Browsing by Author "Robert, Michael A."

Now showing 1 - 9 of 9
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    Discrete and continuous mathematical investigation of juvenile mosquito dynamics
    Walker, Melody Anne (Virginia Tech, 2021-06-15)
    There are thousands of species of mosquitoes, but only a handful of these species carry pathogens that cause human diseases. Here, we study two species, Aedes albopictus and Aedes aegypti, which transmit infections such as dengue, Zika, Mayaro virus, and La Crosse virus. Curtailing these diseases is a good reason to consider control of mosquito populations. However, mosquitoes are quite hardy and spraying of pesticides is typically a short-term solution. Thus, more long-term solutions require careful thought about mosquito populations, including early juvenile aquatic stages: egg, larva, and pupa. In this dissertation, we examine the factors that affect the dynamics of aquatic stages by creating mathematical models. The goal is to assess what key biological features most impact the total population. Both Aedes albopictus and Aedes aegypti lay eggs in small containers, producing limitations on space and food. We investigate how restricting resources changes development time, survival to adulthood, and body mass at emergence. The interactions between these changes are complicated, so to disentangle their effects we create three different mathematical models. The first model is discrete in time and focuses on the best way to incorporate the influence of larval density. We compare the impact of larval density by inputting seven different functional forms altering survival and development time. Larval density used in the model is determined from the average of the population size over the past one to thirty-six days. The second model is also discrete in time but focuses on the interaction between survival, development time, and mass. This model considers three levels of mass. Here, we use the density-dependent function determined from our first model and fit the maximum value for development time from experimental data. Survival values are fit using constants and a density-dependent function. Finally, growth is built in as a function of food. Food decreases at each time point as a function of the total larvae in the environment. We compare between model formulations with Akaike information criterion. The third model examines the ramifications of constricting resources on growth verses death. We employ a partial differential equation that has three independent variables: time, age, and mass. We find that density dependence is highly influential in the maturation of mosquitoes, and it is more essential to include its impacts on development time than on survival. These findings can be incorporated into a larger framework of disease dynamics, and give insight into better control of mosquitoes and disease spread.
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    Effects of Contact Tracing and Self-Reporting in a Network Disease Model
    Gandhi, Punit; Robert, Michael A.; Palacios, John; Chan, David (2022-02-15)
    We examine the effects of symptomatic individuals getting tested and the use of contact tracing in a network model of disease transmission on different epidemio-logical metrics. These metrics include the length of the epidemic, number of people infected, number of tests performed, and the likelihood of an epidemic occurring. We utilize a network model to resolve the influence of contact patterns between individuals as opposed to assuming mass action where all individuals are connected to each other. We find that the effects of self-reporting and contact tracing vary depending on the structure of the network. We also compare the results from the network model with an analogous ODE model that assumes mass action and demonstrate how the results can be dramatically and surprisingly different.
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    Increasing arbovirus risk in Chile and neighboring countries in the Southern Cone of South America
    Eollo, Elizabet L.; Sippy, Rachel; Robert, Michael A.; Ayala, Salvador; Pizard, Carlos J. Barboza; Perez-Estigarribia, Pastor E.; Stewart-Ibarra, Anna M. (Elsevier, 2023-06-23)
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    Ingested histamine and serotonin interact to alter Anopheles stephensi feeding and flight behavior and infection with Plasmodium parasites
    Coles, Taylor A.; Briggs, Anna M.; Hambly, Malayna G.; Cespedes, Nora; Fellows, Abigail M.; Kaylor, Hannah L.; Adams, Alexandria D.; Van Susteren, Grace; Bentil, Ronald E.; Robert, Michael A.; Riffell, Jeffrey A.; Lewis, Edwin E.; Luckhart, Shirley (Frontiers, 2023-07-24)
    Blood levels of histamine and serotonin (5-HT) are altered in human malaria, and, at these levels, we have shown they have broad, independent effects on Anopheles stephensi following ingestion by this invasive mosquito. Given that histamine and 5-HT are ingested together under natural conditions and that histaminergic and serotonergic signaling are networked in other organisms, we examined effects of combinations of these biogenic amines provisioned to A. stephensi at healthy human levels (high 5-HT, low histamine) or levels associated with severe malaria (low 5-HT, high histamine). Treatments were delivered in water (priming) before feeding A. stephensi on Plasmodium yoelii-infected mice or via artificial blood meal. Relative to effects of histamine and 5-HT alone, effects of biogenic amine combinations were complex. Biogenic amine treatments had the greatest impact on the first oviposition cycle, with high histamine moderating low 5-HT effects in combination. In contrast, clutch sizes were similar across combination and individual treatments. While high histamine alone increased uninfected A. stephensi weekly lifetime blood feeding, neither combination altered this tendency relative to controls. The tendency to re-feed 2 weeks after the first blood meal was altered by combination treatments, but this depended on mode of delivery. For blood delivery, malaria-associated treatments yielded higher percentages of fed females relative to healthy-associated treatments, but the converse was true for priming. Female mosquitoes treated with the malaria-associated combination exhibited enhanced flight behavior and object inspection relative to controls and healthy combination treatment. Mosquitoes primed with the malaria-associated combination exhibited higher mean oocysts and sporozoite infection prevalence relative to the healthy combination, with high histamine having a dominant effect on these patterns. Compared with uninfected A. stephensi, the tendency of infected mosquitoes to take a second blood meal revealed an interaction of biogenic amines with infection. We used a mathematical model to project the impacts of different levels of biogenic amines and associated changes on outbreaks in human populations. While not all outbreak parameters were impacted the same, the sum of effects suggests that histamine and 5-HT alter the likelihood of transmission by mosquitoes that feed on hosts with symptomatic malaria versus a healthy host.
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    Modeling the effects of Aedes aegypti’s larval environment on adult body mass at emergence
    Walker, Melody; Chandrasegaran, Karthikeyan; Vinauger, Clément; Robert, Michael A.; Childs, Lauren M. (PLoS, 2021-11-22)
    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.
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    Multiplicative Mixed-Effects Modelling of Dengue Incidence: An Analysis of the 2019 Outbreak in the Dominican Republic
    Freitas, Adelaide; Rodrigues, Helena Sofia; Martins, Natália; Iutis, Adela; Robert, Michael A.; Herrera, Demian; Colomé-Hidalgo, Manuel (MDPI, 2023-02-01)
    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.
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    Observational Characterization of the Ecological and Environmental Features Associated with the Presence of Oropouche Virus and the Primary Vector Culicoides paraenesis: Data Synthesis and Systematic Review
    Walsh, Christine E. S.; Robert, Michael A.; Christofferson, Rebecca C. (MDPI, 2021-09-01)
    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 paraenesis, 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.
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    Relationship between Climate Variables and Dengue Incidence in Argentina
    Lopez, Maria S.; Gomez, Andre A.; Müller, Gabriela V.; Walker, Elisabet; Robert, Michael A.; Estallo, Elizabet L. (US HHS, 2023-05-24)
    BACKGROUND: 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. OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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    Spatiotemporal and meteorological relationships in dengue transmission in the Dominican Republic, 2015–2019
    Robert, Michael A.; Rodrigues, Helena S.; Herrera, Demian; de Mata Donado Campos, Juan; Morilla, Fernando; Del Águila Mejía, Javier; Guardado, María E.; Skewes, Ronald; Colomé-Hidalgo, Manuel (2023-06-02)
    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.