title: Interrupting malaria transmission: quantifying the impact of interventions in regions of low to moderate transmission.
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.
authors.affiliation: Malaria Drug Resistance and Chemotherapy Laboratory, Queensland Institute of Medical Research, Brisbane, Queensland, Australia. michelle.gatton@qimr.edu.au
authors.forename: Michelle L
authors.initials: ML
authors.lastname: Gatton
authors.forename: Qin
authors.initials: Q
authors.lastname: Cheng
mesh_terms: D000818:Animals; D003140:Communicable Disease Control; D003198:Computer Simulation; D019353:Endemic Diseases; D005260:Female; D006801:Humans; D016778:Malaria, Falciparum / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission*; D008297:Male; D008962:Models, Theoretical; D009032:Mosquito Control / Q000379:methods; D010963:Plasmodium falciparum / Q000378:metabolism*; D015995:Prevalence; D011336:Probability; D013269:Stochastic Processes