About the model

How the model works

This tracker models the impact of the malaria vaccine roll-out on malaria cases and deaths. Starting from the date of each shipment, doses are rolled out gradually over the number of children covered by the shipment.

Once each child is vaccinated, they are partly protected from malaria, leading to a predicted drop in cases and deaths. This protection wanes over time based on clinical trial data.

All calculations are client-side and use the data files bundled with this site. You can explore assumptions in the sections below and switch scenarios using the controls on each view.

Understanding the numbers

This tracker shows two types of data:

Sourced Data from official sources (shipments, population, malaria burden)
Estimated Model outputs based on assumptions (cases averted, lives saved, doses administered)

Vaccine efficacy curves

The model accounts for waning vaccine efficacy over time. Efficacy data comes from clinical trials: RTS,S Clinical Trials Partnership (2015) and Datoo et al. (2024).

R21 (starts at 75%) RTS,S (starts at 56%)

Model assumptions

  • Doses per child: Four (three primary doses + one booster at twelve months)
  • Roll-out model: Linear ramp-up over six or twelve months
  • Dose timing: Dose 2 at one month, dose 3 at two months, dose 4 at fourteen months after dose 1
  • Efficacy curve: Flat at initial level until year 1, then linear decay through data points, then exponential extrapolation
  • Three-dose efficacy: Same as four-dose until year 1, then shifted back by one year
  • Dose reallocation: Unused doses from children who don't complete the four-dose course are reassigned over time to vaccinate additional children.
  • Age eligibility: Either the current WHO-recommended 5–36 months or a more expansive 6–60 months
  • Coverage: All children within the age window living in areas at risk of malaria as defined by the World Malaria Report are assumed to be potential targets for vaccination.

Dose completion rates

Not all children who receive a first dose complete the full four-dose course. The model supports three scenarios based on real-world data:

ScenarioDose 2Dose 3Dose 4Source
Optimistic90%88%71%Malawi RTS,S MVIP (WHO evidence report)
Average73%61%39%Mid-point between scenarios
Pessimistic56%34%8%South Sudan R21 roll-out (WHO AFRO)

Dose reallocation: When children drop out, their unused doses are reallocated to future children. This means more children can be fully vaccinated from the same number of doses than if no reallocation occurred.

Dose flow summary

Of the children who start vaccination (Average scenario):

    Vaccine pricing

    The R21 and RTS,S vaccines are roughly equally effective, but differ in production costs.

    VaccinePrice per doseCost per child (four doses)
    R21$2.99$11.96
    RTS,S$9.81$39.24

    Gavi co-financing

    Countries contribute to vaccine costs based on their Gavi eligibility phase:

    PhaseCo-financing
    Initial self-financingFlat $0.20 per dose
    Preparatory transition$0.20/dose + 30% increase per year
    Accelerated transition20% of dose price + 10 points per year
    Fully self-financing100% of dose price

    Vaccination needs

    • The Needs view estimates the current coverage gap based on doses delivered to date and 2023 baseline demographics.
    • The coverage gap is calculated as the number of eligible children in the selected age window minus children fully vaccinated from delivered doses.

    Limitations and caveats

    • Administration timing: The model assumes linear roll-out of doses over 6-12 months. Actual timing varies by country and may be faster or slower.
    • Completion rates: Based on limited real-world data from early roll-outs. Rates may improve as programs mature.
    • Efficacy extrapolation: Long-term efficacy (beyond clinical trial follow-up) is extrapolated and uncertain.
    • Uniform efficacy: The model assumes vaccine efficacy is the same across all countries. Real-world efficacy may vary by malaria transmission intensity.
    • No seasonality: Malaria transmission seasonality is not modeled; incidence is treated as uniform throughout the year.
    • Data lag: Shipment data may be behind real-world deliveries. Some shipments may not be publicly reported.
    • Wastage: The model does not account for vaccine wastage.
    • Coverage: The model assumes all children in the relevant age window in areas at risk of malaria can and should be vaccinated. International organizations and governments are in practice working towards a more limited goal than this.

    These estimates are useful for understanding scale and progress, but should not be used for precise policy decisions without additional analysis.

    Data sources

    About this tool

    This tracker was built by Ollie Sayeed using GPT-5 and Claude Code to make malaria vaccine progress transparent and accessible.

    The code is open source and available on GitHub. Feedback, corrections, and contributions are welcome at oliver.sayeed@1daysooner.org.

    Shipment data up to date with public information as of March 2026. Source: UNICEF Gavi shipment reports.



    Malaria vaccine impact tracker

    Total cases averted Estimated
    Loading…
    Total lives saved Estimated
    Loading…