The COVID-19 pandemic has taken the lives of more than 3.5 million people globally.1 South Asia has become the epicenter of the pandemic. While face masks can slow the spread of the disease and save lives, getting people to consistently and properly wear masks has been a major public health challenge. However, a new model shown to normalize mask-wearing points to a scalable solution. IPA and a large coalition of partners have quickly mobilized to support government and non-government organizations in scaling the model. A summary of the findings, with the latest cost estimate calculations and scaling update, can be found here.


We are working to rapidly expand our network and foster connections to support this scale-up.

If you would like to give financial support:

 

If you have connections/resources to share or can offer support yourself:

 

What is the NORMalize mask-wearing model?

 

In 2020, with researchers from Stanford and Yale, IPA began rigorously testing various strategies to increase mask-wearing at a large scale.

An infographic with 5 icons describing the intervention - person wearing mask, people, masks, megaphone, and medical/scientific icon

We found that a four-part model to change social norms of mask-wearing tripled mask usage at a low cost. Read the full policy brief here and the academic paper here. We are calling the combination that worked N-O-R-M.

Illustration depicting the combination that works to NORMalize mask-wearing: No-cost free masks, Offering information, Reinforcement in-person and in public, and Modeling and endorsement by trusted leaders

Is this a good investment?

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Based on the results, BRAC, the largest non-governmental organization in the world, is scaling up the model to reach 81 million people, beginning in early June (though they have a funding gap; read more below about how you can help). In India, the Self-Employed Women’s Organization (SEWA) is scaling up the approach to 1 million people and expects to expand to millions more. Our large collaborative team has been building other interested coalitions in Bangladesh, India, Pakistan, and now Latin America to scale the model. We have also been offering support and technical assistance, according to each coalition's needs, including on the procurement of high-quality masks; analyzing monitoring data in real time (and in some cases even collecting monitoring data) so implementers can course correct and adapt the interventions to different contexts; and developing a version of the intervention better suited to urban areas (some of the mechanisms that operated in the rural context of the original research might change in an urban setting).

A woman in India wearing a face mask and face shield handing a cloth face mask to another woman also wearing a face mask

Mask distribution by SEWA in India. Photo credit: SEWA

What's next?

 

Emerging scale-up coalitions are underway to reach millions more people in in South Asia, and now also Latin America, with potential to save many thousands of lives. However, funding and technical gaps exist, and further support is needed to make these scale-ups a reality. High leverage opportunities to fill gaps in coalitions include the following:

  • Procuring high-quality masks: some coalitions already have the staff needed to scale it up, but not enough masks. A small purchase of masks (which cost $0.05-$0.10 each) helps ensure the overall package is delivered.
  • Monitoring support: other coalitions have all the pieces for the program but lack a small team to do safe, public observation of mask-wearing to confirm the program is working. In the original program, we found that data to quickly course correct was a critical component in rollout.
  • Technical assistance for implementers: the teams at IPA, J-PAL, Yale, the Lahore University of Management Sciences (LUMS), and Stanford are all providing technical staff to support governments and organizations to deploy the model. These staff need to be complemented as we reach more coalitions.
  • Urban adaptation of the model: the original study was implemented in rural areas, and while we think the mechanisms are similar, the precise activities will necessarily be different. To ensure the model is successfully adapted to urban areas, data should be gathered as it is scaled to adjust if necessary.

 
Partners
BRAC Logo Abdul Latif Jameel Poverty Action Lab (J-PAL) J-PAL South Asia at IFMR Logo Lahore University of Management Sciences (LUMS) Logo
 
SEWA Logo Stanford Medicine Logo Yale University Logo
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 1 As of May 1, 2021. Source: https://coronavirus.jhu.edu/map.html