Risk Of Mosquito-borne Diseases Research Articles

Rapid response Task Force: addressing the detection of Aedes albopictus in Lisbon, Portugal

Abstract Issue The invasive Aedes albopictus mosquitoes are spreading in southern Europe and pose a heightened risk of mosquito-borne diseases, like Dengue and Chikungunya. On September 2023, A. albopictus was first identified in Lisbon through community-based surveillance and a multidisciplinary national Task Force (TF) was convened. Description of the problem The TF included experts in epidemiology, entomology, environmental health, laboratory diagnosis, prevention and control and communication. The objectives were to i) confirm A.albopictus presence in Lisbon and adjust the risk assessment, ii) raise awareness and prevent mosquitoes’ spread, iii) revise national guidelines on arboviruses surveillance and control. During September-December 2023, the National Network for Vectors Surveillance (REVIVE) and the Hygiene and Tropical Medicine Institute sampled mosquito-prone habitats within 2km-radius of the detection point using QGIS software. They used snowball sampling to identify any new foci. They placed ovitraps for ongoing surveillance and conducted morphological analysis and xenomonitoring for pathogen DNA and RNA detection at the national reference laboratory. Results By November 2023, A.albopictus was detected in two new foci. No mosquitoes tested positive for arboviruses, and no autochthonous cases of mosquito-borne diseases were identified. The TF developed national guidelines for vector prevention and control and awareness for arboviruses and trained municipality workers. To raise awareness, we communicated with experts and the public through existing channels and media. As of April 2024, no new foci have been detected. Lessons Community-based surveillance and REVIVE approach were crucial for invasive A.albopictus detection and monitoring in Lisbon. Rapid multidisciplinary TF coordination may have been key for timely vector control.

Explaining Environmental Distribution of Aedes albopictus using Machine Learning

Abstract. The Aedes albopictus mosquito, known for its role in transmitting diseases such as dengue fever, Zika virus, and chikungunya, poses a significant public health threat globally. Understanding its distribution patterns is crucial for effective disease surveillance and control. This study employs machine learning techniques, specifically MaxEnt modeling, to elucidate the relationship between environmental factors and the distribution of Aedes albopictus. Using presence-only data and a suite of environmental variables, we trained MaxEnt models to predict the potential distribution of Aedes albopictus across a geographical region. The models were validated using independent datasets and evaluated for their predictive accuracy and robustness. Our results reveal significant associations between Aedes albopictus presence and environmental factors such as temperature related variables. Furthermore, we employed spatial analysis techniques to identify areas at high risk of Aedes albopictus presence, aiding in targeted vector control strategies and disease prevention efforts. MaxEnt models demonstrated high predictive performance, effectively capturing the complex relationships between environmental variables and mosquito distribution in Nepal, India and Myanmar, along with Spain and Italy. By integrating machine learning algorithms with environmental data, this study provides valuable insights into the ecological drivers of Aedes albopictus distribution, enhancing our ability to mitigate the risk of mosquito-borne diseases in affected regions.

Factors influencing community engagement approaches used in Aedes aegypti management in Cairns, Australia.

An important part of preventing and managing Aedes-borne mosquito disease outbreak risk is engaging the community. Research shows that high-income countries tend to use top-down measures for Aedes mosquito management, favouring educational approaches to engage the community over participatory approaches that actively involve and empower the community in addressing disease risk. Little is known about the reasons behind the use of these approaches and how they could be strengthened. This research explores the community engagement approaches used in Aedes mosquito management in Cairns, Queensland, Australia and the factors influencing the choice of these approaches. A case study design was used, drawing on two qualitative methods-key informant, semi-structured interviews (n = 25), and a document review (n = 20). Thematic analysis was used to identify, analyse and attribute meaning from the data. Various approaches were used to engage the community, including direct interaction through door-to-door inspections, broad outreach via mass media campaigns, and community participation in a novel mosquito replacement strategy. Factors influencing the choice of these approaches included government legislative responsibilities, research-related ethical obligations, work norms within local government and public health units, the perceived importance of gaining community trust, constraints on workforce capacity, time and funding. There were multiple factors influencing the community engagement approaches used in this study. Resource constraints, institutional norms and prevailing attitudes and beliefs were identified as hindering the use of more empowering approaches to engaging the community. These barriers should be considered and addressed in the planning of Aedes mosquito management to better support community engagement in this setting. SO WHAT?: Community engagement is an important aspect of managing the Aedes mosquito disease threat. With the global increase in Aedes mosquito-borne disease risk, these findings can help other at-risk settings understand potential organisational impediments to engaging the community. This is particularly important when advocating for the inclusion of bottom-up approaches in policy, and to ensure sufficient resources are allocated to strengthen community engagement in Aedes mosquito management.

Remote sensing of temperature-dependent mosquito and viral traits predicts field surveillance-based disease risk.

Mosquito-borne diseases contribute substantially to the global burden of disease, and are strongly influenced by environmental conditions. Ongoing and rapid environmental change necessitates improved understanding of the response of mosquito-borne diseases to environmental factors like temperature, and novel approaches to mapping and monitoring risk. Recent development of trait-based mechanistic models has improved understanding of the temperature dependence of transmission, but model predictions remain challenging to validate in the field. Using West Nile virus (WNV) as a case study, we illustrate the use of a novel remote sensing-based approach to mapping temperature-dependent mosquito and viral traits at high spatial resolution and across the diurnal cycle. We validate the approach using mosquito and WNV surveillance data controlling for other key factors in the ecology of WNV, finding strong agreement between temperature-dependent traits and field-based metrics of risk. Moreover, we find that WNV infection rate in mosquitos exhibits a unimodal relationship with temperature, peaking at ~24.6-25.2°C, in the middle of the 95% credible interval of optimal temperature for transmission of WNV predicted by trait-based mechanistic models. This study represents one of the highest resolution validations of trait-based model predictions, and illustrates the utility of a novel remote sensing approach to predicting mosquito-borne disease risk.

Mean daily temperatures can predict the thermal limits of malaria transmission better than rate summation.

Temperature shapes the distribution, seasonality, and magnitude of mosquito-borne disease outbreaks. Mechanistic models predicting transmission often use mosquito and pathogen thermal responses from constant temperature experiments. However, mosquitoes live in fluctuating environments. Rate summation (nonlinear averaging) is a common approach to infer performance in fluctuating environments, but its accuracy is rarely validated. We measured three mosquito traits that impact transmission (bite rate, survival, fecundity) in a malaria mosquito ( Anopheles stephensi ) across temperature gradients with three diurnal temperature ranges (0, 9 and 12°C). We compared thermal suitability models with temperature-trait relationships observed under constant temperatures, fluctuating temperatures, and those predicted by rate summation. We mapped results across An. stephenesi 's native Asian and invasive African ranges. We found: 1) daily temperature fluctuation significantly altered trait thermal responses; 2) rate summation partially captured decreases in performance near thermal optima, but also incorrectly predicted increases near thermal limits; and 3) while thermal suitability characterized across constant temperatures did not perfectly capture suitability in fluctuating environments, it was more accurate for estimating and mapping thermal limits than predictions from rate summation. Our study provides insight into methods for predicting mosquito-borne disease risk and emphasizes the need to improve understanding of organismal performance under fluctuating conditions.

A Review of Botanical Extracts with Repellent and Insecticidal Activity and Their Suitability for Managing Mosquito-Borne Disease Risk in Mexico.

Among the main arboviruses affecting public health in tropical regions are dengue, zika, and chikungunya, transmitted mainly by mosquitoes of the Aedes genus, especially Aedes aegypti. In recent years, outbreaks have posed major challenges to global health, highlighting the need for integrated and innovative strategies for their control and prevention. Prevention strategies include the elimination of vectors and avoiding mosquito bites; this can be achieved through the use of bioinsecticides and repellents based on plant phytochemicals, as they offer sustainable, ecological, and low-cost alternatives. Mexico has a variety of plants from which both extracts and essential oils have been obtained which have demonstrated significant efficacy in repelling and/or killing insect vectors. This review examines the current knowledge on plant species found in Mexico which are promising options concerning synthetic compounds in terms of their repellent and insecticidal properties against mosquitoes of the genus Aedes and that are friendly to the environment and health.

Risk of mosquito-borne diseases in pilgrims to the grand Magal de Touba in Senegal.

Risk of mosquito-borne diseases in pilgrims to the grand Magal de Touba in Senegal.

Mosquito Species Diversity and Abundance Patterns in Plots with Contrasting Land Use and Land Cover in Bloomington, Indiana.

Land use and land cover (LULC) gradients are associated with differences in mosquito species composition and the entomological risk of mosquito-borne disease. Here, we present results from a season-long study of mosquito species richness and abundance with samples collected at 9 locations from 2 plots with contrasting LULC, an urban farm and a forest preserve, in Bloomington, IN, a city in the midwestern USA. With a total sampling effort of 234 trap-nights, we collected 703 mosquitoes from 9 genera and 21 species. On the farm, we collected 15 species (285 mosquitoes). In the preserve, we collected 19 species (418 mosquitoes). Thirteen species were common in both study plots, 2 were exclusive to the farm, and 6 were exclusive to the forest preserve. In both plots, we collected Aedes albopictus and Ae. japonicus. In the farm, the most common mosquito species were Culex restuans/Cx. pipiens and Coquillettidia perturbans. In the preserve, Ae. japonicus and Ae. triseriatus were the 2 most common mosquito species. Time series analysis suggests that weather factors differentially affected mosquito species richness and mosquito abundance in the plots. Temperature, relative humidity (RH), and precipitation were positively associated with richness and abundance at the farm, while increases in the SD of RH decreased both richness and abundance at the preserve. Our results highlight the importance that LULC has for mosquito species diversity and abundance and confirm the presence of Ae. albopictus and Ae. japonicus in southwestern Indiana.

Exploring mosquito abundance and Plasmodium infection through nested-PCR: implications for disease surveillance and control

The Plasmodium is responsible for malaria which poses a major health threat, globally. This study is based on the estimation of the relative abundance of mosquitoes, and finding out the correlations of meteorological parameters (temperature, humidity and rainfall) with the abundance of mosquitoes. In addition, this study also focused on the use of nested PCR (species-specific nucleotide sequences of 18S rRNA genes) to explore the Plasmodium spp. in female Anopheles. In the current study, the percentage relative abundance of Culex mosquitoes was 57.65% and Anopheles 42.34% among the study areas. In addition, the highest number of mosquitoes was found in March in district Mandi Bahauddin at 21 °C (Tmax = 27, Tmin = 15) average temperature, 69% average relative humidity and 131 mm rainfall, and these climatic factors were found to affect the abundance of the mosquitoes, directly or indirectly. Molecular analysis showed that overall, 41.3% of the female Anopheles pools were positive for genus Plasmodium. Among species, the prevalence of Plasmodium (P.) vivax (78.1%) was significantly higher than P. falciparum (21.9%). This study will be helpful in the estimation of future risk of mosquito-borne diseases along with population dynamic of mosquitoes to enhance the effectiveness of vector surveillance and control programs.

Modelling current and future distribution of Aedes aegypti (Diptera: Culicidae) under climate change scenarios in Africa

Climate change is altering mosquito distribution by expanding the geographic range of species like Aedes aegypti (Diptera: Culicidae) into previously inhospitable areas due to rising temperatures and changing precipitation patterns. This shift increases the risk of mosquito-borne diseases in regions that were once unaffected, posing new public health challenges globally. Ae. aegypti is the vector that spreads the arboviral illnesses dengue fever, chikungunya, and zika. Studying Ae. aegypti's probable geographic distribution habitats in Africa under present and projected climatic circumstances is the goal of the current research. The scenarios used are the Beijing Climate Center Climate System Model (BCC-CSM2-MR) with two Shared Socio-economic Pathways (SSPs) for each of the general circulation model (GCMs): SSP126. Altitude, temperature, seasonality (standard deviation *100; bio4), and yearly precipitation (bio12) were found to be the most significant environmental factors influencing Ae. aegypti's spread.

Intensifying the fumigation policy to minimize the risk of mosquito-borne diseases implementing a stochastic optimization approach

This paper presents a stochastic mathematical model for the planning, dosage, and strategic scheduling of fumigation policies to reduce mosquito-borne diseases in a geographic location. Multiple scenarios were generated to account for uncertainty in the existing mosquito population based on a random normal distribution. In addition, the model includes occupational health, considering the permissible limits of each insecticide applied and their residual effect. This stochastic mathematical model applies a Pareto solution method, using a Conditional Value at Risk approach to select solutions that trade off the different objective functions. Results show that the optimal solutions found by the model provide a compromise between the expected infected people and the total cost of applying the insecticides. This methodology improves the current practice by an intensified approach that considers optimal scheduling alternatives that minimize cost while considering the permissible concentration limits to guarantee the health and comfort of the population to minimize the possible incidences of infections.

Development of a regional climate change model for Aedes vigilax and Aedes camptorhynchus (Diptera: Culicidae) in Perth, Western Australia.

Mosquito-borne disease is a significant public health issue and within Australia Ross River virus (RRV) is the most reported. This study combines a mechanistic model of mosquito development for two mosquito vectors; Aedes vigilax and Aedes camptorhynchus, with climate projections from three climate models for two Representative Concentration Pathways (RCPs), to examine the possible effects of climate change and sea-level rise on a temperate tidal saltmarsh habitat in Perth, Western Australia. The projections were run under no accretion and accretion scenarios using a known mosquito habitat as a case study. This improves our understanding of the possible implications of sea-level rise, accretion and climate change for mosquito control programmes for similar habitats across temperate tidal areas found in Southwest Western Australia. The output of the model indicate that the proportion of the year mosquitoes are active increases. Population abundances of the two Aedes species increase markedly. The main drivers of changes in mosquito population abundances are increases in the frequency of inundation of the tidal wetland and size of the area inundated, increased minimum water temperature, and decreased daily temperature fluctuations as water depth increases due to sea level changes, particularly under the model with no accretion. The effects on mosquito populations are more marked for RCP 8.5 when compared to RCP 4.5 but were consistent among the three climate change models. The results indicate that Ae. vigilax is likely to be the most abundant species in 2030 and 2050, but that by 2070 Aedes camptorhynchus may become the more abundant species. This increase would put considerable pressure on existing mosquito control programmes and increase the risk of mosquito-borne disease and nuisance biting to the local community, and planning to mitigate these potential impacts should commence now.

Advances in CRISPR/Cas9-Based Gene Editing Technology in Mosquitoes

As global warming increases, mosquito activity areas are expanding, alongside changes in the natural environment and the misuse of insecticides, thus further increasing mosquito resistance and exposing the world to an elevated risk of mosquito-borne diseases. With advancements in gene editing technology, researchers are continually attempting to modify various mosquito genes and validate their functional roles with CRISPR-Cas9 technology. Here, we review recent applications of CRISPR-Cas9-based gene editing technology in mosquito-borne disease prevention and control, as well as mosquito population suppression, phenotyping, and resistance. We further discuss the development of new techniques, such as ReMOT Control and DIPA-CRISPR, which differ from conventional embryo microinjection and should be expanded in future insect gene editing research.

The Arbovirus Mapping and Prediction (ArboMAP) system for West Nile virus forecasting.

West Nile virus (WNV) is the most common mosquito-borne disease in the United States. Predicting the location and timing of outbreaks would allow targeting of disease prevention and mosquito control activities. Our objective was to develop software (ArboMAP) for routine WNV forecasting using public health surveillance data and meteorological observations. ArboMAP was implemented using an R markdown script for data processing, modeling, and report generation. A Google Earth Engine application was developed to summarize and download weather data. Generalized additive models were used to make county-level predictions of WNV cases. ArboMAP minimized the number of manual steps required to make weekly forecasts, generated information that was useful for decision-makers, and has been tested and implemented in multiple public health institutions. Routine prediction of mosquito-borne disease risk is feasible and can be implemented by public health departments using ArboMAP.

Synergistic Repellent and Irritant Effects of a Mixture of β-Caryophyllene Oxide and Vetiver Oil against Mosquito Vectors.

Repellents play a major role in reducing the risk of mosquito-borne diseases by preventing mosquito bites. The present study evaluated the mosquito-repellent activity of β-caryophyllene oxide 1% (BCO), vetiver oil 2.5% (VO), and their binary mixtures (BCO + VO (1:1), BCO + VO (2:1), BCO + VO (1:2)) against four laboratory-colonized mosquito species, Aedes aegypti (L.), Aedes albopictus (Skuse), Anopheles minimus Theobald, and Culex quinquefasciatus Say, using an excito-repellency assay system. In general, the compound mixtures produced a much stronger response in the mosquitoes than single compounds, regardless of the test conditions or species. The greatest synergetic effect was achieved with the combination of BCO + VO (1:2) in both contact and noncontact trials with An. minimus (74.07-78.18%) and Cx. quinquefasciatus (55.36-83.64%). Knockdown responses to the binary mixture of BCO + VO were observed for Ae. albopictus, An. minimus, and Cx. quinquefasciatus, in the range of 18.18-33.33%. The synergistic repellent activity of BCO and VO used in this study may support increased opportunities to develop safer alternatives to synthetic repellents for personal protection against mosquitoes.

Exposure to ultraviolet-B radiation increases the susceptibility of mosquitoes to infection with dengue virus.

By 2100, greenhouse gases are predicted to reduce ozone and cloud cover over the tropics causing increased exposure of organisms to harmful ultraviolet-B radiation (UVBR). UVBR damages DNA and is an important modulator of immune function and disease susceptibility in humans and other vertebrates. The effect of UVBR on invertebrate immune function is largely unknown, but UVBR together with ultraviolet-A radiation impairs an insect immune response that utilizes melanin, a pigment that also protects against UVBR-induced DNA damage. If UVBR weakens insect immunity, then it may make insect disease vectors more susceptible to infection with pathogens of socioeconomic and public health importance. In the tropics, where UVBR is predicted to increase, the mosquito-borne dengue virus (DENV), is prevalent and a growing threat to humans. We therefore examined the effect of UVBR on the mosquito Aedes aegypti, the primary vector for DENV, to better understand the potential implications of increased tropical UVBR for mosquito-borne disease risk. We found that exposure to a UVBR dose that caused significant larval mortality approximately doubled the probability that surviving females would become infected with DENV, despite this UVBR dose having no effect on the expression of an effector gene involved in antiviral immunity. We also found that females exposed to a lower UVBR dose were more likely to have low fecundity even though this UVBR dose had no effect on larval size or activity, pupal cuticular melanin content, or adult mass, metabolic rate, or flight capacity. We conclude that future increases in tropical UVBR associated with anthropogenic global change may have the benefit of reducing mosquito-borne disease risk for humans by reducing mosquito fitness, but this benefit may be eroded if it also makes mosquitoes more likely to be infected with deadly pathogens.

Ecological Degradation and the Risk of Mosquito-Borne Disease in the Great Lakes Basin.

Ecological Degradation and the Risk of Mosquito-Borne Disease in the Great Lakes Basin.

Fusing time-varying mosquito data and continuous mosquito population dynamics models

Climate change is arguably one of the most pressing issues affecting the world today and requires the fusion of disparate data streams to accurately model its impacts. Mosquito populations respond to temperature and precipitation in a nonlinear way, making predicting climate impacts on mosquito-borne diseases an ongoing challenge. Data-driven approaches for accurately modeling mosquito populations are needed for predicting mosquito-borne disease risk under climate change scenarios. Many current models for disease transmission are continuous and autonomous, while mosquito data is discrete and varies both within and between seasons. This study uses an optimization framework to fit a non-autonomous logistic model with periodic net growth rate and carrying capacity parameters for 15 years of daily mosquito time-series data from the Greater Toronto Area of Canada. The resulting parameters accurately capture the inter-annual and intra-seasonal variability of mosquito populations within a single geographic region, and a variance-based sensitivity analysis highlights the influence each parameter has on the peak magnitude and timing of the mosquito season. This method can easily extend to other geographic regions and be integrated into a larger disease transmission model. This method addresses the ongoing challenges of data and model fusion by serving as a link between discrete time-series data and continuous differential equations for mosquito-borne epidemiology models.

Interactive effects of climate, land use and soil type on Culex pipiens/torrentium abundance

The incidence and risk of mosquito-borne disease outbreaks in Northwestern Europe has increased over the last few decades. Understanding the underlying environmental drivers of mosquito population dynamics helps to adequately assess mosquito-borne disease risk. While previous studies have focussed primarily on the effects of climatic conditions (i.e., temperature and precipitation) and/or local environmental conditions individually, it remains unclear how climatic conditions interact with local environmental factors such as land use and soil type, and how these subsequently affect mosquito abundance.Here, we set out to study the interactive effects of land use, soil type and climatic conditions on the abundance of Culex pipiens/torrentium, highly abundant vectors of West Nile virus and Usutu virus. Mosquitoes were sampled at 14 sites throughout the Netherlands. At each site, weekly mosquito collections were carried out between early July and mid-October 2020 and 2021. To assess the effect of the aforementioned environmental factors, we performed a series of generalized linear mixed models and non-parametric statistical tests.Our results show that mosquito abundance and species richness consistently differ among land use- and soil types, with peri-urban areas with peat/clay soils having the highest Cx. pipiens/torrentium abundance and sandy rural areas having the lowest. Furthermore, we observed differences in precipitation-mediated effects on Cx. pipiens/torrentium abundance between (peri-)urban and other land uses and soil types. In contrast, effects of temperature on Cx. pipiens/torrentium abundance remain similar between different land use and soil types.Our study highlights the importance of both land use and soil type in conjunction with climatic conditions for understanding mosquito abundances. Particularly in relation to rainfall events, land use and soil type has a marked effect on mosquito abundance. These findings underscore the importance of local environmental parameters for studies focusing on predicting or mitigating disease risk.

Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment

Mosquitoes are known vectors for viral diseases in Canada, and their distribution is driven by climate and land use. Despite that, future land-use changes have not yet been used as a driver in mosquito distribution models in North America. In this paper, we developed land-use change projections designed to address mosquito-borne disease (MBD) prediction in a 38 761 km2 area of Eastern Ontario. The landscape in the study area is marked by urbanization and intensive agriculture and hosts a diverse mosquito community. The Dyna-CLUE model was used to project land-use for three time horizons (2030, 2050, and 2070) based on historical trends (from 2014 to 2020) for water, forest, agriculture, and urban land uses. Five scenarios were generated to reflect urbanization, agricultural expansion, and natural areas. An ensemble of thirty simulations per scenario was run to account for land-use conversion uncertainty. The simulation closest to the average map generated was selected to represent the scenario. A concordance matrix generated using map pair analysis showed a good agreement between the simulated 2020 maps and 2020 observed map. By 2050, the most significant changes are predicted to occur mainly in the southeastern region’s rural and forested areas. By 2070, high deforestation is expected in the central west. These results will be integrated into risk models predicting mosquito distribution to study the possibility of humans’ increased exposure risk to MBDs.