Why malaria? Over-researched, over-funded, diminishing returns? Rambling on the need for student mentorship.
Last week I gave an informal lecture on survey sampling to a small group of graduate students from a number of countries. With only one exception, all of the students were working on various aspects of malaria, primarily in basic sciences. The lone non-malaria student was from Vietnam and is interested in Dengue fever.
I praised her for working on Dengue. Dengue presents a serious threat to human health in all countries where the vectors exist, but the burden of disease will be particularly felt in rapidly urbanizing areas of developing countries.
Developing countries are ill equipped to deal with Dengue, and the antiquated nature of their health care systems, leftover by the colonialists, means that diagnostics are mostly non-existent and drugs wholly unavailable. Any fever in most of Sub-Saharan Africa is diagnosed simply as malaria, drugs administered and the patient left on their own.
We have extensive experience, however, with malaria. While there are numerous challenges to reducing malaria incidence, preventing recrudescence and postponing drug resistance, the basic fact is that the best way to eliminate or control malaria is to simply make people less poor. Even countries with holoendemic transmission, wealthier people get malaria less often than poor people, and poor people who live in wealthier areas get sick less than wealthier people in poor areas. This is known (in Game of Thrones parlance).
So, as we discussed the topic during lecture, I softly tried to encourage the students to look at other areas where they might be able to better apply their skills. They were mostly unresponsive, which is fine. Someone has to tell them, it might as well be me.
One of the students, however, indicated that “malaria is where the money is.” I couldn’t disagree. The reason that we put so much money and effort into diseases like malaria and HIV is simply because they yield marketable products. Medications for diseases like tungiasis (jiggers) are so simple as to not be profitable, customers too poor to buy them, and governments and donors too distracted by big diseases like malaria, HIV and TB to be concerned with dumping money to provide them for free.
And this is where the problem lies. We have a self propagating system of companies, researchers and donors, which simply float money between one another with little regard for the needs of the poorest of the poor. Breaking the cycle is difficult, but it starts with academics who need to push students to do work with neglected, overlooked or under-researched diseases. Even small grants can support small, but meaningful projects.
We have reached a point where malaria funding for malaria research is yielding ever diminishing returns. Money needs to be put into programs to deliver the tools we have and make ITNs, ACTs and IRS available to the people who need them, who often have trouble getting them. Moreover, we need economic development to make people less poor in developing coutnries so that fewer of their babies die. Human resources in developed countries need to start focusing on emerging (or already emerged but ignored) threats lke antibiotic resistance, Dengue fever, emerging zoonotics and others. That starts with us as mentors.
I’m only a middle author, but I have a new publication out. After being involved in this, I will never eat mukimo (Kenyan mashed potato dish) ever again. Ever again.
First Report of a Foodborne Providencia alcalifaciens Outbreak in Kenya.
Shah MM, Odoyo E, Larson PS, Apondi E, Kathiiko C, Miringu G, Nakashima M, Ichinose Y.
Am J Trop Med Hyg. 2015 Jun 29. pii: 15-0126.
Providencia alcalifaciens is an emerging bacterial pathogen known to cause acute gastroenteritis in children and travelers. In July 2013, P. alcalifaciens was isolated from four children appearing for diarrhea at Kiambu District Hospital (KDH) in Kenya. This study describes the outbreak investigation, which aimed to identify the source and mechanisms of infection. We identified seven primary and four secondary cases. Among primary cases were four mothers who had children and experienced mild diarrhea after eating mashed potatoes. The mothers reported feeding children after visiting the toilet and washing their hands without soap. P. alcalifaciens was detected from all secondary cases, and the isolates were found to be clonal by random amplified polymorphic DNA (RAPD) fingerprinting. Our study suggests that the outbreak was caused by P. alcalifaciens, although no fluid accumulation was observed in rabbit ileal loops. The vehicle of the outbreak was believed to be the mashed potato dish, but the source of P. alcalifaciens could not be confirmed. We found that lack of hygiene, inadequate food storage, and improper hand washing before food preparation was the likely cause of the current outbreak. This is the first report of a foodborne infection caused by P. alcalifaciens in Kenya.
© The American Society of Tropical Medicine and Hygiene.
PMID: 26123962 [PubMed – as supplied by publisher]
I traveled out to Kwale on the Kenyan Coast and celebrated Eid (the end of Ramadan) with my friend Juma and his family in Mwachinga. It was a great time for everyone (except the goat). It rained on and off, but the ladies made up some great Pilau and the men had some conversations about Islam and witch doctor Senators. Juma even gave us a detailed family history. Finally, everyone had a serious discussion on the impacts of social media on family relations.
After a grueling 12 hour bus ride from Nairobi to Mombasa, the highlight of the trip was a two hour tuk tuk ride across the ferry and all the way out to Kwale Town. I’m still not sure how it made it up all the hills.
Infectious disease transmission dynamics and the ethics of intervention based public health research
I think a lot about ethics and ethical issues. Research in Sub-Saharan Africa presents unique risks for ethical breaches. Given income and power disparities between individuals and foreign researchers and even between individuals and local political leaders the possibility of coercive research is ever present. Pressure to produce can lead to unrealistic assumptions of risks and benefits to very poor individuals. Inadequate knowledge or willful ignorance of local political issues can compromise future research activities, both by international and domestic groups.
Recently, though, an interesting situation came across my desk that included an intersection of ethics and the dynamics of infectious disease transmission.
As everyone knows, not all infectious diseases are the same. Some, like measles, impart full immunity upon exposure, whereas diseases such as malaria impart only partial immunity, requiring repeated exposures to acquire full or adequate immunity to prevent death or serious injury. Moreover, as immunity and immune reactions change over the life course, the time (age) of exposure are sometimes crucial to prevent serious disease. Polio is a great example. Exposure in infancy leads merely to diarrhea, where exposure at older ages can lead to debilitating paralysis.
I was thinking of an population based intervention study which provides some sort of malaria medication to a small population in a holo-endemic area. Given the year round nature of malaria transmission in this area, we would expect that even with a depression in symptomatic and asymptomatic cases, active transmission in the surrounding areas would lead to recrudescence within a very short time. Given the short time frame, we would assume very little interruption in the development of immunity in small children and might even see a short term reduction of childhood mortality. Assuming that this medication presented little or no risk of serious side effects, I believe that there is little reason to assume an ethical breach. A short term reduction in malaria would suggest that the benefits far outweigh the risks.
However, conducting the same study on a very large population in the same area might have very different outcomes. Delivering a malaria medication to, say, an entire county surrounded by other areas of extremely high transmission would indicate that recrudescence is also inevitable but that the time required to return to pre-intervention levels is extended. Infectious disease transmission requires a chain of hosts. The longer that chain, the longer it will take for new hosts to become newly infected.
Theoretically, this could delay infections in small children and it is theoretically possible that we might see a spike in childhood mortality, since the timing of initial malaria infection and frequency of infections are crucial to preventing the worst outcomes.
Of course, I’m not suggesting that people should just get infected to induce immunity, but I am suggesting that a study which seeks to reduce transmission through pharmaceuticals given only intermittently (as opposed to prophylactically) consider all possible implications. Insecticide treated nets (ITNs) provide protection over time and are a form of vector control. A medication given at a single time point merely clears the parasite, but does nothing to prevent bites or kill mosquitoes.
Though I could be overthinking the issue, my worry is that ethical approvals approach the issue of mass distributions of pharmaceuticals as a one size fits all issue without taking other factors such as population size and acquired immunity into account. Malaria, as a complex vector borne disease introduces complexities that, say, measles does not. Researchers, IRBs and ethics board would do well to consider this complexity.
Not much else to post, so I’ll add a few pictures of a bird watching trip in the Gambia. Turns out the Gambia has an incredible bird diversity. Unfortunately, my camera couldn’t capture it but we play with the cards we are dealt with…
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.