How can evaluation help improve data quality and policies on food security during Covid-19 pandemic?

data collection
©FAO/Alberto Conti

How can evaluation help improve data quality and policies on food security during Covid-19 pandemic?

There has been a huge constraint in collecting data due to Covid-19 pandemic: depending on countries situation, data on food production, prices, trade, market access, nutrition and data on population without access/constrained access to food items are all affected.

How can we improve the quality of the available data? How can we enhance the analysis and interpretation of data? How can we help coordinate the efforts by different players on data and analysis during the Covid-19 pandemic to ensure meaningful analysis?

Kind regards,


Dear Njagi,

Thank you very much for this link shared. The initiative is actually ongoing in Senegal the world Bank is in collaboration with the National office of Statistics to drive the evaluation between June to April 2021 and the FAO particularly the Statistics Division contribute by training the office members on the FIES tool adapted to Covid-19.

This type of evaluation are a macro level evaluation at national level and we take the results to be aligned neatly in national policies responses. However we need to have more specific rapid evaluation in the project areas with micro data in relation to the project goals and indicators. We are in a state for proposal for this type of specific rapid evaluation but our approach will be for a scope proposed by FAO for rapid assessment without the phone surveys.

Thank you for your feedback

Dear Diagne,

Thank you very much for sharing your feedback on rapid response. we look forward to learning more about your study and approach and experience from Senegal. On a related note, I came across high-frequency rapid response data collection being undertaken by the World Bank on the COVID-19 in a number of countries, see more information here

My Dears,

I’m joining this interesting discussion, occasion for us to share from the ongoing rapid evaluation assessment proposed by the Coordination Unit for the GAFSP MMI Senegal. Today in this pandemic situation, the rapid evaluation is an effective support for pertinent policies decision and programmatic action for most affected people. In December, in the baseline study, we had used the FIES (Food Insecurity Experience Scale) to evaluate the prevalence of food insecurity, at the time we had a database in FIES module for household and individual level. From this situation, we try to use evaluation with this tool to estimate the impact of the Covid 19 on food security and rural vulnerability. A comparative analysis from data FIES December 2019 to data FIES for June 2020 will give use an effective information on the impact of the covid 19 on food security. In parallel we will use the socio-economic tools to produce more evidence in the rural situation in this pandemic. Our data covers the intervention areas of the project. The Tambacounda region are defined like the more poor region in Senegal. Now from extrapolation the data can be used to estimate the actual situation of prevalence of food insecurity. The results will be used by the project to prepare the post pandemic planification and necessary action and too the more affected sub-areas where producers and households in general need more support.

This rapid evaluation exercise  are in process, so this is a short extract to explain in the urgency situation if you have baseline data how rapid evaluation with practice tool, can help to improve data quality and policies on food security....

I promise after the realization to produce a capitalization document if necessary to share with members.


Great suggestions Emile. The use of scientifically established samples greatly makes the data credible. The common practice of talking to a few people is biased and not credible. however, a key challenge remains to reach these respondents. Phone surveys are now the common approach, however, the desired information should be collected should be very short because it is not possible to keep a respondent for a long period over the phone. The other means you have proposed are ideal but may be unsuitable for people in rural areas without access to the internet and electricity. SMS is also a great option but the information collected through this method is also very short. in addition, incentives must be provided to enhance participation. This also needs careful consideration so as not to bias response.


The additional constraint of the COVID-19 pandemic is the inability to meet physically the actors who need to provide the information. They cannot be encountered at the risk of contamination. It is therefore necessary to contact them remotely, and then collect the required information and data depending on the specified periods. To this end, the database of the institutions usually in charge of collecting information and data on food security could be used. This database would provide a list of previously surveyed households and resource persons and their contacts. Once this list is obtained, it would be enough to launch the information and data collection excercise and invite the households on the list. The data collection could be launched electronically (e-mail) or through the press (newspapers and television). Households interests to participate in the data collection should be invited to contact the institution in charge of the activity in order tto contribute. Households and interested individuals could provide regular information and data by email or social networks (whatsapp, facebook, twitter, etc.). Automatically, the data collected will be reliable. As the data collected is reliable, it is possible to infer relevant calculations and analyses that can be used to define effective food security policies.

[post translated from French]

The Covid-19 pandemic has disrupted the norm in all sectors and professions. The lockdown and other measures to ensure health and safety of citizens have meant that collection of data, especially that which was collected through person to person interactions was not possible.  To the credit of many researchers, evaluators, data collectors, firms and institutions, there have been many and great innovations over the past two months to bridge the gap and ensure that there is data that can inform policy and decision-makers. However, it is important to ensure that the data that comes through is credible and reliable. Wrong, imprecise, incredible, unreliable data can undo the gains to have evidence-based policymaking. Also, the pressure to have data can lead to "bending" of procedures and protocols for data collection, analysis and inference. How then can we ensure the quality of the available data that is coming in? How can we evaluate the quality of analysis and subsequent inference to ensure that we influence the correct policy prescriptions?  How can we promote collaboration and lesson sharing during these times?