The potential impact of improving appropriate treatment for fever on malaria and non-malarial febrile illness management in under-5s: a decision-tree modelling approach

• Published in: PloS one 2013-07, Vol.8 (7), p.e69654-e69654
• Main Authors: Rao, V Bhargavi, Schellenberg, David, Ghani, Azra C
• Format: Article
• Language: English
• Subjects: Antimalarials - therapeutic use; Artemisinin; Case management; Clinical outcomes; Decision making; Decision Support Techniques; Decision Trees; Diagnostic systems; Diagnostic tests; Disease transmission; Drug resistance; Epidemiology; Fever; Fever - drug therapy; Guidelines; Health facilities; Humans; Illnesses; Infectious diseases; Malaria; Malaria - drug therapy; Management; Mathematical models; Medical diagnosis; Medical research; Medicine; Microscopy; Modelling; Plateaus; Public health; Public sector; Reduction; Tropical diseases; Vector-borne diseases; Waste treatment
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0069654

As international funding for malaria programmes plateaus, limited resources must be rationally managed for malaria and non-malarial febrile illnesses (NMFI). Given widespread unnecessary treatment of NMFI with first-line antimalarial Artemisinin Combination Therapies (ACTs), our aim was to estimate the effect of health-systems factors on rates of appropriate treatment for fever and on use of ACTs. A decision-tree tool was developed to investigate the impact of improving aspects of the fever care-pathway and also evaluate the impact in Tanzania of the revised WHO malaria guidelines advocating diagnostic-led management. Model outputs using baseline parameters suggest 49% malaria cases attending a clinic would receive ACTs (95% Uncertainty Interval:40.6-59.2%) but that 44% (95% UI:35-54.8%) NMFI cases would also receive ACTs. Provision of 100% ACT stock predicted a 28.9% increase in malaria cases treated with ACT, but also an increase in overtreatment of NMFI, with 70% NMFI cases (95% UI:56.4-79.2%) projected to receive ACTs, and thus an overall 13% reduction (95% UI:5-21.6%) in correct management of febrile cases. Modelling increased availability or use of diagnostics had little effect on malaria management outputs, but may significantly reduce NMFI overtreatment. The model predicts the early rollout of revised WHO guidelines in Tanzania may have led to a 35% decrease (95% UI:31.2-39.8%) in NMFI overtreatment, but also a 19.5% reduction (95% UI:11-27.2%), in malaria cases receiving ACTs, due to a potential fourfold decrease in cases that were untested or tested false-negative (42.5% vs.8.9%) and so untreated. Modelling multi-pronged intervention strategies proved most effective to improve malaria treatment without increasing NMFI overtreatment. As malaria transmission declines, health system interventions must be guided by whether the management priority is an increase in malaria cases receiving ACTs (reducing the treatment gap), reducing ACT waste through unnecessary treatment of NMFI or expanding appropriate treatment of all febrile illness.