Michael A. Robert

The community composition of vectors and hosts plays a critical role in determining risk of vector-borne disease transmission. Aedes aegypti and Aedes albopictus, two mosquito species that both transmit the viruses that cause dengue, chikungunya, and Zika, share habitat requirements and compete for resources at the larval stage. Ae. albopictus is generally considered a better competitor under many conditions, while Ae. aegypti is able to tolerate higher temperatures and is generally a more competent vector for many pathogens. We develop a stage-structured ordinary differential equation model that incorporates competition between the juvenile stages of two mosquito populations. We incorporate experimental constraints on competition coefficients for high and low quality food resources and explore differences in the potential outcomes of competition. We then incorporate temperature-dependent fecundity rates, juvenile development rates, and adult mortality rates for each species, and we explore competition outcomes as a function of temperature. We show that regions of coexistence and competitive exclusion depend on food quality and relative values of temperature-dependent life history parameters. Finally, we investigate the combined impacts of temperature and competition on the potential for dengue transmission, and we discuss our results in the context of present and future risk of mosquito-borne disease transmission.

Dengue is endemic throughout the tropical areas of the Americas, but little is known about its regional dynamics. We examined seasonal and multiannual dengue trends across the Americas and possible underlying mechanisms using monthly dengue surveillance data from 14 countries. We collected monthly dengue case data from 241 subnational locations in 14 countries, ranging from 1985 to 2018 (6 to 22 years), and used wavelet analysis to isolate seasonal (8 to 16 months) and multiannual (17+ months) patterns. For each location, we assessed seasonal and multiannual dynamics as well as coherence and differences in timing of dengue cycles between 22,578 location pairs. We assessed patterns in coherence over time and space and compared these patterns to variations in temperature, rainfall, and El Niño Southern Oscillation patterns. Strong synchrony in dengue dynamics was identified across the region at the seasonal and multiannual scales. Seasonal dengue dynamics were associated with local climate patterns and dengue dynamics in nearby locations. High synchrony at multiannual scales indicated that large dengue epidemics were shared across the region, with an average temporal lag of only 6 months at distances of up to 10,000 kilometers. Synchrony of these epidemics likely reflects both regional climate variability and human movement. Observed dengue dynamics were not unique to individual countries in the Americas but rather extended across the region reflecting climatic and nonclimatic drivers. These findings can support the development of better early warning tools to support epidemic preparedness and response and underscore the importance of working collaboratively across borders.

Dengue has broadened its global distribution substantially in the past two decades, and many endemic areas are experiencing increases in incidence. The Dominican Republic recently experienced its two largest outbreaks to date with 16,836 reported cases in 2015 and 20,123 reported cases in 2019. With continued increases in dengue transmission, developing tools to better prepare healthcare systems and mosquito control agencies is of critical importance. Before such tools can be developed, however, we must first better understand potential drivers of dengue transmission. To that end, we focus in this paper on determining relationships between climate variables and dengue transmission with an emphasis on eight provinces and the capital city of the Dominican Republic in the period 2015–2019. We present summary statistics for dengue cases, temperature, precipitation, and relative humidity in this period, and we conduct an analysis of correlated lags between climate variables and dengue cases as well as correlated lags among dengue cases in each of the nine locations. We find that the southwestern province of Barahona had the largest dengue incidence in both 2015 and 2019. Among all climate variables considered, lags between relative humidity variables and dengue cases were the most frequently correlated. We found that most locations had significant correlations with cases in other locations at lags of zero weeks. These results can be used to improve predictive models of dengue transmission in the country.

Climate change is an important driver of the increased spread of dengue from tropical and subtropical regions to temperate areas around the world. Climate variables such as temperature and precipitation influence the dengue vector’s biology, physiology, abundance, and life cycle. Thus, an analysis is needed of changes in climate change and their possible relationships with dengue incidence and the growing occurrence of epidemics recorded in recent decades. This study aimed to assess the increasing incidence of dengue driven by climate change at the southern limits of dengue virus transmission in South America. We analyzed the evolution of climatological, epidemiological, and biological variables by comparing a period of time without the presence of dengue cases (1976–1997) to a more recent period of time in which dengue cases and important outbreaks occurred (1998–2020). In our analysis, we consider climate variables associated with temperature and precipitation, epidemiological variables such as the number of reported dengue cases and incidence of dengue, and biological variables such as the optimal temperature ranges for transmission of dengue vector. The presence of dengue cases and epidemic outbreaks are observed to be consistent with positive trends in temperature and anomalies from long-term means. Dengue cases do not seem to be associated with precipitation trends and anomalies. The number of days with optimal temperatures for dengue transmission increased from the period without dengue cases to the period with occurrences of dengue cases. The number of months with optimal transmission temperatures also increased between periods but to a lesser extent. The higher incidence of dengue virus and its expansion to different regions of Argentina seem to be associated with temperature increases in the country during the past two decades. The active surveillance of both the vector and associated arboviruses, together with continued meteorological data collection, will facilitate the assessment and prediction of future epidemics that use trends in the accelerated changes in climate. Such surveillance should go hand in hand with efforts to improve the understanding of the mechanisms driving the geographic expansion of dengue and other arboviruses beyond the current limits. https://doi.org/10.1289/EHP11616

Dengue is a vector-borne disease that is endemic to several countries, including the Dominican Republic, which has experienced dengue outbreaks for over four decades. With outbreaks growing in incidence in recent years, it is becoming increasingly important to develop better tools to understand drivers of dengue transmission. Such tools are critical for providing timely information to assist healthcare authorities in preparing human, material, and medical resources for outbreaks. Here, we investigate associations between meteorological variables and dengue transmission in the Dominican Republic in 2019, the year in which the country’s largest outbreak to date ocurred. We apply generalized linear mixed modelling with gamma family and log link to model the weekly dengue incidence rate. Because correlations in lags between climate variables and dengue cases exhibited different behaviour among provinces, a backward-type selection method was executed to find a final model with lags in the explanatory variables. We find that in the best models, meteorological conditions such as temperature and rainfall have an impact with a delay of 2–5 weeks in the development of an outbreak, ensuring breeding conditions for mosquitoes.

Dengue has broadened its global distribution substantially in the past two decades, and many endemic areas are experiencing increases in incidence. The Dominican Republic recently experienced its two largest outbreaks to date with 16,836 reported cases in 2015 and 20,123 reported cases in 2019. With this upward trend in dengue transmission, developing tools to better prepare healthcare systems and mosquito control agencies is of critical importance. Before such tools can be developed, however, we must first better understand potential drivers of dengue transmission. To that end, we focus in this paper on determining trends between climate variables and dengue transmission with an emphasis on eight provinces and the capital city of the Dominican Republic in the period 2015-2019. We present summary statistics for dengue cases, temperature, precipitation, and relative humidity in this period, and we conduct an analysis of correlated lags between climate variables and dengue cases as well as correlated lags among dengue cases in each of the nine locations. We find that the southwestern province of Barahona had the largest dengue incidence in both 2015 and 2019. Among all climate variables considered, lags between temperature variables and dengue cases were the most highly correlated. We found that most locations had significant correlations at lags of zero weeks; however, both Barahona and the northern province of Monte Cristi had significantly correlated lags with other provinces at up to eight weeks. These results can be used to improve predictive models of dengue transmission in the country.

Mosquitoes vector harmful pathogens that infect millions of people every year, and developing approaches to effectively control mosquitoes is a topic of great interest. However, the success of many control measures is highly dependent upon ecological, physiological, and life history traits of mosquito species. The behavior of mosquitoes and their potential to vector pathogens can also be impacted by these traits. One trait of interest is mosquito body mass, which depends upon many factors associated with the environment in which juvenile mosquitoes develop. Our experiments examined the impact of larval density on the body mass of Aedes aegypti mosquitoes, which are important vectors of dengue, Zika, yellow fever, and other pathogens. To investigate the interactions between the larval environment and mosquito body mass, we built a discrete time mathematical model that incorporates body mass, larval density, and food availability and fit the model to our experimental data. We considered three categories of model complexity informed by data, and selected the best model within each category using Akaike’s Information Criterion. We found that the larval environment is an important determinant of the body mass of mosquitoes upon emergence. Furthermore, we found that larval density has greater impact on body mass of adults at emergence than on development time, and that inclusion of density dependence in the survival of female aquatic stages in models is important. We discuss the implications of our results for the control of Aedes mosquitoes and on their potential to spread disease.

Oropouche virus (OROV), a member of the Orthobunyavirus genus, is an arthropod-borne virus (arbovirus) and is the etiologic agent of human and animal disease. The primary vector of OROV is presumed to be the biting midge, Culicoides paraensis, though Culex quinquefasciatus, Cq. venezuelensis, and Aedes serratus mosquitoes are considered secondary vectors. The objective of this systematic review is to characterize locations where OROV and/or its primary vector have been detected. Synthesis of known data through review of published literature regarding OROV and vectors was carried out through two independent searches: one search targeted to OROV, and another targeted towards the primary vector. A total of 911 records were returned, but only 90 (9.9%) articles satisfied all inclusion criteria. When locations were characterized, some common features were noted more frequently than others, though no one characteristic was significantly associated with presence of OROV using a logistic classification model. In a separate correlation analysis, vector presence was significantly correlated only with the presence of restingas. The lack of significant relationships is likely due to the paucity of data regarding OROV and its eco-epidemiology and highlights the importance of continued focus on characterizing this and other neglected tropical diseases.

Mosquitoes vector harmful pathogens that infect millions of people every year, and developing approaches to effectively control mosquitoes is a topic of great interest. However, the success of many control measures is highly dependent upon ecological, physiological, and life history traits of the mosquito species. The behavior of mosquitoes and their potential to vector pathogens can also be impacted by these traits. One trait of interest is mosquito body mass, which depends upon many factors associated with the environment in which juvenile mosquitoes develop. Our experiments examined the impact of larval density on the body mass of Aedes aegypti mosquitoes, which are important vectors of dengue, Zika, yellow fever, and other pathogens. To investigate the interactions between the larval environment and mosquito body mass, we built a discrete time mathematical model that incorporates body mass, larval density, and food availability and fit the model to our experimental data. We considered three categories of model complexity informed by data, and selected the best model within each category using Akaike’s Information Criterion. We found that the larval environment is an important determinant of the body mass of mosquitoes upon emergence. Furthermore, we found that larval density has greater impact on body mass of adults at emergence than on development time, and that inclusion of density dependence in the survival of female aquatic stages in models is important. We discuss the implications of our results for the control of Aedes mosquitoes and on their potential to spread disease. Author summary: In this work we examined how the environment in which young mosquitoes develop affects their adult body size as measured by adult body mass. Adult size has potential impacts on mosquito behavior and the ability of mosquitoes to transmit disease. We used a combination of experimental work and mathematical modeling to determine important factors affecting adult mosquito body size. In our model, we incorporated potentially interacting aspects of the mosquito life cycle and traits that affect mosquito growth as juveniles. These aspects include body mass, density of the population, and level of available resource. We compared different models to determine the one that best describes the data. As mass at emergence is linked to the success of adult mosquitoes to produce offspring and to their ability transmit pathogens, we discuss how important influences on development and survival of young mosquitoes affect mosquito control and disease spread.