High Frequency Phone Survey on COVID-19 2022, Round 5
Papua New Guinea, 2022
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Reference ID
SPC_PNG_2022_HFPS-W5_v01_M_v01_A_PUF
Producer(s)
World Bank
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Metadata
Created on
Sep 15, 2022
Last modified
Nov 13, 2022
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8907
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Identification
Survey ID Number
SPC_PNG_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 |
|---|---|
| Papua New Guinea | PNG |
Study type
1-2-3 Survey, phase 5 [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 Papua New Guinea, 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 Papua New Guinea.
To monitor the socio-economic impacts of COVID-19 in Papua New Guinea, 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 Papua New Guinea.
Abstract
A strong evidence base is needed to understand the socioeconomic implications of the coronavirus pandemic for the Papua New Guinea. High Frequency Phone Surveys (HFPS) are set up to understand these implications over the years. This data is the fifth round in a series of mobile phone surveys.
Four prior rounds of the HFPS were conducted in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2), July-Aug 2021 (Round 3), and Nov 2021-Dec 2021 (Round 4). Round 5 interviewed 2,630 households across the country between May 30, 2022, and June 22, 2022, on topics including vaccines of COVID-19, employment, income, food security, health, coping strategies, public trust and security, assets and well-being.
Four prior rounds of the HFPS were conducted in June 2020 (Round 1), Dec 2020-Jan 2021 (Round 2), July-Aug 2021 (Round 3), and Nov 2021-Dec 2021 (Round 4). Round 5 interviewed 2,630 households across the country between May 30, 2022, and June 22, 2022, on topics including vaccines of COVID-19, employment, income, food security, health, coping strategies, public trust and security, assets and well-being.
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
2022-09
Version Notes
Dataset distributed by the World Bank Group (WBG).
Scope
Notes
-HOUSEHOLD: Interview information; Basic information; Access food & food security; Coping strategies; Health; Assets and well-being.
-INDIVIDUAL: Basic information, COVID-19 Vaccination; Employment and income information; Public trust and security.
-INDIVIDUAL: Basic information, COVID-19 Vaccination; Employment and income information; Public trust and security.
Topics
| Topic |
|---|
| pacific-skills, education, training |
| pacific-skills, employment |
Keywords
| Keyword |
|---|
| COVID-19 |
| High Frequency Phone Survey |
| Vaccination |
| Food security |
| Health |
| Assets |
| Well-being |
| Employment |
| Income |
Coverage
Geographic Coverage
Urban and rural areas of Papua New Guinea.
Universe
Respondents were aged 18+.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| World Bank | World Bank Group |
Producers
| Name | Affiliation | Role |
|---|---|---|
| International Bank for Reconstruction and Development | World Bank Group | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | WB | 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 2,714 households contacted in Round Four. Five hundred to six hundred calls are done each day, and unsuccessful numbers were attempted 4 to 6 times a day. Of the Round Four households, 1,224 were successfully re-contacted.
For PNG round 5, a total of 2,638 successful surveys were completed, out of which 2,630 were willing to participate. The size of the final analytical sample is 2,630, among which 1,224 households were pre-loaded, and 1,406 were replacement households. Questionnaires and preloaded numbers were supplied by WBG team to support dialing out to lead list for the campaign survey. For the replacement numbers, 10,000-12,000 extra leads (replacement numbers) were extracted from the survey firm's (Digicel's) database. Numbers were randomly allocated to enumerators per listings for outbound dialing, and the numbers were equally distributed amongst each PNG region and province to collect quality data as per the requirements. A total of 89 districts were contacted for the WBG survey.
For more information on sampling, please refer to the presentation slides provided in the External Resources.
For PNG round 5, a total of 2,638 successful surveys were completed, out of which 2,630 were willing to participate. The size of the final analytical sample is 2,630, among which 1,224 households were pre-loaded, and 1,406 were replacement households. Questionnaires and preloaded numbers were supplied by WBG team to support dialing out to lead list for the campaign survey. For the replacement numbers, 10,000-12,000 extra leads (replacement numbers) were extracted from the survey firm's (Digicel's) database. Numbers were randomly allocated to enumerators per listings for outbound dialing, and the numbers were equally distributed amongst each PNG region and province to collect quality data as per the requirements. A total of 89 districts were contacted for the WBG survey.
For more information on sampling, please refer to the presentation slides provided in the External Resources.
Response Rate
Response rate for returning households: 45.10%.
Weighting
The sampling weights were developed for round five of the Papua New Guinea high frequency phone survey in a series of steps. Information from the 2016-2018 Demographic and Health Survey (DHS) was used to construct weights and to reflect nationally representative estimates of the socioeconomic impacts of COVID-19. While a good starting point, this strategy does not address the main shortcoming of using random digit dialing, which is that the resulting data is representative of the population of mobile phone owners rather than the population across the country. According to the most recent data (from Digital 2021 report for Papua New Guinea by DataReportal: https://datareportal.com/reports/digital-2021-papua-new-guinea), the number of mobile connections in Papua New Guinea in January 2021 was equivalent to 34.4% of the total 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 Papua New Guinea population.
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. Using the 2016-2018 DHS, and comparing individuals that own a phone (either landline or a mobile phone) and those without one, we find that phone holders are more likely to be 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 0 and 57 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 individual data set contains weights for vaccine analysis and employment analysis and are named as covid_weight and emp_weight, respectively.
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. Using the 2016-2018 DHS, and comparing individuals that own a phone (either landline or a mobile phone) and those without one, we find that phone holders are more likely to be 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 0 and 57 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 individual data set contains weights for vaccine analysis and employment analysis and are named as covid_weight and emp_weight, respectively.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2022-05-30 | 2022-06-22 | Data collection |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
The data was collected by Digicel. Digicel is a mobile phone network provider in Papua New Guinea. The dates of implementation were between May 30, 2022, and June 22, 2022, and the implementation method was Random Digit Dialing using mobile phone numbers. Since phone numbers in the Papua New Guinea 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 |
|---|
| Digicel |
Questionnaires
Questionnaires
The questionnaire - that can be found in the External Resources of this documentation - was developed both in English and in Pidgin.
The survey instrument for the fifth round consisted of the following modules:
-Basic information,
-Vaccines of COVID-19,
-Employment and Income,
-Access food & food security,
-Coping strategies,
-Health,
-Public trust and security,
-and Assets and wellbeing.
The survey instrument for the fifth round consisted of the following modules:
-Basic information,
-Vaccines of COVID-19,
-Employment and Income,
-Access food & 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 2,630 and is 3,445 in the individual data set. The individual data set contains the employment, income, vaccine, and public trust information for all individuals, whereas the household data set contains information about public services, staple food access and food security, coping strategies, health care, 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 2,630 and is 3,445 in the individual data set. The individual data set contains the employment, income, vaccine, and public trust information for all individuals, whereas the household data set contains information about public services, staple food access and food security, coping strategies, health care, and awareness of COVID-19.
Other Processing
Data was collected and managed using the Survey Solutions software package. 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
"Papua New Guinea, High Frequency Phone Survey on COVID-19 2022 (HFPS 2022-W5) Round 5, Version 01 of the licensed dataset (September 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_PNG_2022_HFPS-W5_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
2022-09-15
DDI Document version
Version 01 (September 2022): This is the first attempt at documenting the fifth round of Papua New Guinea's High Frequency Phone Survey (HFPS) on COVID-19. Done by Statistics for Development Division at Noumea, New Caledonia.