The Aedes aegypti mosquito exhibits a critical behavioral adaptation through its oviposition strategy, laying eggs in dry and wet environments just above the water level, allowing eggs to resist desiccation and hatch only when submerged by rain. To investigate this mechanism, we developed a nonlinear dynamic model incorporating climate-driven parameters affecting egg hatching and adult emergence. Theoretical analysis revealed an imperfect pitchfork bifurcation giving rise to a phenomenon we term basin-mediated hysteresis. Unlike classical hysteresis, which relies on coexisting stable states, this mechanism results from the progressive collapse of the extinction basin boundary. As the control parameter approaches its critical value, the basin of attraction of the trivial equilibrium shrinks. Once the population establishes itself above the threshold, returning the parameter below unity does not restore extinction, leading to an irreversible transition governing population persistence. The model was validated using field data from mosquito traps in a Brazilian city, showing strong agreement with observed seasonal patterns of female captures. Parameters were optimized using the Differential Evolution algorithm, yielding high correlation between model and field data. The results demonstrate that the dual oviposition strategy underlies population persistence and seasonal peaks, providing information for planning interventions amid global arbovirus expansion.

Background Early-evening and outdoor-biting mosquitoes may compromise the effectiveness of frontline malaria interventions, notably insecticide-treated nets (ITNs). This study aimed to evaluate the efficacy of low-cost insecticide-treated eave ribbons and sandals as supplementary interventions against indoor-biting and outdoor-biting mosquitoes in south-eastern Tanzania, where ITNs are already widely used. Methods This study was conducted in three villages, with 72 households participating (24 households per village). The households were divided into four study arms and assigned: transfluthrin-treated sandals (TS), transfluthrin-treated eave ribbons (TER), a combination of TER and TS, or experimental controls. Each arm had 18 households, and all households received new ITNs. Mosquitoes were collected using double net traps (to assess outdoor biting), CDC light traps (to assess indoor biting), and Prokopack aspirators (to assess indoor resting). Protection provided by the interventions was evaluated by comparing mosquito densities between the treatment and control arms. Additional tests were done in experimental huts to assess the mortality of wild mosquitoes exposed to the treatments or controls. Results TERs reduced indoor-biting, indoor-resting and outdoor-biting Anopheles arabiensis by 60%, 73% and 41%, respectively, while TS reduced the densities by 18%, 40% and 42%, respectively. When used together, TER & TS reduced indoor-biting, indoor-resting and outdoor-biting An. arabiensis by 53%, 67% and 57%, respectively. Protection against Anopheles funestus ranged from 42 to 69% with TER and from 57 to 74% with TER & TS combined. Mortality of field-collected mosquitoes exposed to TER, TS or both interventions was 56–78% for An. arabiensis and 47–74% for An. funestus . Conclusion Transfluthrin-treated eave ribbons and sandals or their combination can offer significant household-level protection against malaria vectors. Their efficacy is magnified by the transfluthrin-induced mortality, which was observed despite the prevailing pyrethroid resistance in the study area. These results suggest that TER and TS could be useful supplementary tools against residual malaria transmission in areas where ITN coverage is high but additional protection is needed against early-evening and outdoor-biting mosquitoes. Further research is needed to validate the performance of these tools in different settings, and assess their long-term effectiveness and feasibility for malaria control.

Background Understanding mosquito biting behaviours is important for designing and evaluating protection methods against nuisance biting and mosquito-borne diseases (e.g. dengue, malaria and zika). We investigated the preferred biting sites by Aedes aegypti and Anopheles arabiensis on adult volunteers in standing or sleeping positions; and estimated the theoretical protection limits affordable from protective clothing or repellent-treated footwear. Methods Adult volunteers dressed in shorts and t-shirts were exposed to infection-free laboratory-reared mosquitoes inside screened chambers from 6am to noon (for day-biting Ae . aegypti ) or 6pm to midnight (night-biting An . arabiensis ). Attempted bites on different body parts were recorded. Comparative observations were made on same volunteers while wearing sandals treated with transfluthrin, a vapour-phase pyrethroid that kills and repels mosquitoes. Results An . arabiensis bites were mainly on the lower limbs of standing volunteers (95.9% of bites below the knees) but evenly-distributed over all exposed body surfaces when the volunteers were on sleeping positions (only 28.8% bites below knees). Ae . aegypti bites were slightly concentrated on lower limbs of standing volunteers (47.7% below knees), but evenly-distributed on sleeping volunteers (23.3% below knees). Wearing protective clothing that leave only hands and head uncovered (e.g. socks + trousers + long-sleeved shirts) could theoretically prevent 78–83% of bites during sleeping, and at least 90% of bites during non-sleeping hours. If the feet are also exposed, protection declines to as low as 36.3% against Anopheles . The experiments showed that transfluthrin-treated sandals reduced An . arabiensis by 54–86% and Ae . aegypti by 32–39%, but did not change overall distributions of bites. Conclusion Biting by An . arabiensis and Ae . aegypti occur mainly on the lower limbs, though this proclivity is less pronounced in the Aedes species. However, when hosts are on sleeping positions, biting by both species is more evenly-distributed over the exposed body surfaces. High personal protection might be achieved by simply wearing long-sleeved clothing, though protection against Anopheles particularly requires covering of feet and lower legs. The transfluthrin-treated footwear can reduce biting risk, especially by An . arabiensis . These findings could inform the design and use of personal protection tools (both insecticidal and non-insecticidal) against mosquitoes and mosquito-borne diseases.

Urban Forest remnants are important for the persistence of flora and fauna species, being able to exploited by culicids that have different degrees of synanthropy and preference for distinct habitats. The objective was to evaluate the difference in diversity, abundance, richness and distribution of the Culicidae fauna in a remnant of urban forest. Collections of adult Culicidae using BG-Sentinel ® traps and dry ice as a source of CO 2 were carried out in four distinct sites an urban forest, in the municipality of Sabará, Minas Gerais, Brazil. Fifteen traps were installed weekly a month, between April/2011 and May/2012. Indexes (Shanon-Wiener diversity; Berger-Parker dominance; Bray-Curtis similarity and richness estimators) were used to compare the sampled locations. A total of 3,221 Culicidae belonging to 26 species of 10 genera were identified. The dominant species ( Culex quinquefasciatus, Limatus durhamii, Aedes albopictus, Haemagogus leucocelaenus, Chagasia fajardi and A. aegypti ) accumulated 95% of the total abundance of the collections. Eight (31 %) of the 26 species were found in the four collection sites; six (23 %) were present in three locations, four (15 %) in two areas and eight (31%) were found only in one of the collection sites. Differences were observed between abundance (GLM, ANOVA, p<0.05) and richness (ANOSIM, R=0.81, p<0.0001) between the sampled areas. Habitat fragmentation impacts on abundance, distribution and richness of Culicidae species in urban forest remnants. Ongoing monitoring can help to better understand and assess seasonal factors in the dynamics of species distribution among sampled areas.

This article introduces a technique for using recurrent neural networks to forecast Ae. aegyptimosquito (Dengue transmission vector) counts at neighborhood-level, using Earth Observation data inputs as proxies to environmental variables. The model is validated using in situdata in two Brazilian cities, and compared with state-of-the-art multioutput random forest and k-nearest neighbor models. The approach exploits a clustering step performed before the model definition, which simplifies the task by aggregating mosquito count sequences with similar temporal patterns.

Mosquitoes propagate many human diseases, some widespread and with no vaccines. The Ae. aegypti mosquito vector transmits Zika, Chikungunya, and Dengue viruses. Effective public health interventions to control the spread of these diseases and protect the population require models that explain the core environmental drivers of the vector population. Field campaigns are expensive, and data from meteorological sites that feed models with the required environmental data often lack detail. As a consequence, we explore temporal modeling of the population of Ae. aegypti mosquito vector species and environmental conditions- temperature, moisture, precipitation, and vegetation- have been shown to have significant effects. We use earth observation (EO) data as our source for estimating these biotic and abiotic environmental variables based on proxy features, namely: Normalized difference vegetation index, Normalized difference water index, Precipitation, and Land surface temperature. We obtained our response variable from field-collected mosquito population measured weekly using 791 mosquito traps in Vila Velha city, Brazil, for 36 weeks in 2017, and 40 weeks in 2018. Recent similar studies have used machine learning (ML) techniques for this task. However, these techniques are neither intuitive nor explainable from an operational point of view. As a result, we use a Generalized Linear Model (GLM) to model this relationship due to its fitness for count response variable modeling, its interpretability, and the ability to visualize the confidence intervals for all inferences. Also, to improve our model, we use the Akaike Information Criterion to select the most informative environmental features. Finally, we show how to improve the quality of the model by weighting our GLM. Our resulting weighted GLM compares well in quality with ML techniques: Random Forest and Support Vector Machines. These results provide an advancement with regards to qualitative and explainable epidemiological risk modeling in urban environments.

Mosquito surveillance is an essential component of mosquito control and mosquito traps are a universally employed tool to monitor adult populations. The objective of this paper was to evaluate the new modular Biogents BG-Pro mosquito trap (BGP) and compare its performance to 4 widely used traps for adult mosquitoes: the BG-Sentinel (BGS), the BG Mosquitaire (BGM), the CDC miniature light trap (CDC), and the encephalitis vector survey trap (EVS). One semi-field and 9 field Latin square trials were performed in 7 countries. Results showed that the collection performance of the BGP was equivalent to or exceeded that of the BGS, BGM, CDC, and EVS traps in head-to-head comparisons. The BGP uses 35% less power than the CDC and 75% less than the BGS and BGM. This lower power consumption allows it to run at 5 V for 2 days using a small lightweight 10,000-mAh rechargeable power bank. The BG-Pro is an excellent alternative for the surveillance of mosquito species that are usually monitored with BG-Sentinel, CDC, or EVS traps.

We provide the first evidence of a recent invasion of Aedes aegypti (Linnaeus in Hasselquist, 1762) and Aedes albopictus (Skuse 1894), followed by dengue virus, in tropical montane cities in south-eastern Brazil, Mariana, and Ouro Preto, at mid and high altitudes, respectively. Long-term temperature variation, dengue public data, and sampling of immature and adult mosquitoes (ovitraps and mosquitraps) in contrasting habitats were used to explain the distribution of Aedes in what in these two cities. From 1961 to 2014, the annual temperature increased significantly due to increases in winter temperatures. In the 1990s/2000s, the winter temperature was 1.3°C warmer than in the 1960s, when it varied from 21.2 to 18.9°C. After 2007, the winter temperatures increased and ranged from 21.6 to 21.3°C. The first autochthonous dengue cases in Mariana and Ouro Preto were in 2007, followed by few occurrences until in 2012, when the mean numbers increased three-fold, and peak at 2013. The continuous 'warmer winter' may have trigged the Aedes invasion. Aedes species benefited from higher winter temperatures, which was an important driver of their invasion of the state of Minas Gerais in the 1980s and, more recently, in the remaining montane urban habitats in this region. In both 2009 and 2011, we found more Aedes in Mariana than Ouro Preto, and more Ae. albopictus in green areas and Ae. aegypti in houses, the expected pattern for well-established populations.

O Aedes aegypti e o Aedes albopictus são os principais vetores transmissores de arboviroses no mundo como a dengue, zika, febre de chikungunya e a febre amarela, com maior incidência global desses vetores em regiões tropicais. A pluviosidade exerce considerável influência no desenvolvimento do Aedes spp., favorecendo o aumento do número de criadouros disponíveis para postura de ovos, ocasionando correlação positiva com a incidência de doenças. Um estudo teórico-numérico-computacional do modelo proposto, foi realizado com a finalidade de reproduzir a dependência dos parâmetros entomológicos com a pluviosidade acumulada semanalmente de uma determinada região, para investigar a relação entre a escolha do local de oviposição pela fêmea do mosquito, que pode ocorrer em ambientes secos ou aquáticos, e como essa escolha pode impactar na população de fêmeas. O sistema possui três equações diferenciais não lineares que representa a dinâmica das populações de ovos em ambientes secos e aquáticos e a população de fêmeas sob efeito de variáveis pluviométricas, sendo validado através da comparação com dados experimentais de capturas obtidos pelo monitoramento entomológico da cidade de Caratinga, Minas Gerais, Brasil. Verificou-se que o modelo descreve o ciclo de vida do mosquito, sendo capaz de auxiliar no controle e monitoramento do Aedes.

Objective. To identify and describe broadly the factors related to the occurrence of dengue epidemics in Brazil. Methods. Systematic review of studies published in Medline, Lilacs, PubMed, Cochrane, BVS, Web of Science, Scopus, and thesis and dissertations databases using descriptors cataloged in DeCs and MeSH on dengue and factors associated with the occurrence of epidemics, published from 2008 to 2018. Results. Thirty-five studies carried out in the country were selected. The epidemics recorded in Brazil were associated and/or correlated with multiple factors such as environment, socioeconomic conditions, climate, and aspects related to the vector, among others. Conclusions. Dengue epidemics are complex and multifactorial. The continuity of the vector control actions was found to be relevant to the reduction of Aedes aegypti and for disease control. To contain the spread of the disease, effective measures are needed in all sectors, including health, education, economy, population, business, and government. Actions for the early detection of cases of the disease can prevent new outbreaks of epidemics.

Aedes aegypti mosquitoes are the vector of diseases such as dengue, zika, chikungunya, and yellow fever among others. All the stages of development, eggs, larvae, pupa, and the adult of the species have its population modulated by meteorological variables, such as precipitation and temperature through affecting the productivity of breeding sites, metabolic processes, and others. Since adult females are responsible for transmitting the virus, the population of females becomes a direct indicator of the risk of infection. For this reason, some ongoing vector surveillance programs are based on adult female capture. In turn, all the stages of development have its population modulated by meteorological variables, such as precipitation and temperature, through productivity of breeding sites, metabolic processes and others. In this work, field data of capture of females was used to evaluate if a population dynamics model of Aedes aegypti under the effect of weather would be able to forecast field population. The nonlinear dynamic system model comprises: (1) four equations for the populations of the stages of development of the mosquito, designed for the ongoing surveillance program; (2) parametric dependencies of the rates of development on mean temperature and weekly accumulated precipitation. The dependencies on temperature and precipitation are modelled with aim of simplicity with the fewer number of parameters as possible. Temperature dependence is modelled based on values of the related literature under the assumption of existence of a optimum temperature for the rates, getting worse for extreme temperatures. The dependence on precipitation which is barely treated in experiments is modelled under the assumption of a monotonic dependence described by a power law with values estimated in orders of magnitude from data in the literature. By comparison with field data of an entomological indicator based on the number of Ae. aegypti females captured by a public health program in the city of Caratinga (Minas Gerais, Brazil), the model showed a significant correlation (R = 0.75). The result shows that the approach, if refined, can provide forecasting for of the population size.

The mosquito Aedes aegypti is the main vector of arboviroses and current approaches to control this vector are not sufficiently effective. Adult traps, such as the BG-Sentinel (BGS), have been successfully used for mosquito surveillance and can also suppress vector populations. A new "passive" trap for gravid Ae. aegypti (Gravid Aedes Trap-GAT) has been shown efficient for Aedes collection and suppress Ae. albopictus populations using mass trapping techniques. Here the GAT was evaluated for the first time as a new tool to control Ae. aegypti in semi-field conditions using simulated outdoor environments (SOE). Two identical large screened chambers inside of a SOE containing different numbers and sizes of artificial breeding sites were used to assess the trapping efficiency of the GAT. One hundred mosquitoes were released into the chambers, and recapture rates evaluated after 48h. The parity status of the captured mosquitoes was also recorded. The number of eggs laid, and breeding productivity were also monitored when using different numbers and sizes of breeding sites. The BGS trap was used here as a control (gold standard) trap to compare capture rates to those of the GAT. The GAT recaptured between 50-65% of the mosquitoes independent of the number and sizes of the breeding sites in the SOEs, whereas the BGS recaptured 60-82% of the females. Both traps showed similar results regarding to the parity status of recaptured mosquitoes. Our results confirmed the effectiveness of GAT for the capture of adult female Ae. aegypti in simulated field environments. The BGS trap recaptured gravid Ae. aegypti before egg-laying in different sizes and number of breading sites, whereas the oviposition activity occurred prior to recapture mosquitoes in the GAT. Based on the results, we believe that GAT is a promising candidate for mass-trapping intervention in urban settings, but a source reduction intervention should be made prior trap deployment. Therefore, we suggest future field studies to confirm the use of GAT as a complementary tool in vector control activities.

Mosquito colony maintenance in the laboratory is essential for research but presents logistical and ethical problems with the use of live animals for bloodfeeding. The Glytube is an artificial bloodfeeding system for mosquitoes that uses Parafilm-M® membrane and human blood to feed Aedes aegypti. This study evaluated the efficiency of Glytube with different types of membranes and chicken blood to feed Ae. aegypti and Ae. albopictus. We evaluated 2 artificial (thread seal tape [TST], Parafilm-M) and 2 natural membranes (pork, sheep intestine). The results for Ae. aegypti suggest that TST was the best membrane because it presented a high percentage of fed females (63%), a high average number of eggs per female (54.65), and an egg viability rate significantly similar to control (mouse). For Ae. albopictus, there was no significant difference between the membranes and the control; however, the use of TST is suggested due to the low cost and easy manipulation. The treatments that used chicken blood did not present significant differences in the egg viability when compared with the control. The Glytube functionality can be increased by replacing the Parafilm-M membrane by TST and human to chicken blood.

Over 50% of the world population is at risk of mosquito-borne diseases. Female Ae. aegypti mosquito species transmit Zika, Dengue, and Chikungunya. The spread of these diseases correlate positively with the vector population, and this population depends on biotic and abiotic environmental factors including temperature, vegetation condition, humidity and precipitation. To combat virus outbreaks, information about vector population is required. To this aim, Earth observation (EO) data provide fast, efficient and economically viable means to estimate environmental features of interest. In this work, we present a temporal distribution model for adult female Ae. aegypti mosquitoes based on the joint use of the Normalized Difference Vegetation Index, the Normalized Difference Water Index, the Land Surface Temperature (both at day and night time), along with the precipitation information, extracted from EO data. The model was applied separately to data obtained during three different vector control and field data collection condition regimes, and used to explain the differences in environmental variable contributions across these regimes. To this aim, a random forest (RF) regression technique and its nonlinear features importance ranking based on mean decrease impurity (MDI) were implemented. To prove the robustness of the proposed model, other machine learning techniques, including support vector regression, decision trees and k-nearest neighbor regression, as well as artificial neural networks, and statistical models such as the linear regression model and generalized linear model were also considered. Our results show that machine learning techniques perform better than linear statistical models for the task at hand, and RF performs best. By ranking the importance of all features based on MDI in RF and selecting the subset comprising the most

Understanding geographic population dynamics of mosquitoes is an essential requirement for estimating the risk of mosquito-borne disease transmission and geographically targeted interventions. However, the use of population dynamics measures, such as the intrinsic growth rate, as predictors in spatio-temporal point processes has not been investigated before. In this work we compared the predictive accuracy of four spatio-temporal log-Gaussian Cox models: (i) With no predictors; (ii) mosquito abundance as predictor; (iii) intrinsic growth rate as predictor; (iv) intrinsic growth rate and mosquito abundance as predictors. This analysis is based on Aedes aegypti mosquito surveillance and human dengue data obtained from the urban area of Caratinga, Brazil. We used a statistical Moran Curve approach to estimate the intrinsic growth rate and a zero inflated Poisson kriging model for estimating mosquito abundance at locations of dengue cases. The incidence of dengue cases was positively associated with mosquito intrinsic growth rate and this model outperformed, in terms of predictive accuracy, the abundance and the null models. The latter includes only the spatio-temporal random effect but no predictors. In the light of these results we suggest that the intrinsic growth rate should be investigated further as a potential tool for predicting the risk of dengue transmission and targeting health interventions for vector-borne diseases.

Our ability to effectively prevent the transmission of the dengue virus through targeted control of its vector, Aedes aegypti, depends critically on our understanding of the link between mosquito abundance and human disease risk. Mosquito and clinical surveillance data are widely collected, but linking them requires a modeling framework that accounts for the complex non-linear mechanisms involved in transmission. Most critical are the bottleneck in transmission imposed by mosquito lifespan relative to the virus’ extrinsic incubation period, and the dynamics of human immunity. We developed a differential equation model of dengue transmission and embedded it in a Bayesian hierarchical framework that allowed us to estimate latent time series of mosquito demographic rates from mosquito trap counts and dengue case reports from the city of Vitória, Brazil. We used the fitted model to explore how the timing of a pulse of adult mosquito control influences its effect on the human disease burden in the following year. We found that control was generally more effective when implemented in periods of relatively low mosquito mortality (when mosquito abundance was also generally low). In particular, control implemented in early September (week 34 of the year) produced the largest reduction in predicted human case reports over the following year. This highlights the potential long-term utility of broad, off-peak-season mosquito control in addition to existing, locally targeted within-season efforts. Further, uncertainty in the effectiveness of control interventions was driven largely by posterior variation in the average mosquito mortality rate (closely tied to total mosquito abundance) with lower mosquito mortality generating systems more vulnerable to control. Broadly, these correlations suggest that mosquito control is most effective in situations in which transmission is already limited by mosquito abundance.

Over 50% of the world population is at risk of mosquito-borne diseases. Female Ae. aegypti mosquito species transmit Zika, Dengue, and Chikungunya. The spread of these diseases correlate positively with the vector population, and this population depends on biotic and abiotic environmental factors including temperature, vegetation condition, humidity and precipitation. To combat virus outbreaks, information about vector population is required. To this aim, Earth observation (EO) data provide fast, efficient and economically viable means to estimate environmental features of interest. In this work, we present a temporal distribution model for adult female Ae. aegypti mosquitoes based on the joint use of the Normalized Difference Vegetation Index, the Normalized Difference Water Index, the Land Surface Temperature (both at day and night time), along with the precipitation information, extracted from EO data. The model was applied separately to data obtained during three different vector control and field data collection condition regimes, and used to explain the differences in environmental variable contributions across these regimes. To this aim, a random forest (RF) regression technique and its nonlinear features importance ranking based on mean decrease impurity (MDI) were implemented. To prove the robustness of the proposed model, other machine learning techniques, including support vector regression, decision trees and k-nearest neighbor regression, as well as artificial neural networks, and statistical models such as the linear regression model and generalized linear model were also considered. Our results show that machine learning techniques perform better than linear statistical models for the task at hand, and RF performs best. By ranking the importance of all features based on MDI in RF and selecting the subset comprising the most

Push–pull strategies have been proposed as options to complement primary malaria prevention tools, indoor residual spraying (IRS) and long-lasting insecticide-treated nets (LLINs), by targeting particularly early-night biting and outdoor-biting mosquitoes. This study evaluated different configurations of a push–pull system consisting of spatial repellents [transfluthrin-treated eave ribbons (0.25 g/m2 ai)] and odour-baited traps (CO2-baited BG-Malaria traps), against indoor-biting and outdoor-biting malaria vectors inside large semi-field systems.

The BG-Malaria trap (BGM) is an adaptation of the well-known BG-Sentinel trap (BGS) with greater trapping efficiencies for anopheline and culicine mosquitoes. Its continued optimization requires greater understanding of mosquito flight behaviors near it. We used three high-resolution infrared cameras (68 frames/second) to track flight behaviors of laboratory-reared Anopheles arabiensis females in vicinity of the BGM in comparison with BGS. Additional comparisons were done for BGM at 20, 40 and 80cm heights, and for BGMs baited with Ifakara blend plus CO2, CO2 alone, or no bait. More mosquitoes were observed near BGM than BGS. Both BGMs installed 20cm above the floor and baited with CO2 received more visits by host-seeking mosquitoes than the other BGMs evaluated in their respective experiments. Trap designs, height and attractants all influence mosquito activity in vicinity of the traps which can be readily visualized using infrared cameras to accelerate trap development and testing. The greater activity of host-seeking mosquitoes near BGM than BGS supports the proven superiority of BGM traps in field and semi-field settings.