The potential of the smartphone to place a doctor within reach of people in even very remote or very poor settings means that we have an opportunity to improve healthcare delivery in places regarded traditionally as “hard to reach”, both in economic and geographical terms. This includes many communities across the African continent. But how widespread is phone ownership in Africa? That’s the critical starting point for any intervention, so operators can predict who they can, and more critically who they can’t reach this way. Speaking with Chris Smith, Sally Blower, at UCLA, has been looking at data collected from 33 African countries to try to form a picture of where the gaps are…
Sally – In these resource constrained countries there’s very poor healthcare infrastructure and many people live far away from healthcare facilities, so they have to walk long distances. Having Mhealth interventions in which they can call in with phones means there’ll be better healthcare and people who live far away from it will have greater access to healthcare.
Chris – I must admit, I mean, I’ve traveled in Southern Africa quite extensively. (Yes). Most people I’ve bumped into in rural Africa tell me they would rather go without food than charge for their mobile phone.
Sally – Exactly. It has become an increasingly important part of life. People use it for business, agriculture, education and government health services. For many, for during Covid many people, if you required vaccination, wanted vaccination, you had to go in using your mobile phone to access the services.
Chris – Well, that would suggest then that actually uptake is pretty comprehensive. Is that what you found?
Sally – We found it as pretty comprehensive in that about 80% of people in the 33 African countries we looked at have access / own mobile phones. About half of these people own smartphones, so they have access to the internet and the other half own basic phones. But there’s a huge difference among the 33 countries we looked at. And obviously if 80% own it, there’s 20% who don’t. And that’s quite a large percentage of people.
Chris – Yes, indeed. Also though, is that 80% of the population as a whole, but when you look at the stratification of that population, a hundred percent of kids and a smattering of middle-aged people are no elderly people or is it pretty generalized across? How does it break down?
Sally – There’s a lot of inequity. When it comes to age. Most of the phone owners are because of the demographics of Africa, most phone owners, mobile phone owners are under 30. And they tend to own smartphones. People over 30 tend to own basic phones.
Chris – So that would argue then that we have actually got a problem in some respects because most people in most countries, most of the time access healthcare when they’re older.
Sally – Exactly. So the obvious for women in antenatal care, that will be younger women generally, but yes. For healthcare that, that’s correct. And then we’ve got, we found great inequities into who actually owns phones, mobile phones.
Chris – In what respect?
Sally – Well, there are great gender differences. So men are twice as likely to own mobile phones than women. And we found urban rural differences. People living in urban areas are about three times more likely to own mobile phones than people in rural districts. The age difference I’ve mentioned and wealthy that the poorer you are, the less likely you are to own a mobile phone. Although we did find some interesting differences in that some people who are very poor do own smartphones.
Chris – I was going to say, is this just a function of wealth? Because a lot of those factors do really co-localize with people who are likely to be in work.
Sally – Yes, it does. It does depend a lot on wealth, but wealth can be men and women in a couple can have the same level of wealth, but still the man is likely to own the phone and the woman is not likely. So it’s not a simple function.
Chris – This is quite fine grained data from 33 countries. How did you do this?
Sally – So we got the data from a database called Afro Barometer, and this is a public opinion data questionnaires that are collected throughout 33 countries in Africa. And basically they collect social, social data on politics and economics and governance, but they also have one or two questions on mobile phones. So that’s why we chose to use that database.
Chris – And what are the implications of this then? I mean, I know we started this conversation by looking at the, the reason why this matters in terms of doing health interactions and so on, in resource poor settings. But give them what you’ve now found with this data in hand and these results. How does this guide, change or have implications for what we do about these health interventions over mobile devices?
Sally – Well, I think the thing about the mobile health interventions is they’re being rolled out as pilot studies, so little studies to see if they work or not, if they’re effective when they’re rolled out at the large scale , what will need to be done is to address the inequities, the urban, rural, the gender, the age so that the people who are the most in need of these health interventions do not suffer from not attaining access to them.
Chris – Have you looked over time though, longitudinally at these dates? Presumably this, this survey has been run more than once, and therefore a rate of change could be approximated. Is this a problem that will just take care of itself, it’s going to fix itself and it’s going to do it quite quickly? Or are these entrenched in inequalities that are not going to fix themselves and they do need active intervention?
Sally – Well, I do think a lot of them are entrenched. You’re quite right. The survey has been conducted. This was the seventh wave of the survey and mobile phone usage has been growing over time. Whether it’s going to continue to grow or not depends on what’s happening in Africa. Obviously with the urbanization that’s happening in every country, that suggests that greater wealth and more people would own smartphones. However, the same is, is happening, uh the other way that in rural areas people are getting poorer. So it might be that mobile phones grow, but that most people are buying the basic mobile phones rather than smartphones. But that will be addressed, um more data are being collected and more data will be able to be analyzed as time goes by.
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