{"doc_desc":{"idno":"DDI_TZA_2017-2018_DPHS_v01_M_WB","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"THe World Bank","role":"Documentation of the survey"}],"prod_date":"2022-07-05","version_statement":{"version":"Version 01 (July 2022)","version_date":"2022-07-05"}},"study_desc":{"title_statement":{"idno":"TZA_2017-2018_DPHS_v01_M","title":"Disaster Poverty Household Survey 2017-2018, Dar es Salaam","alt_title":"DPHS 2017-18"},"authoring_entity":[{"name":"Alvina Erman","affiliation":"The World Bank"},{"name":"Silvia Malgioglio","affiliation":"The World Bank"},{"name":"Nobuo Yoshida","affiliation":"The World Bank"},{"name":"Stephane Hallegatte","affiliation":"The World Bank"}],"production_statement":{"funding_agencies":[{"name":"Global Facility for Disaster Reduction and Recovery","abbreviation":"GFDRR","role":"Funded the survey"},{"name":"Tanzanian Urban Resilience Program","abbreviation":"TURP","role":"Funded the survey"}]},"distribution_statement":{"contact":[{"name":"Alvina Erman","affiliation":"GFDRR","email":"aerman@worldbank.org","uri":""}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]","series_info":"The Disaster Poverty Household Survey (DPHS) is designed to collect information to assess the relationship between disaster risk (exposure, vulnerability, and capacity to recover) and poverty in the urban environment. The data can be used to explore policy-relevant research topics related to climate change adaptation, urbanization, urban poverty, and more.\n\nDPHS data contains information on household characteristics, household expenditure, living conditions and household experience with disasters. Household characteristics include household size and member level information on religion, education, and labor. Household expenditure is collected using the Survey of Well-being via Instant and Frequent Tracking (SWIFT) methodology, which estimates household income (or consumption expenditure) based on non-monetary variables that are highly correlated with poverty. Information on living conditions covers housing quality, asset ownership, access to services and jobs, rent and housing costs and tenure arrangements. Information on experiences with disasters includes direct and indirect impacts of historic disasters on household assets, education, health and labor access, as well as impacts on public services. There is also information on coping behaviors and perception of risk of future exposure. The Disaster-Poverty survey can be customized to collect information on different disasters. So far, it has mainly focused on the impacts of urban flooding.\n\nThis initiative is led by Global Facility for Disaster Reduction and Recovery (GFDRR) and was developed and implemented in strong collaboration with the Poverty Global Practice and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL) at the World Bank, as well as counterparts (Ministries of Finance, local and city governments, national statistical agencies, disaster risk management agencies, etc.) and selected survey firms."},"version_statement":{"version":"Version 01","version_date":"2022-06-23"},"study_info":{"abstract":"The DPHS in Dar es Salaam was conducted in two rounds in November-December 2017 and in September 2018, with the objective to assess the role of poverty and other social factors in urban flooding in the city. The survey data collected in 2017 focused on exposure to frequent flooding, while the follow up survey in 2018, targeting the same households, focused on the impact of a flood event that happened in April 2018. During the follow up survey in 2018, additional households were also added to the sample. The data collected is representative at the city level and overrepresented in areas that are flood prone.\n\nThis project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR), the Tanzanian Urban Resilience Program (TURP), the Poverty Global Practice and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL). Data collection was carried out by UDA Consulting under World Bank supervision.","coll_dates":[{"start":"2017-11","end":"2017-12","cycle":"1"},{"start":"2018-09","end":"2018-09","cycle":"2"}],"nation":[{"name":"Tanzania","abbreviation":"TAZ"}],"geog_coverage":"Dar es Salaam, Tanzania.","analysis_unit":"- Household \n- Individual","data_kind":"Sample survey data [ssd]","notes":"The survey covered the following topics:\n- Household information \n- Household roster: demographic characteristic, education attainment, labor participation\n- Asset ownership\n- Housing and services: tenure arrangements, housing costs and rent, tenure security, housing quality, access to services, remittances\n- Weather information\n- Preventive measures flood\n- General information on experience with flooding\n- Information on specific floods\n- Perception of risk and community engagement\n- Household enterprises\n- Investments in housing\n- Food Insecurity (Reduced Coping Strategy Index CSI-R)\n- Coping mechanism codes"},"method":{"data_collection":{"data_collectors":[{"name":"UDA Consulting","abbreviation":"UDA","affiliation":""}],"sampling_procedure":"The selection of households in the survey design had two objectives. First, to select a sample that represents the population of Dar es Salaam and second, to interview enough people who had experienced floods to be able to detect patterns in their socio-economic characteristics.\n\nThe sample size was selected to confidently represent the population of Dar es Salaam given the income level and income distribution. Accordingly, a sample size of 105 EAs and 10 households per EA were selected using Probability Proportion to Size (PPS). In 2018, 28 EAs to the original sample as part of an additional round of data collection.\n\nTo capture enough households that had experienced floods, a flood risk stratum was designed using the Ramani Huria community flood map. EAs were categorized according to three flood risk strata, i.e., \u201cno risk\u201d, \u201clow to medium risk\u201d and \u201chigh risk\u201d, depending on how much of the EA was covered by the flood layer in the map. This categorization of the city was used to oversample in high risk and low-to-medium risk areas by selecting more of those EAs compared to the population living there. Finally, all the selected households were randomly drawn within each EA using satellite imagery.\n\nSampling weights were calculated to compensate for the oversampling in high-risk areas. When applying the sample weights, the dataset is representative at the city level.\n\nReferences: \n \nERMAN, A. E., TARIVERDI, M., OBOLENSKY, M. A. B., CHEN, X., VINCENT, R. C., MALGIOGLIO, S., & YOSHIDA, N. (2019). Wading out the storm: The role of poverty in exposure, vulnerability and resilience to floods in Dar Es Salaam. World Bank Policy Research Working Paper, (8976).","coll_mode":["Computer Assisted Personal Interview [capi]"],"research_instrument":"The survey questionnaire consists of 13 sections that were used to collect the survey data. See the attached questionnaire.","coll_situation":"The DPHS was conducted in two waves. The main survey was conducted in November and December 2017 using the original sample of 1058 selected households. Shortly after in April 2018, there was a significant flood event affecting Dar es Salaam. To evaluate the impacts of the flooding, a phone-based follow up survey was carried out in September 2018. In parallel, the original sample size was increased with 282 additional households that were sampled from high-risk and low-to-high risk areas to further increase precision of estimates regarding this population group. Interviews with additional households were carried out in-person.","act_min":"The World Bank","weight":"The weights are calculated to compensate for the oversampling in flood prone areas and provide city-wide representativeness.","cleaning_operations":"The following data editing was done for anonymization purpose: \n\u2022 Precise location data, such as GPS coordinates, were dropped\n\u2022 Personal information, such as name, citizenship and phone number were dropped\n\u2022 Information on from which region or country the respondent moved from before settling in current dwelling and where respondent was born was categorized into \u201cin Dar es Salaam\u201d and \u201coutside Dar es Salaam\u201d to protect privacy while preserving valuable data. District level information on origin was dropped. \n\u2022 Household size exceeding seven household members was categorized as \u201cabove 7 members\u201d \n\u2022 Household member information for 7th member and above was dropped to avoid reconstruction of the household size variable. \n\nFor more information on the anonymization process, see the Technical Document."},"analysis_info":{"response_rate":"In the 2018 follow up interview, 419 were reached and interviewed out of the 1058 households in the original sample."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Confidentiality has been ensured through a process of anonymization (see Technical Document for details).","required":"","form_no":"","uri":""}],"cit_req":"The World Bank. Disaster-Poverty Household Survey (DPHS), Dar Es Salaam, Tanzania 2018. Ref: TZA_2017-2018_DPHS_v01_M. Dataset downloaded from microdata.worldbank.org  on [date].","conditions":"Data is accessible for licensed users only and further dissemination of data is not allowed.","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."}}},"schematype":"survey","tags":[{"tag":"DOI"}]}