South Sudan: communicating both ways

South Sudan1

WFP/Hagar Ibrahim

We are back in South Sudan, where, in June, we identified two main areas of opportunity for employing a mobile Vulnerability Analysis and Mapping (mVAM) approach: using it to monitor urban food security and applying it to improve early warning systems.

This time, we are pleased to announce that the project is moving forward, we are collecting more and more numbers and are getting closer to piloting an Interactive Voice Response (IVR) system, which will both boost the capacity of our in-house call center and enable beneficiaries to access information and get answers to their questions.

South Sudan2

WFP/Hagar Ibrahim

The food security situation in urban areas in South Sudan has been deteriorating. According to WFP’s latest urban food security assessment in Bor town, 85% of households are food insecure (of which 44% are severely food insecure, and 41% moderately food insecure). As the urban food security situation needs to be monitored frequently and there is better mobile phone coverage in urban than in rural areas, mVAM is stepping in to collect the data.

Through face-to-face assessments and via our partner agencies on the ground, we have collected over 400 phone numbers and used some of them to conduct food security live call interviews with households in urban centers mostly across Greater Equatoria.

South Sudan map

WFP/Map 1: Number of surveyed households by county, September 2017

However, the context for conducting phone surveys in South Sudan continues to be challenging due to the low mobile phone penetration rates and connectivity problems. We had already reported last time that the main mobile network operators downsized their businesses due to recurrent conflicts. In our most recent round of phone surveys, we found that nearly 40% of the numbers were not reachable. Nevertheless, we were able to talk to over 240 households and ask them about their food consumption, negative coping behaviours, and the food security situation in their communities.

The goal of our latest mission was to provide technical support and assist with capacity building at our in-house call centre. We have configured an interactive voice response (IVR) system, a technology which allows users to access relevant information using the phone keypad and speech recognition. Through the pre-recorded voice response option, the system will be used to answer beneficiaries’ questions relating to, for example, the registration process, food distribution dates, and technical issues, such as lost or damaged vouchers. Users will also be able to record their questions, upon which WFP gets back to them. The IVR system can also initiate calls automatically and direct them to an operator only when a respondent picks up the phone, thereby saving the operators time. This will help address a challenge that mVAM operators in South Sudan have had to grapple with all this time.

The next steps for mVAM in South Sudan will involve deploying and improving the IVR system and expanding our contact information database of potential survey respondents with the help of WFP units and our cooperating partners in the field. Until the next time!

 

New places, new tools: what’s up next for mVAM?

KOICA pic 2

We’ve just got back from Rwanda where we were holding a workshop on using mVAM to expand real-time food security and nutrition monitoring with Internally Displaced Persons (IDPs) and refugee populations. The project, which is made possible by the support of the Korean International Cooperation Agency (KOICA), will be implemented in ten countries in sub-Saharan Africa where WFP works.

What’s the project?

The KOICA project has two aims. First, it aims to empower information exchange with marginalized populations, specifically IDPs and Refugees. Secondly, it supports the collection of food security and nutrition data using the latest mobile and satellite technologies. This will happen in ten countries in Sub-Saharan Africa: the Central African Republic (CAR),The Democratic Republic of Congo (DRC), Kenya, Malawi, Niger, Nigeria, Rwanda, Somalia, South Sudan and Uganda.

How are we going to do this?

As you know, two-way communication systems are an important part of our work. As well as getting information that we can use to inform WFP programmes, we want to ensure that the line is open so that people in the communities we serve can contact us and access information that is useful to them. We’ve already been using Interactive Voice Response and live calls to share information with affected populations, and are now expanding our toolbox to include new technologies: Free Basics and a chatbot.

Remote data collection isn’t just done by mobile phones – VAM already uses other sources, such as  satellite imagery analysis – to understand the food security situation on the ground.  Under this project, we’ll also help countries incorporate similar analysis which will complement two-way communication systems to provide a fuller picture of the food security situation.

Finally, we’re going to harness our knowledge of Call Detail Records analysis: de-identified metadata collected via cell phone towers about the number of calls or messages people are sending and which towers they are using. We have already used this technique in Haiti to track displacement after Hurricane Matthew, and we’re really excited to transfer these ideas to another context to ensure we get up-to-date information on where affected communities are so we can better target food assistance in the right locations.

What happened at the workshop?

Representatives from all 10 country offices, three regional bureaus and staff from HQ came together to discuss the three main project components. During the workshop, the different country offices had the chance to learn more from members of the mVAM team about the specific tools they can harness and ensure their collected data is high quality, standardised and communicated effectively. However, the best part about bringing everyone together was that country teams could share their experiences about how they are already using mVAM tools. We heard from the Malawi country office about their Free Basics pilot, and Niger and Nigeria explained how they’re implementing IVR so affected communities can easily contact WFP, even after work hours. Sharing their different experiences and learning about how different tools have worked in each context not only gave everyone an overview of what mVAM is doing so far, it also helped everyone understand the implementation challenges and how to overcome them.

What’s next for the KOICA project?

We’re really excited for the next stage of the project. Each country office has now planned what tools they’re going to use to increase their communications with affected communities and how they will improve their existing data collection systems. It’s going to be great to see the impact these tools will have not only on WFP’s response, but also how they will empower the communities we’re serving. 

Mind the Mode

Settling the (Food Consumption) Score in South Sudan

POC3_Nektarios_Markogiannis

POC 3
Photo: UNMISS/Nektarios Markogiannis

For the second installment of our ‘Mind the Mode’ series, we’re taking you to Juba, South Sudan, where we previously conducted a mode experiment. What we wanted to see was how food security indicators compare when data is collected face-to-face and through operators over the phone.

South Sudan is a complex setting for mobile surveys to begin with. The country has low cell phone penetration- it’s estimated to be only 20%. Network quality is a problem, often calls don’t go through or audio is poor.  Last, but not least, the country has been extremely unstable. While we have been using key informant phone interviews to date, we are investigating the feasibility of conducting phone surveys to collect household food security indicators. Given the complexities, starting with a test to evaluate biases related to survey mode seemed prudent.

Methodology

The mode experiment took place in “POC 3”, a Protection of Civilians (POC) camp in Juba near the main UN compound. POC 3 is the largest of three camps at the UN House site in Juba, with an estimated population of 20,000 people, according to the International Organization for Migration. People in the POC are there in search of protection against the violence and conflict that South Sudan has been experiencing. We’re hoping to use mobile phones to monitor food security indicators in POC communities. POC 3 happens to have good cell phone coverage – a 2014 survey estimated that some 70% of households in the camp had access to a phone.  

 

Photo: WFP/Silvia Passeri

Photo: WFP/Silvia Passeri

We evaluated how mode effects the Food Consumption Score (FCS), which measures the frequency of consumption of different food groups consumed by a household during the 7 days before the survey. A higher score means a better level of the respondent’s household food security. The FCS is a commonly used proxy for household food security.

We carried out two rounds of data collection, round 1 in March and round 2 in May 2016. In round 1, half of the respondents received a voice call survey and the other half participated in an identical interview face-to-face. The ‘treatment’ (voice call) was random. In round 2, some of the respondents that received a voice call took the exact same survey face-to-face, and vice versa.

There were challenges relating to security in the POC and some of the respondents from March were not found in the camp when we conducted the second round in May. As a result, we had 132 voice and 333 face-to-face interviews in round one, but 138 voice and only 117 face-to-face surveys in round 2. This sample size is smaller than we would have liked, but we think it’s indicative enough to tell us how responding to a phone survey differs from one that took place face-to-face.

Calls were placed by operators that were ‘converted’ enumerators – field monitors who usually carry out WFP’s post-distribution monitoring but were new to phone-based surveys. This meant that they were already familiar with the food security indicators and the camp community, but needed training on the protocol for phone-based surveys.

Results

We observed substantial mode effects in round 1. We obtained a mean FCS of 34 via face-to-face surveys, but a much higher score of 45  through voice calls. Our regression analysis shows that mode alone accounted for 7 points in the difference in a household’s response (p<0.01), with other factors accounting for the remainder of the difference. This means that a voice survey would inflate the FCS by 20%, leading to a gross underestimation of the severity of food insecurity in the population of interest. During round 1, the voice FCS question behaved as an almost binary variable – we would get 1s and 7s, but very few 2,3,4,5 answers. That means a lot of people said they ate a given food item one day or every day, but that very few other answers were being recorded.

FCS results, round 1

FCS results, round 1

In round 2, the difference between voice calls and face to face surveys diminished substantially. Also, the difference was not statistically significant. In fact, the slight remaining difference between the two groups was due to respondent households’ socio economic profile, not because of the mode we used to collect data.

 

R2

FCS results, round 2

Lessons learned

For the food consumption score, the differences between voice and face-to-face due to the mode effect were large in round 1, but vanished in round 2. This is a positive finding for us as we are seeking to rigorously test and validate the data collected through mobile and reporting on the results with some degree of confidence. We want to highlight a few lessons here that could help guide others into the right direction.

Lesson 1: Practice makes perfect.  We suspect that the poor quality of the data collected in round 1 is due to our call center being brand new, and experiencing ‘teething’ problems. When an in-house call center is first set up, it tends to be small scale comprising of one or two operators. With resources permitting (and provided there is increased information needs) the call center may be expanded with additional operators who will receive regular training and coaching. Our analysts have been saying anecdotally that data quality improves as time goes by and the system becomes more established. We have a good illustration of the phenomenon here in South Sudan.

Lesson 2: Close supervision is required! Although our operators were familiar with data collection, it took time to train them to implement surveys by phone with quality.  This again shows that operator selection, training, and supervision are key to obtaining good quality data.

Lesson 3: Work with professional call centers. Overall, this encourages us to continue working with professional call centers when possible, and avoid the temptation to do things in-house in a hurry – something that can be all too tempting in an emergency setting.

We also think the method used in South Sudan could be applied elsewhere to help evaluate mode effects. We will post the survey design on the mVAM Resource Center for others to use.