title: Potential for reduction of burden and local elimination of malaria by reducing Plasmodium falciparum malaria transmission: a mathematical modelling study.
abstract: BACKGROUND
  Rapid declines in malaria prevalence, cases, and deaths have been achieved globally during the past 15 years because of improved access to first-line treatment and vector control. We aimed to assess the intervention coverage needed to achieve further gains over the next 15 years.
  
  
  METHODS
  We used a mathematical model of the transmission of Plasmodium falciparum malaria to explore the potential effect on case incidence and malaria mortality rates from 2015 to 2030 of five different intervention scenarios: remaining at the intervention coverage levels of 2011-13 (Sustain), for which coverage comprises vector control and access to treatment; two scenarios of increased coverage to 80% (Accelerate 1) and 90% (Accelerate 2), with a switch from quinine to injectable artesunate for management of severe disease and seasonal malaria chemoprevention where recommended for both Accelerate scenarios, and rectal artesunate for pre-referral treatment at the community level added to Accelerate 2; a near-term innovation scenario (Innovate), which included longer-lasting insecticidal nets and expansion of seasonal malaria chemoprevention; and a reduction in coverage to 2006-08 levels (Reverse). We did the model simulations at the first administrative level (ie, state or province) for the 80 countries with sustained stable malaria transmission in 2010, accounting for variations in baseline endemicity, seasonality in transmission, vector species, and existing intervention coverage. To calculate the cases and deaths averted, we compared the total number of each under the five scenarios between 2015 and 2030 with the predicted number in 2015, accounting for population growth.
  
  
  RESULTS
  With an increase to 80% coverage, we predicted a reduction in case incidence of 21% (95% credible intervals [CrI] 19-29) and a reduction in mortality rates of 40% (27-61) by 2030 compared with 2015 levels. Acceleration to 90% coverage and expansion of treatment at the community level was predicted to reduce case incidence by 59% (Crl 56-64) and mortality rates by 74% (67-82); with additional near-term innovation, incidence was predicted to decline by 74% (70-77) and mortality rates by 81% (76-87). These scenarios were predicted to lead to local elimination in 13 countries under the Accelerate 1 scenario, 20 under Accelerate 2, and 22 under Innovate by 2030, reducing the proportion of the population living in at-risk areas by 36% if elimination is defined at the first administrative unit. However, failing to maintain coverage levels of 2011-13 is predicted to raise case incidence by 76% (Crl 71-80) and mortality rates by 46% (39-51) by 2020.
  
  
  CONCLUSIONS
  Our findings show that decreases in malaria transmission and burden can be accelerated over the next 15 years if the coverage of key interventions is increased.
  
  
  BACKGROUND
  UK Medical Research Council, UK Department for International Development, the Bill & Melinda Gates Foundation, the Swiss Development Agency, and the US Agency for International Development.
authors.affiliation: Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, UK; School of Mathematical Sciences, Queen Mary University of London, London, UK.
authors.forename: Jamie T
authors.initials: JT
authors.lastname: Griffin
authors.affiliation: Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK.
authors.forename: Samir
authors.initials: S
authors.lastname: Bhatt
authors.affiliation: Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK.
authors.forename: Marianne E
authors.initials: ME
authors.lastname: Sinka
authors.affiliation: Spatial Ecology and Epidemiology Group, Department of Zoology, University of Oxford, Oxford, UK.
authors.forename: Peter W
authors.initials: PW
authors.lastname: Gething
authors.affiliation: Global Malaria Programme, World Health Organization, Geneva, Switzerland.
authors.forename: Michael
authors.initials: M
authors.lastname: Lynch
authors.affiliation: Global Malaria Programme, World Health Organization, Geneva, Switzerland; Swiss Tropical and Public Health Institute, Basel, Switzerland; Universität Basel, Basel, Switzerland.
authors.forename: Edith
authors.initials: E
authors.lastname: Patouillard
authors.affiliation: Global Malaria Programme, World Health Organization, Geneva, Switzerland.
authors.forename: Erin
authors.initials: E
authors.lastname: Shutes
authors.affiliation: Global Malaria Programme, World Health Organization, Geneva, Switzerland.
authors.forename: Robert D
authors.initials: RD
authors.lastname: Newman
authors.affiliation: Global Malaria Programme, World Health Organization, Geneva, Switzerland.
authors.forename: Pedro
authors.initials: P
authors.lastname: Alonso
authors.affiliation: Global Malaria Programme, World Health Organization, Geneva, Switzerland.
authors.forename: Richard E
authors.initials: RE
authors.lastname: Cibulskis
authors.affiliation: Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, UK. Electronic address: a.ghani@imperial.ac.uk.
authors.forename: Azra C
authors.initials: AC
authors.lastname: Ghani
mesh_terms: D000818:Animals; D000962:Antimalarials / Q000008:administration & dosage*; D037621:Artemisinins / Q000008:administration & dosage*; D000077332:Artesunate; D009033:Culicidae / Q000821:virology*; D005260:Female; D005843:Geography; D006801:Humans; D015994:Incidence; D007303:Insect Vectors / Q000821:virology*; D057148:Insecticide-Treated Bednets; D016778:Malaria, Falciparum / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission; D008962:Models, Theoretical; D009032:Mosquito Control; D015995:Prevalence
chemical_list: D000962:Antimalarials; D037621:Artemisinins; D000077332:Artesunate
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