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- Publisher Website: 10.1007/s11205-022-02922-9
- Scopus: eid_2-s2.0-85128839483
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Article: Assessing Response Readiness to Health Emergencies: A Spatial Evaluation of Health and Socio-Economic Justice in Pakistan
Title | Assessing Response Readiness to Health Emergencies: A Spatial Evaluation of Health and Socio-Economic Justice in Pakistan |
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Authors | |
Keywords | Community health resilience COVID-19 Geographic information systems Health policy Multivariate spatial clustering |
Issue Date | 2024 |
Citation | Social Indicators Research, 2024, v. 173, n. 1, p. 169-199 How to Cite? |
Abstract | COVID19 pandemic has put the global health emergency response to the test. Providing health and socio-economic justice across communities/regions helps in resilient response. In this study, a Geographic Information Systems-based framework is proposed and demonstrated in the context of public health-related hazards and pandemic response, such as in the face of COVID19. Indicators relevant to health system (HS) and socio-economic conditions (SC) are utilized to compute a response readiness index (RRI). The frequency histograms and the Analysis of Variance approaches are applied to analyze the distribution of response readiness. We further integrate spatial distributional models to explore the geographically-varying patterns of response readiness pinpointing the priority intervention areas in the context of cross-regional health and socio-economic justice. The framework’s application is demonstrated using Pakistan’s most developed and populous province, namely Punjab (districts scale, n = 36), as a case study. The results show that ~ 45% indicators achieve below-average scores (value < 0.61) including four from HS and five from SC. The findings ascertain maximum districts lack health facilities, hospital beds, and health insurance from HS and more than 50% lack communication means and literacy-rates, which are essential in times of emergencies. Our cross-regional assessment shows a north–south spatial heterogeneity with southern Punjab being the most vulnerable to COVID-like situations. Dera Ghazi Khan and Muzaffargarh are identified as the statistically significant hotspots of response incompetency (95% confidence), which is critical. This study has policy implications in the context of decision-making, resource allocation, and strategy formulation on health emergency response (i.e., COVID19) to improve community health resilience. |
Persistent Identifier | http://hdl.handle.net/10722/349716 |
ISSN | 2023 Impact Factor: 2.8 2023 SCImago Journal Rankings: 0.965 |
DC Field | Value | Language |
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dc.contributor.author | Sajjad, Muhammad | - |
dc.contributor.author | Raza, Syed Hassan | - |
dc.contributor.author | Shah, Asad Abbas | - |
dc.date.accessioned | 2024-10-17T07:00:20Z | - |
dc.date.available | 2024-10-17T07:00:20Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Social Indicators Research, 2024, v. 173, n. 1, p. 169-199 | - |
dc.identifier.issn | 0303-8300 | - |
dc.identifier.uri | http://hdl.handle.net/10722/349716 | - |
dc.description.abstract | COVID19 pandemic has put the global health emergency response to the test. Providing health and socio-economic justice across communities/regions helps in resilient response. In this study, a Geographic Information Systems-based framework is proposed and demonstrated in the context of public health-related hazards and pandemic response, such as in the face of COVID19. Indicators relevant to health system (HS) and socio-economic conditions (SC) are utilized to compute a response readiness index (RRI). The frequency histograms and the Analysis of Variance approaches are applied to analyze the distribution of response readiness. We further integrate spatial distributional models to explore the geographically-varying patterns of response readiness pinpointing the priority intervention areas in the context of cross-regional health and socio-economic justice. The framework’s application is demonstrated using Pakistan’s most developed and populous province, namely Punjab (districts scale, n = 36), as a case study. The results show that ~ 45% indicators achieve below-average scores (value < 0.61) including four from HS and five from SC. The findings ascertain maximum districts lack health facilities, hospital beds, and health insurance from HS and more than 50% lack communication means and literacy-rates, which are essential in times of emergencies. Our cross-regional assessment shows a north–south spatial heterogeneity with southern Punjab being the most vulnerable to COVID-like situations. Dera Ghazi Khan and Muzaffargarh are identified as the statistically significant hotspots of response incompetency (95% confidence), which is critical. This study has policy implications in the context of decision-making, resource allocation, and strategy formulation on health emergency response (i.e., COVID19) to improve community health resilience. | - |
dc.language | eng | - |
dc.relation.ispartof | Social Indicators Research | - |
dc.subject | Community health resilience | - |
dc.subject | COVID-19 | - |
dc.subject | Geographic information systems | - |
dc.subject | Health policy | - |
dc.subject | Multivariate spatial clustering | - |
dc.title | Assessing Response Readiness to Health Emergencies: A Spatial Evaluation of Health and Socio-Economic Justice in Pakistan | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s11205-022-02922-9 | - |
dc.identifier.scopus | eid_2-s2.0-85128839483 | - |
dc.identifier.volume | 173 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 169 | - |
dc.identifier.epage | 199 | - |
dc.identifier.eissn | 1573-0921 | - |