High Frequency Phone Survey on COVID-19 2022, Round 4
Solomon Islands, 2022
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Reference ID
SPC_SLB_2022_HFPS-W4_v01_M_v01_A_PUF
Producer(s)
World Bank
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Metadata
Created on
Aug 25, 2022
Last modified
Aug 25, 2022
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Identification
Survey ID Number
SPC_SLB_2022_HFPS-W4_v01_M_v01_A_PUF
Title
High Frequency Phone Survey on COVID-19 2022, Round 4
Subtitle
Round 4
Country
| Name | Country code |
|---|---|
| Solomon Islands | SLB |
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 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 fourth 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 fourth 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 fourth of the five planned rounds of mobile surveys.
Three rounds of the HFPS are already completed in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2) and July-Aug 2021 (Round 3). Round 4 interviewed 2,671 households across the country between January 11, 2022, and February 25, 2022, on topics including vaccines of COVID-19, employment, income, food security, health, and coping strategies, and public trust and security.
Three rounds of the HFPS are already completed in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2) and July-Aug 2021 (Round 3). Round 4 interviewed 2,671 households across the country between January 11, 2022, and February 25, 2022, on topics including vaccines of COVID-19, employment, income, food security, health, and coping strategies, and public trust and security.
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
Version Notes
Dataset distributed by the World Bank Group (WBG).
Scope
Notes
-HOUSEHOLD: Interview information; Basic information; Vaccines of COVID-19; Employment and income information; Access food and food security; Coping strategies; 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 |
|---|
| High Frequency Phone Survey |
| COVID-19 |
| Employment |
| Health |
| Vaccination |
| Education |
| Income |
| Assets |
| Consumption |
Coverage
Geographic Coverage
Urban and rural areas of Solomon Islands.
Universe
All respondents must be aged 18 and over and have a phone.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| World Bank | World Bank Group |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | Funding | |
| Korea Trust Fund for Economic and Peace-Building Transitions | Funding | |
| Austalian Department of Foreign Trade | DFAT | 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 Four data collection sought to re-contact all 2,503 households contacted in Round Three. 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 Three households, 1,106 were successfully re-contacted.
In Round Four, Honiara and Guadalcanal were over-represented in the World Bank HFPS (constituting 19.7 percent and 26.0 percent of the survey sample, respectively). All other provinces were deemed under-represented, with the largest differences being for Malaita, which represented 15.7 percent of the survey sample compared to 21.4 percent of the population in the census. Urban areas constituted 34.3 percent of the survey sample, compared to a quarter (25.6 percent) of the census.
The target geographic distribution for the survey was based on the population distribution across provinces from the preliminary 2019 census results. According to the population census, Honiara constituted almost one quarter (18.0 percent) of the total population. 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.
In Round Four, Honiara and Guadalcanal were over-represented in the World Bank HFPS (constituting 19.7 percent and 26.0 percent of the survey sample, respectively). All other provinces were deemed under-represented, with the largest differences being for Malaita, which represented 15.7 percent of the survey sample compared to 21.4 percent of the population in the census. Urban areas constituted 34.3 percent of the survey sample, compared to a quarter (25.6 percent) of the census.
The target geographic distribution for the survey was based on the population distribution across provinces from the preliminary 2019 census results. According to the population census, Honiara constituted almost one quarter (18.0 percent) of the total population. 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.
Response Rate
Response rate for returning households: 44.19%.
Weighting
The sampling weights were developed for round four 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 8 and 15 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. The data set also contains 'weight_g1' and 'weight_g2' that represents weights for two groups of households. Group 1 represents weights of households that completed sections on food security, and health, group 2 households completed sections on income, and coping strategies. These households were randomly selected.
The individual data set contains weights for vaccine analysis, employment analysis, and public trust analysis and are named as covid_weight, emp_weight and public_trust_weight, respectively.
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 8 and 15 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. The data set also contains 'weight_g1' and 'weight_g2' that represents weights for two groups of households. Group 1 represents weights of households that completed sections on food security, and health, group 2 households completed sections on income, and coping strategies. These households were randomly selected.
The individual data set contains weights for vaccine analysis, employment analysis, and public trust analysis and are named as covid_weight, emp_weight and public_trust_weight, respectively.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2022-01-11 | 2022-02-25 | 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 between January 11, 2022, and February 25, 2022, 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.
Group 1 are the households that answered sections on vaccines, food security, and health. Group 2 answered sections on income, and coping strategies.
Additional questions in section 4, employment, were added in the questionnaire after February 2, 2022. These questions (new1-3) were asked to households whose main employment activity was fishing.
Group 1 are the households that answered sections on vaccines, food security, and health. Group 2 answered sections on income, and coping strategies.
Additional questions in section 4, employment, were added in the questionnaire after February 2, 2022. These questions (new1-3) were asked to households whose main employment activity was fishing.
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 fourth round consisted of the following modules:
-Basic information,
-Vaccines of COVID-19,
-Employment and Income,
-Access food and food security,
-Coping strategies,
-Health,
-Public trust and security,
-and Assets and wellbeing.
The survey instrument for the fourth round consisted of the following modules:
-Basic information,
-Vaccines of COVID-19,
-Employment and Income,
-Access food 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 2,671 and is 4,038 in the individual data set. The individual data set contains the employment, vaccine, and public trust information for all individuals, whereas the household data set contains information about public services, income, coping strategies, and awareness of COVID-19.
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 2,671 and is 4,038 in the individual data set. The individual data set contains the employment, vaccine, and public trust information for all individuals, whereas the household data set contains information about public services, income, coping strategies, and awareness of COVID-19.
Data Appraisal
Data Appraisal
Imputation was done for missing education values in Round 4 when calculating the household and 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 2022 round 4 (HFPS 2022-W4), 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_2022_HFPS-W4_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
2022-08-31
DDI Document version
Version 01 (August 2022): This is the first attempt at documenting the fourth round of the 2022 High Frequency Phone Survey on COVID-19 of Solomon Islands. Done by Statistics for Development Division at Noumea, New Caledonia.