Nigeria - COVID-19 National Longitudinal Phone Survey 2020

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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 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 Nigeria COVID-19 NLPS 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 Nigeria COVID-19 NLPS households which can be leveraged to assess the differential impacts of the pandemic in the country. Each month, the households will be 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.

Type: 
Microdata
Acronym: 
COVID-19 NLPS 2020
Languages Supported: 
English
Topics: 
Topic not specified
Geographical Coverage: 
Nigeria
Economy Coverage: 
Economy Coverage not specified
Release Date: 
June 4, 2020

Last Updated

Last Updated: 
July 29, 2020

Harvest System ID

Harvest System ID: 
Microdata

Harvest Source ID

Harvest Source ID: 
11415
Disclaimer: 
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.
Version Description: 
Version 02 (July 2020). This metadata contains Baseline (Round 1) and Round 2 survey information.
Publisher Name: 

Development Economics Data Group; The World Bank

Funding Name, Abbreviation, Role: 
Bill and Melinda Gates Foundation, Federal Government of Nigeria
Study Type: 
Other Household Survey [hh/oth]
Series Information: 
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 support 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 NLPS that can be used to help assess the economic and social implications of the COVID-19 pandemic on households and individuals.
Universe: 
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Primary Investigator Name, Affiliation: 
National Bureau of Statistics (NBS); Federal Government of Nigeria
Sampling Procedure: 
Wave 4 of the GHS-Panel conducted in 2018/19 served as the frame for the Nigeria 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 Nigeria COVID-19 NLPS. To obtain a nationally representative sample for the Nigeria 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.
Response Rates: 
BASELINE (ROUND 1): 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. ROUND 2: Interviewers attempted to contact and interview all 1,950 households that were successfully interviewed in the baseline of the COVID-19 NLPS. 1,852 households (95% of the 1,950 attempted) were contacted and 1,820 (93.3%) were successfully interviewed in the second round. Of those contacted, 22 households refused outright to be interviewed and 10 were partially interviewed.
Weighting: 
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 Nigeria COVID-19 NLPS, but the weights must be adjusted to reflect the selection and interviewing process. The weights for the Nigeria 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. In subsequent rounds of the survey, steps 4, 5, and 6 will be applied to the final baseline weights.
Questionnaires: 
BASELINE (ROUND 1): One questionnaire, the Household Questionnaire, was administered to all households in the sample. 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. ROUND 2: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic goods and services; employment (including non-farm enterprise and agricultural activity); other income; food security; and social safety nets.
Data Collector(s) Name: 
National Bureau of Statistics
Data Editing: 
COMUPTER ASSISTED TELEPHONE INTERVIEW (CATI): The Nigeria COVID-19 NLPS 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 interviewer was given two 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 Nigeria COVID-19 NLPS was highly automated. Each interviewer 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 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 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. CONFIDENTIAL INFORMATION: For purposes of maintaining the confidentiality of the data, all names, phone numbers, and addresses have been removed from the datasets.
Other Processing: 
The Nigeria COVID-19 National Longitudinal Phone Survey 2020 covered the following topics: - Household Roster (Rounds 1, 2) - Knowledge Regarding the Spread of COVID-19 (Round 1) - Behaviour and Social Distancing (Round 1) - Access to Basic Services (Rounds 1, 2) - Employment (Rounds 1, 2) - Income Loss (Round 1) - Other Income (Round 2) - Food Security (Rounds 1, 2) - Concerns (Round 1) - Coping/Shocks (Round 1) - Social Safety Nets (Rounds 1, 2)

No Visualizations Available.

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 National Bureau of Statistics. Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020. Dataset downloaded from [source] on [date].

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 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 Nigeria COVID-19 NLPS 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 Nigeria COVID-19 NLPS households which can be leveraged to assess the differential impacts of the pandemic in the country. Each month, the households will be 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.

FieldValue
Modified Date
2020-07-30
Release Date
Identifier
b6287915-e98b-4fb0-9520-45ace296bb0d
License
License Not Specified
Contact Email
Public Access Level
Public
Rating: 
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No votes yet
Acronym: 
COVID-19 NLPS 2020
Type: 
Languages Supported: 
Disclaimer: 
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.
Response Rates: 
BASELINE (ROUND 1): 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. ROUND 2: Interviewers attempted to contact and interview all 1,950 households that were successfully interviewed in the baseline of the COVID-19 NLPS. 1,852 households (95% of the 1,950 attempted) were contacted and 1,820 (93.3%) were successfully interviewed in the second round. Of those contacted, 22 households refused outright to be interviewed and 10 were partially interviewed.
Weighting: 
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 Nigeria COVID-19 NLPS, but the weights must be adjusted to reflect the selection and interviewing process. The weights for the Nigeria 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. In subsequent rounds of the survey, steps 4, 5, and 6 will be applied to the final baseline weights.
Economy Coverage: 
Primary Investigator Name, Affiliation: 
National Bureau of Statistics (NBS); Federal Government of Nigeria
Publisher Name: 
Development Economics Data Group; The World Bank
Version Description: 
Version 02 (July 2020). This metadata contains Baseline (Round 1) and Round 2 survey information.
Universe: 
The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.
Geographical Coverage: 
Data Classification of a Dataset: 
Series Information: 
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 support 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 NLPS that can be used to help assess the economic and social implications of the COVID-19 pandemic on households and individuals.
Sampling Procedure: 
Wave 4 of the GHS-Panel conducted in 2018/19 served as the frame for the Nigeria 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 Nigeria COVID-19 NLPS. To obtain a nationally representative sample for the Nigeria 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.
Release Date: 
Thursday, June 4, 2020
Last Updated Date: 
Wednesday, July 29, 2020
Questionnaires: 
BASELINE (ROUND 1): One questionnaire, the Household Questionnaire, was administered to all households in the sample. 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. ROUND 2: One questionnaire, the Household Questionnaire, was administered to all households in the sample. The Household Questionnaire provides information on demographics; access to basic goods and services; employment (including non-farm enterprise and agricultural activity); other income; food security; and social safety nets.
Data Editing: 
COMUPTER ASSISTED TELEPHONE INTERVIEW (CATI): The Nigeria COVID-19 NLPS 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 interviewer was given two 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 Nigeria COVID-19 NLPS was highly automated. Each interviewer 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 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 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. CONFIDENTIAL INFORMATION: For purposes of maintaining the confidentiality of the data, all names, phone numbers, and addresses have been removed from the datasets.
Other Processing: 
The Nigeria COVID-19 National Longitudinal Phone Survey 2020 covered the following topics: - Household Roster (Rounds 1, 2) - Knowledge Regarding the Spread of COVID-19 (Round 1) - Behaviour and Social Distancing (Round 1) - Access to Basic Services (Rounds 1, 2) - Employment (Rounds 1, 2) - Income Loss (Round 1) - Other Income (Round 2) - Food Security (Rounds 1, 2) - Concerns (Round 1) - Coping/Shocks (Round 1) - Social Safety Nets (Rounds 1, 2)
Harvest Source: 
Harvest System ID: 
11415
Citation Text: 
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 National Bureau of Statistics. Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020. Dataset downloaded from [source] on [date].
Modified date: 
18472
Study Type: 
Other Household Survey [hh/oth]
Primary Dataset: 
Yes
Data Collector(s) Name: 

National Bureau of Statistics

Funding Name, Abbreviation, Role: 

Bill and Melinda Gates Foundation, Federal Government of Nigeria

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