Tracking Spread of Disease Through Mobile Phones

Disease Intelligence Network, Part II

A while ago I told you all about the concept of the Disease Intelligence Network. As a refresher, the elevator pitch is this: we plan to collect health data and make it useful to the health workers. We want to know who has a cough (and where they are) this week to prevent it in others next week.  Well, concept has become reality! At least a little bit.

The last four weeks, I’ve sent surveys with the health reps. It’s unfortunate for the data enterer (me) that there are only about three male Kurian names (Mwita, Maroa, Chacha). If you’re lucky, you get a “Christian” name mixed in there (e.g. Peter, George…because George was a very important character in the Bible). But last names work differently here. They’re not really last; they “other” names. Parents like to keep the memory of all their relatives alive in their children’s names; unfortunately their relatives were also called Mwita, Maroa and Chacha.

What has drastically improved the efficiency of data entry is printing an individual sheet with the farmers names ALREADY printed. The Health Rep from Gesiora Group is a lot better at finding Mr. Chacha Mwita of Gesiora Group than I am at discerning “Chacha Mwita” scrawled on paper and finding which of the 35 Chacha Mwitas I should put that data under. Also, they know who’s married to whom a lot better than I do (so if a wife answers a survey, I know which family it’s from).

That hurdle overcome, the next step is to input the data. With the lists pre-printed, I just need to Ctrl-F my way to victory. It took me about an hour to put in the data for most of the farmers. Not too shabby, but shabby nonetheless. A present work in progress is to figure out how to make that faster and not me. Computer literacy here is very poor and experiments computer trainings have been disappointing (it took one person new to computers an hour to input one of the seventy groups). Our most promising lead is to get the Health Reps to do it themselves.

“Wait!” you must be thinking, “But how are you going to get 70 laptops?” And I would say in reply, “Who needs laptops when cell phones do everything laptops can!” We’ve been talking with SMS:Frontline Medic, an organization that does great work in using cell phones for communicating with CHWs. People don’t know how to use computers at all, but almost everyone knows and/or is learning to use cell phones. And PS just so you know, the cell networks are amazing here. I can buy GPRS data for about $0.03 per MB. And I haven’t found a dead spot yet. Take that developed world!

So after a month of data, what do we see? It’s tough to say. I’m proposing to Stanford that we do this formally for 6 months and analyze it rigorously. But for now, I think I see certain patterns. For example, there was an area one week with a single case of diarrhea; the next week, there were dozens in that area. Did the one cause the others? We can’t know yet. (Technically with what I have proposed, we can’t ever actually determine causality; but who cares? Because we may be able to determine that there is a strong correlation between a particular case of diarrhea and cases in the weeks to follow).

DIN may allow for other cool things beyond just the common diseases. Unaltered, it can help track and stem outbreaks of serious diseases like Cholera. We can send and alert and mobilize our team to warn people in at-risk areas and to distribute water purification products. Another possible idea is linking it with our in-planning health insurance; we can identify certain situations like a Malaria outbreak and use insurance to actually help stem the spread of the disease, rather than just pay for its treatment. If we predict a big Malaria outbreak with DIN, we can drop the patient co-pays for malaria visits to zero for a week or two (and announce this by health reps); this would increase those taking anti-malarials and may actually prevent the outbreak. This would, in addition to helping people directly, save money for us, the insurer, contributing to Nuru’s sustainability.

The bottom line is this: rapidly moving disease can be tracked with a precision and resolution previously unheard of. I had the privilege of meeting someone from the provincial medical office yesterday. We chatted about Nuru’s programs and he was mildly interested; but when he saw our first map, he said, “This is Revolutionary.” I certainly hope it is; I hope that it will bring better health for these people.


About David Carreon

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