High Frequency Phone Survey on COVID-19 2022, Round 4
Solomon Islands, 2022
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Reference ID
SLB_2022_HFPS-W4_v01_ES_M_v01_A_OCS
Producer(s)
World Bank
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Metadata
Created on
Jan 13, 2023
Last modified
Jan 13, 2023
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Identification
Survey ID Number
SLB_2022_HFPS-W4_v01_ES_M_v01_A_OCS
Title
High Frequency Phone Survey on COVID-19 2022, Round 4
Country
| Name | Country code |
|---|---|
| Solomon Islands | SLB |
Study type
Socio-Economic/Monitoring Survey [hh/sems]
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
Households, individuals
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 |
Producers
| Name | Role |
|---|---|
| World Bank | Funding |
| Korea Trust Fund for Economic and Peace-Building Transitions | Funding |
| Austalian Department of Foreign Trade | Funding |
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 |
|---|---|
| 2022-01-11 | 2022-02-25 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
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
Access policy
Contacts
| Name | Affiliation |
|---|---|
| World Bank | World Bank Group |
Confidentiality
The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO
Access conditions
Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
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"
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_SLB_2022_HFPS-W4_v01_ES_M_v01_A_OCS
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Statistics for Development Division | SDD | Pacific Community | Metadata producer |
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adapted for FAM |