Community Code Library for Subnational Tailoring of Malaria Interventions

English version

About

A community-developed, openly licensed reference of R and Python code for analyses commonly used in subnational tailoring (SNT) of malaria interventions. Not an SNT manual, dataset, or step-by-step country plan.

What Is the SNT Code Library?

Subnational tailoring (SNT) adapts a country’s disease response at the subnational level to account for and appropriately address local heterogeneities in transmission, its determinants, and the likely impact of various intervention strategies. Data, analysis, and modeling play an important role in certain steps of the SNT process to inform understanding of the epidemiological and intervention context and to guide intervention design.

The steps in the SNT process are intended to align with and provide additional evidence during standard malaria planning and implementation processes. WHO has issued guidance for countries on the preparation of national malaria strategic plans (NMSPs) and related programme reviews, operational plans, and costing, all aligned with national health sector plans. SNT should be nested within these processes and timelines: it is not a separate process, as it is aimed at directly informing the programme reviews, NMSPs, resource mobilization, and implementation. WHO published its Manual for subnational tailoring of malaria interventions in October 2025.

Many steps of SNT require analysis: descriptive, statistical, geospatial, modeling, economic, and financial, among others. While there is no standardized analysis for SNT, there are common steps done in nearly all countries that have undergone an SNT exercise. After doing SNT in more than 30 countries, analysts have come together to share experiences and code. The community-developed SNT code library is the result of this sharing.

The SNT code library provides quality-assured, explained code as a public reference resource to:

  • Share experience from past SNT exercises with new country teams
  • Improve quality and reproducibility through tested code and documented best practices
  • Make SNT methods more accessible through organised, adaptable code examples
  • Offer bilingual content (English and French) with parallel R and Python where applicable
  • Provide end-to-end worked examples on a teaching dataset (Sierra Leone)
  • Explain how each analysis is done and why, including assumptions and validation checks
  • Cover common analytical building blocks of SNT: data assembly, stratification, and intervention review

We remain responsible for adapting the code in this library to the needs of the local SNT team and country realities.

WarningWhat the SNT code library does not do
  • Provide guidance for conducting SNT (see WHO’s Manual for subnational tailoring of malaria interventions)
  • Prescribe a step-by-step analysis plan: not all code will be relevant to every country, and all of it will require adaptation
  • Provide country data: we must bring our own routine, survey, and spatial inputs. The Sierra Leone data is a teaching example only
  • Replace local epidemiological knowledge, programmatic experience, or country-team judgement
  • Cover the full SNT process: stakeholder engagement, prioritisation, costing, and NMSP integration sit outside its scope
  • Teach R or Python: it assumes basic familiarity with at least one
  • Function as a dashboard or interactive tool: we run the code on our own machines

While the SNT code library is built on experiences with SNT as applied to malaria, similar approaches could also be used for other diseases and adapted as needed.

Where to Start

This library is available in English and French. Use the language selector in the navbar to switch between versions.

If you are new to the library, start with the audience guide that matches your role:

Acknowledgements

Special Thanks

We sincerely thank Dr. Abdul Mac Falama and Mr. Musa Sillah-Kanu from the Sierra Leone National Malaria Control Programme (SLNMCP) for permitting the use of Sierra Leone routine data as a teaching tool for this code library.

This code library would not be possible without contributions from many people in the SNT analysis community. We sincerely thank everyone who contributed code, developed pages, tested code, and reviewed content.

Project Leads

Name Institution
Jaline Gerardin AHADI
Mohamed Yusuf AHADI

Developers

Name Institution
Asha Ali AHADI
Ousmane Diallo Northwestern University
Bea Galatas AHADI
Mohamed Kanu Northwestern University
Tabitha Wayua Muema AHADI
Silas Mbivya Mwandikwa AHADI
Chricencia Winny Odhach AHADI
Samuel Oppong Malaria Atlas Project, The Kids Research Institute Australia, and Ghana National Malaria Elimination Program
Safa Siddiqui Northwestern University
Sumaiyya Thawer Swiss Tropical and Public Health Institute
Valérian Turbé Clinton Health Access Initiative

Contributors

Name Institution
Victor Alegana World Health Organization African Region, Precision Public Health Metrics Unit
Celestin Danwang World Health Organization African Region and Clinton Health Access Initiative
Tobias Holden Northwestern University
Anna Makido Harvard T.H. Chan School of Public Health
Christina Matta Harvard T.H. Chan School of Public Health
Mujahid Nouredayem World Health Organization, Global Malaria Programme

Reviewers

Name Institution
Kate Battle Institute for Disease Modeling
Justin Millar PATH
Ricky Richter AHADI
Hayley Thompson PATH

Funding

The SNT code library is funded by the Gates Foundation.

License

The SNT code library is released under two complementary licences:

You are free to reuse, adapt, and redistribute this material, provided appropriate credit is given.

How to Cite

To cite the SNT code library in a publication, report, or programme document, use:

AHADI and contributors. Community Code Library for Subnational Tailoring of Malaria Interventions. 2025–. https://github.com/ahadi-analytics/snt-code-library.

Disclaimer

The views and analytical approaches presented in this library are those of the contributors and do not necessarily reflect the views of WHO or any other listed institution. The findings and conclusions are also those of the contributors and do not necessarily reflect positions or policies of the Gates Foundation.

The code is provided as-is, without warranty of any kind. We are responsible for verifying that any code is appropriate for our data, context, and use case, and for adapting it accordingly.

Use of code from this library does not imply review, validation, or endorsement by any contributor, partner institution, or funder of any user’s analysis or its conclusions.

The contact form, GitHub issues, and email channels are used to improve the library itself. They do not constitute a technical-support channel for country-specific adaptations or pipelines.

Contact Us

We welcome your questions, feedback, and contributions. Here’s how to get in touch depending on your need:

Submit a Question or Comment

If you have a question about library content, a suggestion for the library, or have found an error in the library, please submit to the code library suggestion box by filling out this form.

Contribute to the Library

The library is developed openly on GitHub at ahadi-analytics/snt-code-library. If you would like to contribute, please contact info@appliedhealthanalytics.org with a request to be added as a contributor and a brief description of what you would like to contribute. Bug reports and suggestions can also be opened directly as GitHub issues.

Contributors are expected to engage respectfully and constructively with reviewers and other contributors.

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