Getting community engagement right from the start: a reflection on the Cyclone Idai humanitarian response

If I had to summarize Translators without Borders’ learning from the Cyclone Idai response, it would be: language support can be a significant tool for effective, accountable humanitarian action. But only if there is a more comprehensive approach to community engagement from the outset. 

It is one thing to read a statistic about the linguistic diversity and low literacy levels of the population in Mozambique. It is another thing entirely to sit down with a group of Cyclone Idai survivors in Beira and hear it in person. To learn from one person after another that they are unable to communicate with aid workers in a language they understand. 

Community engagement MozambiqueThis is what TWB’s assessment team and I heard a few weeks ago when we conducted a rapid language assessment in four temporary accommodation sites. We found that many people do not understand the main languages and formats used by humanitarian organizations. They voiced frustration about how difficult it is to access information about available assistance. After one of southern Africa’s worst disasters in decades, we learned that much humanitarian communication is failing because it is in the wrong language.

Today, in the comfort of my home, I’m thinking about what this means. In a way, it shows that humanitarians still fall short of meeting their commitments to “leave no one behind” and “put people at the center.” This is probably not news to many. But it leaves me torn when thinking about the impact of TWB’s language support services in the Cyclone Idai response. Looking at our project, I can say we worked with others to strengthen communication with affected people in the relevant languages. But looking at the remaining gaps, I am less convinced that our work ensured effective engagement with all those affected from the onset of the response.

My point here is not to be skeptical about the first-phase emergency aid delivered in Mozambique. Many communities lost everything due to Cyclone Idai and rely on that aid to rebuild their lives. But I want to reflect on learning in the humanitarian sector. I think we generally try to question ourselves. However, it sometimes feels like we spend more energy evaluating how things went wrong after the fact than we do getting it right up front. 

IOM response to Cyclone Idai, Beira, Mozambique
Credit: Andrew Lind / IOM

In recent years, there has been no shortage of research on the importance of meaningful community engagement. Effective two-way communication is an essential element of engagement. Yet, activities aimed at ensuring people’s voices are heard and understood are still implemented as optional ‘add-ons.’ They are rushed, under-resourced or restricted to the later stages of a response. That needs to change.

What then, can be done?

For a start, we need to collect and share language data as part of needs assessments. That data is a basis for workable and effective communication strategies. It tells organizations three key things: 

  • Which language skills we need to recruit for; 
  • Which languages and formats we need to provide information in; and
  • Which languages and communication preferences we need to tailor feedback mechanisms to. 

Language assessments of the kind carried out by TWB in Beira can provide additional insight into information comprehension and specific vulnerabilities. On that basis, language support like translation and interpreting can be built into community engagement response plans and budgets. 

It is not too late to start collecting, sharing, and using this data in the Cyclone Idai response. But we need to apply this change from the outset of the next emergency. It is the time to ensure we are accountable to the people that need it most, and that this process is in the languages and formats they want. We owe it to the people we aim to help – and to ourselves to maximize the learning we get from them. 

Any takers?

Written by Mia Marzotto, Senior Advocacy Officer for Translators without Borders