I just found this short article on the LSE blog from Professor Sylvia Chant, who does work on female genital mutilation in Sub-Saharan Africa:
“Opportunities for taking one’s research beyond textbooks and journal articles are critical for teaching at LSE, where students at all levels and from an extensive range of geographical and disciplinary backgrounds are eager to see theory translated into practice, and to engage with impact. From my experience, it is the anecdotes about the lives of people who have formed part of one’s research which help to make ideas and arguments more accessible; how one went about fieldwork in different localities, or the stories of what you, as lecturer, have done in the public and policy domain (whether acting as an expert witness in court cases for asylum seekers, or playing an advisory or consultant role for international agencies). These really grab students’ attention, with photographs and video clips adding more value still!”
I completely agree. Graphs and tables are great for making specific points of interest to researchers, but photos and videos humanize the results and make our research accessible to regular folks and policy makers. People have a real hard time with numbers, which are essentially about communities, countries and institutions, but are used to listening to stories of the struggles and challenges of individuals. Providing plenty of interesting visuals and stories is essential to what we do.
Public health work is about people. Our mission is to be an advocate for the sick and those at risk of becoming sick, who are often marginalized, poor or lack a political voice. Telling their stories simply in a way that non-experts can understand helps us to draw support for what we do.
I have long taken the position that we are essentially journalists. Though we, as scientists, follow a strict set of protocols and rules, our job is to tell stories of particular groups of people and provide information which is often difficult to obtain.
Doing research in developing countries is not easy. However, with a bit of care and planning, one can do quality work which can have an impact on how much we know about the public health in poor countries and provide quality data where data is sadly scarce.
The root of a survey, however, is sampling. A good sample does its best to successfully represent a population of interest and can at least qualify all of the ways in which it does not. A bad sample either 1) does not represent the population (bias) and no way to account for it or 2) has no idea what it represents.
Without being a hater, my least favorite study design is the “school based survey.” Researchers like this design for a number of reasons.
First, it is logistically simple to conduct. If one is interested in kids, it helps to have a large number of them in one place. Visiting households individually is time consuming, expensive and one only has a small window of opportunity to catch kids at home since they are probably at school!
Second, since the time required to conduct a school based survey is short, researchers aren’t required to make extensive time commitments in developing countries. They can simply helicopter in for a couple of days and run away to the safety of wherever. Also, there is no need to manage large teams of survey workers over the long term. Data can be collected within a few days under the supervision of foreign researchers.
Third, school based surveys don’t require teams to lug around large diagnostic or sampling supplies (e.g. coolers for serum samples).
However, from a sampling perspective, assuming that one wishes to say something about the greater community, the “school based survey” is a TERRIBLE design.
The biases should be obvious. Schools tend to concentrate students which are similar to one another. Students are of similar socio-economic backgrounds, ethnicity or religion. Given the fee based structure of most schools in most African countries, sampling from schools will necessarily exclude the absolute poorest of the poor. Moreover, if one does not go out of the way to select more privileged private schools, one will exclude the wealthy, an important control if one wants to draw conclusions about socio-economic status and health.
Further, schools based surveys are terrible for studies of health since the sickest kids won’t attend school. School based surveys are biased in favor of healthy children.
So, after this long intro (assuming anyone has read this far) how does this work in practice?
I have a full dataset of socio-econonomic indicators for approximately 17,000 households in an area of western Kenya. We collect information on basic household assets such as possession of TVs, cars, radios and type of house construction (a la DHS). I boiled these down into a single continuous measure, where each households gets a wealth “score” so that we can compare one or more households to others in the community ( a la Filmer & Pritchett).
We also have a data set of school based samples from a malaria survey which comprises ~800 primary school kids. I compared the SES scores for the school based survey to the entire data set to see if the distribution of wealth for the school based sample compared with the distribution of wealth for the entire community. If they are the same, we have no problems of socio-economic bias.
We can see, however, from the above plot that the distributions differ. The distribution of SES scores for the school based survey is far more bottom heavy than that of the great community; the school based survey excludes wealthier households. The mean wealth score for the school based survey is well under that of the community as a whole (-.025 vs. -.004, t=-19.32, p<.0001).
Just from this, we can see that the school based survey is likely NOT representative of the community and that the school based sample is far more homogeneous than the community from which the kids are drawn.
Researchers find working with continuous measure of SES unwieldy and difficult to present. To solve this problem, they will often place households into socio-economic "classes" by dividing the data set up into . quantiles. These will represent households which range from "ultra poor" to "wealthy." A problem with samples is that these classifications may not be the same over the range of samples, and only some of them will accurately reflect the true population level classification.
In this case, when looking at a table of how these classes correspond to one another, we find the following:
Assuming that these SES “classes” are at all meaningful (another discussion) We can see that for all but the wealthiest households more than 80% of households have been misclassified! Further, due to the sensitivity of the method (multiple correspondence analysis) used to create the composite, 17 of households classified as “ultra poor” in the full survey have suddenly become “wealthy.”
Now, whether these misclassifications impact the results of the study remains to be seen. It may be that they do not. It also may be the case that investigators may not be interested in drawing conclusions about the community and may only want to say something about children who attend particular types of schools (though this distinction is often vague in practice). Regardless, sampling matters. A properly designed survey can improve data quality vastly.
I wanted to go and see what this jigger thing was really about so I had my guys rent a car and we drove into Mtsangatamu town. Mtsangatamu (I still can’t pronounce it properly) lies along the edge of the Shimba Hills Wildlife Reserve and, according to my data, is a hot spot for tungiasis, or infections from the so called “jigger flea.”
It is a beautiful area. Filled with tropical trees and overgrowth, the landscape looks almost uncontrollable, despite the soil being so sandy that not a drop of water stands anywhere. The air is blistering hot.
People don’t get out here much, though the packed buses that pass by every few minutes indicate that the area isn’t entirely isolated. We drop off some gas for one of our drivers, who has to slowly fill his tank, drop by drop, with the tiniest of plastic funnels. Some development project should provide proper plastic funnels to these guys.
For some reason, we drive into the bush along a foot path, until we find ourselves wedged between a number of small pine trees. “We have to walk now,” I am told while I wonder why we drove this far anyway. Walking would have been easier.
We exit the car, walk through what a patch of neatly arranged trees. A tiny tree farm. I never see this in Western, ever. Coming out, we walk into a compound laid out in a manner wholly uncharacteristic of Kenya. A two story building sporting an upstairs patio complete with a winding staircase to the top, the place looked like the type of patchwork architecture that you associate with off-gridders in the US rather than Kenyan peasants.
The Mighty Paraffee turns out to be a kid of about 24, chilling out in the shade. He built this place himself, installed power, has a guest room and an upstairs shower and toilet. His room is decorated with reggae stars and pictures of the saints. Indian music is blaring out of the building. I’ve seen creative interiors from reggae fans in Kenya, but this is something else. This kid should be in architectural school. He even made sure to place the building under a giant tree to keep it cool.
I never figure out what the family does for money and no one can tell me, but the mother is exceedingly proud.
No jiggers here. We walk on. After about a kilometer, we find a poor family sitting outside their house. Children aren’t in school and no one speaks any English indicating that none of them go.
Hassan (one or our workers) brings over a little girl and tells me to look at her feet. Fatuma is 10 years old and her feet are infested with jiggers. She says the don’t hurt much in the day, but they itch at night. Her brother apparently has them, too. Her mother and her aunt do not.
Everyone is barefoot and they all sleep in the same house. I’m wondering if there might be something about the skin which makes kids susceptible while adults are spared.
I notice a group of goats in a pen and start asking questions about animals.
Tungiasis is a zoonotic disease. It is passed from wildlife to domesticated animals to people who bring it into the household and infect their other family members. Or so it is though. Not many people have really explored the question sufficiently. Of course, this is why I’m here.
They have about 15 goats, a few chickens and I notice a young dog and a cat walking around. I ask if they ever notice whether the dog ever has jiggers. They say no.
“What kinds of wildlife do you see around here?” One of the kids was killed by an elephant last year. There are wild dogs and hyenas which come and try to get the goats. Wild pigs dig up the cassava at night.
Pigs. That has to be it. A big mystery has been why there is such a tight relationship between distance to the park and jiggers infections. Wild pigs come out of the forest, raid the fields of the locals and get water from the river, and then recede back into the darkness before morning. 5km is approximately the distance that a pig could feasibly travel and return home in one night.
Pigs travel through and around the compound, dropping eggs, they mature and are probably picked up by dogs, but are most likely picked up by kids walking in the bush. They then bring them back home and pass them on to their family members.
Hassan associates jiggers with mango flowers, but I probe him further and find that the flowers coincide with the very dry season, which could explain why pigs are making the trek to the river and why they prefer the fields since both water and food are probably scarce in the forest.
I have to send a student out to investigate this further.
An old man comes out. He looks nearly 90, but is mostly likely on 60 at most. He has arthritis in his back. He shows me his feet which are moderately infected, mostly only between the toes. He asks for medicine. I tell him I’ll send some along. He offers me some boiled cassava which I graciously take. My colleague refuses because there are no cashew nuts with it, but I suspect that he’s worried about getting sick. I become concerned.
We take some pictures and go.
On the way back, we run into an elderly lady. She’s sitting next to her husband, who is busy getting lit on homemade beer at 11 in the morning. She shows me her feet. The spaces around her feet are infested with jiggers. It must be horribly painful.
She points out that she doesn’t have a whole lot of feeling in her left foot. I notice that her skin in this area is clear; the bone is visible through her skin. I ask what happened. She says that she got bitten by a snake 40 years ago. She was pregnant. I ask her if the baby was ok. “The baby is standing there!”
I consider making a joke about a snake baby, but think better of it. I’m just amazed that both of them survived. The wound was horrible looking.
Somehow, we manage to pull ourselves out of the trees and move on. There are some baboons removing mites from one another on the road on the way back, and I take some pictures. My colleague is about to pass out from the heat. I offer to drive.
What are we talking about when we discuss socio-economic position and health in developing countries?
A wide body of literature has found that socio-economic position (SEP) has profound impacts on the health status of individuals. Poor people are sicker than rich people. We find this relationship all over the world and in countries like the United States, it couldn’t be more apparent.
Poor people, particularly poor minorities, are more likely to see their children die, are more likely to be obese, have worse cardiac outcomes, develop cancer more often, are disproportionately afflicted by infectious diseases and die earlier than people who are not poor. There is ample evidence to support this.
However, the exact factors which lead to this disparity are up to debate. Some focus on issues of lifestyle, diet, neighborhood effects and access to health care. Poor people, particularly minorities, live hard, eat worse, live in dangerous or toxic environments and have low access to quality care all contributing to a perfect storm of dangerous health risks.
However, even when controlling for all or any of these factors, we still find that poor people, and particularly African-Americans, still get sick more often, get sicker and die earlier. This leads us to speculate that health disparities are not simply a matter of access to material goods which promote good health, but are tightly related to something less tangible, such as social marginalization and racism, which are both incredibly difficult to measure. Though difficult to quantify, however, we do have plenty of well documented qualitative and historical data which indicate that these relationships are entirely plausible.
The awful history of slavery and apartheid, however, is somewhat (but not completely) unique to the United States. Further, our ideas of class come from another Western idea, the Marxist concept of one privileged group exploiting the weak for their own financial gain, particularly in the context of manufacturing.
Yet, though these ways of conceiving of race and class are so specific to the West, they are applied liberally to analyses of developing country health, with little consideration of their validity.
It is not uncommon to see studies of socio-economic status and health. The typical method of measuring socio-economic status in developing countries is to examine the collection of household assets such as TVs, radios, bicycles, etc. and, using statistically derived weights, sum up all of the things a household owns and call that sum a total measure of wealth. The collection of total measures for each household are then divided into categories, with the implication that they roughly approximate our conception of class.
Not surprisingly, it is usually found that people who don’t own much are, compared with people who do, at higher risk for malaria, TB, diarrheal disease, infant and maternal mortality and a host of other things that one wouldn’t wish on anyone.
But this measure is problematic. First, there is often little care taken to parse out which items are related to the disease of interest. For example, we would expect that better housing conditions are associated with a decreased risk for malaria, since mosquitoes aren’t able to enter a house at night. We would also expect that people with access to clean water would be more likely to not get cholera. If we find relationships of SEP with malaria or diarrheal disease which include these items, these associations should be treated with suspicion.
Second, if we do find a relationship of “class” with health, can we view it in the same way in which we might view this relationship in the United States? A Marxist approach, with a few exploiting the many for profit, in sub-Saharan Africa doesn’t make a whole lot of sense. The manufacturing capacity of African countries is tiny, and most people are sole entrepreneurs operating in an economy that hasn’t changed appreciably from pre-colonial times. Stripping away any requirements of legal protection of property rights, Africa looks incredibly libertarian.
Further, the elite in Africa hardly profit financially from the poor, receiving their cash flows mainly from abroad in the form of foreign aid or bribery and foreign activity is mostly limited to resource exploitation, which doesn’t make a dent into Africa’s vast levels of unemployment. While the West is certainly complicit is Africa’s economic woes, post slavery, the West rarely engages Africans themselves.
So, is it valid to attempt to apply the same ideas of class to African health problems? Is there a way to attribute health disparities to class in societies with limited economic capacity and where the “citizenry” is only marginally engaged and groups suffer mainly from a reluctance to cooperate and engage people of other tribes or neighboring countries?
Certainly, the causes of poverty and marginalization in Africa need to be examined, but I don’t think that we can approach them in the same way we do in the States.
New Publication (from me): “Insecticide-treated net use before and after mass distribution in a fishing community along Lake Victoria, Kenya: successes and unavoidable pitfalls”
This was was years in the making but it is finally out in Malaria Journal and ready for the world’s perusal. Done.
Insecticide-treated net use before and after mass distribution in a fishing community along Lake Victoria, Kenya: successes and unavoidable pitfalls
Peter S Larson, Noboru Minakawa, Gabriel O Dida, Sammy M Njenga, Edward L Ionides and Mark L Wilson
Insecticide-treated nets (ITNs) have proven instrumental in the successful reduction of malaria incidence in holoendemic regions during the past decade. As distribution of ITNs throughout sub-Saharan Africa (SSA) is being scaled up, maintaining maximal levels of coverage will be necessary to sustain current gains. The effectiveness of mass distribution of ITNs, requires careful analysis of successes and failures if impacts are to be sustained over the long term.
Mass distribution of ITNs to a rural Kenyan community along Lake Victoria was performed in early 2011. Surveyors collected data on ITN use both before and one year following this distribution. At both times, household representatives were asked to provide a complete accounting of ITNs within the dwelling, the location of each net, and the ages and genders of each person who slept under that net the previous night. Other data on household material possessions, education levels and occupations were recorded. Information on malaria preventative factors such as ceiling nets and indoor residual spraying was noted. Basic information on malaria knowledge and health-seeking behaviours was also collected. Patterns of ITN use before and one year following net distribution were compared using spatial and multi-variable statistical methods. Associations of ITN use with various individual, household, demographic and malaria related factors were tested using logistic regression.
After infancy (<1 year), ITN use sharply declined until the late teenage years then began to rise again, plateauing at 30 years of age. Males were less likely to use ITNs than females. Prior to distribution, socio-economic factors such as parental education and occupation were associated with ITN use. Following distribution, ITN use was similar across social groups. Household factors such as availability of nets and sleeping arrangements still reduced consistent net use, however.
Comprehensive, direct-to-household, mass distribution of ITNs was effective in rapidly scaling up coverage, with use being maintained at a high level at least one year following the intervention. Free distribution of ITNs through direct-to-household distribution method can eliminate important constraints in determining consistent ITN use, thus enhancing the sustainability of effective intervention campaigns.
Ebola is a cool disease. It transmits among fruit bats in the area in and around the Central African Republic. Apes live in and under the trees the bats live in and ingest their feces. Humans who ingest the apes pick up the virus when slaughtering the animal, or so some think. The truth is that no one really knows for sure.
Contacts between humans is increasing as settlements expand and a demand for meat increases. Lacking access to formal methods of employment, individual sellers happily take advantage of market demand and a thinly profitable trade in bushmeat profulgates. Meat equals success and in the place of professionally or pastorally raised beef, which is mostly unavailable to poor people in countries like Liberia and Sierre Leone, people eat the monkeys, chimps and many other of our cousins which are able to harbor the many of the same pathogens we do.
One person gets sick. He or she has no access to formal care because his or her government can’t or won’t provide it so he remains at home. The family consults the local herbalist who provides some medications which offer temporary psychological relief but nothing more. As time ticks on, the victim becomes even sicker until the situation becomes so serious that the family has no choice but to carry their dying loved one to a health clinic 20 km away from their house. Along the way, everyone carrying him or her touches infected feces and vomit and three weeks later the process is repeated.
This could have all been avoided if rural economies were developed enough so that a mass migration to urban areas wasn’t necessary, had there been safer sources of meat available for an affordable price, were there sufficient jobs which wouldn’t necessitate the bushmeat trade, were the governments of Liberia and Sierre Leone effective enough to place a proper health facility close by to patient 0’s house and if health care was dependable enough to be able to spot and deal with an Ebola case.
Ebola is a conflation of ecology, economics, sociology, culture and politics, all mixed together to create conditions for one of the worst health crises the African continent has seen since HIV. It’s going to erase any of the gains of the past decade and collapse the already struggling health systems of some of the poorest places on the planet.
Meanwhile, the United States is having another 9/11 moment and this is where I’m starting to get quite concerned. Panic is about to become policy. Fears of global terrorism prompted our entry into Afghanistan, which might have been justified. But it also paved the way for the invasion of Iraq, which, from the beginning, was a disaster waiting to happen. Out of 9/11, we got the Patriot Act, a massive expansion in government powers to search, seize and detain and America stood by and allowed it to happen with little debate.
I am not a Libertarian, though keep getting accused of being one. I believe in public schools, public health care and government oversight of dangerous industries. So there. John Galt wouldn’t be much into me (but I guess from the far, far left anyone looks like a Libertarian).
I am, however, despite my leftist pedigree, quite concerned with the rights of individuals and the potential for panic and ignorance to lead to a rhetoric that can quickly spiral out of control and veer seemingly caring people away from the direction that the moral compass would normally point us in. I am remembering how many Americans supported torture during Bush II and wondered how many of them would support torture were it to be practiced on their own children. Though seemingly alarmist, I think that we need to be extremely careful.
Enough about me. The reality of Ebola is that it is a man-made crisis. Forest dwelling locals have eaten bushmeat for as long as humans have lived there but there is little evidence that there has ever been a large scale outbreak like the one we are currently experiencing (though history in Africa is often obscure). As I noted earlier, many forces are at play, all of which are associated with the rapid social change that Sub-Saharan African states are currently experiencing.
Some of these forces are inevitable. Population growth, as it did in Europe and Asia before, has led to the creation of mega-cities. The connections, however, between the rural and the urban, however have not been severed. People are going to do what they do, regardless of risk, particularly if they can make a buck meeting some market demand.
Some forces, though, are avoidable. While health care did not initiate the crisis, it helped drag it along. Liberia and Sierre Leone can boast to have two of the worst health systems in the world, but their poor capabilities are hardly unique in Sub-Saharan Africa. NGOs and missionary groups work to plug some of the gaps, but the reality is that without a concerted and proactive effort from the governments of those countries, the system will never improve. International funding is too poor and weak national economies and top heavy tax structures can’t adequately fund these systems domestically. Poor funding leaves many clinics, particularly those in rural areas where these outbreaks begin, without supplies, trained staff and diagnostic equipment. In Kenya, Malawi and Tanzania, I’ve seen more than one rural clinic without power or clean water. Worse yet, Ebola outbreaks, though devastating, are infrequent so that more pressing needs like malaria, diarrheal disease and HIV eat up the brunt of the already scarce funds clinics receive. Pathogens not only compete in the wild, but also for funding and support. This leaves many rural health workers without the protective gear they need, so that they work are the highest risk for death from diseases like Ebola.
What can we do? First, we can calm down. In the United States, the reality is that one of far more likely to be killed by an oncoming car than from Ebola and the probability of sustained transmission extremely low. Though people like to view domestic transmission events such as the one in Texas as failure, the reality is that public health and medical resources move much more quickly and effectively in Texas than in troubled Liberia. Much is made over Ebola’s lethality, but a patient who is found to be infected in the United States has a vastly higher likelihood of surviving than one in Liberia.
Second, leaders can stop spreading and capitalizing on misinformation. While attractive, promoting hysteria only leads to bad policy. The tendency in America is to view as some kind of apocalyptic movie scenario. While fun (not to me), the reality is that there are people in the world who are dying who shouldn’t be. Moreover, closing schools because someone knows someone who knows a Liberian is just simply unwise and counterproductive in the long term.
Third, the international community needs to engage the governments of Liberia and Sierre Leone to improve their public health infrastructure. This is not an easy task. The histories of working relationships of international health bodies and developing countries governments are fraught with failure. Mutual distrust, corruption and indifference of political leaders to the plight of their constituencies has created a mostly untenable system. However, providing supplies and training come at little cost is a mostly uncontroversial affair.
How long will this last? No one knows but it is inevitable that, even if this epidemic is brought under control, it certainly won’t be the last of its kind. We don’t have time to waste.
I’m reading through news about the American rights hijacking of the Ebola crisis for their own political gain. Did this outbreak have to occur right before the midterms, and right before a Senate election? The awful toll it will take on West African states aside, the virus couldn’t have picked a worse time (or a better, depending on how you look at it).
Ebola is a scary virus, assuming that one ever has the misfortune to come into contact with it. “Contact” in this case, means that you have to have direct contact with the blood, feces or vomit of a person infected and symptomatic with Ebola. Unfortunately for the virus, people don’t really live that long once they become symptomatic with the disease and the people who survive appear to be immune to it
This is a terrible model for an infectious pathogen. The symptoms are so severe that all around the person will immediately run away (except health workers, who bear the brunt of the risk) and the host doesn’t live very long providing only a short window with which to infect other hosts.
So the duration of infectiousness is short, the pathways are really awful and repeat infections are unlikely.
To put this into perspective, looks at the most successful pathogens out there, pathogens like influenza. Influenza transmits easily, nearly two thirds of those infected show no symptoms and thus can happily shed viral particles to everyone they know undetected. When symptoms do occur, they aren’t so bad as to keep every outside of a 5 miles radius of you. Influenza mutates at an incredible rate, so that a single infection doesn’t provide much protection against later infections. Even better, though its rapid mutation rate sometimes leads to horribly virulent strains like the 1918 flu pandemic which killed millions, in most cases influenza spares a healthy host.
It has developed an incredibly efficient and effective survival strategy (and for this reason is far scarier than Ebola).
So I’ve been thinking of how a virus like Ebola might persist in the wild, given it’s odd mode of transmission.
Now, we know that Ebola is a zoonotic disease, that is, it is transmitted from animal to humans. Since humans have not developed genetic resistance to the disease, we are at particular risk for its worst effects. Many of the scariest diseases out there are zoonoses. Examples would include HIV, SARS and, of course, influenza. While not always true, we tend to make peace with pathogens that are old and exclusively human. Many of the bacteria which live happily in your gut would be examples. As we haven’t had sufficient time to make peace with Ebola or HIV, the outcomes can be far worse than those seen in their normal hosts.
Thus, it is possible that Ebola is far less serious in whatever host it is adapted for. Nipa virus, which has a case fatality rate (the percentage of all infections of a pathogen which result in death) of more than 90% does nothing to the fruit bats it happily resides in. It is possible that Ebola is also harmless to whatever host it depends on.
However, it is possible that Ebola might be harmless in some hosts, while deadly in others, and this difference might be the result of a successful evolutionary adaptation.
Ebola has been pegged as residing in bats possibly explaining its wide range over central Africa. [1-6] Bats are a pathogens dream. They multiply quickly, providing ample opportunities for transmission and for evolutionary adaptations to the pathogen which might insure its long term survival. Better yet, they fly so that pathogens can disperse themselves quickly over a large geographic space. This is particularly useful if the pathogens wants to maintain healthy genetic diversity (though the creation of multiple sub-populations) and if it can infect multiple hosts which may or may not be all that mobile.
Apes would be a good example of the latter. Apes, being fairly sensitive to environmental changes, don’t like to move around a whole lot (unlike humans which are highly adaptable to just about any environment on the planet) but still might be important to the survival of the pathogen.
Ebola has been found in apes and the disease is currently devastating local populations.[4, 7-10]
And this is where I get stuck. In nature, plenty of things happen for no reason at all, but with pathogens, even accidental occurrences can have implications for survival and are often part of the tool box with which diseases evolve and persist.
A bleeding ape on a forest floor will likely kill all of its relatives in quick fashion, assuming its family doesn’t just hightail it out in which case transmission is over anyway. But the dead ape might serve an important purpose. Predators and scavengers will quickly arrive to feast on the infected corpse, transmitting the virus to carnivorous animals all around the forest. This could provide ample opportunities for transmission to other species. Even though many of these species could be poor hosts for the disease, they could also represent new opportunities for survival.
HIV would be an example of this. From HIV’s standpoint (assuming a collective viral consciousness), the jump to humans was extremely fortuitous. Humans love to have sex with multiple people, often even after having already reproduced, and physiologically they proved resistant enough to allow the virus to hang out for a few years before dying, allowing for years of transmission possibilities.
Thus, while on the surface, blood based modes of transmission seem pretty useless, they could serve a larger purpose of insuring a pathogens survival on a macro-level. In the case of HIV, humans didn’t turn into a dead end host (as they are with diseases like Brucella) but rather a new opportunity for survival.
The deadly nature of the virus in apes and humans, then might be like an insurance policy. Like a retirement portfolio, a diversified package of stocks will keep you alive in retirement much better than a portfolio with a single stock. Work has been done on pathogens which infect multiple species, and, depending on the nature of the pathogen, species diversity can either work for or against the survival of the pathogen.[11-13]
In the case of Ebola, there is no real evidence that humans play a role in sustaining transmission, but blood and predation could be sustaining something like Brucella or Q Fever in the wild.
Now, in this article, I have rambled on and bored you to death (and bless you if you made it this far) but I have to point out that I am under no illusions that pathogens act consciously, though I have like many of my colleagues present it as such. Actually, no living thing really does have a long term plan outside of its narrow goals of producing offspring. But new opportunities for transmission do present new opportunities for the long term evolutionary survival or a biological entity. These lucky occurrences are not consciously sought out, but rather enable the pathogen to do what it does successfully.
It must be said that the ecology of Ebola is somewhat of a mystery. Not much work has been done on the subject, as the pathogen hides out in some of the most inaccessible areas of the planet, and conflict and political instability in places like the Central African Republic and Northern Uganda prevent researchers from doing extensive work on the pathogen.
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