Mohamed Ismail is Director of Analytical Research Ltd, and an Affiliate Research Fellow at the Oxford Institute of Population Ageing, University of Oxford. Trained in engineering, computer science, and mathematical finance, he began his career as a quantitative analyst in the City of London, working with major global financial institutions including Merrill Lynch, HSBC, Mizuho, and Credit Suisse. Since 2009, he has focused on quantitative social research, applying advanced statistical and mathematical modelling techniques to large and complex datasets. He collaborates internationally, has published in peer-reviewed journals, and regularly delivers invited talks.
His current research explores how mathematical and dynamical systems can inform our understanding of population ageing, particularly in relation to health and social care.
- How can countries prepare health systems for rapidly increasing long-term care needs driven by population ageing?
Most health systems were built to treat acute illness, things like a heart attack, an infection or a broken hip, and then send people home. Ageing populations need something the system was never really designed for: ongoing help with everyday tasks for people living with chronic conditions, disability and a gradual loss of function, often over many years. In many low- and middle-income countries, that shift is arriving faster than institutions can adapt to it.
The honest starting point is that most governments don’t know the scale of the problem they face. They can usually tell you how many older people live in the country, but not how many of them struggle to wash, dress, cook or move around without help. When that information is missing, planning becomes a reaction to crisis rather than something done in advance.
That gap is what our recent work tried to address. We built the LTC Needs Index to produce a population-level estimate of who is likely to need care, drawing on demographic and disease data that countries already collect rather than waiting for surveys that may be years away. An estimate is only a first step, though. The harder task is to start treating long-term care as part of mainstream health planning, including its financing, workforce and services, while there is still time to build it, rather than scrambling once the pressure has already arrived.
- What role do non-communicable diseases play in shaping future care dependency and health system demand?
Non-communicable diseases sit right at the centre of this. Diabetes, cardiovascular disease, dementia and Parkinson’s are usually discussed as causes of death, but they are also among the main routes by which people come to need daily care, because of the disability and functional decline that follow them.
In our study, recorded disability remained the strongest single driver of care need in seven of the eight countries we examined. What struck us was how much the diseases behind that need varied from one country to the next. Qatar was the exception: there, diabetes accounted for a larger share of estimated care need, close to 39 per cent, than disability did. That is a very different picture from Saudi Arabia, where disability on its own explains most of the need.
So, the practical conclusion, for me, is that you cannot really draw a clean line between chronic disease policy and long-term care policy; they are the same conversation. A country that manages diabetes and heart disease well, and picks up cognitive decline early, is also reducing the number of people who will need intensive care later. In that sense, money spent on prevention is already long-term care spending, and it simply shows up earlier in the system.
- Why is investing in data on ageing, disability, and care needs essential for achieving equitable health outcomes?
This is an equity question more than a technical one. The evidence shows that long-term care needs are not distributed evenly across a population; they are strongly tied to factors such as income, gender, disability and where people live. Yet across much of the world, particularly in lower-income regions, almost none of that is measured systematically.
The result is a real blind spot in policy. A government may have a good count of its older population while having no clear idea how many of those people need help with basic tasks such as eating or bathing, or with the more complex activities of daily living like managing money and medication. If you can’t see who is going without support, you can’t direct help to them, and resources tend to flow to wherever demand is loudest rather than to where the need is greatest.
Better data on ageing and disability lets policymakers identify unmet needs, share resources fairly and design services around how vulnerability is distributed rather than around assumptions. Without it, the people least able to advocate for themselves are usually the ones who stay invisible.
- How can integrating long-term care into universal health coverage strengthen SDG 3 in ageing societies?
Universal health coverage is usually framed around getting people access to treatment, but ageing well takes more than treatment. It takes sustained support with daily life, and that is exactly the part that tends to lie outside the package.
When long-term care is left out of universal coverage, a particular group slips through the middle: older adults living with disability or chronic illness whose needs are treated as too ‘social’ for the health system and too ‘medical’ for whatever social care exists. They end up belonging to neither. Bringing long-term care inside universal coverage closes that gap. It nudges systems towards earlier intervention, rehabilitation and steady support, rather than waiting for the fall, the stroke or the hospital admission that could often have been delayed or avoided. That matters more as people live longer, because living longer only counts for much if those extra years come with enough support to live them reasonably well.
- What strategies can reduce reliance on informal caregivers and promote more sustainable, inclusive care systems?
Take the MENA region as an example. There, long-term care is still carried almost entirely by families, and overwhelmingly by women. The WHO estimates that across much of MENA, somewhere between 80 and 95 per cent of it is provided by unpaid female relatives. That work is largely invisible, and it carries real costs to women’s health, to their earnings, and to their ability to stay in paid employment. Easing that burden means building the alternatives that barely exist in many countries: home care and community services, rehabilitation, and a trained, paid care workforce. It also means supporting the family carers who will remain central for a long time yet, through respite, training and some form of financial protection, instead of simply taking their labour for granted. One thing our results kept showing is that there is no single template for this. The balance between disability and disease, and therefore the kind of care a country needs, looks quite different in Morocco than it does in Qatar. What holds everywhere is the timing: it is far easier to build these systems incrementally, ahead of the demographic shift, than to assemble them in a hurry once that shift has already happened.
Thank you for joining and sharing, Dr Ismail!
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