Predictive model for microclimatic temperature and its use in mosquito population modeling

Thermal tolerance of mosquito eggs is associated with urban adaptation and human interactions

Climate change is expected to profoundly affect mosquito distributions and their ability to serve as vectors for disease, specifically with the anticipated increase in heat waves. The rising temperature and frequent heat waves can accelerate mosquito life cycles, facilitating higher disease transmission. Conversely, higher temperatures could increase mosquito mortality as a negative consequence. Warmer temperatures are associated with increased human density, suggesting a need for anthropophilic mosquitoes to adapt to be more hardy to heat stress. Mosquito eggs provide an opportunity to study the biological impact of climate warming as this stage is stationary and must tolerate temperatures at the site of female oviposition. As such, egg thermotolerance is critical for survival in a specific habitat. In nature, Aedes mosquitoes exhibit different behavioral phenotypes, where specific populations prefer depositing eggs in tree holes and prefer feeding non-human vertebrates. In contrast, others, particularly human-biting specialists, favor laying eggs in artificial containers near human dwellings. This study examined the thermotolerance of eggs, along with adult stages, for Aedes aegypti and Ae. albopictus lineages associated with known ancestry and shifts in their relationship with humans. Mosquitoes collected from areas with higher human population density, displaying increased human preference, and having a human-associated ancestry profile have increased egg viability following high-temperature stress. Unlike eggs, thermal tolerance among adults showed no significant correlation based on the area of collection or human-associated ancestry. This study highlights that the egg stage is likely critical to mosquito survival when associated with humans and needs to be accounted when predicting future mosquito distribution.

Effects of climatic and environmental factors on mosquito population inferred from West Nile virus surveillance in Greece

Mosquito-borne diseases' impact on human health is among the most prominent of all communicable diseases. With limited pool of tools to contrast these diseases, public health focus remains preventing mosquito-human contacts. Applying a hierarchical spatio-temporal Bayesian model on West Nile virus (WNV) surveillance data from Greece, we aimed to investigate the impact of climatic and environmental factors on Culex mosquitoes' population. Our spatio-temporal analysis confirmed climatic factors as major drivers of WNV-transmitting-Culex mosquitoes population dynamics, with temperature and long periods of moderate-to-warm climate having the strongest positive effect on mosquito abundance. Conversely, rainfall, high humidity, and wind showed a negative impact. The results suggest the presence of statistically significant differences in the effect of regional and seasonal characteristics, highlighting the complex interplay between climatic, geographical and environmental factors in the dynamics of mosquito populations. This study may represent a relevant tool to inform public health policymakers in planning preventive measures.

Multiobjective optimization to assess dengue control costs using a climate-dependent epidemiological model

Arboviruses, diseases transmitted by arthropods, have become a significant challenge for public health managers. The World Health Organization highlights dengue as responsible for millions of infections worldwide annually. As there is no specific treatment for the disease and no free-of-charge vaccine for mass use in Brazil, the best option is the measures to combat the vector, the Aedes aegypti mosquito. Therefore, we proposed an epidemiological model dependent on temperature, precipitation, and humidity, considering symptomatic and asymptomatic dengue infections. Through computer simulations, we aimed to minimize the amount of insecticides and the social cost demanded to treat patients. We proposed a case study in which our model is fitted with real data from symptomatic dengue-infected humans in an epidemic year in a Brazilian city. Our multiobjective optimization model considers an additional control using larvicide, adulticide, and ultra-low volume spraying. The work's main contribution is studying the monetary cost of the actions to combat the vector demand versus the hospital cost per confirmed infected, comparing approaches with and without additional control. Results showed that the additional vector control measures are cheaper than the hospital treatment without the vector control would be.

The effects of microclimatic winter conditions in urban areas on the risk of establishment for Aedes albopictus

The tiger mosquito, Aedes albopictus, has adjusted well to urban environments by adopting artificial water containers as oviposition sites. Its spread in temperate regions is favoured by the deposition of cold-tolerant diapausing eggs that survive winter temperatures to a certain degree. The probability of establishment in new geographical areas is estimated using predictive models usually based on meteorological data measured at coarse resolution. Here, we investigated if we could obtain more precise and realistic risk scenarios for the spread of Ae. albopictus when considering the winter microclimatic conditions of catch basins, one of the major sites of oviposition and egg overwintering in temperate urban areas. We monitored winter microclimatic conditions of catch basins in four Swiss cities and developed a regression model to predict the average microclimatic temperatures of catch basins, based on available meteorological parameters, accounting for the observed differences between cities. We then used the microclimatic model to correct the predictions of our previously developed risk model for the prediction of Ae. albopictus establishment. Comparison of the predictive model’s results based on local climate data and microclimate data indicated that the risk of establishment for Ae. albopictus in temperate urban areas increases when microhabitat temperatures are considered.

A Retrospective Study of Climate Change Affecting Dengue: Evidences, Challenges and Future Directions

Climate change is unexpected weather patterns that can create an alarming situation. Due to climate change, various sectors are affected, and one of the sectors is healthcare. As a result of climate change, the geographic range of several vector-borne human infectious diseases will expand. Currently, dengue is taking its toll, and climate change is one of the key reasons contributing to the intensification of dengue disease transmission. The most important climatic factors linked to dengue transmission are temperature, rainfall, and relative humidity. The present study carries out a systematic literature review on the surveillance system to predict dengue outbreaks based on Machine Learning modeling techniques. The systematic literature review discusses the methodology and objectives, the number of studies carried out in different regions and periods, the association between climatic factors and the increase in positive dengue cases. This study also includes a detailed investigation of meteorological data, the dengue positive patient data, and the pre-processing techniques used for data cleaning. Furthermore, correlation techniques in several studies to determine the relationship between dengue incidence and meteorological parameters and machine learning models for predictive analysis are discussed. In the future direction for creating a dengue surveillance system, several research challenges and limitations of current work are discussed.