Temperature impacts parasite transmission and the effectiveness of public health interventions

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00:00:14.08 Hi, my name is Dr. Karena Nguyen.
00:00:16.10 I’m a postdoctoral fellow at Emory University.
00:00:19.05 And today I’ll be talking about how temperature impacts
00:00:22.27 parasite transmission and the effectiveness of public health interventions.
00:00:28.10 It may come as no surprise to many of you,
00:00:30.25 but the earth is warming.
00:00:34.08 And the steady warming of our planet
00:00:36.05 has impacted our human health,
00:00:39.22 our local and global economies,
00:00:42.11 and our ecosystems.
00:00:44.22 In this video from NOAA,
00:00:46.15 which shows the global temperature compared to the 20th-century average,
00:00:50.06 as time has progressed the earth has gotten warmer
00:00:54.15 and warmer and warmer.
00:00:57.18 As a disease ecologist and parasitologist,
00:01:00.00 one of the factors of global climate changes that I’m most concerned about
00:01:04.08 is how temperature impacts parasite transmission
00:01:07.01 and the effectiveness of public health interventions.
00:01:10.02 So, how exactly does parasite transmission…
00:01:14.14 how is that impacted by temperature?
00:01:17.02 Before I get to the parasite part,
00:01:19.01 what I want to introduce are
00:01:21.24 some of these common organisms
00:01:24.00 that you may have encountered before.
00:01:25.22 We have snails, we have tsetse files,
00:01:28.29 mosquitoes that you’ve likely encountered in your own backyard.
00:01:33.02 And although these organisms look really different
00:01:36.13 and inhabit different environments,
00:01:39.22 one thing that they do have in common is that they are ectotherms,
00:01:43.05 meaning that they cannot regulate their own body temperature,
00:01:46.20 and are entirely susceptible to environmental conditions.
00:01:52.18 Now, something you may not have thought about
00:01:55.06 is that these organisms can also harbor parasites
00:01:58.16 that you may not recognize.
00:01:59.27 So, schistosomiasis, leishmaniasis,
00:02:04.05 elephantiasis, sleeping sickness…
00:02:07.28 these are all neglected tropical diseases,
00:02:10.22 which are human diseases caused by parasites
00:02:13.23 that predominantly occur in developing countries
00:02:16.28 in tropical and subtropical climates,
00:02:19.05 where these organisms occur.
00:02:22.06 And in 2015, the World Health Organization
00:02:25.18 estimated that over 1 billion people
00:02:28.07 — that’s 13% of the world’s population —
00:02:32.02 is infected with at least one neglected tropical disease.
00:02:35.24 So, in this map,
00:02:38.03 which shows the number of individuals needing treatment
00:02:40.06 from at least one neglected tropical disease,
00:02:42.26 increasing in dark green,
00:02:44.27 there are millions of people worldwide
00:02:47.21 who need treatment for neglected tropical diseases.
00:02:51.14 And moreover, many of these individuals
00:02:54.19 live in tropical and sub-tropical climates,
00:02:56.25 which again are expected to be impacted
00:02:59.00 by global climate change.
00:03:01.09 So, hopefully I’ve convinced you at this point
00:03:04.08 that there are many common organisms
00:03:06.12 — snails, mosquitoes, tsetse flies —
00:03:09.11 and these organisms can harbor parasites,
00:03:13.23 and that both parasites and these hosts that harbor them
00:03:17.23 are ectotherms that can be impacted by temperature.
00:03:20.09 And many of their traits,
00:03:22.18 such as survival and reproduction,
00:03:24.25 will therefore be impacted by temperature and global climate change.
00:03:28.29 But what exactly is a parasite?
00:03:31.25 Well, consider this analogy.
00:03:36.14 Do you have a Netflix account?
00:03:39.26 Well, imagine that your parents have a Netflix account,
00:03:43.19 and you’re using your parents account,
00:03:46.09 but they don’t really watch Netflix at all.
00:03:49.12 So, you’re receiving a benefit while they’re paying for this subscription
00:03:52.14 that they’re not using.
00:03:54.06 In effect, you’re being a parasite!
00:03:57.04 And this is exactly what parasites do.
00:03:59.19 Specifically, they’re defined as organisms
00:04:03.06 that live in or on another live organism;
00:04:07.00 they depend on that organism for habitat and/or resources,
00:04:12.16 and lastly they incur direct negative effects
00:04:16.15 on the organisms that they inhabit.
00:04:18.13 So, going back to one of my original examples,
00:04:21.03 the parasites that cause schistosomiasis, elephantiasis,
00:04:24.18 and sleeping sickness…
00:04:26.21 these parasites also harm the hosts that they infect.
00:04:30.25 And eventually, when they get to us,
00:04:32.26 they harm us as well.
00:04:35.05 I’m particularly interested in snails
00:04:38.18 and the parasites that cause human schistosomiasis.
00:04:42.20 So, what is schistosomiasis?
00:04:45.23 This is a parasite that cycles between humans and snails,
00:04:50.06 and individuals become infected
00:04:53.09 when they come into contact with infested waters.
00:04:57.17 Currently, more than 200 million people
00:05:00.11 are infected with this parasite
00:05:01.29 and more than 800 million people
00:05:04.05 are at risk of contracting this parasite,
00:05:06.00 and more than 90% of cases occur in Africa.
00:05:11.09 And although this disease is easily treatable,
00:05:14.01 and actually costs between only 20-30 cents,
00:05:17.04 reinfection is extremely common,
00:05:19.27 and children often carry the highest burden of disease.
00:05:24.05 In this photo that you see…
00:05:27.17 this is… this was taken at Lake Victoria in Tanzania,
00:05:30.10 where schistosomiasis is endemic.
00:05:33.09 And children, as I stated,
00:05:36.07 often carry the highest burden of disease
00:05:38.03 due to activities such as swimming, bathing,
00:05:42.06 and it’s extremely easy for them to become reinfected with this parasite,
00:05:45.02 even if they are treated.
00:05:47.08 And over time, chronic infection can cause
00:05:50.16 liver damage, kidney failure, etc.
00:05:54.05 And these symptoms can actually
00:05:58.00 trap individuals in poverty.
00:06:01.25 So, let’s break down the life cycle a little bit.
00:06:04.13 When individuals are infected with this parasite,
00:06:08.06 adult worms will produce eggs,
00:06:11.03 which will be excreted into water bodies via urine or feces,
00:06:15.02 depending on the species of schistosomes.
00:06:19.28 These eggs will then hatch into miracidia,
00:06:22.19 which is the first life stage of the parasite.
00:06:25.19 These miracidia will then go on to infect snails.
00:06:29.07 And these snails will then produce cercariae,
00:06:31.23 which is the second life stage of the parasite.
00:06:35.08 The cercariae will then go on to infect individuals
00:06:38.16 who come into contact with infested waters,
00:06:40.29 and the life cycle starts all over again.
00:06:45.10 And what I want you to know is that
00:06:47.15 this parasite really spans both humans
00:06:52.01 — in which it is subjected to a very stable temperature —
00:06:56.00 but much of its life cycle is also spent in the aquatic environment,
00:06:59.25 where it’s subject to variable temperature.
00:07:02.07 And so when we’re asking and thinking about
00:07:04.27 how might temperature impact transmission,
00:07:06.21 what I’m looking at are these parts of the life cycle that occur in the water.
00:07:10.14 So, why does temperature matter?
00:07:12.22 Well, parasites and hosts
00:07:16.19 all have traits that have specific,
00:07:19.20 measurable responses to temperature.
00:07:21.24 These are called thermal response curves.
00:07:25.04 And take, for example, a trait like reproduction.
00:07:28.05 At low temperature, reproduction might also be low.
00:07:31.25 But as temperature increases,
00:07:34.07 there will eventually be a point
00:07:36.29 where maximum reproduction occurs.
00:07:39.06 This is called the thermal optimum, or the Topt,
00:07:42.03 for that trait.
00:07:45.16 But consider that parasites and hosts
00:07:47.24 have many, many different traits.
00:07:51.24 So, take, for example, reproduction and mortality.
00:07:55.16 And all of these traits will have different responses to temperature,
00:07:59.27 and subsequently different thermal optimums.
00:08:03.18 And overall, the combination
00:08:07.08 of all of these different thermal responses
00:08:09.12 and their thermal optimums
00:08:11.24 will combine to influence overall transmission risk,
00:08:14.28 which is what I’m mostly interested in.
00:08:17.17 So, one of the first questions I wanted to ask in this study is,
00:08:20.27 can we build an epidemiological model
00:08:23.12 that incorporates the effect of temperature
00:08:26.10 on parasite and host traits?
00:08:28.17 And mostly, again,
00:08:31.04 looking at the effects of temperature on parts of the life cycle
00:08:33.09 that are impacted by temperature, right?
00:08:36.07 And this makes sense.
00:08:38.17 So, what did we do?
00:08:40.19 We broke down the life cycle
00:08:42.29 and incorporated the same individuals, right?
00:08:45.06 Humans, snails, and the parasite.
00:08:47.27 And so, here in this figure
00:08:50.15 we have susceptible humans,
00:08:52.12 and the arrows simply indicate
00:08:55.21 individuals can leave or enter the system.
00:08:57.24 So, in this parasite system,
00:08:59.17 we can have susceptible humans enter in or leave,
00:09:02.25 but if susceptible humans…
00:09:05.06 if they are infected,
00:09:07.15 they become infected humans.
00:09:09.01 And infected humans can go on to produce miracidia,
00:09:12.04 which is that first life stage of the parasite.
00:09:15.00 Miracidia can leave the system,
00:09:16.27 but they can also infect susceptible snails.
00:09:20.13 And again, there can be snails that enter the system or leave,
00:09:24.12 but if snails become infected,
00:09:26.11 they then become infected snails.
00:09:28.19 And these infected snails can also leave the system,
00:09:31.10 but then they can also go on to produce cercariae,
00:09:33.26 which is that second life stage of the parasite.
00:09:36.20 And cercariae can also leave the system,
00:09:39.01 but they can also go on to infect susceptible humans,
00:09:42.07 and so on and so forth.
00:09:45.17 And so, again, when we’re looking at the life cycle,
00:09:48.07 we have the human body,
00:09:50.10 which represents a stable temperature environment for the parasite,
00:09:52.28 and also the aquatic environment,
00:09:55.18 where the parasite is susceptible to variable temperature.
00:09:59.13 So, one of the first things that we did
00:10:01.22 was look at both published data
00:10:04.18 and performed our own experiments
00:10:06.20 and looked at the response
00:10:10.25 of miracidia, cercariae, and snails.
00:10:15.25 We looked at their reproduction across temperatures.
00:10:20.14 And so, you see here,
00:10:22.08 with temperature on the x-axis
00:10:24.13 and recruitment or reproduction on the y,
00:10:26.25 that miracidi, cercariae, and snails
00:10:29.08 all have different responses to temperature.
00:10:32.15 And we did the same thing for mortality,
00:10:36.01 for all of these three key players in the life cycle.
00:10:39.29 And the key point that I want you to take from these two figures
00:10:43.23 is that miracidia, that first life stage of the parasite,
00:10:47.29 cercariae, that second life stage of the parasite,
00:10:50.05 and snails, the hosts that harbor them…
00:10:52.24 they all have different responses to temperature
00:10:56.00 when we’re looking at their reproduction and their mortality.
00:10:59.26 This led us to the discovery that the overall optimum temperature for transmission
00:11:06.02 is 21.7 degrees Celsius for schistosomiasis,
00:11:09.26 which is a really, really cool result.
00:11:12.10 So, here we have temperature on the x-axis.
00:11:14.07 It’s showing the thermal response for overall transmission,
00:11:18.02 and we have transmission risk on the y.
00:11:21.10 So, now that we identified the optimum temperature for transmission,
00:11:25.14 how do we actually go about interrupting transmission?
00:11:29.20 There are a variety of public health interventions or control measures
00:11:33.14 that are already put in place to try to interrupt this parasitic disease,
00:11:38.00 and we modeled three of them.
00:11:40.20 So, first you can actually treat humans,
00:11:43.05 as I mentioned at the beginning of the talk.
00:11:45.00 You can also get rid of snails, right?
00:11:48.03 You can use snail control
00:11:50.25 and remove them from the system.
00:11:52.13 Lastly, you can also treat water bodies
00:11:54.27 to get rid of cercariae,
00:11:57.01 that second life stage of the parasite.
00:11:58.21 And so, we hypothesized that all three of these different interventions
00:12:01.20 would decrease transmission risk.
00:12:04.13 But we also hypothesized that targeting snails or cercariae
00:12:08.25 may also impact the thermal optimum for transmission,
00:12:12.19 because these two parts of the life stage
00:12:14.19 are susceptible to temperature.
00:12:17.12 So, what did we find?
00:12:19.24 So, in this figure we have treatment rate
00:12:22.06 ranging from 0-100%.
00:12:24.16 On the y, we have a ratio of transmission risk
00:12:27.20 when the control method is applied
00:12:31.07 over the transmission risk when no control is applied at all.
00:12:37.06 And our hypothesis was supported.
00:12:39.25 So, all three interventions decreased transmission risk,
00:12:43.19 but the degree to which they did was different.
00:12:46.18 So, cercarial control actually had the smallest decrease,
00:12:51.02 whereas human treatment actually reduced transmission risk by 10-fold,
00:12:56.27 and amazingly,
00:12:58.23 we found that snail control reduced transmission risk by over 100-fold,
00:13:01.29 which is huge when we’re thinking about
00:13:05.00 decreasing transmission risk to humans.
00:13:07.22 But what about the effect of these different control methods
00:13:11.01 on the overall optimum for transmission?
00:13:15.00 So, again, we have treatment rate
00:13:17.07 ranging from 0-100% on the x-axis,
00:13:19.20 and on the y, we now have the difference
00:13:22.10 between the thermal optimum of applying the control method
00:13:26.03 to the thermal optimum when no control is applied.
00:13:31.10 And so, here we found that…
00:13:33.27 again, treating humans doesn’t impact the overall optimum for transmission at all.
00:13:39.01 And this makes sense because humans
00:13:42.09 represent that stable temperature environment.
00:13:45.05 But what was cool and super interesting
00:13:47.28 is applying cercarial control
00:13:49.29 actually increased the thermal optimum for transmission.
00:13:54.21 And then when we looked at snail control,
00:13:57.11 this actually shifted the thermal optimum for transmission
00:14:00.05 up to 1.3 degrees C.
00:14:03.02 And this was essentially because removing additional snails, right?
00:14:07.00 Additional snail mortality actually changed
00:14:09.20 the contribution of this trait
00:14:12.29 to the overall temperature transmission relationship.
00:14:16.06 And so, it changed the overall optimal temperature for transmission.
00:14:21.02 So, the results of our model
00:14:23.11 suggested that regional surface water temperatures
00:14:25.28 will actually shape seasonal schistosomiasis dynamics.
00:14:31.20 So, to test this hypothesis,
00:14:33.28 we extracted surface water temperatures
00:14:36.07 from a previous study
00:14:38.22 and projected transmission risk from 1965 to 2014
00:14:42.27 using this historical data.
00:14:46.11 And we looked at two regions
00:14:49.03 that are endemic for schistosomiasis,
00:14:51.11 so southwest Burkina Faso,
00:14:53.10 which represents a kind of semi-arid climate,
00:14:57.03 and also southeast Uganda,
00:14:58.27 which represents a tropical climate.
00:15:01.18 And these are just shown as A and B on the map.
00:15:04.14 Okay.
00:15:05.25 So, the first thing that we did was plotted
00:15:08.14 mean decadal monthly stream temperature.
00:15:11.04 So, on the x-axis, you have just months of the year,
00:15:14.09 and on the y, you have stream temperatures.
00:15:18.09 And then the different colored lines
00:15:20.10 simply represent the different decades
00:15:22.13 going all the way up to 2014.
00:15:24.23 So, here, in panel A,
00:15:26.16 when we’re looking at southwest Burkina Faso,
00:15:28.22 we do see seasonal variation.
00:15:31.25 So, there are certain times of the year
00:15:33.19 when stream temperatures are low.
00:15:35.16 This increases throughout the summer months
00:15:37.19 and then decreases towards the winter months.
00:15:40.11 This is in sharp contrast to southeast Uganda,
00:15:43.11 where temperatures are actually pretty consistent throughout the year
00:15:47.10 and are actually very close to the thermal optimum
00:15:49.28 for schistosomiasis transmission,
00:15:52.03 which we’ve depicted as the dotted line on the figure.
00:15:57.23 And what’s important to note here is that
00:16:00.18 southeast Uganda is actually very close to the equator,
00:16:02.23 so it makes sense that stream temperatures there
00:16:04.18 will be relatively consistent throughout the year,
00:16:07.07 whereas in Burkin-Faso,
00:16:09.06 where there is more seasonality,
00:16:10.22 then accordingly stream temperatures
00:16:12.16 will also show seasonal variation.
00:16:16.22 Now, what happens when we apply these stream temperatures
00:16:19.25 to look at how transmission risk is affected?
00:16:24.12 So, again, we have months of the year on the x-axis,
00:16:28.02 and now we have transmission risk on the y.
00:16:33.01 So, in southwest Burkina Faso, in panel A,
00:16:35.22 there are again seasonal differences in transmission risk,
00:16:41.18 whereas in southeast Uganda
00:16:43.14 you have pretty consistent and high transmission risk
00:16:46.15 throughout the year.
00:16:49.04 And these trends make sense when we look at stream temperatures.
00:16:53.18 So, in southwest Burkina Faso,
00:16:56.06 when stream temperatures are close to the thermal optimum for transmission,
00:16:59.21 you have higher transmission risk.
00:17:02.22 When stream temperatures greatly exceed
00:17:07.15 the thermal optimum for transmission,
00:17:09.24 you actually get a very great reduction in transmission risk.
00:17:14.02 This is again in sharp contrast to Uganda,
00:17:16.10 where stream temperatures are almost always
00:17:19.01 near the thermal optimum for transmission,
00:17:21.05 and accordingly, transmission risk
00:17:24.13 is almost always high.
00:17:27.14 And so, when we married this experimental data with our model,
00:17:31.29 we essentially found that there’s
00:17:35.25 a correlation between the stream temperatures
00:17:39.29 being close to the thermal optimum for transmission
00:17:41.29 and transmission risk.
00:17:44.04 And the results suggest that as global climate change increases,
00:17:48.19 stream temperatures in areas that are currently above the thermal optimum for transmission
00:17:53.12 will likely have a reduction in transmission risk.
00:17:56.05 Conversely, in areas that are currently
00:18:00.07 at or below the thermal optimum for transmission,
00:18:02.20 warming associated with global climate change
00:18:05.05 may actually increase transmission risk in these areas.
00:18:09.18 Okay, so, just to recap…
00:18:12.08 we found that parasite and host traits
00:18:16.02 have specific different responses to temperature,
00:18:19.12 and when we combined these different responses,
00:18:22.05 we were able to identify the overall thermal optimum for transmission
00:18:26.07 at 21.7 degrees C for schistosomiasis.
00:18:31.01 Next, we found that snail control
00:18:33.15 had the largest effect
00:18:35.15 on both decreasing transmission risk
00:18:38.16 and also shifting the optimum temperature for transmission.
00:18:42.20 And when we applied this to a retrospective study
00:18:46.28 that had tracked stream temperatures in these areas
00:18:49.13 where schistosomiasis is endemic,
00:18:52.02 we found that regions that have seasonal variation
00:18:55.24 will also show seasonal variation in transmission risk,
00:18:59.17 and that regions moving closer to the thermal optimum for transmission
00:19:04.07 may actually have increased transmission risk in the future.
00:19:08.11 So, what I’ve hopefully imparted today
00:19:11.25 is that temperature is a really important driving factor of parasite transmission,
00:19:16.12 and will effectively impact, also,
00:19:20.21 public health interventions.
00:19:22.28 And so, considering regional seasons
00:19:26.08 and the timings of interventions in the future
00:19:29.19 will improve human health outcomes
00:19:32.27 as we experience a changing climate.
00:19:35.09 Thanks.

This Talk

Speaker: Karena Nguyen

Audience:

Student
Educators of Adv. Undergrad / Grad
Researcher
Educators

Recorded: July 2021

Talk Overview

More than 200 million people are infected with schistosomes, aquatic parasites that cycle between snails and humans, and cause the human disease schistosomiasis. Risk of contracting this disease is expected to rise in the coming years due to climate change, agricultural expansion, and population growth. In her Share Your Research Talk, Dr. Karena Nguyen provides an overview of the schistosome life cycle, including the points at which interventions can disrupt this cycle in order to reduce disease transmission. She then goes on to discuss her work modeling the impact of these interventions.

Speaker Bio

Karena Nguyen

Karena Nguyen is a disease ecologist, parasitologist, and environmental microbiologist. She studies schistosomes, the parasites that cause schistosomiasis in humans using a combination of molecular tools and epidemiological models. As a postdoctoral fellow at Emory University in the Fellowship in Science Research and Teaching (FIRST) program, she studied the epidemiological impact of hybrid schistosomes. She… Continue Reading

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Jiefei Yuan (iBiology): Editor
Chris George (iBiology): Graphics
Hubbard (iBiology): Graphics

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