View in EDS PDF Full Text

Mapping Child Leprosy Cases and Its Factors Associated in Indonesia Using Geographically Weighted Poisson Regression Model.

Saved in:
Bibliographic Details
Title: Mapping Child Leprosy Cases and Its Factors Associated in Indonesia Using Geographically Weighted Poisson Regression Model.
Authors: Suyitno1 suyitno@fmipa.unmul.ac.id, Darnah2 darnahfmipaunmul@gmail.com, Hayati, Memi Nor3 meminorhayati@fmipa.unmul.ac.id, Prangga, Surya2 suryapranggae@fmipa.unmul.ac.id, Dani, Andrea Tri Rian3 andreatririandani@fmipa.unmul.ac.id, Mahmuda, Siti1 sitimahmuda@fmipa.unmul.ac.id, Tumilaar, Rinancy1 rinancytumilaar@gmail.com, Nugraha, Pratama Yuly2 pratamayn@fmipa.unmul.ac.id, Aulia, Misbah Nur3 misbahnuraulia3403@gmail.com
Source: IAENG International Journal of Applied Mathematics. May2026, Vol. 56 Issue 5, p1654-1667. 14p.
Subjects: Hansen's disease, Geographic spatial analysis, Health policy, Indonesians, Population density, Poverty, Vaccination coverage
Geographic Terms: Indonesia
Abstract: This study applies Geographically Weighted Poisson Regression (GWPR) to analyze child leprosy cases in Indonesia, aiming to identify spatial variations and influencing factors. Leprosy remains a significant health issue, particularly for children, causing severe disabilities. The GWPR model accounts for spatial heterogeneity, offering a localized approach to understanding leprosy trends. Key findings reveal that global factors like poverty rates and local factors such as population density and immunization coverage are critical in influencing leprosy prevalence. The model provides more accurate, regionspecific insights into leprosy distribution, highlighting areas needing targeted interventions. This study emphasizes the importance of tailored health policies to address regional disparities in leprosy cases and improve recovery rates. The methodology includes Poisson regression, maximum likelihood estimation, and spatial heterogeneity testing. Results are used to recommend policy changes to prevent leprosy spread and improve recovery, focusing on children. This research provides valuable guidance for the Indonesian government in developing practical, region-specific strategies to combat leprosy and enhance child health outcomes. [ABSTRACT FROM AUTHOR]
Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Links:
  – Type: pdflink
Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 193517526
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Mapping Child Leprosy Cases and Its Factors Associated in Indonesia Using Geographically Weighted Poisson Regression Model.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Suyitno%22">Suyitno</searchLink><relatesTo>1</relatesTo><i> suyitno@fmipa.unmul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Darnah%22">Darnah</searchLink><relatesTo>2</relatesTo><i> darnahfmipaunmul@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Hayati%2C+Memi+Nor%22">Hayati, Memi Nor</searchLink><relatesTo>3</relatesTo><i> meminorhayati@fmipa.unmul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Prangga%2C+Surya%22">Prangga, Surya</searchLink><relatesTo>2</relatesTo><i> suryapranggae@fmipa.unmul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Dani%2C+Andrea+Tri+Rian%22">Dani, Andrea Tri Rian</searchLink><relatesTo>3</relatesTo><i> andreatririandani@fmipa.unmul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Mahmuda%2C+Siti%22">Mahmuda, Siti</searchLink><relatesTo>1</relatesTo><i> sitimahmuda@fmipa.unmul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Tumilaar%2C+Rinancy%22">Tumilaar, Rinancy</searchLink><relatesTo>1</relatesTo><i> rinancytumilaar@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Nugraha%2C+Pratama+Yuly%22">Nugraha, Pratama Yuly</searchLink><relatesTo>2</relatesTo><i> pratamayn@fmipa.unmul.ac.id</i><br /><searchLink fieldCode="AR" term="%22Aulia%2C+Misbah+Nur%22">Aulia, Misbah Nur</searchLink><relatesTo>3</relatesTo><i> misbahnuraulia3403@gmail.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Applied+Mathematics%22">IAENG International Journal of Applied Mathematics</searchLink>. May2026, Vol. 56 Issue 5, p1654-1667. 14p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Hansen's+disease%22">Hansen's disease</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+spatial+analysis%22">Geographic spatial analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Health+policy%22">Health policy</searchLink><br /><searchLink fieldCode="DE" term="%22Indonesians%22">Indonesians</searchLink><br /><searchLink fieldCode="DE" term="%22Population+density%22">Population density</searchLink><br /><searchLink fieldCode="DE" term="%22Poverty%22">Poverty</searchLink><br /><searchLink fieldCode="DE" term="%22Vaccination+coverage%22">Vaccination coverage</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Indonesia%22">Indonesia</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study applies Geographically Weighted Poisson Regression (GWPR) to analyze child leprosy cases in Indonesia, aiming to identify spatial variations and influencing factors. Leprosy remains a significant health issue, particularly for children, causing severe disabilities. The GWPR model accounts for spatial heterogeneity, offering a localized approach to understanding leprosy trends. Key findings reveal that global factors like poverty rates and local factors such as population density and immunization coverage are critical in influencing leprosy prevalence. The model provides more accurate, regionspecific insights into leprosy distribution, highlighting areas needing targeted interventions. This study emphasizes the importance of tailored health policies to address regional disparities in leprosy cases and improve recovery rates. The methodology includes Poisson regression, maximum likelihood estimation, and spatial heterogeneity testing. Results are used to recommend policy changes to prevent leprosy spread and improve recovery, focusing on children. This research provides valuable guidance for the Indonesian government in developing practical, region-specific strategies to combat leprosy and enhance child health outcomes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=193517526
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 1654
    Subjects:
      – SubjectFull: Hansen's disease
        Type: general
      – SubjectFull: Geographic spatial analysis
        Type: general
      – SubjectFull: Health policy
        Type: general
      – SubjectFull: Indonesians
        Type: general
      – SubjectFull: Population density
        Type: general
      – SubjectFull: Poverty
        Type: general
      – SubjectFull: Vaccination coverage
        Type: general
      – SubjectFull: Indonesia
        Type: general
    Titles:
      – TitleFull: Mapping Child Leprosy Cases and Its Factors Associated in Indonesia Using Geographically Weighted Poisson Regression Model.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Suyitno
      – PersonEntity:
          Name:
            NameFull: Darnah
      – PersonEntity:
          Name:
            NameFull: Hayati, Memi Nor
      – PersonEntity:
          Name:
            NameFull: Prangga, Surya
      – PersonEntity:
          Name:
            NameFull: Dani, Andrea Tri Rian
      – PersonEntity:
          Name:
            NameFull: Mahmuda, Siti
      – PersonEntity:
          Name:
            NameFull: Tumilaar, Rinancy
      – PersonEntity:
          Name:
            NameFull: Nugraha, Pratama Yuly
      – PersonEntity:
          Name:
            NameFull: Aulia, Misbah Nur
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 19929978
          Numbering:
            – Type: volume
              Value: 56
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: IAENG International Journal of Applied Mathematics
              Type: main
ResultId 1