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Snake Bites in Kwale, Kenya: Into the Field

snakebitesWe just spent the day driving around Kwale looking for snakes, and/or people who had been bitten by snakes. As the last post showed, snakebites are a persistent problem along the Kenyan Coast, with more then 5% of the households we survey indicating that at least one person in the household had been bitten in the past two years.

It wasn’t difficult to find them.

Snakes are universally feared all over Africa and the associations with witchcraft make it a common topic of discussion. Everyone knows someone who has been bitten. They often know all the details, including where it happened and what occurred following the bite. It’s never a happy story.

We went deep into Kinango, an extremely rural area west of Kwale Town and found a friendly lady who seemed to know everything about everyone. She was incredibly jolly, pulled out some plastic chairs for us to sit under and cracked jokes the whole time. I even got to copy her collection of Sangeya music which she had recorded on her phone (another post but you can hear some of it here) at some local music festivals. In total I got more than five hours of live Sengeya and Chilewa music. In the music world, these would be called “field recordings.” Here, this is just music she cooks and cleans to.

Switching back and forth between snakes and Sengenya (in Africa it seems to be possible to have multiple conversations at once), she told us about a kid who had been bitten two days previous. She even told us where to find her, so off we went.

The child was collecting firewood around a mango tree near her home, when she was suddenly bitten by a large green snake, not once but three times on the foot. The snake bit once skated away, decided it wasn’t enough and came back and bit her twice more.

Ants had moved into the dead tree and hollowed out the area underneath. Presumably, the snake moved in previously and came out to warm up during the day.

The mother thankfully took the child immediately to Kinango Hospital and treated was administered. The child was given a three day course of antivenom injections and charcoal was wrapped around the wounds to absorb any venomous discharge. Though the child complains of some numbness in the area, it looks as if there won’t be any permanent damage. Thankfully.


Snake bite (species unknown). Note the charcoal. Victim is a 10 year old girl.

We were also told of an old woman who had been bitten more than 20 years ago, and was badly scarred, figured out where she was and off we went again.

As we pulled up a friendly young lady came out to greet us, and showed us the way to the house out back. In the distance, we could see an old lady walking with a limp. Otherwise, she was completely fit and seemed to be cutting her own firewood with a panga.

She brought us out some chairs and sat down to chat. In 1992, she had been out back collecting firewood (a pattern) and was bitten on the foot by puff adder, one of the deadliest snakes in the world. She was bitten on the foot, and became immobile for nearly a week. A series of witch doctors were brought in, who administered charcoal rubbed into small cuts in the skin.

Necrosis set in, and watery blood erupted out of the wound site. A large number of maggots appeared. Finally, someone had the good sense to take her to the hospital, where she spent an entire year.

The details were unclear, but it appeared that the gangrene was so severe that multiple infections were presents. They likely had her on intravenous antibiotics for an extended amount of time. Despite this, the foot did not heal. Some Christian missionaries came, and convinced her to convert to Christianity, which, she claimed, improved her condition. This is likely coincidental.


Puff Adder wound. Note the permanent curvature of the foot. She continues to have to wrap it and use topical medication, 24 years following the bite.

The doctors suggested a skin graft to improve the foot, but she refused. Necrosis was so deep that it permeated the bone and the foot is permanently curved as a result. The leg still shows sign of swelling even more than 24 years after the bite. In most cases, they probably would have simply amputated.

The lady was born in 1948, bore ten children, one of which was born just as she was bitten. She was unable to breast feed or care for the child. Regardless, the daughter has two children of her own now.

Snakebites are bad news. In this woman’s case, the disregard for proper medical care simply made a bad situation worse. She is truly lucky to be alive. If she had died, it is doubtful that the Mgangas would have admitted any responsibility.


Puff Adder victim, born in 1948. Ten kids. Still going strong.

Snakebites in Kwale, Kenya

I sent our DSS out looking for snake bites, and they found them! We simply asked households if anyone in the household had been bitten by a snake in the past five years. More then 5% of them said “yes” and since we know the locations of the households, we were able to make this cool map. Note that the snake bites tend to cluster around two large areas and are noticeably absent from others.

Kenya hosts many varieties of extremely poisonous snakes included the Puff Adder, the Black and Green Mamba and the spitting Cobra. Snakes are universally feared here and often killed on sight by the locals.


More “music” no one will care about.

DG002 (1 of 1).jpgBecause we shouldn’t deceive ourselves. The digital age has provided too many opportunities for people who shouldn’t necessarily be putting out records  and flooded whatever market may exist, reducing opportunities for everyone.

It’s like the famous tragedy of the commons, “an economic theory of a situation within a shared-resource system where individual users acting independently and rationally according to their own self-interest behave contrary to the common good of all users by depleting that resource.” So, I just quoted Wikipedia. Strike two, maybe.

So here I am, acting in my own self-interest and behaving contrary to the common good, through my second collection of songs for Mark Maynard’s Saturday Six Pack Radio show. For those who don’t know, I wake up every Saturday, improvise a song and send it to him for airplay later than evening. It requires little work from me, no financial investment, and gives me something to do besides mope in my Nairobi apartment about what my life has become.

Enjoy (if you can). You can find it here on Bandcamp and even purchase it if you are feeling particularly sorry for me.

Here’s the video for the lead track.


Rising wealth in Kenya: is everyone benefitting?

Picture1Looking at some data on socio-economic status (SES) from two regions of Kenya, I was able to compare current levels of household wealth with those of 2007 in the same households.

We measured SES using a method common to studies of developing countries. An accounting of specific material goods including ownership of radios, TVs and bikes along with type of water source, toilet is performed. We then use multiple correspondence analysis to assign weights to each item as they appear in the data set and a total score is calculated for each household (Filmer and Pritchett, 2001 though they use PCA). Each score (ideally) represents the relative level of wealth of each household.

Kenya’s GDP has been increasing rapidly since 2001. During my five years of travelling to this country, I’ve seen the place transform itself. There are more goods on the shelves, people look better, kids die less and women have fewer children. HIV and malaria are down and people are busier. It’s worth noting that Kenya has no real natural resources; its economy is mostly based on a well developed domestic market economy and agricultural exports.

The question, however, is whether these economic gains are being felt by everyone equally. To test this, I compared data from 2007 and 2015 to see if all households experienced an increase in wealth during this period.

I made the graph above. Assuming I’m interpreting the graph correctly, this would suggest that while wealthier households in 2007 consistently continue to be wealthy in 2015, the relationship for poor households is scattered. Some households are doing better, while other may have experience no change, while others may be poorer in 2015.

Clearly, no matter how one interprets these results, we should be explore what types of households might be falling behind, or experience no gains at all.

New Publication: “First Report of a Foodborne Providencia alcalifaciens Outbreak in Kenya.”

mukimoI’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]

Eid in Kwale, Kenya

untitled shoot-051

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.

Does sampling design impact socio-economic classification?

DSC_2057Doing 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).

Distributions 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:

Misclassification of households in school based sample

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.

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