Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan
The authors build a new database of highly spatially disaggregated indicators related to risk and resilience to the social and economic impacts of the COVID-19 pandemic in Uzbekistan. The outbreak disproportionately affects groups, the elderly, the...
| Main Authors: | , , , , |
|---|---|
| Format: | Report |
| Language: | English |
| Published: |
World Bank, Washington, DC
2020
|
| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/544151607576919401/Uzbekistan-Dynamically-Identifying-Community-Level-COVID-19-Impact-Risks http://hdl.handle.net/10986/34925 |
| id |
okr-10986-34925 |
|---|---|
| recordtype |
oai_dc |
| spelling |
okr-10986-349252022-02-17T18:27:23Z Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan Seitz, William Tulyakov, Eldor Khakimov, Obid Purevjav, Avralt-Od Muradova, Sevilya CORONAVIRUS COVID-19 PANDEMIC IMPACT POVERTY ECONOMIC SHOCK SMALL AREA POVERTY ESTIMATION ELDERLY PANEL SURVEY The authors build a new database of highly spatially disaggregated indicators related to risk and resilience to the social and economic impacts of the COVID-19 pandemic in Uzbekistan. The outbreak disproportionately affects groups, the elderly, the poor, those living in areas under lockdown, and families who rely on remittance income are all examples of groups that are especially vulnerable to effects of the crisis in Uzbekistan. The authors assemble indicators summarizing concentrations of these and other risk factors at the lowest administrative level in the country, neighborhood-sized units called mahallas. Local official administrative statistics (published for the first time in this study) are combined with monthly panel survey data from the ongoing Listening to the Citizens of Uzbekistan project to produce an overall risk index, which is decomposable by dimension or risk factor to inform targeted and issue-specific responses. We then demonstrate a process for updating key indicators (such as employment or remittance flows) on a monthly basis using linked survey data combined with small area estimation techniques. These neighborhood-level results are intended to improve resource allocation decisions and are particularly relevant in Uzbekistan where local representatives are responsible for implementing key social and economic programs to respond to the outbreak. 2020-12-14T20:15:00Z 2020-12-14T20:15:00Z 2020-12-09 Report http://documents.worldbank.org/curated/en/544151607576919401/Uzbekistan-Dynamically-Identifying-Community-Level-COVID-19-Impact-Risks http://hdl.handle.net/10986/34925 English CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Economic & Sector Work Economic & Sector Work :: Other Poverty Study Europe and Central Asia Uzbekistan |
| repository_type |
Digital Repository |
| institution_category |
Foreign Institution |
| institution |
Digital Repositories |
| building |
World Bank Open Knowledge Repository |
| collection |
World Bank |
| language |
English |
| topic |
CORONAVIRUS COVID-19 PANDEMIC IMPACT POVERTY ECONOMIC SHOCK SMALL AREA POVERTY ESTIMATION ELDERLY PANEL SURVEY |
| spellingShingle |
CORONAVIRUS COVID-19 PANDEMIC IMPACT POVERTY ECONOMIC SHOCK SMALL AREA POVERTY ESTIMATION ELDERLY PANEL SURVEY Seitz, William Tulyakov, Eldor Khakimov, Obid Purevjav, Avralt-Od Muradova, Sevilya Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan |
| geographic_facet |
Europe and Central Asia Uzbekistan |
| description |
The authors build a new database of
highly spatially disaggregated indicators related to risk
and resilience to the social and economic impacts of the
COVID-19 pandemic in Uzbekistan. The outbreak
disproportionately affects groups, the elderly, the poor,
those living in areas under lockdown, and families who rely
on remittance income are all examples of groups that are
especially vulnerable to effects of the crisis in
Uzbekistan. The authors assemble indicators summarizing
concentrations of these and other risk factors at the lowest
administrative level in the country, neighborhood-sized
units called mahallas. Local official administrative
statistics (published for the first time in this study) are
combined with monthly panel survey data from the ongoing
Listening to the Citizens of Uzbekistan project to produce
an overall risk index, which is decomposable by dimension or
risk factor to inform targeted and issue-specific responses.
We then demonstrate a process for updating key indicators
(such as employment or remittance flows) on a monthly basis
using linked survey data combined with small area estimation
techniques. These neighborhood-level results are intended to
improve resource allocation decisions and are particularly
relevant in Uzbekistan where local representatives are
responsible for implementing key social and economic
programs to respond to the outbreak. |
| format |
Report |
| author |
Seitz, William Tulyakov, Eldor Khakimov, Obid Purevjav, Avralt-Od Muradova, Sevilya |
| author_facet |
Seitz, William Tulyakov, Eldor Khakimov, Obid Purevjav, Avralt-Od Muradova, Sevilya |
| author_sort |
Seitz, William |
| title |
Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan |
| title_short |
Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan |
| title_full |
Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan |
| title_fullStr |
Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan |
| title_full_unstemmed |
Dynamically Identifying Community Level COVID-19 Impact Risks : Uzbekistan |
| title_sort |
dynamically identifying community level covid-19 impact risks : uzbekistan |
| publisher |
World Bank, Washington, DC |
| publishDate |
2020 |
| url |
http://documents.worldbank.org/curated/en/544151607576919401/Uzbekistan-Dynamically-Identifying-Community-Level-COVID-19-Impact-Risks http://hdl.handle.net/10986/34925 |
| _version_ |
1764481946001342464 |