Date Published: September 27, 2017
Publisher: The American Society of Tropical Medicine and Hygiene
Author(s): Alexander K. Rowe.
Malaria remains a major cause of preventable death. The World Health Organization estimated that malaria killed 429,000 people (uncertainty range: 235,000–639,000) in 2015, with most deaths occurring in sub-Saharan Africa and among children under 5 years old.1 Nearly two decades ago, the Roll Back Malaria (RBM) partnership was created to help combat this plague. The initial targets were to halve malaria mortality from 2000 to 2010 and again from 2010 to 2015.2 In addition, the Millennium Development Goals (MDGs) included a target of reducing malaria incidence by 2015. With global incidence falling by an estimated 37% compared with 2000, this target has been achieved.3 Current targets, which correspond to the era of the Sustainable Development Goals (SDGs), are to reduce malaria incidence and mortality by 90% from 2015 to 2030.4 More than US$ 20 billion has been dedicated to the fight over the past decade, with an estimated US$ 2.9 billion spent on malaria control and elimination in 2015.1
Yé et al. have updated RBM’s decade-old framework for evaluating the impact of malaria control efforts.19 This expanded framework includes new features, such as examining high-risk subpopulations most likely to demonstrate improvement from intervention scale-up, using a national platform framework, and analyzing complete birth histories from national household surveys to characterize the association between exposure to malaria control interventions and all-cause child mortality (ACCM).
Although this supplement includes some very fine work, the validity of future impact evaluations could be improved further, and to do so requires tackling several important methodologic challenges. First, in the context of large historical declines in ACCM in most countries, the counterfactual (what would have occurred in the absence of malaria control) needs to be better estimated. Second, programs and advocates would surely appreciate a clearer quantification of programmatic impact on malaria-related deaths, which would also require standard methods for calculating the uncertainty of impact estimates. Third, limitations exist for the high-quality household surveys that are used in all evaluations, such as recall bias and failure to collect the full range of data needed for a given analysis (e.g., data on ITNs discarded before the survey visit, retrospective ITN use by individual children, or immunization coverage among children who died).24 Fourth, better data are needed on the uptake and impact of case-management, which is a major pillar of all malaria control programs. Fifth, we need to find better ways of weaving practical impact evaluations into routine programs. Future impact evaluations should be anticipated, with needed data collected and analyzed prospectively, so the time to produce a formal impact evaluation is reduced. Continuous household and health facility surveys, for example, might allow for future impact evaluations to be done more quickly, updated regularly (e.g., every 1–2 years), and reflect the effect of scaling-up malaria case-management.28 Finally, despite improvements in many countries, the fact that routine HMIS data often still have poor (or unknown) validity and limited representativeness remains an important obstacle, especially for monitoring future progress toward SDGs. Weak HMIS data was a theme throughout the entire supplement. Timely, valid, and representative HMIS data are, of course, also useful for managing programs and essential for malaria elimination efforts. With improved HMIS data and optimal intervention coverage, and eventually the achievement of malaria elimination, we will finally know the precise proportion of malaria deaths prevented: 100%.