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Background The number of clinical cases of malaria is often recorded in resource constrained or conflict settings as a proxy for disease burden. Interpreting case count data in areas of humanitarian need is challenging due to uncertainties in population size caused by security concerns, resource constraints and population movement. Malaria prevalence in women visiting ante-natal care (ANC) clinics has the potential to be an easier and more accurate metric for malaria surveillance that is unbiased by population size if malaria testing is routinely conducted irrespective of symptoms. Methods A suite of distributed lag non-linear models was fitted to clinical incidence time-series data in children under 5 years and ANC prevalence data from health centres run by Médecins Sans Frontières in the Democratic Republic of Congo, which implement routine intermittent screening and treatment alongside intermittent preventative treatment in pregnancy. These statistical models enable the temporal relationship between the two metrics to be disentangled. Results There was a strong relationship between the ANC prevalence and clinical incidence suggesting that both can be used to describe current malaria endemicity. There was no evidence that ANC prevalence could predict future clinical incidence, though a change in clinical incidence was shown to influence ANC prevalence up to 3 months into the future. Conclusions The results indicate that ANC prevalence may be a suitable metric for retrospective evaluations of the impact of malaria interventions and is a useful method for evaluating long-term malaria trends in resource constrained settings. Electronic supplementary material The online version of this article (10.1186/s12936-018-2460-9) contains supplementary material, which is available to authorized users.

As international funding for malaria programmes plateaus, it is critical to better understand how to implement interventions such as first-line Artemisinin Combination Therapies (ACTs) most effectively through an existing health system. This thesis presents an expansion of a mathematical model of malaria transmission to provide insight to the role of health systems factors as barriers to the effectiveness of ACTs, and interventions to overcome them; considering dimensions of access to care, different sectors through which care is delivered, and the quality of care provided. Data from the IMPACT 2 study in Tanzania was used to parameterise this approach. Primary-care based interventions had most impact on transmission. In low-prevalence scenarios some single interventions, e.g. ensuring 100% care-seeking, eliminated parasite prevalence. Diagnostic-led therapy with adequate stocks of ACTs was as effective in all settings as a policy of presumptive treatment, reducing parasite prevalence in under-fives in moderate transmission settings by up to 86% depending on the sector of implementation. Modelling combinations of hospital-based interventions shifted the pattern of severe malaria away from a peak at early ages (greater than 70% relative reduction in 0-5 year olds in medium transmission settings) towards a more sustained lower incidence across 0-20 years of age as seen in low prevalence settings. This was not immune-mediated and demonstrates the role of health systems interventions preventing the development of severe malaria in those at risk, and reducing mortality. Weak health systems and a poorly controlled diversity of antimalarial sources act as barriers to deploying ACTs effectively both as a control measure and first-line treatment. Addressing these constraints needs consideration of existing healthcare provision and local priorities, e.g. reducing ACT wastage, but through specific planning may improve progress towards targets set by Roll Back Malaria to decrease clinical disease and mortality, and in low transmission settings, to approach elimination. Open Access