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Dynamical malaria modeling as a tool for bold policy-making

Nature Medicine volume 28, pages 610–611 (2022)Cite this article

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To the Editor—The malaria community have been called upon to be bold1. Pedro Alonso’s recent Comment in Nature Medicine asked us to adapt established interventions to new areas, to tailor preventive strategies to local contexts and to strive to reach the hard-to-reach1. We would like to highlight the pivotal role that dynamical modeling can and does play in making these necessary policy shifts.

Malaria is complex. Describing its dynamics requires an understanding of the parasite, the various mosquito vectors, the human hosts’ level of immunity, human behavior and the policy landscape and environment in which all these factors interact. Dynamical modeling suites for malaria, such as the Swiss Tropical and Public Health Institute’s OpenMalaria, provide platforms where all these factors can be taken into account simultaneously2,3. After adequately capturing the current state of malaria in a given setting, we use the calibrated model as a tool to explore the potential impact of deploying additional interventions. Dynamical modeling has many limitations, is inherently replete with uncertainty and can only ever be as trustworthy as the data upon which it rests. But even given these caveats, with its evidence-based, explicit and interrogable assumptions, modeling provides a crucial framework for comparing possible approaches.

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References

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Acknowledgements

The work of B.N.O., M.W. and E.P. was supported by a Bill and Melinda Gates Foundation grant (investment ID INV-030449). The SMC implementation trial was funded through philanthropic donations received largely as a result of the Malaria Consortium being awarded Top Charity status by GiveWell. GiveWell is a nonprofit organization dedicated to finding outstanding giving opportunities.

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Author notes

  1. These authors contributed equally: James K. Tibendrana, Emilie Pothin

Authors and Affiliations

  1. Swiss Tropical and Public Health Institute, Basel, Switzerland

    Branwen Nia Owen, Munir Winkel & Emilie Pothin

  2. Universität Basel, Basel, Switzerland

    Branwen Nia Owen, Munir Winkel & Emilie Pothin

  3. Malaria Consortium, London, UK

    Craig Bonnington & Jane Achan

  4. Malaria Consortium, Kampala, Uganda

    Anthony Nuwa & James K. Tibenderana

  5. National Malaria Control Programme, Kampala, Uganda

    Jimmy Opigo

  6. Clinton Health Access Initiative, New York, NY, USA

    Emilie Pothin

Authors
  1. Branwen Nia Owen
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  2. Munir Winkel
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  3. Craig Bonnington
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  4. Anthony Nuwa
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  5. Jane Achan
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  6. Jimmy Opigo
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  7. James K. Tibenderana
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  8. Emilie Pothin
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Contributions

All authors were involved in the conceptualization of this correspondence. B.N.O., M.W. and E.P. contributed to the dynamical modelling methodology, analysis and validation. B.N.O. prepared the first draft. All authors were involved in review and editing.

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Correspondence to Branwen Nia Owen.

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Owen, B.N., Winkel, M., Bonnington, C. et al. Dynamical malaria modeling as a tool for bold policy-making. Nat Med 28, 610–611 (2022). https://doi.org/10.1038/s41591-022-01756-9

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