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 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.
Although the first case of COVID-19 in Uganda was confirmed on the 22nd of March, Government of Uganda had undertaken several actions starting on the 18th of March, including travel restrictions, a 14-day quarantine for all international arrivals, and cancellation of all international conferences and public gatherings, including, but not limited to, religious services, weddings and concerts. On the 30th of March, the President declared a nationwide curfew from 7 pm to 6:30 am; banned public transportation; and instituted strict regulations for the movement of government and private vehicles. As governments implement various 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 the UHFS is to monitor the socio-economic effects of COVID-19 and its related restrictions. The survey will follow the evolving COVID-19 pandemic in real time and will contribute to filling critical gaps in information that could be used by the government and stakeholders to help design policies to mitigate the negative impacts on its population. The UHFS is proposed to have multiple rounds to accommodate the evolving nature of the crisis, including revision of the questionnaire before the next round of survey. The final sample for the first round of the survey is 2,257 households selected from those of the Uganda National Panel Survey (UNPS) wave 8 that had phone number for at least one household member or one reference individual. All households not explicitly refusing to participate in round 1 were attempted to be reached in round 2. The final sample for round 2 is 2199; whereas the final sample for round 3 and round 4 counts 2147 and 2136 households respectively. In Round 5, 2122 households and in Round 6, 2100 households were interviewed. In round 7 the interviews completed were 1950. Weights are adjusted to be nationally representative in each round. Weights are adjusted to be nationally representative in each round.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Version 08: Edited, anonymized dataset for public distribution.
Round 7 data has been added to the documenation.
The Uganda High-Frequency Phone Survey on COVID-19 covered the following topics:
- Household Roster
- Knowledge and False Beliefs Regarding the Spread of COVID-19
- Behaviour and Social Distancing
- Access to Basic Services
- Non-Agricultural Business
- Income Loss
- Food Security
- Credit- Concerns
- Social Safety Nets
Producers and sponsors
Uganda Bureau of Statistics (UBOS)
Gouvernement of Uganda
The World Bank
To obtain a nationally representative sample for the COVID-19 Impact Survey, 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. Thus, all the households in the 2019/20 round of the UNPS that had phone numbers for at least one household member, or a reference individual were included in the initial sample. This consisted of 2227 households, that is the 72 % of the UNPS 2019/20 sample.
In the baseline (Round 1) 2246 households were reached and 2227, that is the 93 % of the initial sample were fully interviewed; of these 1644 reside in the rural area, while 583 in the urban area.
In round 2, 2221 households were reached and 2199, that is the 93 %of the initial sample, were fully interviewed; of these 1641 reside in the rural area, while 558 in the urban area.
In round 3, 2221households were reached and 2147 that is the 91 % of the initial sample, were fully interviewed; of these 1603 reside in the rural area, while 544 in the urban area.
The response rate for round 4 is 90.5 percent: 2136 households were fully interviewed; of these1593 reside in the rural area, while 543 in the urban area.
The response rate for round 5 is 91.7 per cent. Indeed, in February 2122 households were fully interviewed.
To produce national estimates from the successfully interviewed sample, weights must be applied to the information provided by sampled households. Weights for the UNPS serve as the basis for the COVID-19 impact survey, but the weights were adjusted to reflect the selection and interviewing process. The weights for the baseline COVID-19 impact survey were therefore calculated as outlined in Himelein, K. (2014):
1. Begin with base weights from the UNPS 2019/20 for each household.
2. Incorporate probability ofsub-selection of round 1 unit for each of the phone survey households. We calculate the probability of selection for each of the 4strata (regions) in the UNPS by creating the numerators as the number of completed phone interviews and the denominator as the number of households in the UNPS for each stratum.
3. Pool the weights in Steps 1 and 2.
4. Derive attrition-adjusted weights for all individuals by running a logistic response propensity model based on characteristics of the household head (i.e. education, labor force status, demographic characteristics), characteristics of the household (consumption, assets, financial characteristics), and characteristics of the dwelling (house ownership, overcrowding).
5. Trim weights by replacing the top two percent of observations with the 98th percentile cut-off point; and
6. Post-stratify weights to known population totals to correct for the imbalances across the regional sample. In doing so, we ensure that the distribution in the survey matches the distribution in the UNPS.
Additional technical details and explanations on each of the steps briefly outlined above can be found in Himelein, K. (2014).
Dates of Data Collection
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Training of the enumerators were carried out both in office - in observance of social distancing measures - and via zoom. Valuable input during the training of enumerators was got from the World Bank via Skype and zoom. Supervision and enumerator follow-up were undertaken remotely.
Data Collection Notes
Since government-imposed social distancing practices to fight the spread of COVID-19 limited the use of traditional, face-to-face interviews, the interviews were conducted by phone using a Computer-Assisted Telephone Interviewing (CATI) application using the Survey Solution software. For the first round of data collection, phone centers could not be operated due to restrictions of movement and assembly of people, therefore, enumerators worked from their own home.
The COVID-19 survey had consisted of one main Household questionnaire per each round. The questionnaire is divided into several sections and the number of questions in each section varied accordingly.
ROUND 1: The Household Questionnaire for Round 1 provides information on demographics; knowledge and false beliefs regarding the spread of COVID-19; behavior and social distancing; access to basic services; employment; Agriculture; income loss; food security; concerns; coping/shocks; and social safety nets.
ROUND 2: The Household Questionnaire for Round 2 provides information on demographics; Perceptions Re: Efficacy of Government Actions; behavior and social distancing; access to basic services; employment; Agriculture; non-agricultural income; income loss; food security; credit; concerns; and social safety nets.
ROUND 3: The Household Questionnaire for Round 3 provides information on demographics; Perceptions Re: Efficacy of Government Actions behavior and social distancing; access to basic services; employment; Agriculture; non-agricultural income; income loss; food security; credit; concerns; and social safety nets.
ROUND 4: The Household Questionnaire for Round 4 provides information on demographics; Education; Perceptions Re: Efficacy of Government Actions behavior and social distancing; access to basic services; employment; Agriculture; non-agricultural income; income loss; food security; concerns; and social safety nets.
ROUND 5: The questionnaire for Round 5 comprises information on demographics; Education; Childhood development (parental support at home); behavior and social distancing; access to basic services; assets; employment; Agriculture; non-agricultural income; income loss; food security; concerns; and social safety nets.
ROUND 6: The questionnaire for Round 6 comprises information on demographics; Education; Childhood development (child behaviour and child discipline); behavior and social distancing; access to basic services; employment of the respondent and other household member; assets; Agriculture; non-agricultural income; income loss; food security; concerns; shocks and coping strategies; and social safety nets.
ROUND 7: The questionnaire for Round 7 comprises information on demographics; Education; knowledge regarding the spread of COVID-19; perception on government action against COVID-19; behavior and social distancing; access; employment of the respondent and other household member; agriculture; non-agricultural business; food security; concerns; and social safety nets.
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
Uganda Bureau of Statistics. Uganda High-Frequency Phone Survey on COVID-19 (HFPS) 2020-2021. Ref. UGA_2020_HFPS_v08_M. Dataset downloaded from [source] on [date].
LSMS Data Manager
The World Bank
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.
World Bank 2021
DDI Document ID
Development Economics Data Group
The World Bank
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 08 (January 2022)
Data and documentation for round 7 added.