IDEAS home Printed from https://ideas.repec.org/a/spr/soinre/v158y2021i1d10.1007_s11205-021-02699-3.html
   My bibliography  Save this article

COVID Health Structure Index: The Vulnerability of Brazilian Microregions

Author

Listed:
  • Diogo Ferraz

    (University of Hohenheim
    Federal University of Ouro Preto (UFOP)
    São Paulo State University (UNESP), Núcleo Residencial Presidente Geisel)

  • Enzo Barberio Mariano

    (São Paulo State University (UNESP), Núcleo Residencial Presidente Geisel)

  • Patricia Regina Manzine

    (Federal University of São Carlos (UFSCar))

  • Herick Fernando Moralles

    (Federal University of São Carlos (UFSCar))

  • Paulo César Morceiro

    (DST/NRF South African Chair in Industrial Development, College of Business and Economics, University of Johannesburg)

  • Bruno Guimarães Torres

    (Fluminense Federal University (UFF))

  • Mariana Rodrigues Almeida

    (Federal University of Rio Grande do Norte (UFRN))

  • João Carlos Soares de Mello

    (Fluminense Federal University (UFF))

  • Daisy Aparecida do Nascimento Rebelatto

    (University of São Paulo (EESC/USP))

Abstract

Many developing countries have highly unequal health systems across their regions. The pandemic of COVID-19 brought an additional challenge, as hospital structures equipped with doctors, intensive care units and respirators are not available to a sufficient extent in all regions. Using Data Envelopment Analysis, we create a COVID Index to verify whether the hospital structures in 543 Brazilian microregions are adequate to deal with COVID-19 and to verify whether public policies were implemented in the right direction. The results indicate that hospital structures in the poorest microregions were the most vulnerable, although the peak of COVID-19 occurred in the richest microregions (Sao Paulo). The Southeast states could relocate hospital resources or even patients between their regions. The relocation was not possible in many states in the Northeast, as the health system poorly assisted the interior of these states. These findings reveal that the heterogeneity of microregions’ hospital structures follows the patterns of socioeconomic inequalities. We conclude that it is easier for the wealthier regions to reallocate hospital resources internally than for the poorest regions. By using the COVID Index, policymakers and hospital managers have straightforward information to decide which regions must receive new investments and reallocate underutilized resources.

Suggested Citation

  • Diogo Ferraz & Enzo Barberio Mariano & Patricia Regina Manzine & Herick Fernando Moralles & Paulo César Morceiro & Bruno Guimarães Torres & Mariana Rodrigues Almeida & João Carlos Soares de Mello & Da, 2021. "COVID Health Structure Index: The Vulnerability of Brazilian Microregions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 158(1), pages 197-215, November.
  • Handle: RePEc:spr:soinre:v:158:y:2021:i:1:d:10.1007_s11205-021-02699-3
    DOI: 10.1007/s11205-021-02699-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11205-021-02699-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11205-021-02699-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kris Siddharthan & Melissa Ahern & Robert Rosenman, 2000. "Data Envelopment Analysis to determine efficiencies of health maintenance organizations," Health Care Management Science, Springer, vol. 3(1), pages 23-29, January.
    2. Peng Zhou & Xing-Lou Yang & Xian-Guang Wang & Ben Hu & Lei Zhang & Wei Zhang & Hao-Rui Si & Yan Zhu & Bei Li & Chao-Lin Huang & Hui-Dong Chen & Jing Chen & Yun Luo & Hua Guo & Ren-Di Jiang & Mei-Qin L, 2020. "Addendum: A pneumonia outbreak associated with a new coronavirus of probable bat origin," Nature, Nature, vol. 588(7836), pages 6-6, December.
    3. Babak Daneshvar Rouyendegh & Asil Oztekin & Joseph Ekong & Ali Dag, 2019. "Measuring the efficiency of hospitals: a fully-ranking DEA–FAHP approach," Annals of Operations Research, Springer, vol. 278(1), pages 361-378, July.
    4. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    5. Peng Zhou & Xing-Lou Yang & Xian-Guang Wang & Ben Hu & Lei Zhang & Wei Zhang & Hao-Rui Si & Yan Zhu & Bei Li & Chao-Lin Huang & Hui-Dong Chen & Jing Chen & Yun Luo & Hua Guo & Ren-Di Jiang & Mei-Qin L, 2020. "A pneumonia outbreak associated with a new coronavirus of probable bat origin," Nature, Nature, vol. 579(7798), pages 270-273, March.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    8. Diogo Ferraz & Enzo B. Mariano & Daisy Rebelatto & Dominik Hartmann, 2020. "Linking Human Development and the Financial Responsibility of Regions: Combined Index Proposals Using Methods from Data Envelopment Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(2), pages 439-478, July.
    9. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    10. D K Despotis, 2005. "A reassessment of the human development index via data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 969-980, August.
    11. Enzo Barberio Mariano & Daisy Aparecida do Nascimento Rebelatto, 2014. "Transformation of wealth produced into quality of life: analysis of the social efficiency of nation-states with the DEA’s triple index approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(11), pages 1664-1681, November.
    12. Flávio C Coelho & Raquel M Lana & Oswaldo G Cruz & Daniel A M Villela & Leonardo S Bastos & Ana Pastore y Piontti & Jessica T Davis & Alessandro Vespignani & Claudia T Codeço & Marcelo F C Gomes, 2020. "Assessing the spread of COVID-19 in Brazil: Mobility, morbidity and social vulnerability," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-11, September.
    13. Patrícia Varela & Gilberto de Martins & Luiz Fávero, 2010. "Production efficiency and financing of public health: an analysis of small municipalities in the state of São Paulo — Brazil," Health Care Management Science, Springer, vol. 13(2), pages 112-123, June.
    14. Cláudia Araújo & Carlos Barros & Peter Wanke, 2014. "Efficiency determinants and capacity issues in Brazilian for-profit hospitals," Health Care Management Science, Springer, vol. 17(2), pages 126-138, June.
    15. Laura Botega & Mônica Viegas Andrade & Gilvan Ramalho Guedes, 2020. "Brazilian hospitals’ performance: an assessment of the unified health system (SUS)," Health Care Management Science, Springer, vol. 23(3), pages 443-452, September.
    16. Habib Zare & Madjid Tavana & Abbas Mardani & Sepideh Masoudian & Mahyar Kamali Saraji, 2019. "A hybrid data envelopment analysis and game theory model for performance measurement in healthcare," Health Care Management Science, Springer, vol. 22(3), pages 475-488, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ben Lahouel, Béchir & Ben Zaied, Younes & Taleb, Lotfi & Kočišová, Kristína, 2022. "The assessment of socio-environmental performance change: A Benefit of the Doubt indicator based on Directional Distance Function and Malmquist productivity index," Finance Research Letters, Elsevier, vol. 49(C).
    2. Lorena Androutsou & Michail Kokkinos & Dimitra Latsou & Mary Geitona, 2022. "Assessing the Efficiency and Productivity of the Hospital Clinics on the Island of Rhodes during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(23), pages 1-12, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rita Matos & Diogo Ferreira & Maria Isabel Pedro, 2021. "Economic Analysis of Portuguese Public Hospitals Through the Construction of Quality, Efficiency, Access, and Financial Related Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(1), pages 361-392, August.
    2. Diogo Ferraz & Enzo B. Mariano & Daisy Rebelatto & Dominik Hartmann, 2020. "Linking Human Development and the Financial Responsibility of Regions: Combined Index Proposals Using Methods from Data Envelopment Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(2), pages 439-478, July.
    3. Mansour Zarrin & Jan Schoenfelder & Jens O. Brunner, 2022. "Homogeneity and Best Practice Analyses in Hospital Performance Management: An Analytical Framework," Health Care Management Science, Springer, vol. 25(3), pages 406-425, September.
    4. Mariano, Enzo Barberio & Sobreiro, Vinicius Amorim & Rebelatto, Daisy Aparecida do Nascimento, 2015. "Human development and data envelopment analysis: A structured literature review," Omega, Elsevier, vol. 54(C), pages 33-49.
    5. Enzo Barberio Mariano & Diogo Ferraz & Simone Cristina Oliveira Gobbo, 2021. "The Human Development Index with Multiple Data Envelopment Analysis Approaches: A Comparative Evaluation Using Social Network Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 443-500, September.
    6. Gobbo, Simone Cristina de Oliveira & Mariano, Enzo Barberio & Gobbo Jr., José Alcides, 2021. "Combining social network and data envelopment analysis: A proposal for a Selection Employment Contracts Effectiveness index in healthcare network applications," Omega, Elsevier, vol. 103(C).
    7. Zhu, Qingyuan & Li, Xingchen & Li, Feng & Wu, Jie & Zhou, Dequn, 2020. "Energy and environmental efficiency of China's transportation sectors under the constraints of energy consumption and environmental pollutions," Energy Economics, Elsevier, vol. 89(C).
    8. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    9. Tingting Liu & Zichen Zheng & Yuneng Du, 2021. "Evaluation on regional science and technology resources allocation in China based on the zero sum gains data envelopment analysis," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1729-1737, August.
    10. Comim, Flavio & Hirai, Tadashi, 2022. "Sustainability and Human Development Indicators: A Poset Analysis," Ecological Economics, Elsevier, vol. 198(C).
    11. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    12. Jesús Peiró-Palomino & Andrés J. Picazo-Tadeo, 2018. "OECD: One or Many? Ranking Countries with a Composite Well-Being Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(3), pages 847-869, October.
    13. Annalina Sarra & Eugenia Nissi, 2020. "A Spatial Composite Indicator for Human and Ecosystem Well-Being in the Italian Urban Areas," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(2), pages 353-377, April.
    14. Pourmahmoud, Jafar & Bagheri, Narges, 2023. "Uncertain Malmquist productivity index: An application to evaluate healthcare systems during COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    15. Matthias Klumpp & Dominic Loske & Silvio Bicciato, 2022. "COVID-19 health policy evaluation: integrating health and economic perspectives with a data envelopment analysis approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(8), pages 1263-1285, November.
    16. Costa, Naijela Silveira da & Ferraz, Diogo & Moralles, Herick Fernando & Nascimento, Daisy do, 2022. "Economic complexity and human development: comparing standard and slack-based data envelopment analysis models," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), August.
    17. Sepideh Kaffash & Marianna Marra, 2017. "Data envelopment analysis in financial services: a citations network analysis of banks, insurance companies and money market funds," Annals of Operations Research, Springer, vol. 253(1), pages 307-344, June.
    18. Singh, Sanjeet, 2016. "Evaluation of world’s largest social welfare scheme: An assessment using non-parametric approach," Evaluation and Program Planning, Elsevier, vol. 57(C), pages 16-29.
    19. Eugenia Nissi & Annalina Sarra, 2018. "A Measure of Well-Being Across the Italian Urban Areas: An Integrated DEA-Entropy Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 1183-1209, April.
    20. Nikolaos Zirogiannis & Kerry Krutilla & Yorghos Tripodis & Kathryn Fledderman, 2019. "Human Development Over Time: An Empirical Comparison of a Dynamic Index and the Standard HDI," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 773-798, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:soinre:v:158:y:2021:i:1:d:10.1007_s11205-021-02699-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.