The changing endemicity and disease burden of Plasmodium falciparum in Africa since 2000

Malaria, a parasitic disease spread by mosquitoes, kills around a million people each year and causes illness in hundreds of millions of others. After decades of neglect, the war against malaria has entered an unprecedented era. The disease is high on the policy agenda and a huge surge in international funding is beginning to translate into large increases in the number of people protected by insecticide-treated bed-nets, effective drugs, and other control measures.

Sustaining this flow of funding during times of global economic austerity is a central challenge for the malaria control community. Of fundamental importance is the capacity to reliably measure the risk posed by the disease in different places and how this may be changing in response to control efforts. Without this, it is not possible to provide decision-makers with the evidence they need that investment is having an impact, nor where the priorities are for future funding. Examining how and where malaria risk is changing can also highlight where control measures are not working as might be expected.

Despite this importance, estimation of malaria burden is a neglected topic. In Africa, where malaria is most intense, records of cases from clinics and hospitals are known to be an unreliable way of tracking the disease and other approaches based on maps of risk have been developed as an alternative. These map-based approaches vary in complexity and in the type, quality, and volume of input data and there is therefore no consensus on the number of people currently suffering from malaria each year in Africa. Importantly, there have also been no systematic attempts to assess how malaria risk may be changing. As such, the approximately US$ 2 billion now committed annually on malaria control is spent in the absence of a reliable mechanism for assessing impact or targeting new investment.

To address this paucity of information, I propose in this fellowship to address the following questions:
i) How has the transmission of malaria changed in Africa since 2000, and what are the geographical patterns of this change?
ii) What have been the implications of this change on malaria disease burden over the same period?
iii) How do the patterns of change relate to control efforts in different places, and to other potentially important factors such as changing climate or living standards?

These questions will be answered by developing new state-of-the-art approaches to space-time modelling of malaria risk that will map the evolving landscape of infection through time and predict corresponding changes in the number of people falling ill in each country since the year 2000. The largest challenge is in modelling the uncertainty in these estimates, so that real change can be differentiated from spurious trends resulting from poor data coverage. Existing modelling approaches take enormous computing power and are not well-suited to measuring change through time, and exciting new developments in geospatial modelling and computation will be explored to address these challenges. The Malaria Atlas Project (MAP) already holds the world's largest database of malaria surveys going back to 1985. In the next few years, an unprecedented number of African countries will undertake nationwide malaria surveys and these will be added to the database to provide a rich assembly of input data on changing malaria risk.

The outcomes of this research are anticipated to enhance the evidence base needed for international advocacy and planning of donor investment, give practical information to national malaria programmes for local disease control decision-making and, by evaluating changing disease burden, enable African countries to gauge their success in meeting the malaria targets of Millennium Development Goal 6. MAP's existing network of links to African Ministries of Health and to key international partner agencies will be leveraged to ensure maximum dissemination and impact.

At a time when increases in funding for malaria control in Africa have led to widespread intervention scale-up, our understanding of how malaria transmission, disease, and death may be changing remains inadequate to support evidence-based decision making and advocacy for sustained finance. The aim of this fellowship is to use the world's largest database of P. falciparum parasite rate surveys and develop novel space-time modelling approaches to assess how malaria endemicity has changed in Africa since 2000, the implications of these changes for malaria disease burdens, and their spatiotemporal association with malaria intervention coverage and efficacy.

A spatiotemporal model-based geostatistical (MBG) modelling framework will be constructed that allows generation of a space-time 'cube' of predicted P. falciparum infection prevalence through time at 5x5 km resolution with appropriate uncertainty metrics, and an ensemble of biological and empirical models will be used to convert this to estimates of clinical incidence. High-resolution multi-temporal population data will then ultimately allow estimation of malaria disease burden by country by year from 2000-2015. Elaborate handling of covariates in time and space will allow assessment of the potentially complex associations between disease control efforts and evolving patterns of malaria endemicity, adjusting for contemporaneous changes in background factors such as climate and socio-demographics. Comparison of the outcome time-series of changing malaria disease burden with equivalent existing estimates of malaria mortality will provide opportunities for epidemiological triangulation and cross-refinement of both approaches. This work will utilise the world's largest database of point-located P. falciparum parasite rate surveys since 1985 augmented with more recent national malaria survey data from around twenty African countries.

The underlying motivation for my research to-date, and the rationale for the work proposed in this application, is to generate research outcomes that can underpin optimal control, audit global progress in disease reduction, and support international advocacy for investment against malaria. The ultimate beneficiaries, then, are the more than two billion people worldwide living at risk of the disease, for whom the sustainability and appropriate disbursement of funding for malaria control is an issue of the most profound importance. Tangible impact towards this objective will be achieved at three levels.

First, detailed descriptions of sub-national change in the landscape of malaria transmission will form an important aspect of the evidence base for formulating appropriate control strategies within national malaria control programmes. Identifying areas where endemicity and disease burden have declined, remained steady, or increased in relation to the deployment of interventions provides a fundamentally important monitoring and evaluation vehicle for iterative improvements in control strategies. Whilst most programmes will undertake their own evaluations, resources constraints mean these are often rudimentary and sub-optimal for decision making, despite large amounts invested in data collection. I will ensure this impact is realised by exploiting existing networks of contacts and mechanisms for national-level engagement and dissemination within the Malaria Atlas Project (see Pathways to Impact).

Second, improved understanding of what, where and, potentially, why different types and levels of malaria control have led to different transmission and disease burden responses can improve the evidence-base for appropriate and equitable disbursement of international funds, and can act as a powerful resource for international organisations seeking to advocate for sustained financing. As the flow of international development aid is placed under increasing strain, donors are acutely aware of the need to demonstrate that disease control dollars are being spent strategically and that cost-effective impact is being achieved. The absence of robust and transparent mechanisms for tracking recent change in malaria transmission and disease burden can no longer be justified and the research outputs of this fellowship can contribute to overcoming this shortfall. Appropriate engagement with the international community will be achieved primarily via dissemination at policy fora, high-impact publications and effective interactions with the media, all of which build on my existing experience (see Pathways to Impact).

Third, robust modelled evaluations of changing transmission intensity will represent a valuable open-access resource to a diverse constituency of technical users in academia and operational research investigating policy-relevant questions in malaria control. Numerous large research programmes are using transmission models to assess and optimise control options, and models describing observed changes provide ideal baseline data for testing and calibration. This feeds directly into contemporary questions in malaria control concerning the effect of vector control, drugs and vaccines and timelines to elimination.