Abstract
Malaria has been eliminated from over 40 countries with an additional 39 currently planning for, or committed to, elimination. Information on the likely impact of available interventions, and the required time, is urgently needed to help plan resource allocation. Mathematical modelling has been used to investigate the impact of various interventions; the strength of the conclusions is boosted when several models with differing formulation produce similar data. Here we predict by using an individual-based stochastic simulation model of seasonal Plasmodium falciparum transmission that transmission can be interrupted and parasite reintroductions controlled in villages of 1,000 individuals where the entomological inoculation rate is <7 infectious bites per person per year using chemotherapy and bed net strategies. Above this transmission intensity bed nets and symptomatic treatment alone were not sufficient to interrupt transmission and control the importation of malaria for at least 150 days. Our model results suggest that 1) stochastic events impact the likelihood of successfully interrupting transmission with large variability in the times required, 2) the relative reduction in morbidity caused by the interventions were age-group specific, changing over time, and 3) the post-intervention changes in morbidity were larger than the corresponding impact on transmission. These results generally agree with the conclusions from previously published models. However the model also predicted changes in parasite population structure as a result of improved treatment of symptomatic individuals; the survival probability of introduced parasites reduced leading to an increase in the prevalence of sub-patent infections in semi-immune individuals. This novel finding requires further investigation in the field because, if confirmed, such a change would have a negative impact on attempts to eliminate the disease from areas of moderate transmission.
Highlights
Past malaria elimination campaigns have resulted in more than 40 countries becoming malaria-free [1,2], reinforcing that local elimination is possible, from marginal areas with unstable transmission where an estimated 1 billion people live [3]
While the WHO malaria elimination guidelines provide valuable information on how to transition from control to elimination, they do not address the likely impact of the suggested interventions or the time frame required to achieve elimination in different transmission settings [6]
Baseline simulations in the moderate transmission scenario (EIR,15) represent a community where the frequency of fever episodes decreased with age from 3.5–3.9 per person per year in the 0–3 year age group to 1.7–2.4 fevers per person per year in .14 year olds
Summary
Past malaria elimination campaigns have resulted in more than 40 countries becoming malaria-free [1,2], reinforcing that local elimination is possible, from marginal areas with unstable transmission where an estimated 1 billion people live [3]. Mathematical models have long been used to model disease patterns with the main practical aim of understanding the dynamics of transmission and impact of interventions well enough to guide and manage control programs [7]. To this end, numerous models have been developed and used to estimate the impact of interventions including, but not limited to, insecticide treated nets (ITNS) [8,9,10], artemisinin combination therapy (ACT) [11], case management [12] and vaccines [10,13] in specific settings, usually Africa. The financial and logistic reality is that most regions need to select a subset of interventions and need information about the relative effects of different combinations
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