As epidemic threats like influenza, Zika and Ebola increase, there has never been a greater need for health economists to guide prevention and reaction strategies
A century ago, the Spanish flu pandemic created a permanent legacy: the threat of another worldwide influenza pandemic with the potential to kill tens of millions of people. In our increasingly interconnected world, infectious diseases such as HIV/AIDS, tuberculosis (TB), and malaria cause millions of deaths worldwide each year. At the same time, diseases like Ebola and SARS have re-emerged to pose major threats. Antimicrobial resistance also threatens to make many current treatment options ineffective.
Against this background, infectious disease control has become one of the most complex global health challenges of our time. To tackle this challenge, epidemiologists have become highly skilled at using mathematical modelling to predict how epidemics will play out.
But for economists, controlling infectious disease is not just a mathematical equation. It is also about human behaviour. People’s individual choices about prevention and treatment can change the course of disease outbreaks.
Evidence from the HIV epidemic has shed light on how individuals change their behaviour as their perception of risk changes
Our research programme in the Department of Infectious Disease Epidemiology and the Centre for Health Economics & Policy Innovation at Imperial College London is looking at how we can better incorporate the impact of human behaviour into epidemiological models, design cost-effective health interventions, and strengthen health systems.
At the heart of our work is a new generation of powerful, dynamic transmission models that can predict the impact of changes in individuals’ behaviour and lifestyle choices on infectious disease interventions. Our aim is to give policymakers more effective tools to tackle future disease outbreaks.
The need to factor in human behaviour
The use of mathematical techniques to model the spread of infectious diseases goes back more than 200 years. Standard epidemiological models assume all individuals behave in the same way no matter what their environment. Yet, in reality, some people are more willing to take risks, while others are risk adverse – and some have greater concern for the future, while others live more in the present.
Diagnostics, medicines and vaccines mean little without strong healthcare systems to deliver them
Evidence from the HIV epidemic has shed light on how individuals change their behaviour as their perception of risk changes. If individuals think the risk of infection is high, they are more likely to adopt protective behaviour, like using condoms. This has a dampening effect on epidemics, even in the absence of policy interventions. On the flip side, when individuals think the risk is low, some may increase their risk-taking behaviour.
As a result, initially successful interventions can become ineffective because individuals’ behaviour works against them. This makes infectious disease harder to eradicate. A good example of this is the introduction of highly active antiretroviral therapy, which substantially reduced illness and deaths from HIV/AIDS, but may also have led to a rise in risky sexual behaviour in some individuals.
Although in its infancy, eco-epi modelling – merging health economics, behavioural economics, and infectious disease modelling – has the potential to optimise epidemic control and help policymakers to make the best use of limited resources.
In these communities, at least half the people infected with HIV don’t know it, and won’t be so inclined to take precautions to protect others
Cost-effectiveness is crucial: resources are finite
Today’s governments face the increasing challenge of allocating scarce resources efficiently and effectively amid spiralling healthcare costs and limited budgets. With many middle-income countries in Africa and Asia making the transition to universal health coverage, the role and importance of health economics to guide these investment decisions is growing.
As economists, we help policy makers decide on the societal value of services by determining which are essential, buy the most life years, and should be included in equitable, good-quality health benefit packages. Most importantly, we also identify those interventions that cannot be provided if funds are limited. By estimating the costs and benefits of preventive and treatment interventions in countries decimated by endemic diseases like HIV and TB, we can identify the ones that offer the greatest benefits to population health.
As part of the landmark HPTN071 (PopART) trial, we have spent the last four years conducting an economic evaluation of the impact of a comprehensive community-wide HIV testing, prevention, counselling and treatment package on new infections in high prevalence communities in Zambia and South Africa. In these communities, at least half the people infected with HIV don’t know it, and won’t be so inclined to take precautions to protect others. By comparing the economic value of the lives that are saved by PopART interventions with the costs, we hope to identify the most cost-effective strategy to reduce HIV transmission.
People’s individual choices about prevention and treatment can change the course of disease outbreaks
Ensuring progress translates into lives saved
Diagnostics, medicines and vaccines mean little without strong healthcare systems to deliver them. Consider TB, for example, which kills 5000 people every day. While the WHO treatment strategy has been adopted in every country, implementation has been compromised by the poor reach of public health systems and lack of infrastructure. Similarly, even today, around half of the 38 million people living with HIV (18.5 million) lack access to antiretroviral therapy.
Ultimately, achieving universal health coverage requires joining the dots between scientific advances and effective delivery. Only this will ensure public health interventions reach the people who need them most. So another area of our research is to identify the optimal balance between investing in health system strengthening (e.g. medical staff, physical infrastructure, laboratory equipment, supply chains) and spending on actual interventions. And we are also investigating the cost-effectiveness of solutions for integrated interventions in resource-poor settings – for example, combining the home-based delivery of HIV testing and counselling with active TB case finding.
The economics of infectious diseases is an exciting field of research. The integration of infectious disease modelling, health economics, and behavioural economics is in its infancy, and more multidisciplinary approaches are needed to inform policy makers. Ultimately, we hope that our research will increase accessibility to cost-effective interventions and reduce the burden of infectious disease around the world.