IDEAS home Printed from https://ideas.repec.org/a/bjc/journl/v11y2024i15p730-738.html
   My bibliography  Save this article

Spatial Regression Analysis on Factors Influencing Number of HIV/AIDS Cases in Indonesia

Author

Listed:
  • Herlina Hanum

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Sriwijaya University, Kampus Inderalaya Km 32 Ogan Ilir 30662, Indonesia)

  • Yuli Andriani

    (Department of Mathematics, Faculty of Mathematics and Natural Sciences, Sriwijaya University, Kampus Inderalaya Km 32 Ogan Ilir 30662, Indonesia)

  • Risma Dwi Yunita Yana

    (Department of Soil Science, Faculty of Agriculture, Sriwijaya University, Kampus Inderalaya Km 32 Ogan Ilir 30662, Indonesia)

  • Dwi Setyawan

    (Department of Soil Science, Faculty of Agriculture, Sriwijaya University, Kampus Inderalaya Km 32 Ogan Ilir 30662, Indonesia)

Abstract

HIV/AIDS cases from one region are thought to be influenced by the surrounding areas. Analysis of factors influencing HIV/AIDS cases can be done through classical Linear Regression. However, Spatial Regression analysis is a more appropriate method to use if it takes location into account. The purpose of this study was to conduct a spatial regression analysis on HIV/AIDS cases in Indonesia in 2021. Spatial dependency testing and selection of spatial regression models were carried out using Moran’s I and Lagrange Multiplier (LM) tests. The Moran’s index value obtained0

Suggested Citation

  • Herlina Hanum & Yuli Andriani & Risma Dwi Yunita Yana & Dwi Setyawan, 2024. "Spatial Regression Analysis on Factors Influencing Number of HIV/AIDS Cases in Indonesia," International Journal of Research and Scientific Innovation, International Journal of Research and Scientific Innovation (IJRSI), vol. 11(15), pages 730-738, November.
    • Handle: RePEc:bjc:journl:v:11:y:2024:i:15:p:730-738
    as

    Download full text from publisher

    File URL: https://www.rsisinternational.org/journals/ijrsi/digital-library/volume-11-issue-15/730-738.pdf
    Download Restriction: no
    File URL: https://rsisinternational.org/journals/ijrsi/articles/spatial-regression-analysis-on-factors-influencing-number-of-hiv-aids-cases-in-indonesia/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lyndsay Shand & Bo Li & Trevor Park & Dolores Albarracín, 2018. "Spatially varying auto‐regressive models for prediction of new human immunodeficiency virus diagnoses," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(4), pages 1003-1022, August.
    2. Nushrat Nazia & Zahid Ahmad Butt & Melanie Lyn Bedard & Wang-Choi Tang & Hibah Sehar & Jane Law, 2022. "Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review," IJERPH, MDPI, vol. 19(14), pages 1-28, July.
    Full references (including those not matched with items on IDEAS)

    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. X. Angela Yao & Andrew Crooks & Bin Jiang & Jukka Krisp & Xintao Liu & Haosheng Huang, 2023. "An overview of urban analytical approaches to combating the Covid-19 pandemic," Environment and Planning B, , vol. 50(5), pages 1133-1143, June.
    2. Conceição Leal & Leonel Morgado & Teresa A. Oliveira, 2023. "Mathematical and Statistical Modelling for Assessing COVID-19 Superspreader Contagion: Analysis of Geographical Heterogeneous Impacts from Public Events," Mathematics, MDPI, vol. 11(5), pages 1-18, February.
    3. Pavlov, Konstantin & Timiryanova, Venera & Yusupov, Kasim & Krasnoselskaya, Dina, 2022. "Анализ волн распространения Covid-19 в России [Analysis of Covid-19 wave distribution in Russia]," MPRA Paper 114637, University Library of Munich, Germany.
    4. Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
    5. Ming Sun & Tiange Xu, 2024. "Identification and Management of Epidemic Hazard Areas for Urban Sustainability: A Case Study of Tongzhou, China," Sustainability, MDPI, vol. 16(18), pages 1-25, September.
    6. I Gede Nyoman Mindra Jaya & Farah Kristiani & Yudhie Andriyana & Anna Chadidjah, 2024. "Sensitivity Analysis on Hyperprior Distribution of the Variance Components of Hierarchical Bayesian Spatiotemporal Disease Mapping," Mathematics, MDPI, vol. 12(3), pages 1-16, January.
    7. Peter Congdon, 2022. "A Model for Highly Fluctuating Spatio-Temporal Infection Data, with Applications to the COVID Epidemic," IJERPH, MDPI, vol. 19(11), pages 1-17, May.

    More about this item

    Statistics

    Access and download statistics

    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:bjc:journl:v:11:y:2024:i:15:p:730-738. 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: Dr. Renu Malsaria (email available below). General contact details of provider: https://rsisinternational.org/journals/ijrsi/ .

    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.