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Improving the control of measles epidemics in Niger through a combination of anticipatory and real-time tools
This study will develop state-of-the-art statistical models for epidemic prediction and simple alert detection algorithms, validated retrospectively against twenty years of data and applied prospectively during the 2023/24 measles season in Niger.
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Principal Investigators: Dr. Anton Camacho, Abdoul-Aziz Idrissa
Purpose
The study will investigate whether national measles surveillance and immunisation data in Niger can be reliably combined to anticipate the spatio-temporal risk of measles outbreaks in order to provide actionable results to the Nigerien Ministry of Health (MSPP) and Doctors Without Borders (MSF) to improve their proactive and reactive vaccination activities.
The research project will build a statistical framework to quantify the risk of a measles outbreak in each district during the upcoming year. It will also develop an alert system to rapidly identify areas with emerging measles outbreaks and a real-time spatial forecasting model to assist intervention prioritisation throughout the measles season. Finally, the study will assess the reliability of these tools and their ability to inform decision making.
Abdoul-Aziz Idrissa
Epicentre Niger
At present, the effectiveness of measles control in Niger is heavily undercut by the absence of risk-based allocation and strategy. Our research project should support data-driven decision making for measles outbreaks. We hope to demonstrate the added value of these methods over those that use surveillance data alone.
Expected Outcomes
If successful, the suite of tools developed here will provide an evidence basis to improve proactive vaccine distribution, reduce outbreak response times, and facilitate real-time planning and prioritisation throughout the measles season. All three of these impacts should translate into improved efficiency and efficacy of MSPP and MSF activities.
For the MSPP, it is hoped that the tools developed will be integrated into existing decision-making processes for:
Vaccine stockpiling ahead of the measles season.
Selection of districts for catch-up campaigns.
Vaccine allocation and prioritisation during reactive campaigns.
For MSF, the tools are envisaged to be used not only to prioritise areas for reactive vaccination and case management but also to better predict the quantity of supplies/personnel needed for interventions.
More broadly, this project will directly contribute to the yet nascent but growing base of public health literature and practices on data-driven approaches for epidemic control in humanitarian contexts.
Measles Vaccination campaign: MSF continues to support the Nigerien authorities in their response to new outbreaks of measles and meningitis in the country. Credit: MSF/Johnny Bissakonou Songomalet
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