All posts by Andrew Park

Ebola spillover risk

Andrew and lab alum Laura were involved in a recent study demonstrating the spatio-temporal risk of Ebola spillover in Africa. Using historical spillover data, the research (published in Emerging Infectious Diseases with lead author JP Schmidt of the Odum School of Ecology) shows that much of Central Africa (an historic hotspot) exhibits year round risk, while Southern, Eastern and Western regions of Africa show seasonal risk pulses often associated with transitions between wet and dry seasons. Until the recent 2014 outbreak in West Africa (the worst in history), that area was not considered to be a likely location for Ebola spillover. However, much of Africa, including West Africa, has the right blend of animal and human populations, as well as the climate conditions associated with former outbreaks, at certain times of year.

Jenna awarded summer CURO fellowship and presented at recent CURO symposium

Congratulations to Jenna on being awarded a summer 2017 CURO Fellowship to continue her studies in the lab. Jenna is researching patterns of tick diversity in the mammalian phylogeny to lay the foundations for better understanding the distribution of tick-borne diseases. She recently presented her research, “Patterns of tick-host associations in terrestrial mammals”, at the CURO symposium.

David awarded NSF Graduate Research Fellowship

David Vasquez, co-advised by Vanessa Ezenwa and Andrew Park, is pursuing his doctorate as part of the Interdisciplinary Disease Ecology Across Scales program. His research interests include disease ecology, social network theory, animal behavior, co-infection dynamics, ecoimmunology, and ecophysiology. Congratulations!

Predicting host species

Unsampled host species may associate with parasites of interest, but it can be challenging to predict with which species a given parasite will associate. We tested the predictability of a parasite’s host range (the set of host species it can infect) using a large database of helminth parasites of fish and boosted regression trees (recommended R resource). Tad Dallas led the research, which was recently published in Parasitology. While host traits and environmental variables were predictive, the single best class of predictors was the parasite community itself.

Situation critical

Led by Chris Dibble, we recently published a paper in JRS Interface that asked the question, “As R0 increases through 1, how long until a disease outbreak?”. Many systems have slowly increasing parasite fitness whether it’s through parasite evolution, demographic susceptible recruitment, or abandonment of vaccination (sweep rate). Susceptible populations are also regularly challenged with infectious individuals that have the potential to ‘spark’ an outbreak (spark rate). We integrated these two rates with epidemiology models and survivorship theory (which characterizes time to an event) to establish the waiting time to infectious disease emergence. We demonstrated that this time is influenced by factors such as infectious period, meaning that different infectious disease systems can cause outbreaks sooner after R0 exceeds 1, than others.

Spatial spread of Ebola

The Odum School’s Drew Kramer led a study on the recent spatial spread of Ebola in West Africa, and former lab member Laura Alexander and Andrew were contributors to this work, which was recently published in the Royal Society’s Open Science journal. Among the findings were that a gravity model provided a good description of the spread. This means that transmission between towns depended on the population size of each, and their distance from each other. Additionally, if one town was inside the hotspot of Guinea, Liberia and Sierra Leone and the other was outside, then risk of transmission out of the core region was lower, due to border closures. Individual movement patterns from cell phone data did not provide a competitively good fit. Counterfactual scenario building showed that the initial town infected would have a large effect on the regional extent of the spread of Ebola. As well as highlighting the importance of integrated geography in controlling epidemic processes, the study provides methods to predict vulnerable towns and those where intervention may have the most impact.

The big picture of infectious diseases

Macroecology is big. Spatially, temporally, taxonomically. Andrew is part of working group applying ideas from macroecology to host-parasite data. To kick things off, the group has written a review/synthesis paper explaining the goals and outlining the challenges and opportunities that lie ahead. It’s here.

Coral diseases under the microscope

As part of large group, lab members Ashton, Brett and Andrew have been exploring some of the challenges in identifying causal agents of disease affecting coral populations. The host species is elkhorn coral, which has been experiencing alarming declines in recent times. These studies help to develop surveillance, diagnostic and modeling approaches to learn as much as we can about this important reef-building coral species.

Refugia and drug resistance

MRSA and extensively drug-resistant TB are just two examples where we’re running out of solutions to combat pathogens. In animal health, refugia are increasingly discussed as a management strategy. Refugia are untreated subpopulations – they provide a safe haven for pathogens. By connecting refugia with drug-treated populations there is hope to limit the spread of drug resistance at an acceptable cost in terms of disease burden. Basically, the connections let drug-susceptible pathogens into the treated population to stop their drug-resistant counterparts taking over. We built a model to try and clarify when this sort of strategy might work (Park et al. 2015, Biol. Lett.). We found that the anticipated outcome (strong connections = high prevalence and low resistance in treated groups) was too simplistic. Rather, there are epidemiological and evolutionary interactions at work and these can be understood by decoupling transmission and selection through mathematical analysis.

(How) does vector species richness increase parasite transmission?

midgesThis is a question we got interested in through hemorrhagic disease, a vector-borne viral disease affecting white-tailed deer. We observed that disease reporting rate was positively associated with vector species richness (VSR: where species of midge belong to the large genus Culicoides). We thought this could be because high VSR:

  1. is associated with high vector abundance
  2. increases the likelihood that the vector community contains a highly competent subset
  3. is associated with long seasonal transmission if vector species in a community exhibit distinct phenologies

We found no support for 1 and 2 in our system, but strong support for 3. This means that VSR can manifest as functional diversity, facilitating parasite transmission. It remains to be seen if this operates more widely in vector borne diseases.