High Frequency Phone Survey on COVID-19 2022, Round 5
Solomon Islands, 2022
World Bank
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April 20, 2023
Last modified
April 20, 2023
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Identification
Survey ID Number
SPC_SLB_2022_HFPS-W5_v01_M_v01_A_PUF
Title
High Frequency Phone Survey on COVID-19 2022, Round 5
Subtitle
Round 5
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 fifth 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 fifth 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 fifth of the five planned rounds of mobile surveys.
Four rounds of the HFPS are already completed in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2), July-Aug 2021 (Round 3) and Jan 2022-Feb 2022 (Round 4), Round 5 interviewed 2,507 households across the country between July 30, 2022, and September 8, 2022, on topics including vaccines of COVID-19, employment, income, food security, health, and coping strategies, and public trust and security.
Four rounds of the HFPS are already completed in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2), July-Aug 2021 (Round 3) and Jan 2022-Feb 2022 (Round 4), Round 5 interviewed 2,507 households across the country between July 30, 2022, and September 8, 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: Cleaned, labelled and anonymized version of the master file.
Version Date
2023-03-23
Version Notes
Dataset distributed by the World Bank Group (WBG).
Scope
Notes
-HOUSEHOLD: Interview information (S1); Basic information (S2); Health (S5); Access food & food security (S7); Coping strategies (S10); Assets and well-being (S11); Public trust and security (S12).
-INDIVIDUAL: Basic information (S2); Information about COVID-19 (S3); Vaccines of COVID-19 (S4); Employment and income information (S8).
-CHILD: Education (S6).
-INDIVIDUAL: Basic information (S2); Information about COVID-19 (S3); Vaccines of COVID-19 (S4); Employment and income information (S8).
-CHILD: Education (S6).
Topics
| Topic |
|---|
| pacific-skills, education, training |
| pacific-skills, employment |
Keywords
| Keyword |
|---|
| High Frequency Phone Survey |
| COVID-19 |
| Health |
| Employment |
| Vaccination |
| Access to food |
| Assets |
| Security |
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 |
Producers
| Name | Affiliation | Role |
|---|---|---|
| The International Bank for Reconstruction and Development | World Bank Group | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | Funding | |
| Australian Department of Foreign Affairs and Trade | DFAT | Funding |
Sampling
Sampling Procedure
As the objective of the survey was to measure changes as the pandemic progresses, Round Five data collection sought to re-contact all 2,671 households contacted in Round Four. 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. A new survey company (Sistemas) was hired for the fifth round, and the old survey company (Tebbutt) did not provide the phone numbers of the old households contacted in previous rounds. Hence, no returning households can be identified in round 5.
In Round Five, Honiara was over-represented in the World Bank HFPS (constituting 47.7 percent of the survey sample). All other provinces were deemed under-represented, with the largest differences being for Malaita and Western, which represented 9.5 percent (Census: 21.4 percent), and 12.5 percent of the survey sample (Census: 21.4 percent), respectively. Urban areas constituted 58.3 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.
For more information on sampling, please refer to the presentation slides provided in the External Resources.
In Round Five, Honiara was over-represented in the World Bank HFPS (constituting 47.7 percent of the survey sample). All other provinces were deemed under-represented, with the largest differences being for Malaita and Western, which represented 9.5 percent (Census: 21.4 percent), and 12.5 percent of the survey sample (Census: 21.4 percent), respectively. Urban areas constituted 58.3 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.
For more information on sampling, please refer to the presentation slides provided in the External Resources.
Weighting
The sampling weights were developed for round five 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 17 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. 'Weight_hh_coping' variable can be used for coping-strategy-related questions.
The individual data set contains weights for vaccine analysis and employment analysis and are named as covid_weight and emp_weight, respectively. For analyses of public-trust-related questions, 'covid_weight' should be used.
The child data set contains weights for child education analysis and are named as childeduc_weight.
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 17 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. 'Weight_hh_coping' variable can be used for coping-strategy-related questions.
The individual data set contains weights for vaccine analysis and employment analysis and are named as covid_weight and emp_weight, respectively. For analyses of public-trust-related questions, 'covid_weight' should be used.
The child data set contains weights for child education analysis and are named as childeduc_weight.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2022-07-30 | 2022-09-08 | Data collection |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Data Collection Notes
Sistemas is a full-service market research and social research agency with expertise in Pacific Islands research. The dates of implementation were between July 30, 2022 and September 8, 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.
Both the household data and individual data have 2,507 observations. The child data set has 1,260 observations. The individual data set has the demographic and employment information for the respondent and the household head. However, the employment information is missing for 40 individuals because of a skip pattern error. The child data set has education information for households who answered the child education section (section 6).
Both the household data and individual data have 2,507 observations. The child data set has 1,260 observations. The individual data set has the demographic and employment information for the respondent and the household head. However, the employment information is missing for 40 individuals because of a skip pattern error. The child data set has education information for households who answered the child education section (section 6).
Data Collectors
| Name |
|---|
| Sistemas |
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 fifth round consisted of the following modules:
-Basic information,
-Information about COVID-19,
-Vaccines of COVID-19,
-Health,
-Education,
-Access food & food security,
-Employment and Income,
-Coping strategies,
-Public trust and security,
-and Assets and wellbeing.
The survey instrument for the fifth round consisted of the following modules:
-Basic information,
-Information about COVID-19,
-Vaccines of COVID-19,
-Health,
-Education,
-Access food & food security,
-Employment and Income,
-Coping strategies,
-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 three data sets: household data set, individual data set, and child data set. The total number of observations in the household data set is 2,507 in the individual data set and is 1,260 in the child data set. The child data set contains the education information for children of all households who answered this section, the individual data set contains the employment and vaccine information for all individuals, and the household data set contains information about health, access food & food security, coping strategies, public trust and security, and assets and well-being.
The data is presented in three data sets: household data set, individual data set, and child data set. The total number of observations in the household data set is 2,507 in the individual data set and is 1,260 in the child data set. The child data set contains the education information for children of all households who answered this section, the individual data set contains the employment and vaccine information for all individuals, and the household data set contains information about health, access food & food security, coping strategies, public trust and security, and assets and well-being.
Other Processing
Imputation was done for missing education values in Round 5 when calculating the household, individual, and child education weights.
Access policy
Access authority
| Name | Affiliation | URL |
|---|---|---|
| World Bank | World Bank Group | https://www.worldbank.org/ |
Contacts
| Name | Affiliation | URL |
|---|---|---|
| World Bank | World Bank Group | https://www.worldbank.org/ |
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 5 (HFPS 2022-W5), Version 01 of the licensed dataset (March 2022), provided by the Pacific Data Hub - Microdata Library. https://microdata.pacificdata.org/index.php/home"
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-W5_v01_M_v01_A_PUF
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics for Development Division | SDD | Pacific Community (SPC) | Documentation of the survey |
Date of Metadata Production
2023-04-20
DDI Document version
Version 01 (April 2023): This is the first attempt at documenting the fifth round of the 2022 High Frequency Phone Survey on COVID-19 of Solomon Islands. Done by Statistics for Development Division at Noumea, New Caledonia.