COVID-19 National Longitudinal Phone Survey 2020, Baseline
Other Household Survey [hh/oth]
The World Bank is providing support to countries to help mitigate the spread and impact of the new coronavirus disease (COVID-19). One area of support is for data collection to inform evidence-based policies that may help mitigate the effects of this disease. Towards this end, the World Bank is leveraging the Living Standards Measurement Study - Integrated Survey on Agriculture (LSMS-ISA) program to implement high-frequency phone surveys on COVID-19 in 5 African countries – Nigeria, Ethiopia, Uganda, Tanzania, and Malawi. This effort is part of a broader first wave of World Bank-supported National Longitudinal Phone Surveys (NLPS) that can be used to help assess the economic and social implications of the COVID-19 pandemic on households and individuals.
Nigeria was among the first few countries in Sub-Saharan Africa to identify cases of COVID-19. Reported cases and fatalities have been increasing since it was first identified. The government implemented strict measures to contain the spread of this virus (such as travel restrictions, school closures and home-based work). While the Government is implementing these containment measures, it is important to understand how households in the country are affected and responding to the evolving crises, so that policy responses can be designed well and targeted effectively to reduce the negative impacts on household welfare.
The objective of Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) is to monitor the socio-economic effects of this evolving COVID-19 pandemic in real time. These data will contribute to filling critical gaps in information that could be used by the Nigerian government and stakeholders to help design policies to mitigate the negative impacts on its population. The COVID-19 NLPS in Nigeria is designed to accommodate the evolving nature of the crises, including revision of the questionnaire on a monthly basis.
The households were drawn from the sample of households interviewed in 2018/2019 for Wave 4 of the General Household Survey—Panel (GHS-Panel). The extensive information collected in the GHS-Panel just over a year prior to the pandemic provides a rich set of background information on the COVID-19 NLPS households which can be leveraged to assess the differential impacts of the pandemic in the country.
Each month, the households are asked a set of core questions on the key channels through which individuals and households are expected to be affected by the COVID-19-related restrictions. Food security, employment, access to basic services, coping strategies, and non-labour sources of income are channels likely to be impacted. The core questionnaire is complemented by questions on selected topics that rotate each month. This provides data to the government and development partners in near real-time, supporting an evidence-based response to the crisis.
The Baseline is the 1st round of the COVID-19 NLPS.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Version 01: Edited, anonymized dataset for public distribution
The Nigeria COVID-19 National Longitudinal Phone Survey 2020 Baseline covered the following topics:
- Household Roster
- Knowledge Regarding the Spread of COVID-19
- Behaviour and Social Distancing
- Access to Basic Services
- Income Loss
- Food Security
- Social Safety Nets
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Producers and sponsors
National Bureau of Statistics (NBS)
Federal Government of Nigeria
The World Bank
Collaborated in the implementation of the survey
Bill and Melinda Gates Foundation
Funded the study
Federal Government of Nigeria
Funded the study
Wave 4 of the GHS-Panel conducted in 2018/19 served as the frame for the COVID-19 NLPS survey. The GHS-Panel sample includes 4,976 households that were interviewed in the post-harvest visit of the fourth wave in January/February 2019. This sample of households is representative nationally as well as across the 6 geopolitical Zones that divide up the country. In every visit of the GHS-Panel, phone numbers are collected from interviewed households for up to 4 household members and 2 reference persons who are in close contact with the household in order to assist in locating and interviewing households who may have moved in subsequent waves of the survey. This comprehensive set of phone numbers as well as the already well-established relationship between NBS and the GHS-Panel households made this an ideal frame from which to conduct the COVID-19 monitoring survey in Nigeria.
Among the 4,976 households interviewed in the post-harvest visit of the GHS-Panel in 2019, 4,934 (99.2%) provided at least one phone number. Around 90 percent of these households provided a phone number for at least one household member while the remaining 10 percent only provided a phone number for a reference person. Households with only the phone number of a reference person were expected to be more difficult to reach but were nonetheless included in the frame and deemed eligible for selection for the COVID-19 NLPS.
To obtain a nationally representative sample for the COVID-19 NLPS, a sample size of approximately 1,800 successfully interviewed households was targeted. However, to reach that target, a larger pool of households needed to be selected from the frame due to non-contact and non-response common for telephone surveys. Drawing from prior telephone surveys in Nigeria, a final contact plus response rate of 60% was assumed, implying that the required sample households to contact in order to reach the target is 3,000.
3,000 households were selected from the frame of 4,934 households with contact details. Given the large amount of auxiliary information available in the GHS-Panel for these households, a balanced sampling approach (using the cube method) was adopted. The balanced sampling approach enables selection of a random sample that still retains the properties of the frame across selected covariates. Balancing on these variables results in a reduction of the variance of the resulting estimates, assuming that the chosen covariates are correlated with the target variable. Calibration to the balancing variables after the data collection further reduces this variance (Tille, 2006). The sample was balanced across several important dimensions: state, sector (urban/rural), household size, per capita consumption expenditure, household head sex and education, and household ownership of a mobile phone.
All 3,000 households were contacted in the baseline round of the phone survey. 69 percent of sampled households were successfully contacted. Of those contacted, 94 percent or 1,950 households were fully interviewed. These 1,950 households constitute the final successful sample and will be contacted in subsequent rounds of the survey.
In order to produce national estimates from the successfully interviewed sample, weights must be applied to the information provided by sampled households. Weights for the GHS-Panel serve as the basis for the NLPS, but the weights must be adjusted to reflect the selection and interviewing process. The weights for the baseline COVID-19 NLPS were calculated in several stages.
1. Begin with the GHS-Panel full sample household weights.
2. Apply an adjustment factor for the selection into the frame (GHS-Panel households that have contact details). A ratio adjustment was applied at the Zone-level (the strata for the GHS-Panel) to preserve the sum of household weights within each Zone between the full GHS-Panel sample and the NLPS frame.
3. Apply an adjustment for selection into the NLPS sample. The adjustment is a simple expansion factor that is the inverse of the selection probability from the frame for each sampled unit.
4. Apply an adjustment factor for non-contact of sampled households. This was again performed with a ratio adjustment at the Zone-level.
5. Apply an adjustment factor for non-response of contacted households through a ratio adjustment at the Zone-level.
6. Calibrate the weights (following adjustments 2-5) according to the properties of the full weighted GHS-Panel sample. This calibration step adjusts the weights such that the estimates obtained from the final NLPS sample will match the weighted means of the full GHS-Panel sample for specified characteristics. The calibration was performed using only information obtained from the GHS-Panel interview and thus will only reflect changes in the sample composition and not changes over time. The calibration applied here aims to correct for selection bias that is introduced at any point between identification of the frame and the final successfully interviewed sample. Selection bias is of particular concern in phone surveys since some segment of the population does not have access to a phone and there are more difficult barriers to successfully reach and interview households over the phone. The calibration was applied using the ReGenesees package in R. The characteristics that were considered in the calibration were the same factors included in the balanced sample selection described in 3.1 above. The weights were also applied to the total number of households in the population given by the GHS-Panel weights.
7. Trim the weights. Outlier weights were trimmed using the ReGenesees package in R which adjusts the weights to given bounds while minimizing the deviation from the estimates obtained from the calibration in step 6.
Dates of Data Collection
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Data Collection Notes
ORGANIZATION OF FIELDWORK: Data were collected by trained NBS enumerators who individually made phone calls from their respective homes. Since the country was on a lockdown during the preparation and data collection exercise, interviewers were not allowed to be in the office. Therefore, all interviews were conducted from interviewers’ homes. In addition, all other correspondence to the interviewers were made through WhatsApp, phone and emails.
PRE-LOADED INFORMATION: Basic information on every household was pre-loaded in the CATI assignments for each enumerator. The information was pre-loaded to (1) assist enumerators in calling and identifying the household and (2) ensure that each pre-loaded person is properly addressed and easily matched to the most recent face-to-face visits. Basic household information (location, household head name, phone number, etc.) was pre-loaded. The list of individuals from GHS-Panel Wave 4 post-harvest visit and their basic characteristics were uploaded. This helped maintain the panel of individuals and ensured the status of each individual in the Baseline survey.
RESPONDENTS: The COVID-19 NLPS had ONE RESPONDENT per household. The respondent was the household head or a knowledgeable adult household member. The respondent must be a member of the household. Unlike many other household surveys, enumerators were not expected to seek out other household members to provide their own information. The respondent may still consult with other household members as needed to respond to the questions, including to provide all the necessary information on each household member.
DATA MONITORING AND EVALUATION: As an additional aid to ensuring good quality data, extensive monitoring was done. Three monitoring exercises were implemented during the data collection. First, Survey Solutions’ audio recording functionality was activated for 15 percent of the sample. However, due to personnel limitations, 10 percent of recorded interviews were audited by 3 trained monitors. On a daily basis, the monitors will listen to these recordings and fill in a structured questionnaire with their observations on interviewer performance. The feedback from these audio audits are then filtered to the respective interviewers.
The second quality check implemented were call backs to contacted households. The call backs were conducted by trained interviewers who are not part of the main data collection interviewers. Each day, 36 households that were contacted by the interviewing team are called by these call back interviewers. The call back interviewers conduct a short interview with the household to confirm that the interviewer did indeed conduct the interview, that certain key elements were clearly stated to the respondent, that the interviewer conducted themselves in a professional manner, and other details on the interview process. Further, the call back team asked several time-invariant questions of the respondent to further confirm the interview was fully conducted and the interviewer captured the information correctly. Feedback from call backs were routed to the respective interviewers to improve on identified areas. Further, the call back interviewers also called households that were not successfully contacted by the main interviewer. In some cases, the call back interviewer was able to reach the household. In such cases, the case was sent back to the interviewer to conduct the interview.
The third quality check was interviews with “mystery respondents”. These were interviews conducted with the monitoring team without the interviewer’s knowledge. Interviewers were given an assignment with pre-filled details from a household not selected for the NLPS but where the prefilled contact details routed the call to a member of the monitoring team. The mystery respondents were given pre-determined answers to questions in the questionnaire such that when the interviewer calls, they should provide those responses. A short questionnaire was also prepared for the mystery respondents to fill during or immediately after the interview to share their feedback on the interviewer’s performance. The feedback from this exercise were the routed to the interviewers to improve on areas highlighted by the monitoring team.
As a result of these quality checks, some of the interviewers were dropped from participating in the survey. There were also regular check-ins to address questions and issues the interviewers might have.
National Bureau of Statistics
Federal Government of Nigeria
The COVID-19 NLPS Baseline consists of one questionnaire. The Household Questionnaire was administered to all households in the sample.
Household Questionnaire: The Household Questionnaire provides information on demographics; knowledge regarding the spread of COVID-19; behaviour and social distancing; access to basic services; employment; income loss; food security; concerns; coping/shocks; and social safety nets.
CATI: The COVID-19 NLPS Baseline exercise was conducted using Computer Assisted Telephone Interview (CATI) techniques. The household questionnaire was implemented using the CATI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Data Analytics and Tools Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given tablets which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CATI was highly successful, as it allowed for timely availability of the data from completed interviews.
DATA COMMUNICATION SYSTEM: The data communication system used in the COVID-19 NLPS Baseline was highly automated. Each enumerator was given a mobile modem allowing for internet connectivity and daily synchronization of their tablet. This ensured that head office in Abuja has access to the data in real-time. Once the interview is completed and uploaded to the server, the data is first reviewed by the Supervisors, and then routed for call back or audio audit if selected. A feedback questionnaire was also designed in Survey Solutions where interviewers receive respective feedback on their tablet from the various monitoring stages. This activity is done on a daily basis throughout the duration of the baseline data collection.
DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.
The second stage cleaning involved the use of Supervisors in Survey Solutions. As indicated above, once the interview is completed and uploaded to the server, the Supervisors reviewed completed interviews for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. The supervisor will provide general and question-specific comments when rejecting a particular completed interview. These errors were then corrected based on a another call to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning and has no issues is then approved by the Supervisor.
The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) formatting. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.
LSMS Data Manager
The World Bank
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Nigeria National Bureau of Statistics. COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020, Baseline. Dataset downloaded from www.microdata.worldbank.org on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.