• 1.

    Bhatt S et al.2015. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature 526: 207211.

  • 2.

    World Health Organization , 2019. Guidelines for Malaria Vector Control. Geneva, Switzerland: World Health Organization. Available at: https://www.who.int/malaria/publications/atoz/9789241550499/en/.

    • Search Google Scholar
    • Export Citation
  • 3.

    Tanzania Ministry of Health and Social Welfare , 2014. National Malaria Strategic Plan 2014–2020. Dar es Salaam, Tanzania: Ministry of Health and Social Welfare.

    • Search Google Scholar
    • Export Citation
  • 4.

    Kramer K , Mandike R , Nathan R , Mohamed A , Lynch M , Brown N , Mnzava A , Rimisho W , Lengeler C , 2017. Effectiveness and equity of the Tanzania National Voucher Scheme for mosquito nets over 10 years of implementation. Malar J 16: 255.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Eze IC , Kramer K , Msengwa A , Mandike R , Lengeler C , 2014. Mass distribution of free insecticide-treated nets do not interfere with continuous net distribution in Tanzania. Malar J 13: 196.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Yukich J et al.2020. Sustaining LLIN coverage with continuous distribution: the school net programme in Tanzania. Malar J 19: 158.

  • 7.

    Lalji S et al.2016. School distribution as keep-up strategy to maintain universal coverage of long-lasting insecticidal nets: implementation and results of a program in southern Tanzania. Glob Health Sci Pract 4: 251263.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 8.

    RTI International, 2016. Tanzania Vector Control Scale-up Project (TVCSP): Final Report. Research Triangle Park, NC: RTI International. Available at: https://pdf.usaid.gov/pdf_docs/PA00MGW9.pdf.

  • 9.

    Ministry of Health, Community Development, Gender, Elderly and Children , (MoHCDGEC) [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), ICF, 2017. Tanzania Malaria Indicator Survey 2017. Dar es Salaam, Tanzania, and Rockville, MD: MoHCDGEC, MoH, NBS, OCGS, and ICF. https://dhsprogram.com/pubs/pdf/MIS31/MIS31.pdf.

  • 10.

    Kisinza WN et al.2017. Multiple insecticide resistance in Anopheles gambiae from Tanzania: a major concern for malaria vector control. Malar J 16: 439.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 11.

    Jones CM et al.2013. The dynamics of pyrethroid resistance in Anopheles arabiensis from Zanzibar and an assessment of the underlying genetic basis. Parasit Vectors 6: 343.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Feachem RGA et al.2019. Malaria eradication within a generation: ambitious, achievable, and necessary. Lancet 394: 10561112.

  • 13.

    World Health Organization , 2021. World Malaria Report. Geneva, Switzerland: World Health Organization.

  • 14.

    Knox TB et al.2014. An online tool for mapping insecticide resistance in major Anopheles vectors of human malaria parasites and review of resistance status for the Afrotropical region. Parasit Vectors 7: 76.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    World Health Organization , 2018. Test Procedures for Insecticide Resistance Monitoring in Malaria Vector Mosquitoes (Second edition). Geneva, Switzerland: WHO. Available at: https://www.who.int/malaria/publications/atoz/9789241511575/en/.

    • Search Google Scholar
    • Export Citation
  • 16.

    Weiss DJ et al., 2018. A global map of travel time to cities to assess inequalities in accessibility in 2015. Nature 553: 333–336.

    • Crossref
    • Export Citation
  • 17.

    QGIS Development Team ( YEAR ) , QGIS Geographic Information System. Open Source Geospatial Foundation Project. Available at: http://qgis.osgeo.org.

  • 18.

    GRASS Development Team , 2018. Geographic Resources Analysis Support System (GRASS) Software, Version 7.4. Open Source Geospatial Foundation. Available at: https://grass.osgeo.org.

  • 19.

    Hastie TJ , Tibshirani RJ , 1990. Generalized Additive Models. Boca Raton, FL: Routledge.

  • 20.

    Blangiardo M , Cameletti M , 2015. Spatial and Spatio-temporal Bayesian Models with R-INLA. Hoboken, NJ: John Wiley & Sons.

  • 21.

    Abuelmaali SA , Elaagip AH , Basheer MA , Frah EA , Ahmed FTA , Elhaj HFA , Seidahmed OME , Weetman D , Hamid MMA , 2013. Impacts of agricultural practices on insecticide resistance in the malaria vector Anopheles arabiensis in Khartoum State, Sudan. PLoS One 8: e80549.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Hancock PA , Hendriks CJM , Tangena JA , Gibson H , Hemingway J , Coleman M , Gething PW , Cameron E , Bhatt S , Moyes CL , 2020. Mapping trends in insecticide resistance phenotypes in African malaria vectors. PLoS Biol 18: e3000633.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Moyes CL , Athinya DK , Seethaler T , Battle KE , Sinka M , Hadi MP , Hemingway J , Coleman M , Hancock PA , 2020. Evaluating insecticide resistance across African districts to aid malaria control decisions. Proc Natl Acad Sci USA 117: 2204222050.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 24.

    Matowo NS , Munhenga G , Tanner M , Coetzee M , Feringa WF , Ngowo HS , Koekemoer LL , Okumu FO , 2017. Fine-scale spatial and temporal heterogeneities in insecticide resistance profiles of the malaria vector, Anopheles arabiensis in rural south-eastern Tanzania. Wellcome Open Res 2: 96.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Foster GM et al.2016. Spatial and temporal trends in insecticide resistance among malaria vectors in Chad highlight the importance of continual monitoring. PLoS One 11: e0155746.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26.

    Verhaeghen K , Bortel WV , Roelants P , Okello PE , Talisuna A , Coosemans M , 2010. Spatio-temporal patterns in kdr frequency in ermethrin and DDT resistant Anopheles gambiae s.s. from Uganda. Am J Trop Med Hyg 82: 566573.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 27.

    Kweka E , Mahande A , Ouma J , Karanja W , Msangi S , Temba V , Lyaruu L , Himeidan Y , 2018. Novel indoor residual spray insecticide with extended mortality effect: a case of SumiShield 50WG against wild resistant populations of Anopheles arabiensis in northern Tanzania. Glob Health Sci Pract 6: 758765.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 28.

    Oxborough RM et al.2019. Susceptibility testing of Anopheles malaria vectors with the neonicotinoid insecticide clothianidin; results from 16 African countries, in preparation for indoor residual spraying with new insecticide formulations. Malar J 18: 264.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 29.

    World Health Organization , 2017. Conditions for Deployment of Mosquito Nets Treated with a Pyrethroid and Piperonyl Butoxide. Geneva, Switzerland: World Health Organization. Available at: https://apps.who.int/iris/bitstream/handle/10665/258939/WHO-HTM-GMP-2017.17-eng.pdf?sequence=5.

    • Search Google Scholar
    • Export Citation
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Modelling Insecticide Resistance of Malaria Vector Populations in Tanzania

Donal BisanzioRTI International, Washington, District of Columbia;
School of Medicine, Nottingham University, Nottingham, United Kingdom;

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Mohamed AllyNational Malaria Control Program, Dar es Salaam, Tanzania;

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Abdullah S. AliZanzibar Malaria Elimination Program, Stonetown, Zanzibar;

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Chonge KitojoUS President’s Malaria Initiative, US Agency for International Development, Dar es Salaam, Tanzania;

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Naomi SerbantezUS President’s Malaria Initiative, US Agency for International Development, Dar es Salaam, Tanzania;

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William N. KisinzaNational Institute for Medical Research, Amani Research Center, Tanzania

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Stephen MagesaNational Institute for Medical Research, Amani Research Center, Tanzania

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Richard ReithingerRTI International, Washington, District of Columbia;

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ABSTRACT.

Anopheline mosquito insecticide resistance is a major threat to malaria control efforts and ultimately countries’ ability to eliminate malaria. Using publicly available and published data we conducted spatial analyses to document and model the geo-spatial distribution of Anopheles gambiae s.l. insecticide resistance in Tanzania at national, regional, district and sub-district levels for the 2011 – 2017 period. We document anopheline mosquito resistance to all four major insecticide classes, with overall mosquito mortality declining from 2011 to 2016, and mean reductions of 1.6%, 0.5%, 0.4%, and 9.9% observed for organophosphates, carbamates, organochlorines and pyrethroids, respectively. An insecticide resistance map modeled for 2017 predicted that anopheline vector mortality was still above the 90% susceptibility threshold for all insecticide classes, except for pyrethroids. Using the model’s output we calculated that resistance to organophosphates, carbamates, organochlorines, and pyrethroids is expected to exist in 11.6%, 15.6%, 8.1%, and 19.5% of Tanzania’s territory, respectively, with areas in the Lake Zone and eastern Tanzania particularly affected. The methodology to predictively model available insecticide resistance data can readily be updated annually, allowing policy makers and malaria program management staff to continuously adjust their vector control approaches and plans, and determine where specific insecticides from various classes should be used to maximize intervention effectiveness.

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Author Notes

Address correspondence to Donal Bisanzio, RTI International, Washington, DC. E-mail: dbisanzio@rti.org

Financial support: Analyses were performed with internal RTI funds. Insecticide resistance data as reported through the IRMapper platform was collected by the Tanzania National Malaria Control Program, the Zanzibar Malaria Elimination Program, and academic research institutions through the support of various multilateral, bilateral and academic research funding sources. Partial funding for manuscript development was provided by the US President's Malaria Initiative via the U.S. Agency for International Development Okoa Maisha Dhibiti Malaria project (Cooperative Agreement 72062118CA-00002).

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