Measles Anticipation: Improving measles control in Niger through anticipatory and real-time analytic tools
Study design
Modelling study based on routinely collected surveillance and vaccination data
Context
Measles remains a substantial burden in Niger. The country experiences seasonal outbreaks, the timing of which is consistent with annual agricultural labour migration. However, the subnational dynamics of these annual outbreaks are complex and characterised by significant variability in location and size. This pattern not only reflects sub-optimal and heterogenous measles vaccination coverage but also creates serious challenges for MSF and the Nigerien Ministry of Public Health, Population and Social Action (MSPP) when anticipating and responding to measles outbreaks.
Anticipate measles aims to develop a set of validated and operationally sustainable tools for rapid outbreak detection and risk-based vaccine allocation
Objective
This project aimed to develop and evaluate three tools to assist measles operations throughout and in advance of the annual season. In particular:
- Risk Mapping: To develop annually updated spatial profiles of outbreak risk to facilitate vaccine distribution in advance of the measles season.
- Early Warning: To create a simple but effective system to identify outbreaks as quickly as possible without still minimizing the risk of false alerts.
- Forecasting: To build a real time model to help interpret and prioritize epidemic trends throughout the measles season.
Our role
- Coordination and investigation
Partenaires
- Ministère de la Santé Publique, de la Population et des Affaires Sociales du Niger (MSPP);particularly, la Direction de la Surveillance et de la Riposte aux Epidémies (DSRE).
- The London School of Hygiene & Tropical Medicine (LSHTM)
