David Bath1, Jackie Cook2, John Govere3, Phillemon Mathebula3, Natashia Morris4, Khumbulani Hlongwana5, Jaishree Raman6, Ishen Seocharan7, Alpheus Zitha8, Matimba Zitha3, Aaron Mabuza8, Frans Mbokazi8, Elliot Machaba9, Erik Mabunda9, Eunice Jamesboy10, Joseph Biggs11, Chris Drakeley11, Devanand Moonasar12, Rajendra Maharaj13, Maureen Coetzee10, Catherine Pitt14, Immo Kleinschmidt15. 1. Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK; Department of Health Services Research and Policy, London School of Hygiene & Tropical Medicine, London, UK. Electronic address: david.bath@lshtm.ac.uk. 2. Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK. 3. Wits Research Institute for Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. 4. Health GIS Centre, South African Medical Research Council, Durban, South Africa. 5. School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa. 6. Wits Research Institute for Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Centre for Emerging, Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg, South Africa; Institute for Sustainable Malaria Control, University of Pretoria, Pretoria, South Africa. 7. Biostatistics Unit, South African Medical Research Council, Durban, South Africa. 8. Mpumalanga Provincial Malaria Control Programme, Nelspruit, South Africa. 9. Limpopo Provincial Malaria Control Programme, Polokwane, South Africa. 10. Wits Research Institute for Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Centre for Emerging, Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg, South Africa. 11. Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, UK. 12. School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa; South Africa National Malaria Programme, National Department of Health, Pretoria, South Africa. 13. Office of Malaria Research, South African Medical Research Council, Durban, South Africa; Institute for Sustainable Malaria Control, University of Pretoria, Pretoria, South Africa. 14. Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK. 15. Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Wits Research Institute for Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Southern African Development Community Malaria Elimination Eight Secretariat, Windhoek, Namibia.
Abstract
BACKGROUND: Increasing insecticide costs and constrained malaria budgets could make universal vector control strategies, such as indoor residual spraying (IRS), unsustainable in low-transmission settings. We investigated the effectiveness and cost-effectiveness of a reactive, targeted IRS strategy. METHODS: This cluster-randomised, open-label, non-inferiority trial compared reactive, targeted IRS with standard IRS practice in northeastern South Africa over two malaria seasons (2015-17). In standard IRS clusters, programme managers conducted annual mass spray campaigns prioritising areas using historical data, expert opinion, and other factors. In targeted IRS clusters, only houses of index cases (identified through passive surveillance) and their immediate neighbours were sprayed. The non-inferiority margin was 1 case per 1000 person-years. Health service costs of real-world implementation were modelled from primary and secondary data. Incremental costs per disability-adjusted life-year (DALY) were estimated and deterministic and probabilistic sensitivity analyses conducted. This study is registered with ClinicalTrials.gov, NCT02556242. FINDINGS:Malaria incidence was 0·95 per 1000 person-years (95% CI 0·58 to 1·32) in the standard IRS group and 1·05 per 1000 person-years (0·72 to 1·38) in the targeted IRS group, corresponding to a rate difference of 0·10 per 1000 person-years (-0·38 to 0·59), demonstrating non-inferiority for targeted IRS (p<0·0001). Per additional DALY incurred, targeted IRS saved US$7845 (2902 to 64 907), giving a 94-98% probability that switching to targeted IRS would be cost-effective relative to plausible cost-effectiveness thresholds for South Africa ($2637 to $3557 per DALY averted). Depending on the threshold used, targeted IRS would remain cost-effective at incidences of less than 2·0-2·7 per 1000 person-years. Findings were robust to plausible variation in other parameters. INTERPRETATION: Targeted IRS was non-inferior, safe, less costly, and cost-effective compared with standard IRS in this very-low-transmission setting. Saved resources could be reallocated to other malaria control and elimination activities. FUNDING: Joint Global Health Trials.
RCT Entities:
BACKGROUND: Increasing insecticide costs and constrained malaria budgets could make universal vector control strategies, such as indoor residual spraying (IRS), unsustainable in low-transmission settings. We investigated the effectiveness and cost-effectiveness of a reactive, targeted IRS strategy. METHODS: This cluster-randomised, open-label, non-inferiority trial compared reactive, targeted IRS with standard IRS practice in northeastern South Africa over two malaria seasons (2015-17). In standard IRS clusters, programme managers conducted annual mass spray campaigns prioritising areas using historical data, expert opinion, and other factors. In targeted IRS clusters, only houses of index cases (identified through passive surveillance) and their immediate neighbours were sprayed. The non-inferiority margin was 1 case per 1000 person-years. Health service costs of real-world implementation were modelled from primary and secondary data. Incremental costs per disability-adjusted life-year (DALY) were estimated and deterministic and probabilistic sensitivity analyses conducted. This study is registered with ClinicalTrials.gov, NCT02556242. FINDINGS:Malaria incidence was 0·95 per 1000 person-years (95% CI 0·58 to 1·32) in the standard IRS group and 1·05 per 1000 person-years (0·72 to 1·38) in the targeted IRS group, corresponding to a rate difference of 0·10 per 1000 person-years (-0·38 to 0·59), demonstrating non-inferiority for targeted IRS (p<0·0001). Per additional DALY incurred, targeted IRS saved US$7845 (2902 to 64 907), giving a 94-98% probability that switching to targeted IRS would be cost-effective relative to plausible cost-effectiveness thresholds for South Africa ($2637 to $3557 per DALY averted). Depending on the threshold used, targeted IRS would remain cost-effective at incidences of less than 2·0-2·7 per 1000 person-years. Findings were robust to plausible variation in other parameters. INTERPRETATION: Targeted IRS was non-inferior, safe, less costly, and cost-effective compared with standard IRS in this very-low-transmission setting. Saved resources could be reallocated to other malaria control and elimination activities. FUNDING: Joint Global Health Trials.
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