Griffin J Bell1, Matthew Loop2, Hillary M Topazian3, Michael Hudgens4, Tisungane Mvalo5, Jonathan J Juliano6, Portia Kamthunzi7, Gerald Tegha8, Innocent Mofolo9, Irving Hoffman10, Jeffrey A Bailey11, Michael Emch12. 1. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: gjbell86@live.unc.edu. 2. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: mloop@email.unc.edu. 3. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: hillaryt@live.unc.edu. 4. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: mhudgens@email.unc.edu. 5. University of North Carolina, Chapel Hill, NC 27599, USA; University of North Carolina Project, Lilongwe, Malawi. Electronic address: tmvalo@unclilongwe.org. 6. Division of Infectious Diseases, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: jonathan_juliano@med.unc.edu. 7. University of North Carolina, Chapel Hill, NC 27599, USA; University of North Carolina Project, Lilongwe, Malawi. Electronic address: pkamthunzi@unclilongwe.org. 8. University of North Carolina Project, Lilongwe, Malawi. Electronic address: gtegha@unclilongwe.org. 9. University of North Carolina, Chapel Hill, NC 27599, USA; University of North Carolina Project, Lilongwe, Malawi. Electronic address: imofolo@unclilongwe.org. 10. University of North Carolina, Chapel Hill, NC 27599, USA; University of North Carolina Project, Lilongwe, Malawi. Electronic address: irving_hoffman@med.unc.edu. 11. Department of Pathology and Laboratory Medicine, Brown University, Providence, RI 02903, USA. 12. Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599, USA. Electronic address: emch@unc.edu.
Abstract
BACKGROUND: RTS,S/AS01, the most advanced vaccine against malaria, is now undergoing pilot implementation in Malawi, Ghana, and Kenya where an estimated 360,000 children will be vaccinated each year. In this study we evaluate RTS,S/AS01 alongside bed net use and estimate cost-effectiveness. METHODS: RTS,S/AS01 phase III trial and bed net prevalence data were used to determine the effect of vaccination in the urban/periurban and rural areas of Lilongwe, Malawi. Cost data were used to calculate the cost-effectiveness of various interventions over three years. FINDINGS: Since bed nets reduce malaria incidence and homogeneous vaccine efficacy was assumed, participants without bed nets received greater relative benefit from vaccination with RTS,S/AS01 than participants with bed nets. Similarly, since malaria incidence in rural Lilongwe is higher than in urban Lilongwe, the impact and cost-effectiveness of vaccine interventions is increased in rural areas. In rural Lilongwe, we estimated that vaccinating one child without a bed net would prevent 2·59 (1·62 to 3·38) cases of malaria over three years, corresponding to a cost of $10·08 (7·71 to 16·13) per case averted. Alternatively, vaccinating one child with a bed net would prevent 1·59 (0·87 to 2·57) cases, corresponding to $16·43 (10·16 to 30·06) per case averted. Providing RTS,S/AS01 to 30,000 children in rural Lilongwe was estimated to cost $782,400 and to prevent 58,611 (35,778 to 82,932) cases of malaria over a three-year period. Joint interventions providing both vaccination and bed nets (to those without them) were estimated to prevent additional cases of malaria and to be similarly cost-effective, compared to vaccine-only interventions. INTERPRETATION: To maximize malaria prevention, vaccination and bed net distribution programs could be integrated. FUNDING: Impacts of Environment, Host Genetics and Antigen Diversity on Malaria Vaccine Efficacy (1R01AI137410-01).
BACKGROUND:RTS,S/AS01, the most advanced vaccine against malaria, is now undergoing pilot implementation in Malawi, Ghana, and Kenya where an estimated 360,000 children will be vaccinated each year. In this study we evaluate RTS,S/AS01 alongside bed net use and estimate cost-effectiveness. METHODS:RTS,S/AS01 phase III trial and bed net prevalence data were used to determine the effect of vaccination in the urban/periurban and rural areas of Lilongwe, Malawi. Cost data were used to calculate the cost-effectiveness of various interventions over three years. FINDINGS: Since bed nets reduce malaria incidence and homogeneous vaccine efficacy was assumed, participants without bed nets received greater relative benefit from vaccination with RTS,S/AS01 than participants with bed nets. Similarly, since malaria incidence in rural Lilongwe is higher than in urban Lilongwe, the impact and cost-effectiveness of vaccine interventions is increased in rural areas. In rural Lilongwe, we estimated that vaccinating one child without a bed net would prevent 2·59 (1·62 to 3·38) cases of malaria over three years, corresponding to a cost of $10·08 (7·71 to 16·13) per case averted. Alternatively, vaccinating one child with a bed net would prevent 1·59 (0·87 to 2·57) cases, corresponding to $16·43 (10·16 to 30·06) per case averted. Providing RTS,S/AS01 to 30,000 children in rural Lilongwe was estimated to cost $782,400 and to prevent 58,611 (35,778 to 82,932) cases of malaria over a three-year period. Joint interventions providing both vaccination and bed nets (to those without them) were estimated to prevent additional cases of malaria and to be similarly cost-effective, compared to vaccine-only interventions. INTERPRETATION: To maximize malaria prevention, vaccination and bed net distribution programs could be integrated. FUNDING: Impacts of Environment, Host Genetics and Antigen Diversity on Malaria Vaccine Efficacy (1R01AI137410-01).
Authors: Katya Galactionova; Fabrizio Tediosi; Flavia Camponovo; Thomas A Smith; Peter W Gething; Melissa A Penny Journal: Vaccine Date: 2016-11-24 Impact factor: 3.641
Authors: Anushay Mistry; Boaz Odwar; Fredrick Olewe; Jonathan Kurtis; Ann M Moormann; John Michael Ong'echa Journal: Am J Trop Med Hyg Date: 2022-04-18 Impact factor: 3.707
Authors: Griffin J Bell; Matthew S Loop; Tisungane Mvalo; Jonathan J Juliano; Innocent Mofolo; Portia Kamthunzi; Gerald Tegha; Marc Lievens; Jeffrey Bailey; Michael Emch; Irving Hoffman Journal: BMC Public Health Date: 2020-06-12 Impact factor: 3.295