High Frequency Phone Survey on COVID-19 2021, Round 3
Solomon Islands, 2021
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Reference ID
SPC_SLB_2021_HFPS-W3_v01_M_v01_A_PUF
Producer(s)
World Bank
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Metadata
Created on
Aug 25, 2022
Last modified
Aug 31, 2022
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Identification
Survey ID Number
SPC_SLB_2021_HFPS-W3_v01_M_v01_A_PUF
Title
High Frequency Phone Survey on COVID-19 2021, Round 3
Subtitle
Round 3
Country
| Name | Country code |
|---|---|
| Solomon Islands | SLB |
Study type
1-2-3 Survey, phase 3 [hh/123-3]
Series Information
The World Bank is providing support to countries to help mitigate the spread and impact of the new corona-virus 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.
To monitor the socio-economic impacts of COVID-19 in Solomon Islands, five rounds of High Frequency Phone Survey on COVID-19 (HFPS) are planned. The documented dataset refers to the third round of the HFPS of Solomon Islands.
To monitor the socio-economic impacts of COVID-19 in Solomon Islands, five rounds of High Frequency Phone Survey on COVID-19 (HFPS) are planned. The documented dataset refers to the third round of the HFPS of Solomon Islands.
Abstract
A strong evidence base is needed to understand the socioeconomic implications of the coronavirus pandemic for the Solomon Islands. High Frequency Phone Surveys (HFPS) are set up to understand these implications over the years. This data is the third of the five planned rounds of mobile surveys.
Two rounds of the HFPS are already completed in June 2020 (Round 1) and Dec 2020-Jan 2021 (Round 2). Round 3 interviewed 2,503 households across the country between 29th June 2021 and 11th Aug 2021, on topics including Vaccines of COVID-19, Employment & Income, Food security, Coping strategies, Health, and Public trust and security. Telephone interviews were conducted through a Solomon Islands call center set up by Tebbutt Research.
Two rounds of the HFPS are already completed in June 2020 (Round 1) and Dec 2020-Jan 2021 (Round 2). Round 3 interviewed 2,503 households across the country between 29th June 2021 and 11th Aug 2021, on topics including Vaccines of COVID-19, Employment & Income, Food security, Coping strategies, Health, and Public trust and security. Telephone interviews were conducted through a Solomon Islands call center set up by Tebbutt Research.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household and Individual.
Version
Version Description
Version 01: Clean, labelled and anonymized version of the Master file.
Version Date
2022-07-01
Version Notes
Dataset distributed by the World Bank Group (WBG).
Scope
Notes
-HOUSEHOLD: Interview information; Basic information; Vaccines of COVID-19; Employment & ESP; Income; Coping strategies; Access food and food security; Health; Public trust and security; Assets and well-being.
-INDIVIDUAL: Basic information and employment information.
-INDIVIDUAL: Basic information and employment information.
Topics
| Topic |
|---|
| pacific-skills, education, training |
| pacific-skills, employment |
Keywords
| Keyword |
|---|
| COVID-19 |
| Employment |
| Income |
| Subsistence |
| Education |
| Health |
| Assets |
Coverage
Geographic Coverage
Urban and rural areas of Solomon Islands.
Universe
Respondents must be at least 18 years of age to participate the survey.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| World Bank | World Bank Group |
Funding Agency/Sponsor
| Name | Role |
|---|---|
| The World Bank | Funding |
| Korea Trust Fund for Economic and Peace-Building Transitions | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| UNICEF | United Nations | Technical assistance |
Sampling
Sampling Procedure
As the objective of the survey was to measure changes as the pandemic progresses, Round Three data collection sought to re-contact all 2,882 households contacted in Round Two. The protocols for re-contact were a maximum of 3 attempts per caller shift, spaced between 1.5 and 2.5 hours apart depending on whether the phone was busy or there was no answer, and 15 attempts in total. Of the Round Two households, 1,182 were successfully re-contacted.
Honiara was over-represented in the sample (accounting for 36.9 percent of the sample). Compensating factors for these differences were developed and included in the re-weighting calculations. Due to the limited sample sizes outside of Honiara, most results are disaggregated into only three geographic regions: Honiara, other urban areas, and rural areas.
To reach the target sample size of at least 2500 households, 980 new replacement households were added to the World Bank survey. The final sample of completed interviews was 2,503. The employment questions were asked for both the respondent and the household head by proxy (if different from the respondent), yielding a total sample size for the individual-level employment analysis of 3,188.
Further information regarding weighting can be found in the HFPS Round One and HFPS Round Two reports, which followed the same weighting methodology. Because of considerable attrition between rounds, most statistics showing changes through time reflect data from repeated cross sections rather than panels.
Honiara was over-represented in the sample (accounting for 36.9 percent of the sample). Compensating factors for these differences were developed and included in the re-weighting calculations. Due to the limited sample sizes outside of Honiara, most results are disaggregated into only three geographic regions: Honiara, other urban areas, and rural areas.
To reach the target sample size of at least 2500 households, 980 new replacement households were added to the World Bank survey. The final sample of completed interviews was 2,503. The employment questions were asked for both the respondent and the household head by proxy (if different from the respondent), yielding a total sample size for the individual-level employment analysis of 3,188.
Further information regarding weighting can be found in the HFPS Round One and HFPS Round Two reports, which followed the same weighting methodology. Because of considerable attrition between rounds, most statistics showing changes through time reflect data from repeated cross sections rather than panels.
Response Rate
Response rate for returning households: 41.01%.
Weighting
The sampling weights were developed for round three of the Solomon Islands high frequency phone survey in a series of steps. As the main shortcoming of using random digit dialing is that the resulting data is representative of the population of mobile phone owners, and according to the most recent data (from International Telecommunication Union, World Telecommunication/ICT Development Report and data base (2018)) available for mobile phone penetration estimates usage as 74 percent of the population, coverage is concentrated in population centers, and better off households and individuals are more likely to have a mobile phone which is charged and turned on. Therefore, the pool of respondents is very different from a representative sample of the Solomon Islands population.
Auxiliary data to serve as inputs to the weights is severely limited as there are few recent nationally representative sources. The results from the recently completed census are not yet available and the last Household Income and Expenditure Survey (HIES) was from 2012/2013. The most recent nationally representative dataset including a measure of welfare was the Solomon Islands Demographic and Health Survey 2015 (DHS).
Weights are required for unbiased estimation. because the survey was administered by mobile phones, the respondents were a representative sample of mobile phone holders, not the population overall, and non-random non-response can exacerbate these differences. Previous literature has shown that mobile phone holders are more likely to be male, urban, wealthier, and more highly educated. To make inferences at the level of the population instead of mobile phone holders, it was necessary to reweight the survey data.
Definitionally, the DHS deciles each contain 10 percent of the sample. Using the maximum and minimum threshold values for the DHS deciles to map the mobile phone survey results, it is clear there is a strong bias toward the upper deciles (wealthier) households in the distribution. While weighting can adjust for the bias, there are only 14 and 14 observations in the bottom two deciles of the distribution, respectively. These sample sizes are too small to yield estimates of adequate precision to report results.
Therefore, direct analysis is limited to the bottom four deciles (bottom 40 percent), and then the middle two deciles (middle quintile) and top four deciles (top 40 percent). In addition, each statistic is reported with its confidence interval and all econometric findings are statistically significant, unless otherwise stated.
The "weight" variable in the household dataset is called "weight_hh" and represents household cross-sectional weights, whereas the "weight" variable in the individual data set is called as "weight_ind" and represents individual cross-sectional weights.
Auxiliary data to serve as inputs to the weights is severely limited as there are few recent nationally representative sources. The results from the recently completed census are not yet available and the last Household Income and Expenditure Survey (HIES) was from 2012/2013. The most recent nationally representative dataset including a measure of welfare was the Solomon Islands Demographic and Health Survey 2015 (DHS).
Weights are required for unbiased estimation. because the survey was administered by mobile phones, the respondents were a representative sample of mobile phone holders, not the population overall, and non-random non-response can exacerbate these differences. Previous literature has shown that mobile phone holders are more likely to be male, urban, wealthier, and more highly educated. To make inferences at the level of the population instead of mobile phone holders, it was necessary to reweight the survey data.
Definitionally, the DHS deciles each contain 10 percent of the sample. Using the maximum and minimum threshold values for the DHS deciles to map the mobile phone survey results, it is clear there is a strong bias toward the upper deciles (wealthier) households in the distribution. While weighting can adjust for the bias, there are only 14 and 14 observations in the bottom two deciles of the distribution, respectively. These sample sizes are too small to yield estimates of adequate precision to report results.
Therefore, direct analysis is limited to the bottom four deciles (bottom 40 percent), and then the middle two deciles (middle quintile) and top four deciles (top 40 percent). In addition, each statistic is reported with its confidence interval and all econometric findings are statistically significant, unless otherwise stated.
The "weight" variable in the household dataset is called "weight_hh" and represents household cross-sectional weights, whereas the "weight" variable in the individual data set is called as "weight_ind" and represents individual cross-sectional weights.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2021-06-29 | 2021-08-11 | Data collection |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Data Collection Notes
Tebbutt Research is a full-service market research and social research agency with expertise in Pacific Islands research. The dates of implementation were 29th June 2021 through 11th Aug 2021, and the implementation method was Random Digit Dialing using mobile phone numbers. Since phone numbers in the Solomon Islands do not contain any location information, it was not possible to do any geographical targeting, and therefore the sample was developed based on targets for completed interviews by location.
Data Collectors
| Name | Affiliation |
|---|---|
| Tebbutt Research | Government of Solomon Islands |
Questionnaires
Questionnaires
The questionnaire - that can be found in the External Resources of this documentation - was developed both in English and in Solomons Pijin.
The survey instrument for the third round consisted of the following modules:
-Basic information,
-Vaccines of COVID-19
-Employment & ESP,
-Income,
-Food access and food security,
-Coping strategies,
-Health
-Public trust and security,
-and Assets and wellbeing.
The survey instrument for the third round consisted of the following modules:
-Basic information,
-Vaccines of COVID-19
-Employment & ESP,
-Income,
-Food access and food security,
-Coping strategies,
-Health
-Public trust and security,
-and Assets and wellbeing.
Data Processing
Data Editing
At the end of data collection, the dataset was cleaned by the World Bank team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes. Data was edited using STATA.
The data is presented in two data sets: household data set and individual data set. The total number of observations in the household data set is 2,503 and 3,188 in the individual data set. The individual data set mentions the employment information for all the household members, whereas the household data set contains information about vaccines of COVID-19, food access and food security, coping strategies, health, public trust and security, and assets.
The data is presented in two data sets: household data set and individual data set. The total number of observations in the household data set is 2,503 and 3,188 in the individual data set. The individual data set mentions the employment information for all the household members, whereas the household data set contains information about vaccines of COVID-19, food access and food security, coping strategies, health, public trust and security, and assets.
Data Appraisal
Data Appraisal
Imputation was done for missing education values when calculating the individual weights
Access policy
Contacts
| Name | Affiliation | URL |
|---|---|---|
| World Bank | World Bank Group | Link |
Confidentiality
Before being granted access to the dataset, all users must 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 needs to be immediately brought to the attention of the data depositor.
Access conditions
The dataset has been anonymized and is available as a Public Use Dataset. It is accessible to all for statistical and research purposes only, under the following terms and conditions:
1. The data and other materials will not be redistributed or sold to other individuals, Institutions, or organizations without the written agreement of the World Bank Microdata Library.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations,
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the World Bank Microdata Library.
4. No attempt will be made to produce links among datasets provided by the World Bank Microdata Library, or among data from the World Bank Microdata Library and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the World Bank Microdata Library will cite the source of data in accordance with the Citation Requirement provided with each dataset.
1. The data and other materials will not be redistributed or sold to other individuals, Institutions, or organizations without the written agreement of the World Bank Microdata Library.
2. The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations,
3. No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the World Bank Microdata Library.
4. No attempt will be made to produce links among datasets provided by the World Bank Microdata Library, or among data from the World Bank Microdata Library and other datasets that could identify individuals or organizations.
5. Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the World Bank Microdata Library will cite the source of data in accordance with the Citation Requirement provided with each dataset.
Citation requirements
"Solomon Islands, High Frequency Phone Survey on COVID-19 2021 round 3 (HFPS 2021-W3), Version 01 of the licensed dataset (July 2022), provided by the Pacific Data Hub - Microdata Library. https://microdata.pacificdata.org/index.php/home"
Access authority
| Name | Affiliation | URL |
|---|---|---|
| World Bank | World Bank Group | Link |
Disclaimer and copyrights
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.
Metadata production
DDI Document ID
DDI_SPC_SLB_2021_HFPS-W3_v01_M_v01_A_PUF
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics for Development Division | SDD | Pacific Community | Documentation of the study |
Date of Metadata Production
2022-08-30
DDI Document version
Version 01 (August 2022): This is the first attempt at documenting the 3rd round of the 2021 High Frequency Phone Survey on COVID-19 of Solomon Islands. Done by Statistics for Development Division at Noumea, New Caledonia.