Research Pillars

What It Is

Atypical transmission refers to infectious disease spread that falls outside the most common or expected patterns of transmission and disease presentation. Rather than focusing only on the “normal” pathogen or the usual route of spread, this approach examines the unusual forms of infection and transmission that can have outsized consequences.

This includes:

• Asymptomatic carriage, where people carry and spread a pathogen without obvious symptoms
• Long-term chronic infections, which can sustain transmission over extended periods
• Rare or overlooked transmission routes, such as sexual transmission of pathogens not usually studied that way
• Spillover and shifting species ranges, where pathogens move between animal hosts and humans in unexpected ways

Why It Matters

Atypical transmission matters because variation often drives infectious disease dynamics. Unusual pathogens, rare presentations, and less common transmission routes can shape:

• Drug resistance evolution
• Pathogen persistence
• Pandemic emergence
• Spread in populations that are often underserved or undermeasured

Studying this variability is essential because it reveals the mechanisms that allow pathogens to persist, adapt, and emerge in new settings. It also helps us better understand infection and transmission in health-vulnerable populations, where endemic diseases may persist and novel pathogens may emerge.

What It Is

Infection history and co-infection refer to the idea that disease outcomes are rarely shaped by a single pathogen in isolation. Instead, current health and disease reflect the combined effects of past infections, ongoing infections, and interactions among multiple infectious agents, all filtered through host immunity and physiology.

This perspective looks beyond a snapshot of present illness to ask how a host’s prior exposures influence current responses to:

• New infectious diseases
• Chronic infections
• Acute infections
• Environmental exposures
• Long-term health outcomes more broadly

Why It Matters

This matters because health outcomes are often the product of cumulative exposure, not just current infection status. A person’s history of infection may alter immune function, physiology, and general wellness in ways that shape:

• Susceptibility to future infection
• Severity of disease
• Interactions between pathogens
• Responses to chronic disease and environmental stressors
• Patterns of heterogeneity across populations

Understanding these layered effects is essential for explaining why individuals and populations respond differently to the same pathogen or exposure.

What It Is

Vector-borne diseases are infections and related health conditions transmitted by arthropods such as ticks and mosquitoes. In this context, the focus is especially on ticks, which are the most important vector-borne disease vectors in the United States by a wide margin.

Ticks are associated with a remarkably broad range of health threats, including at least 15 different pathogens and conditions, spanning:

• Viruses
• Bacteria
• Protozoa
• Toxin- or allergy-related syndromes, such as alpha-gal syndrome

This is not a single-disease problem. Tick-borne disease ecology is shaped by multiple pathogens, multiple vector species, and frequent co-infections.

Why It Matters

Vector-borne diseases matter because they represent a major and growing public health challenge, especially in regions where tick populations and pathogen diversity are high. In Pennsylvania, and especially in Centre County, the risk is particularly important:

• Centre County is one of the Lyme disease hotspots in Pennsylvania
• Pennsylvania is a national hotspot for tick-borne pathogens
• Co-infections are common, making diagnosis, treatment, and surveillance more complicated

The problem is further intensified by the presence of multiple medically important tick species, including:

• Hard ticks such as Ixodes, Amblyomma, and Dermacentor
• Soft ticks
• Invasive ticks, including Haemaphysalis species such as the Asian longhorned tick

What It Is

Model-based interventions use mathematical and computational models to understand infectious disease systems and to evaluate how best to prevent, manage, and respond to disease. Models provide a common framework for linking processes across biological scales—from pathogens and hosts to populations and environments—and for translating knowledge across disciplines.

Rather than serving only as predictive tools, models help explain how disease systems work and how interventions may succeed, fail, or produce unintended consequences.

This includes using models to study:

• The spread of emerging infectious diseases
• The trajectory of outbreaks
• The impacts of disease management strategies
• Behavioral interventions
• Interactions among pharmaceuticals
• Indirect, off-target, or delayed effects of interventions
• The biological mechanisms underlying observed patterns in data

Why It Matters

Model-based interventions matter because they allow researchers and decision-makers to test many possible scenarios before acting in the real world. Infectious disease systems are complex, and interventions often have effects that are difficult to anticipate without a formal framework. Models help us:

• Assess and anticipate disease spread
• Compare alternative intervention strategies
• Estimate the likely effects of control measures
• Identify unintended consequences
• Understand interactions between biology, behavior, and environment

This is especially important for emerging infections, where decisions often must be made quickly and under uncertainty.