How do i bite thee? let me count the ways: Exploring the implications of individual biting habits of Aedes aegypti for dengue transmission

A Coupled Statistical and Deterministic Model for Forecasting Climate-Driven Dengue Incidence in Selangor, Malaysia

The mosquito-borne dengue virus remains a major public health concern in Malaysia. Despite various control efforts and measures introduced by the Malaysian Government to combat dengue, the increasing trend of dengue cases persists and shows no sign of decreasing. Currently, early detection and vector control are the main methods employed to curb dengue outbreaks. In this study, a coupled model consisting of the statistical ARIMAX model and the deterministic SI-SIR model was developed and validated using the weekly reported dengue data from year 2014 to 2019 for Selangor, Malaysia. Previous studies have shown that climate variables, especially temperature, humidity, and precipitation, were able to influence dengue incidence and transmission dynamics through their effect on the vector. In this coupled model, climate is linked to dengue disease through mosquito biting rate, allowing real-time forecast of dengue cases using climate variables, namely temperature, rainfall and humidity. For the period chosen for model validation, the coupled model can forecast 1-2 weeks in advance with an average error of less than 6%, three weeks in advance with an average error of 7.06% and four weeks in advance with an average error of 8.01%. Further model simulation analysis suggests that the coupled model generally provides better forecast than the stand-alone ARIMAX model, especially at the onset of the outbreak. Moreover, the coupled model is more robust in the sense that it can be further adapted for investigating the effectiveness of various dengue mitigation measures subject to the changing climate.

Indian Ocean temperature anomalies predict long-term global dengue trends

Despite identifying El Niño events as a factor in dengue dynamics, predicting the oscillation of global dengue epidemics remains challenging. Here, we investigate climate indicators and worldwide dengue incidence from 1990 to 2019 using climate-driven mechanistic models. We identify a distinct indicator, the Indian Ocean basin-wide (IOBW) index, as representing the regional average of sea surface temperature anomalies in the tropical Indian Ocean. IOBW is closely associated with dengue epidemics for both the Northern and Southern hemispheres. The ability of IOBW to predict dengue incidence likely arises as a result of its effect on local temperature anomalies through teleconnections. These findings indicate that the IOBW index can potentially enhance the lead time for dengue forecasts, leading to better-planned and more impactful outbreak responses.

Aedes albopictus is not an arbovirus aficionado - Impacts of sylvatic flavivirus infection in vectors and hosts on mosquito engorgement on non-human primates

The contact structure between vertebrate hosts and arthropod vectors plays a key role in the spread of arthropod-borne viruses (arboviruses); thus, it is important to determine whether arbovirus infection of either host or vector alters vector feeding behavior. Here we leveraged a study of the replication dynamics of two arboviruses isolated from their ancestral cycles in paleotropical forests, sylvatic dengue-2 (DENV-2) and Zika (ZIKV), in one non-human primate (NHP) species from the paleotropics (cynomolgus macaques, Macaca fascicularis) and one from the neotropics (squirrel monkeys, Saimiri boliviensis) to test the effect of both vector and host infection with each virus on completion of blood feeding (engorgement) of the mosquito Aedes albopictus. Although mosquitoes were starved and given no choice of hosts, engorgement rates varied dramatically, from 0% to 100%. While neither vector nor host infection systematically affected engorgement, NHP species and body temperature at the time of feeding did. We also interrogated the effect of repeated mosquito bites on cytokine expression and found that epidermal growth factor (EGF) and macrophage migration inhibitory factor (MIF) concentrations were dynamically associated with exposure to mosquito bites. This study highlights the importance of incorporating individual-level heterogeneity of vector biting in arbovirus transmission models.

Unexpected behavioural adaptation of yellow fever mosquitoes in response to high temperatures

Temperature is a major ecological driver of mosquito-borne diseases as it influences the life-history of both the mosquito and the pathogen harboured within it. Understanding the mosquitoes' thermal biology is essential to inform risk prediction models of such diseases. Mosquitoes can respond to temperatures by microhabitat selection through thermal preference. However, it has not yet been considered that mosquitoes are likely to adapt to changing temperatures, for example during climate change, and alter their preference over evolutionary time. We investigated this by rearing six cohorts of the yellow fever mosquito Aedes aegypti at two temperatures (24 °C, 30 °C) for 20 generations and used these cohorts to explicitly separate the effects of long-term evolution and within-generation acclimation on their thermal preferences in a thermal gradient of 20-35 °C. We found that warm-evolved mosquitoes spent 31.5% less time at high temperatures, which affects their efficiency as a vector. This study reveals the complex interplay of experimental evolution, rearing temperatures, and thermal preference in Ae. aegypti mosquitoes. It highlights the significance of incorporating mosquito microhabitat selection in disease transmission models, especially in the context of climate change.

Identifying Knowledge Gaps through the Systematic Review of Temperature-Driven Variability in the Competence of Aedes aegypti and Ae. albopictus for Chikungunya Virus

Temperature is a well-known effector of several transmission factors of mosquito-borne viruses, including within mosquito dynamics. These dynamics are often characterized by vector competence and the extrinsic incubation period (EIP). Vector competence is the intrinsic ability of a mosquito population to become infected with and transmit a virus, while EIP is the time it takes for the virus to reach the salivary glands and be expectorated following an infectious bloodmeal. Temperatures outside the optimal range act on life traits, decreasing transmission potential, while increasing temperature within the optimal range correlates to increasing vector competence and a decreased EIP. These relatively well-studied effects of other Aedes borne viruses (dengue and Zika) are used to make predictions about transmission efficiency, including the challenges presented by urban heat islands and climate change. However, the knowledge of temperature and chikungunya (CHIKV) dynamics within its two primary vectors-Ae. aegypti and Ae. albopictus-remains less characterized, even though CHIKV remains a virus of public-health importance. Here, we review the literature and summarize the state of the literature on CHIKV and temperature dependence of vector competence and EIP and use these data to demonstrate how the remaining knowledge gap might confound the ability to adequately predict and, thus, prepare for future outbreaks.

Automated analysis of feeding behaviors of females of the mosquito Aedes aegypti using a modified flyPAD system

Mosquitoes present a global health challenge due to their ability to transmit human and animal pathogens upon biting and blood feeding. The investigation of tastants detected by mosquitoes and their associated feeding behaviors is needed to answer physiological and ecological questions that could lead to novel control methods. A high-throughput system originally developed for research in fruit flies feeding behavior, the flyPAD, was adapted and tested for behaviors associated with the interaction or consumption of liquid diets offered to females of the mosquito Aedes aegypti Liverpool strain. Females were given water, sucrose solution and sheep blood in choice and non-choice assays. The volume ingested was evaluated with fluorescein. The placement of the system on a heated surface allowed blood consumption, and without females puncturing a membrane. The flyPAD system recorded nine feeding behavioral variables, of which the number of sips and number of activity bouts correlated with meal volume ingested for both sucrose solution and blood. The adaptation to mosquitoes of the flyPAD system differentiated feeding behavior variables between two feeding deterrents, capsaicin, and caffeine. The flyPAD has potential to quickly assess diverse tastants in both sucrose and blood and may contribute to characterizing more precisely their mode of action.

Arbovirus Transmission Predictions Are Affected by Both Temperature Data Source and Modeling Methodologies across Cities in Colombia

Weather variables has been described as major drivers of vector proliferation and arbovirus transmission. Among them, temperature has consistently been found to be impactful in transmission dynamics, and models that incorporate temperature have been widely used to evaluate and forecast transmission or arboviruses like dengue, zika, or chikungunya virus. Further, there is growing evidence of the importance of micro-environmental temperatures in driving transmission of Aedes aegypti-borne viruses, as these mosquitoes tend to live within domiciles. Yet there is still a considerable gap in our understanding of how accounting for micro-environmental temperatures in models varies from the use of other widely-used, macro-level temperature measures. This effort combines field-collected data of both indoor and outdoor household associated temperatures and weather station temperature data from three Colombian cities to describe the relationship between the measures representing temperature at the micro- and macro-levels. These data indicate that weather station data may not accurately capture the temperature profiles of indoor micro-environments. However, using these data sources, the basic reproductive number for arboviruses was calculated by means of three modeling efforts to investigate whether temperature measure differences translated to differential transmission predictions. Across all three cities, it was determined that the modeling method was more often impactful rather than the temperature data-source, though no consistent pattern was immediately clear. This suggests that temperature data sources and modeling methods are important for precision in arbovirus transmission predictions, and more studies are needed to parse out this complex interaction.