# WHO Collaborating Centre
The Malaria Atlas Project has received designation as a World Health Organization (WHO) Collaborating Centre in Geospatial Disease Modelling. This designation primarily recognises MAP’s contribution to supporting the modelling, monitoring and evaluation activities of the WHO Global Malaria Programme.
MAP collaborates with WHO in three main areas:
# Estimation of malaria programme coverage and disease burden
The methodological problem is to predict annualized malaria endemicity (P. falciparum and P. vivax parasite prevalence rate (PfPR and PvPR respectively)) and coverage of anti-malarial interventions at 5×5 km resolution for each year from 2000 onwards. Anti-malarial interventions will initially focus on insecticide treated nets (ITNs) but the aim is to provide estimates of coverage of indoor residual spraying (IRS), intermittent preventive treatment in pregnancy (IPTp), diagnostic testing and treatment in future years.
The Bayesian geostatistical models developed by MAP to generate cross-sectional endemicity maps and assess changes over time (published in Nature as a set of cubes for Africa in 2015) provide the methodological foundation. However, these models were driven by survey data, which although reasonably abundant for Africa is scarcer for the rest of the malaria-endemic world. New models are under development to allow the incorporation of routine activity and case reporting data, which opens up the prospect of more accurate predictions for areas of South-East Asia and the Americas where surveys are rare but routine reporting is abundant.
MAP maintains the world’s most comprehensive assembly of household surveys (more than 20,000 survey points covering 1985-2015) and very extensive routine case reporting data (more than 68,000 regional case reports covering 1982-2015, although note these data are distinct from the WHO’s own database of case data provided by country NMCPs).
Using this empirical approach, standardized across countries, it is anticipated that a diverse set of policy-relevant questions can be considered:
- Are observed changes in endemicity associated in time and space with major scale-up of key interventions?
- Have factors other than deliberate disease control (such as climate, land-use change, urbanization) played a major role in some locations?
- Are the magnitude and timelines of observed changes broadly consistent with theoretical predictions from mathematical simulation models?
- Do any regions appear anomalous, for example where high intervention coverage has yielded little change, or where reductions appear to have pre-dated significant scale-up?
- Are any major patterns of variation unexplained by the assembled covariate suite, suggesting that additional unidentified factors may be important?
In all cases, the robust handing of uncertainty means such questions can be addressed with the appropriate circumspection, since the spatiotemporally varying credible intervals on the fixed effect coefficients will allow differentiation of times and regions where robust relationships can, or cannot, be quantified given the underlying data distributions.
The work will form the basis of WHO World Malaria Reports 2018-2020, and a report on malaria programme coverage in 2018. A prominent component will be maps of estimated (i) malaria parasite prevalence rate, derived from statistical models developed by the MAP group (ii) annual parasite incidence, derived from routine case data provided to the WHO by country NMCPs. It will also be used in a review of progress towards GTS milestones for 2020 and recommended next steps (this may be a stand- alone report or an expanded edition of the World Malaria Report).
This work, undertaken with WHO-GMP staff, will be linked to the assembly of updated API data from endemic countries, the maintenance of digital administrative unit boundary files, and subject to standard WHO-GMP country consultation processes according to defined timetables.
# Projecting changes in malaria risk to 2040
It is anticipated that the global risk-map of malaria will change dramatically over the next two decades due to factors such as improved or declining economic situations, climate change, improved or declining healthcare systems, and changes in where populations are centred. In collaboration with WHO-GMP, MAP will gather and curate appropriate data and develop statistical methods to explore the non-programmatic factors affecting malaria transmission and the incidence of disease, including:
- Urbanization – MAP will model and analyse the risks of malaria in urban settings, how this has changed historically, and predict how this will change in the future.
- Infrastructure – MAP will model and analyse the impact of key metrics of physical development (housing, electrification, paved areas, transport links) on malaria risk historically and predict potential future impacts on malaria transmission, taking into account differences between rural and urban areas.
- Climate change – MAP will model and analyse the impact of climate change on malaria risk. Factors will include changing rainfall regimes, temperature, and seasonality. MAP already holds very large volumes of data on climate information.
- Nutrition – MAP will gather and curate data on nutrition and develop statistical models to show the historical impact of nutritional status on malaria risk and predict future trends.
- Demographics – MAP will consider growth in the geographical extent of urban areas and the populations living in them, changing age structures of populations and the impact of migration.
In order to predict changes in some of these proximate determinants of malaria risk it will be necessary to better understand how they are influenced by broader economic changes such as growth in GDP and changes in government expenditure. Moreover, it will be necessary to understand how reductions in malaria affect economic activity. GMP is undertaking work on the micro and macro-economic impact of malaria and malaria control, with a particular interest in household expenditures and labour productivity and the contribution of malaria control to economic growth. The information generated will be of value in assessing how malaria control can affect the proximate determinants above (in addition to assessing how the proximate determinants affect malaria). The information will also help to assess the appropriate level of investments that should be made in malaria control programmes, and in making an investment case, as well as understanding.
Various surveys of household income and expenditure exist to provide information on the microeconomic impact of malaria and there is a potential to use information on night lights as an indicator of broader economic activity. If these data can be linked with available malaria-metric data on parasite rates, case incidence, and anti-malarial interventions, then appropriate statistical methods can be developed to assess the economic impact of malaria and malaria control efforts. Under the coordination of the WHO-GMP, MAP will facilitate the linkage of appropriate data and the development of statistical methods. MAP will collaborate with other academics working in the field of econometrics and related fields.
The results of the work will contribute to an assessment of changing malaria risk for WHO’s Malaria Eradication Strategic Advisory Group which will finalize its recommendations in mid-2018. They can also lead to peer review publications on selected topics and potentially WHO reports on particular issues.