dengue virus spreads through the community. We combined surveillance case mapping, prospective serological studies, year-round mosquito surveys, socio-economic and Knowledge Attitudes and Practices surveys across Delhi. We identified lack of access to tap water (≤98%) as an important risk factor for dengue virus IgG sero-positivity (adjusted Odds Ratio 4.69, 95% C.I. 2.06–10.67) and not poverty per se. Wealthier districts had a higher dengue burden despite lower mosquito densities than the Intermediary income communities (adjusted Odds Ratio 2.92, 95% C.I. 1.26–6.72). This probably reflects dengue being introduced by people travelling from poorer areas to work in wealthier houses. These poorer, high density areas, where temperatures are also warmer, also had dengue cases during the winter. Control strategies based on improved access to a reliable supply of tap water plus focal intervention in intra-urban heat islands prior to the dengue season could not only lead to a reduction in mosquito abundance but also eliminate the reservoir of dengue virus clearly circulating at low levels in winter in socio-economically disadvantaged areas.

Identifying disease hotspots and individual risk factors for dengue can enable targeted intervention strategies. We conducted combined serological, entomological and socio-economic surveys across 18 areas within Delhi, taken from the total 1280 colonies (i.e. the administrative units of reference in Delhi) for which we classified their socio-economic typology. We additionally performed a Knowledge, Attitudes, Practices survey at a household level within the most socially disadvantaged sub-districts. Finally, we mapped all the winter dengue cases to 250 m x 250 m units along with their winter mean temperatures. We found that access to tap water was an important risk factor for exposure to dengue virus (DENV) and this was confirmed even within the socially disadvantaged sub-districts. The Wealthy colonies had a high burden of DENV infection despite low mosquito densities, likely linked to their connectedness through daily human mobility. The winter burden of dengue occurred majoritarily in the socio-economically disadvantaged colonies, which also have higher mean temperatures and urban heat islands. Improved access to tap water could lead to a reduction in dengue, not only for those directly affected but for the general population. Targeted intervention through mosquito control in winter in the socially disadvantaged areas could offer a rational strategy for optimising control efforts.