Measles

Measles epidemics occur frequently in the DRC and remain a major cause of mortality and morbidity among children. To tackle these epidemics, MSF is deploying a risk-targeted response project in the Katanga region of the Democratic Republic of Congo.

The project was initiated in 2018 by MSF in collaboration with the local MoH to improve prevention and response strategies to measles epidemics in 4 provinces of the Democratic Republic of Congo (DRC) Grand-Katanga Region (Haut Katanga, Haut Lomami, Lualaba, Tanganyika). The project includes an operational component (led by MSF) and surveillance and research components (led by Epicentre) and focuses on the following areas:

• Surveillance strategies: we have implemented an efficient surveillance system in collaboration with the local MoH that allows early detection of outbreaks in need of interventions. As part of this system, we identify outbreaks in need of interventions based on threshold systems, and we developed a decision tool to prioritize outbreaks for interventions.
• Targeted prevention activities: we conduct preventive vaccination activities in identified high-risk health zones (= health zones at high risk of large epidemics).
• Laboratory confirmation: is required for the MoH to initiate reactive vaccination activities; MSF is supporting surveillance activities in the laboratory in Lubumbashi and shipment of samples where necessary.
• Interventions: including case management and vaccination activities.

The project also includes an operational research component to improve the components listed above.

The Urgepi strategy uses a risk- targeted approach, where more resources are located towards geographic areas at higher risk of large epidemics. As part of the project we previously developed and tested outbreak identification systems, as well as vaccination allocation prioritization approaches. Large parts of the technical proposal are based on the experience gained during the Urgepi project.

Here we capitalize on two of the epidemiological activities that took place before and during a large-scale epidemic in 2021/22: (i) the identification of high-risk health zones (HZ) for preventive activities and enhanced surveillance, and (ii) the prioritization of alerts for interventions.

Methods

To evaluate the selection of high-risk HZ in 2021/22, as well as potential alternative selection approaches, we compared outbreak sizes by risk category based on national surveillance data and evaluated preventive vaccination activities in 9 selected high-risk HZ. We further evaluated the alert scoring algorithm by comparing outbreak sizes by alert score and assessed final operational decisions guided by the score.

Results

Although, the initial selection of high-risk HZ in 2021 allowed the identification of HZ with large epidemics, choosing all HZ with coverage below 40% seems to be the most efficient approach. While a third (3/9) of HZ with preventive vaccination experienced a large epidemic, the proportion was 90% (9/10) among high-risk HZ without preventive/early vaccination. Regarding the evaluation of the alert scoring algorithm, the median size of epidemics and the risk of large epidemics increased with an increasing alert score. Median epidemic durations were shorter in HZ with MSF interventions than in HZ with non-MSF vaccination campaigns or HZ without any vaccination campaigns.

Conclusion

Selecting HZ with low vaccination coverage may be a simple efficient alternative to the current model-based strategy to identify high-risk HZ. The targeted implementing of preventive vaccination probably averted large epidemics in 6 of the 9 vaccinated HZ. The alert scoring algorithm allowed efficient operational decision making during the epidemic in 2021/22, resulting in shorter epidemics in HZ with MSF interventions.

Improving the control of measles epidemics in Niger through a combination of anticipatory and real-time tools

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:

1. Risk Mapping: To develop annually updated spatial profiles of outbreak risk to facilitate vaccine distribution in advance of the measles season.
2. Early Warning: To create a simple but effective system to identify outbreaks as quickly as possible without still minimizing the risk of false alerts.
3. Forecasting: To build a real time model to help interpret and prioritize epidemic trends throughout the measles season.

Country

Niger

Status

On-going

Who's involved outside MSF?

• 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)

Tentative End date

June 2025

Our role

Coordination & Investigation