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Principal Investigator: Dustin Brisson
Organization: UNIVERSITY OF PENNSYLVANIA
Fiscal Year: 2024
Award: $580,899
Funding agency: National Institute of Allergy and Infectious Diseases
The proposed projects are a comprehensive effort to rigorously investigate the contribution of phenology -
or seasonal activity - to pathogen transmission dynamics using 3 widespread zoonotic pathogens carried
by black-legged ticks. Variation in seasonal activity patterns and life-history events, which are well
documented in species inhabiting temperate regions, can result in dramatic population dynamics including
population extinctions or explosions. Phenological variation across time and geography also alters the
frequency and strength of inter-species interactions and thus opportunities for pathogen transmission,
which likely has profound impacts on pathogen transmission dynamics and human disease risk. Despite
the likely importance to public health, the consequences of phenological variation on disease transmission
dynamics remain notably under-studied in many complex zoonotic disease systems. The tick-borne
disease system in North America provides the ideal system to determine the impact of phenology on
pathogen transmission dynamics both theoretically and empirically. We will build and evaluate solvable
analytical models, computational models, and advanced statistical models, all of which explicitly
incorporate tick seasonal activity, and validate these models with empirical data from natural field sites.
The proposed projects will (1) determine the quantitative impact of different phenological scenarios on the
transmission dynamics of, and thus disease risk from, 3 human pathogens, (2) empirically evaluate model
predictions, and (3) identify specific phenological and environmental features that result in different
transmission dynamic outcomes among pathogen species. We will develop 3 modeling frameworks to
investigate the impact of phenology on transmission dynamics, identify and quantify phenological and
environmental drivers of transmission dynamics in 3 important human pathogens, and empirically validate
the outcomes of the theoretical and statistical models. Empirical validation of both the phenological drivers
and model predictions is essential not only for public health management but also to identify mechanistic
processes driving these patterns. The proposed research provides both theoretical and empirical
frameworks to investigate the impact of phenology on transmission dynamics in the multitude of disease
systems involving multiple host species or life-stages from insect-vectored plant pathogens to pathogens
with multi-host life-cycles.
Terms: <Automobile Driving><Black-legged Tick><Complex><Computer Models><Computerized Models><Data><Deer Tick><Disease><Disorder><Event><Explosion><Extinction><Frequencies><Geography><I scapularis><I. scapularis><Insect Vectors><Ix scalpularis><Ix. scapularis><Ixodes dammini><Ixodes scapularis><Ixodida><Life><Life Cycle><Life Cycle Stages><Modeling><North America><Outcome><Parasites><Pattern><Plants><Population><Population Dynamics><Probabilistic Models><Probability Models><Process><Public Health><Research><Seasons><Site><Statistical Models><System><Theoretic Models><Theoretical model><Tick-Borne Diseases><Ticks><Time><Transmission><Validation><Variant><Variation><Zoonoses><Zoonotic><Zoonotic Infection><blacklegged tick><communicable disease transmission><computational modeling><computational models><computer based models><computer based prediction><computerized modeling><disease risk><disease transmission><disorder risk><driving><health care management><health management><healthcare management><human disease><human pathogen><infectious disease transmission><life course><life history><pathogen><predictive modeling><statistical linear mixed models><statistical linear models><tick-borne illness><tickborne disease><tickborne illness><transmission process><validations>