MS01 - MEPI-1
Cartoon Room 2 (#3147) in The Ohio Union

Climate and vector-borne disease: insights from mathematical modeling

Monday, July 17 at 10:30am

SMB2023 SMB2023 Follow Monday during the "MS01" time block.
Room assignment: Cartoon Room 2 (#3147) in The Ohio Union.
Note: this minisymposia has multiple sessions. The other session is MS02-MEPI-1 (click here).

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Michael Robert, Zhuolin Qu, Christina Cobbold


Many vector-borne diseases are emerging in previously naive areas, while other regions are experiencing a rapid intensification of endemic diseases. Although there are a number of factors driving the spread and intensity of vector-borne diseases, it is likely that climate is one of the primary drivers. Vector-borne diseases are particularly influenced by climate and changes therein because precipitation, temperature, and humidity play critical roles in vector life cycles, and these meteorological variables can also have an impact on pathogen life cycles and pathogen transmission. While it is widely accepted that changes in climate are influencing changes in vector-borne disease emergence, spread, and intensity, many questions remain about how these changes are impacting different diseases. Mathematical modeling is a particularly useful tool for investigating how meteorological variables influence different components of the vector life cycle, as well as the pathogen transmission cycle. Additionally, models can help us better understand how future changes in climate may impact disease transmission and how mitigation strategies may slow or prevent current and future spread. In this minisymposium, we focus on studies of climate and vector-borne disease through the lens of mathematical modeling. The minisymposium feature speakers utilizing various different modeling approaches to investigate questions about a number of different diseases.

Christina Cobbold

University of Glasgow (School of Mathematics and Statistics)
"Vector population dynamics and trait variation drive trends in global disease incidence"
Climate change is having profound effects on the incidence of vector borne disease. However, developing effective measures of disease risk on a global scale are challenged by the complex ways in which environmental variation acts in vector-host-pathogen systems. Current models over-simplify the interaction between vector traits and environmental variation and so risk mis-estimating disease risk. Here, we derive a mathematical model for Aedes albopictus, the vector of dengue, and demonstrate how the interaction of vector traits and population dynamics explain the location, magnitude and timing of historical dengue outbreaks. We find long lived individuals that developed under favourable conditions can persist within the population long after the environmental conditions that created them have passed and may consequently have a disproportionate effect on pathogen transmission dynamics that cannot be accounted for by approaches that omit trait dynamics.
Additional authors: Dominic Brass (UK Centre for Ecology and Hydrology); Steven White (UK Centre for Ecology and Hydrology); Beth Purse (UK Centre for Ecology and Hydrology); David Ewing (Biomathematics and Statistics Scotland)

Morgan Jackson

Virginia Commonwealth University (Department of Mathematics and Applied Mathematics)
"Evaluating a Temperature-dependent Mosquito Population Model"
Dengue Virus causes over 390 million infections and around 40,000 deaths each year. This virus is primarily transmitted by the mosquito Aedes aegypti. The life cycle of these mosquitos is significantly impacted by temperature, however, temperature in often neglected in mechanistic models. Predictive models of mosquito populations thus require the inclusion of temperature and are valuable for helping medical officials plan for the impact of outbreaks. Using mosquito and climate data collected in Córdoba, Argentina from 2010-2013, we developed a non-autonomous ordinary differential equations model that includes temperature dependent parameters associated with mosquito life history. We performed local sensitivity and identifiability analysis to determine which model parameters should be estimated. We explored the effects of incorporating temperature in different combinations of life history characteristics to find the most parsimonious model that includes temperature. Additionally, we estimated values for combinations of density-dependent parameters to improve the model fit. These parameters control nonlinear population regulation but are often difficult to estimate from data alone. We found that including even just three temperature-based parameters: eggs laid per adult female, development rate of juveniles to adults, and adult mortality rate, produced a model that matches the data well. Additionally, we fit a density-dependent parameter and combinations of density dependent parameters to improve the model fit. We discuss these results in the context of improving mosquito population and dengue epidemiological models.
Additional authors: Elizabet Estallo (Instituto de Investigaciones Biológicas y Tecnológicas, CONICET - Universidad Nacional de Córdoba, Centro de Investigaciones Entomológicas de Córdoba, Argentina); Cheng Ly (Virginia Commonwealth University); Michael Robert (Virginia Tech)

Stacey Smith?

The University of Ottawa (Department of Mathematics and Faculty of Medicine)
"Comparing malaria surveillance with periodic spraying in the presence of insecticide-resistant mosquitoes: Should we spray regularly or based on human infections?"
There is an urgent need for more understanding of the effects of surveillance on malaria control. Indoor residual spraying has had beneficial effects on global malaria reduction, but resistance to the insecticide poses a threat to eradication. We develop a model of impulsive differential equations to account for a resistant strain of mosquitoes that is entirely immune to the insecticide. The impulse is triggered either due to periodic spraying or when a critical number of malaria cases are detected. For small mutation rates, the mosquito-only submodel exhibits either a single mutant-only equilibrium, a mutant-only equilibrium and a single coexistence equilibrium, or a mutant-only equilibrium and a pair of coexistence equilibria. Bistability is a likely outcome, while the effect of impulses is to introduce a saddle-node bifurcation, resulting in persistence of malaria in the form of impulsive periodic orbits. If certain parameters are small, triggering the insecticide based on number of malaria cases is asymptotically equivalent to spraying periodically.
Additional authors: Kevin Church

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Annual Meeting for the Society for Mathematical Biology, 2023.