What is parasite ecology?

Since you’re reading a blog called Parasite Ecology, you probably already know what a “parasite ecologist” studies. If you do, you’re a member of a global minority – congratulations! Your membership ID card will be arriving in the mail any day now.

If I had a nickel for every time someone asked me what “parasite ecologists” study, or came to the blog after Googling “what is parasite ecology?”, I could buy another pumpkin latte today. In some ways, it’s weird that I’m asked this so often, because I don’t go around introducing myself as a parasite ecologist. (I think my job prospects are better if I sell myself more broadly to other scientists, and I think my communication with non-scientists is more effective if I say that I study “infectious diseases in wildlife and sometimes people, like rabies.”) But because I have a Parasite Ecology blog – maybe even The Parasite Ecology Blog? – I suppose I am The Chosen Answerer of This Question. So, here it is:

Parasite ecologists study the ecology of parasites: the interactions between parasites (or pathogens), hosts, and their (abiotic and biotic) environments.

If you’re looking for something more specific, I also made you this word cloud to illustrate the terms that parasite ecologists used the most in 2017 publications.* Like other types of ecologists, parasite ecologists want to understand the distribution and abundance of individual species, as well as the processes that affect species diversity. To do that, we study individuals, populations, and communities. Sometimes we study the effects of parasites on ecosystems and/or the effects of ecosystems on parasites, but ecosystem-level studies aren’t as common in this subfield, as is corroborated by the fact that ecosystems didn’t make it into the word cloud.

WordCloud115WordsV2.png

So there you have it! But perhaps you’re thinking, “Wait, that sounds like disease ecology. What’s the difference?” The answer is that parasite ecology = disease ecology. But I think that parasite ecology is a better term, because not all infected hosts are diseased.

If you want to complicate matters further, have you seen my old post about the difference between disease ecology and parasitology? 😛

*To make the word cloud, I performed an ISI Web of Knowledge search for all papers published in 2017 that contained the terms parasit* AND ecology. I performed the search on 28 October 2017, and it picked up several papers from November journal issues. I used the titles and abstracts from all 410 papers to create the word cloud. (I didn’t filter the papers at all, so there are probably a few papers in the dataset that aren’t highly relevant.) If you would like to make your own word cloud, you can access the data and the R code on my GitHub.

Disease ecology versus parasitology

Hey, what’s the difference between a disease ecologist and a parasitologist?

Disease ecologists have job opportunities!

KIDDING, KIDDING. But really, it turns out that there are more disease ecologists than parasitologists in US universities, if you exclude vet schools and the like. There also appear to be more job postings for US university positions that target disease ecologists than parasitologists.

So, we return to my original question, but seriously this time: what’s the difference between disease ecology and parasitology? We might say that parasitology tends to focus more on things like the biochemistry, histopathology, morphology, and systematics of parasites, as well as parasite life cycles. In contrast, disease ecology tends to focus more on population to ecosystem-level phenomena involved in host-parasite interactions. But obviously, there’s a lot of overlap between the two disciplines, if they are indeed separate disciplines, because parasitologists often think about classically “ecological” concepts and disease ecologists can’t study parasites without some parasitological knowledge. So I guess it’s more like gradient with parasitology at one end and disease ecology at the other?

Here is a my own handy flow chart for figuring out if you’re a disease ecologist versus a parasitologist. Anyone have a better dichotomous key?

diseaseecologyvsparasitology

The Disease Triangle and the One Health Concept

Two important frameworks in disease ecology are the Disease Triangle and the One Health Concept. Today I want to describe these two paradigms and how they fit together.

The Disease Triangle represents a simple concept: in order for a parasite to cause pathology – that is, for “disease” to occur – the parasite must be present, a susceptible host must be present, and environmental conditions must be sufficient to result in pathology. If you chop off one side of the triangle, there will be no disease. For instance, if you inject a parasite into an immune host, the pathogen will not be able to establish, and there will be no disease. Or, if you inject a pathogen into a susceptible host, but the host is living fat and happy in a high-resource, low-stress environment, the ‘parasite’ may not affect the host’s fitness even after successfully establishing. I’ve covered the context-dependent nature of symbiosis in several recent posts (here, here, here, here), so check those out to see other examples of how the fitness consequences of harboring symbionts can vary with environmental/ecological conditions.

DiseaseTriangle

Let’s talk about humans as our focal hosts now. In order for pathogens to cause disease in humans, we again need susceptible human hosts and environmental conditions that lead to pathology. But we should specify exactly what we mean by “environment.” For instance, where does ecology fit in the environment? The One Health Concept explicitly recognizes the role of wildlife and livestock in human health, and distinguishes this from other environmental factors. The idea is that the health of the environment, wildlife, livestock, and humans are all intricately tied together, and when the health of one component declines, the health of the other components also declines. Usually, people draw this concept as a triangle or a venn diagram with the three vertexes/circles as humans, animals, and the environment, like this:

One Health V1.2

Today, I’m going to present the idea somewhat differently. First, I want to continue to have the pathogens as an explicit component in the One Health Concept. Second, I like to think about the environmental component in a more dynamic way, so I’ve shifted things around a bit:

OneHealth V2

Animals:

The majority (61%) of human pathogens are zoonotic, meaning that they are transmitted between animals and humans (Taylor et al. 2001). And if we limit our concerns to just emerging infectious diseases (EID) of humans, 75% of those are zoonotic!  (If you aren’t sure what an EID is, check out last week’s post.) Here are some examples of major human pathogens that either spillover from animals or are vectored by animals:

Ebola Virus – primates, bats, etc.

Rabies – dogs, bats, etc.

Influenza – pigs, chickens, etc.

Schistosomiasis – snails as intermediate hosts

HIV – originally spilled over from primates

Hanta Virus – rats

Bubonic Plague – vectored by fleas (and lice?), spilled over from rats

Lyme Disease – vectored by ticks, spills over from mammals

Malaria – vectored by mosquitoes

Hendra virus – bats, horses

Clearly, understanding how pathogens are transmitted among wildlife and livestock and how these pathogens then spillover into human populations is a vital step in understanding how and when these pathogens will emerge in human populations. And when pathogens do not just jump hosts into human once, but are maintained in animal populations and repeatedly transmitted to humans (e.g., Lyme Disease), community ecology may be an important determinant of human infection risk (i.e., dilution and amplification effects).

Humans:

As I mentioned previously, susceptible humans need to be present in order for disease to occur. There are also many socioeconomic considerations that can influence whether an epidemic occurs, the magnitude or duration of the epidemic, and/or the degree of pathology (e.g., morbidity, mortality) that individuals experience. I can’t describe all of those factors in one post, but here are a few:

Trust of government and health officials: This is a huge consideration. For instance, in the United States, there are currently outbreaks of pathogens that are entirely preventable by readily available vaccinations, but distrust of vaccinations has led citizens to refuse to vaccinate their children. Similarly, hygienic practices are vital for containing the spread of Ebola virus in the affected African countries. However, citizens mistrust health workers, and they may not follow advice for reducing virus transmission, such as going to the hospital as soon as they experience symptoms and avoiding kissing the deceased and going to the hospital as soon as they experience symptoms (Gross 2014).

Population Size: Population density can play a big role in determining the probability that a pathogen will successfully invade a human population, as well as determining whether the pathogen will persist or fade out after the initial epidemic.

Globalization: By connecting populations of humans that otherwise would not be connected, global travel makes it possible for pandemics to occur when there would otherwise be contained, regional epidemics after spillover of a pathogen from animals into humans.

Food: Where we acquire our food and how we prepare it can also have important implications for the spread of infectious diseases. For instance, if we allow farmers to grind up cows and put that protein into the feed of other cows, we increase the risk of mad cow disease (bovine spongiform encephalopathy) in our livestock and new variant Creutzfeldt-Jakob disease in humans. If we raise livestock in dense populations, we increase the probability of pathogen epidemics in our livestock, and these pathogens may then spillover into human populations when humans interact with or consume infected animals. Similarly, if hunters come into close contact with wild animals in the process of acquiring, cooking, and selling bushmeat, they increase their personal risks of contracting wildlife pathogens, which may then spread through human populations. And if we use antibiotics on a massive-scale in our farming practices, we may inadvertently select for highly resistant bacteria that we can no longer combat with existing medical resources.

Hygiene/Sanitation/Social Norms: Are sick people encouraged to stay home from work, and do they feel like they can afford to miss work or school? Do people use condoms to reduce the probably of contracting STIs? Do people typically kiss or shake hands when they greet?

Pathogens:

In addition to the presence of the focal pathogen, it is important to consider other symbionts that hosts may harbor. For instance, infection with one pathogen may increase susceptibility to other pathogens, or co-infection may turn hosts into pathogen superspreaders.

Environment:

Finally, just like we discussed with the Disease Triangle concept, even if pathogens, animals, and humans are all present, we won’t necessarily see an emerging infectious disease. Environmental conditions can tip the scale in one direction or the other, as indicated by the green and white arrows illustrating the transition from the disease-free to disease-present venn diagrams. Here are a few environmental factors that may be important:

Pollution: Pollution can stress animal and human populations, making them more susceptible to disease.

Deforestation/Agriculture: When we clear forest land for agriculture, we often bring humans, their livestock, and wildlife into closer contact than they would be otherwise, and this can increase the risk of pathogen spillover from wildlife to humans. For instance, when we raise pigs near fruit trees visited by bats, we increase the risk of virus transmission from bats to pigs and then to humans. Additionally, deforestation, urbanization, pollution, and other types of environmental change may result in changes in animal communities, which may in turn affect pathogen transmission.

Not all anthropogenic changes to the environment will result in increased transmission risk. For instance, by draining wetlands in massive regions of the United States, citizens eradicated much mosquito habitat, and therefore eliminated malaria as a major pathogen in the United States. Similarly, climate change has the potential to tip the scale favorably for some pathogens in some locations, but not all pathogens in all locations will be positively affected by climate change. Therefore, the environmental conditions that are “favorable” for some diseases won’t necessarily be the same for other diseases.

References:

Gross, M. 2014. Our shared burden of diseases. Current Biology 24(24): pR1139–R1141.

Taylor, L.H., S.M. Latham, M.E. Woolhouse. 2001. Risk factors for human disease emergence. Philos Trans R Soc Lond B Biol Sci. 356(1411):983-9.

Resistance vs. Tolerance to Parasites

In disease ecology and parasitology, we often talk about a host’s ability to resist or tolerate parasites.  What’s the difference?  Resistance is a measure of a host’s ability to reduce parasite establishment.  For instance, imagine that two hosts are each exposed to 10 parasites.  In the first host, 8 of those parasites manage to evade the host’s immune system and successfully establish, and in the second host, only 2 of the parasites successfully establish.  The second host is more resistant to infection.  Tolerance is a measure of a host’s ability to “deal with” a given parasite load.  Now imagine that two hosts each have 5 parasites.  Those parasites hardly affect the first host’s ability to survive or reproduce, but the same number of parasites causes a huge reduction in the second host’s ability to survive and reproduce.  The first host is more tolerant.  (A really great figure from Raberg et al. (2007) sums this up.)

What determines a host’s ability to resist or tolerate parasites?  Good question!  This is a hot topic for research.  Body condition (i.e., overall health) likely has something to do with resistance and tolerance.  And then there is that ever-present explainer of all the things: genetics (Raberg et al. 2007).  But today, I want to talk about something else.  Do paternal effects influence resistance and tolerance?

In a recent, awesome, open access study, Kaufmann et al. (2014) exposed three-spined stickleback “sires” (fathers/dads/sperm-makers) to nematodes.  Then they used sperm from either these exposed sires or unexposed sires to fertilize strickleback eggs.  Here’s what they found: when the sires were exposed to parasites, the eggs were less likely to develop and the juveniles were less likely to survive.   But if they took surviving offspring from both exposed and unexposed sires, and then exposed some of those offspring to nematodes, the offspring from exposed sires had higher tolerance to parasites.  Specifically, parasites had a big effect on the body condition of offspring from unexposed sires, but no effect on offspring from exposed sires.  Neat!  Surprisingly, parental effects didn’t influence offspring resistance to parasites.  Unsurprisingly, genetics also played a role in both resistance and tolerance.

References:

Raberg, L., D. Sim, and A.F. Read. 2007. Disentangling Genetic Variation for Resistance and Tolerance to Infectious Diseases in Animals. Science 318(5851): 812-814.

Kaufmann, J., T.L. Lenz, M. Milinski, and C. Eizaguirre.  2014. Experimental parasite infection reveals costs and benefits of paternal effects. Ecology Letters. (Open access.)

Preparing for Disease Ecology Prelims

Here’s a little post for all you PhD students nearing your qualifying/comprehensive/preliminary exams.  If I were asked to study disease ecology for such an exam, this is what I would know:

Who are the most influential modern day disease ecologists (or parasite ecologists)?  You might start with my list of the most prolific parasite ecologists in the 21st century.

What is the disease triangle?

What were Koch’s Postulates?

What proportion of Earth’s species are parasites/pathogens?  What proportion of the total biomass in an ecosystem is parasite biomass?  I have some related posts: here and here.

Do parasites/pathogens regulate host populations?  Somehow, I think I I’ve only blogged about this once

How do parasites affect food webs?  You might start here and here.

What are the differences between microparasites and macroparasites?  Here.

What are the differences between predators, parasites, and parasitoids?  Here.

Why are macroparasites aggregately distributed among hosts, and why does it matter?  Here and here and here.

What are the hypotheses regarding the evolution of virulence?  I haven’t blogged about that much, but there’s a bit here.

What are SIR models?  SI models?  SIS models?  SEIR models? Vector transmission models?  

What is R0?  What happens when R0 > 1 and when R0 < 1?  How can you reduce R0?  What is the critical proportion of susceptible individuals that needs to be vaccinated so that R0 < 1?  Somehow, I haven’t covered this in any detail.  But I have a cute cow cartoon about herd immunity.

What are density dependent and frequency dependent parasite transmission?  Here and here.

Are there invasion thresholds is disease systems? Link to PDF.

Is culling a viable strategy for disease management?  See previous two questions.

What role does contact heterogeneity play in disease transmission?  What are superspreaders?  What is a superreceiver? Here, here, and here.

Is disease risk related to biodiversity?  What is the dilution effect?  Amplification effect? Neutral effect?  Here and here, for starters.

What are the main types of pathogen transmission? E.g., direct vs. indirect, sexually transmitted, vectored, trophically transmitted, etc.

Explain the concept of parasite manipulation of host behavior.  Is it adaptive?  What are the consequences for communities/ecosystems?  Here and here, but there is waaay more material out there.

Do hosts and parasites coevolve?  Is there evidence of parasite-mediated selection?

What is parasite-mediated competition?  Does it happen in real systems?

Are there general laws in parasite ecology?  PDF link.

How are resistance and tolerance different? Here.

Did I miss anything?  Add in the comments or shoot me an email!


The Dilution Effect – Numbers, Densities, and Prevalences

This post is the first in a series of posts that I’m going to be writing about a current hot topic hypothesis in the field of disease ecology.  This week is an introduction to the dilution effect hypothesis, and next week I’ll talk about the recent debates as to whether the dilution effect really happens – and how often it happens – in disease systems.  Stay tuned! 

The dilution effect hypothesis suggests that there is a negative relationship between (human) disease risk and host diversity.  That is, high host diversity “dilutes” disease risk.  This idea is best explained with an example, so let me introduce the host-parasite system that has been studied the most with regards to the dilution effect:

Lyme disease is caused by the spirochete bacterium Borrelia burgdorferi that is vectored by the black-legged tick.  Larval ticks are born uninfected, but they can become infected by taking a blood meal from an infected host.  The first blood meal often comes from a white-footed mouse, and mice tend to be very competent hosts – they’re good at transmitting B. burgdorferi to ticks.  After the blood meal, the larva leaves the mouse, and will eventually molt into a nymph.  The nymph then needs to take a blood meal, and it may feed on a variety of mammalian hosts, including humans.  (In fact, because nymphs are so hard to see, humans are much more likely to be infected by B. burgdorferi by being bitten by a nymphal tick than an adult tick.)  So, the nymph takes a blood meal, possibly transmitting B. burgorferi to the host if the tick is infected, and possibly becoming infected with B. burgdorferi if the host is infected but the tick isn’t.  As before, after the blood meal, the nymph drops off the host and then molts into an adult tick.  Adult ticks also need a blood meal, and so they, too, must find a host, which is very commonly the white-tailed deer.  Adults mate, and then the females lay eggs in the leaf litter that will later hatch into uninfected larval ticks.

Image

The tick life cycle and Lyme disease transmission. Infected animals are lime, for Lyme disease. Figure adapted (significantly) from here. Pretend my larval ticks only have six legs.  There are more than 4 host species for ticks; these are just examples.  That orange thing is a human.

As I said before, when we talk about the dilution effect, we’re trying to determine human disease risk under various biodiversity scenarios.  In the Lyme disease system, human disease risk is high when there are many infected ticks in a given area, and there are two ways to get high numbers of infected ticks in an area: high total densities of ticks and/or high prevalences of infected ticks.  The following two scenarios illustrate how total density and infection prevalence in ticks affect the number of infected ticks and human disease risk:

Scenario One:  You have two identical areas.  In each area, 50% of the ticks are infected (=constant prevalence).  In Area 1, there are 10 ticks, and in Area 2, there are 20 ticks.  Based on a 50% prevalence, in Area 1, there are 5 infected ticks, and in Area 2, there are 10 infected ticks.  So, human disease risk is higher in Area 2.  In this example, varying total tick density varied human disease risk.

Image

Scenario Two:  Again, you have two identical areas.  This time, each area has 10 ticks (=constant density).  In Area 1, 50% of ticks are infected, and in Area 2, 80% of ticks are infected.  So there are 5 and 8 infected ticks, and human disease risk is higher in Area 2.  But in this example, tick density was constant, and varying the prevalence in tick infection varied human disease risk.

prevalence3

Hopefully, it is now clear that human disease risk is related to the number of infected ticks in an area, and we can change the number of infected ticks in an area by changing the total tick density and/or the prevalence of infected ticks.  So, how do we change those two variables?  Well, as it turns out, there are a wide variety of host species for ticks, and they vary in their ability to 1) provide blood meals to ticks and thus affect tick density and 2) infect ticks with B. burgdorferi (=host competency) and thus affect the prevalence of tick infection. So, the density of ticks and the prevalence of tick infection should be related to which hosts there are in a given area.

Image

Deer provide many blood meals to hungry adult ticks, so having high deer densities may increase total tick densities. Conversely, opossums tend to groom off and eat their ticks, so opossums might decrease total tick densities. Furthermore, host species vary in reservoir competence – their ability to transmit B. burgdorferi to ticks. White-footed mice are very competent hosts, and deer and opossums are poor reservoir hosts.  (50% transmission success from an opossum is high, but I can’t be bothered to color in only part of a tick.  You get the graphics you pay for on this blog!)

We now have all of the information that we need to discuss the dilution effect!  Imagine again that you have two identical areas, but one has high host diversity and one has low host diversity.  We’ll assume that In the high biodiversity area (Area 1), you have a mix of mice and lower competency hosts, like opossums and deer.  In the low biodiversity area (Area 2), the hosts tend to be mostly mice, which are highly competent hosts.  If the two areas have the same tick density, but Area 1 has high host biodiversity and Area 2 has low host biodiversity, Area 2 should have higher prevalence of infected ticks and thus higher disease risk for humans.  The disease risk in Area 1 is diluted by biodiversity, because ticks are feeding on hosts that are less likely to infect them.  That’s the dilution effect!

Image

Human disease risk is higher in the low biodiversity area (Area 2, right).

You might be wondering what happens if Area 1 has higher biodiversity and lower prevalence of infected ticks, but ALSO higher tick density because of the presence of deer?  Uhm.  Well.  Good question.  In that case, if increased tick density cancels out decreased tick infection prevalence, you might not see a change in human disease risk – a “neutral effect” instead of a “dilution effect.”  Or you might even see an increase in human disease risk if the increase in tick density outweighs the reduced prevalence of infected ticks – an “amplification effect” instead of a “dilution effect.”

If this doesn’t seem complicated enough for you, try thinking about different forests with different levels of biodiversity and different host densities and different host infection prevalences and different tick densities and different prevalences of tick infection.  Where is Lyme disease risk highest for humans?

Under what conditions should we see a dilution effect?

Hopefully, this introduction has emphasized that you won’t necessarily see a dilution effect in every host-parasite system, and if you do, you might not see a dilution effect all the time.  The dilution effect is context-dependent, and there are some very specific conditions that need to be met in order for a dilution effect to occur:

  1. The vector (in this case, the tick) needs to be a host generalist.  In the Lyme disease system, ticks feed on a range of host species, and not just humans.
  2. The vectors must usually become infected by biting infected hosts, rather than through vertical transmission of infection from parent to offspring.  In the Lyme disease system, larval ticks are born uninfected and become infected via taking blood meals from infected hosts.
  3. Hosts must vary in reservoir competence.  In the Lyme disease system, mice are very competent hosts and opossums and deer are not.
  4. The most resilient host species – the ones that are left in low biodiversity communities – must also be the highly competent host species.  In the Lyme disease system, mice are the most abundant hosts in low biodiversity systems, and they are highly competent reservoirs.
  5. Increased host biodiversity doesn’t also cause an increase in vector density.  Or if it does, the increase in vector density is outweighed by the decrease in the prevalence of infected vectors.  Not sure if this happens in the Lyme disease system or not.  (So, I’ve only ever seen this stated as an assumption in Wood and Lafferty 2013, and they don’t cite it, so I guess they were the first to include it as an assumption.  It’s very important!)

So, that’s the dilution effect!  Come back next week to witness some sassy language as scientists argue about whether the dilution effect really happens in disease systems!

Reference:

Wood, C. L., and K. D. Lafferty. 2013. Biodiversity and disease: a synthesis of ecological perspectives on Lyme disease transmission. Trends in Ecology & Evolution 28: 239–47.