MS04 - MEPI-07 Part 1 of 3

Recent Trends in Mathematics of Vector-borne Diseases and Control (Part 1)

Tuesday, July 15 at 4:00pm

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Note: this minisymposia has multiple sessions. The other sessions are: Part-2 and Part-3.

Abba Gumel (University of Maryland), Alex Safsten, Arnaja Mitra (both University of Maryland)

Description:

Vector-borne diseases, such as malaria, dengue, Lyme disease, leishmaniasis, and West Nile virus, constitute over 17% of all infectious diseases of humans, with malaria (which causes in excess of 600,000 deaths annually, mostly in children under the age of five) being the most important of these diseases. These vectors are typically controlled by using insecticide-based control measures, and their lifecycle (and those of the pathogens they vector) are greatly affected by changes in local climatic conditions, such as temperature, precipitation, and humidity. This minisymposium brings together researchers to discuss the recent advances in modeling the spread and control of vector-borne diseases. Some of the topics to be discussed include whether or not the recent quest to eradicate malaria is feasible using currently-available insecticides-based control resources, assessing the impact of insecticide and drug resistance on vector population abundance and the intensity of the disease they cause, assessing the potential for alternative biocontrol measures (such as sterile insect technique and the use of Wolbachia infection-based measures and the release of gene drives, such as CRISPR-Cas9) to control vector species, assessing the impact of climate change on the distribution and abundance of vector species etc.

Michael Robert

Virginia Tech

"Climate-informed mitigation of mosquito-borne disease: the case of dengue in an emerging environment"

Mosquito-borne diseases endemic to areas with tropical climates have been spreading in temperate regions of the world with greater frequency in recent years. Numerous factors contribute to this spread, including urbanization, increases in global travel, and changes in temperature, precipitation, and humidity patterns due to climate change. Understanding the role of climate in mosquito-borne disease emergence and spread is critical for projecting future outbreaks and informing control measures. We have developed mathematical models incorporating temperature and precipitation into mosquito population and disease transmission dynamics to investigate how seasonal fluctuations in meteorological variables impact the probability and magnitude of outbreaks. We have parameterized these models for recent dengue outbreaks in the temperate city of Córdoba, Argentina, and with these models, we investigate strategies for implementing different mosquito control measures. By incorporating projections for future climate scenarios, we also investigate how approaches to control may need to change as temperatures increase and precipitation patterns become more erratic as a result of climate change.

Salihu Musa

University of Maryland

"Mathematical modeling of the geo-spatial dynamics of Lyme disease under various climate change projection scenarios"

Lyme disease, the most common vector-borne disease in North America, is increasingly prevalent in Maryland, with climate change, particularly rising temperatures, accelerating its spread. Temperature plays a critical role in the ecology of Ixodes scapularis ticks and the transmission dynamics of Borrelia burgdorferi, affecting both vector-host interactions and the seasonal timing of disease risk. In this study, we develop a temperature-driven epidemiological model to investigate the spatial and temporal spread of Lyme disease across Maryland. By integrating ecological and climate datasets with temperature- dependent tick-host interactions, we assess how warming patterns influence tick proliferation, seasonal activity, and disease transmission intensity. Simulations under Representative Concentration Pathways (RCP 4.5 and 8.5) project substantial increases in disease burden, with particularly pronounced effects in Central and Western Maryland. We further evaluate the impact of vector control strategies and show that combining habitat modification with rodent-targeted interventions significantly reduces the basic reproduction number (Ro), especially when community participation in environmental clearance exceeds 50%. Spatial projections also indicate a northward shift in high-risk zones, highlighting the evolving geographic landscape of Lyme disease risk. This work provides a quantitative framework for optimizing prevention strategies and informing climate-resilient public health policies aimed at mitigating Lyme disease transmission in a warming environment.

Kathleen Hoffman

University of Maryland Baltimore County

"Parameter Sensitivity, Identifiability, & Estimation for a Data-Driven Model of Malaria"

Parameters are ubiquitous in biological models and significantly influence the model behavior. While some parameters can be estimated from experimental data, many cannot . This work focuses on the role of parameters in two vector-borne diseases: malaria and dengue fever. Parameter identifiability considers the mapping of parameters to observables with and without noise. We compute the Sobol index to determine the sensitivity of the parameters, that is how the output changes in response to changes in the parameter values. Finally, we use techniques from data assimilation for forward prediction and to estimate parameters that cannot be determined from experimental data alone. Joint work with Mac Luu, Katie Gurski, Animikh Biswas, Nigel Seymour, Owen McMann

Abba Gumel

University of Maryland

"Recent advances and challenges in the mathematics of malaria dynamics"

Since its spillover to humans some 12,000 years ago, malaria, a deadly parasitic disease transmitted between humans via the bite of an infected adult female Anopheles mosquitoes, remains one of the deadliest infectious diseases of mankind. Much progress has been recorded in the battle against malaria over the last decade or two, prompting a renewed quest to significantly reduce its burden (by 90% by 2030) or eradicate it by 2040. Unfortunately, these efforts are threatened by several challenges, such as widespread resistance to all the currently-available insecticides used in vector control, evolution of drug resistance, climate change, land-use changes, emergence of invasive species, human mobility (rural-urban migration), and quality of public health infrastructure and care. I will discuss some of these advances and challenges associated with the mathematical modeling and analysis of malaria transmission dynamics, aimed at assessing the impacts of some of the aforementioned factors that potentially get in the way of the malaria eradication objective.

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Annual Meeting for the Society for Mathematical Biology, 2025.