Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging
Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the c...
Gespeichert in:
Veröffentlicht in: | Journal of physics. Conference series 2018-03, Vol.971 (1), p.12010 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 1 |
container_start_page | 12010 |
container_title | Journal of physics. Conference series |
container_volume | 971 |
creator | Prasetiyowati, S S Sibaroni, Y |
description | Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time. |
doi_str_mv | 10.1088/1742-6596/971/1/012010 |
format | Article |
fullrecord | <record><control><sourceid>proquest_iop_j</sourceid><recordid>TN_cdi_proquest_journals_2572062466</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2572062466</sourcerecordid><originalsourceid>FETCH-LOGICAL-c432t-a7c3bbee00f09e87ec0e13e2d3b2c156bbd7e1db36609cb00c1a67bf861bcb083</originalsourceid><addsrcrecordid>eNqFkE9LwzAYh4MoOKdfQQJeFKxN0i1tj7I5NxjoQfEY8uftzJxpTVrFb29KZR7NJXnJ8_slPAidU3JDSVGkNJ-whE9LnpY5TWlKKCOUHKDR_uJwfy6KY3QSwpaQLK58hMKjB2N1a2uH6wrPlwtsbAAZAIfGgzTWbXAj2xa8C7gL_WjdJ_gIRLCVTkPAX2A3ry0YfLmav1xd49rHnPTfWDqDO2d7Xu7wm7ebWHCKjiq5C3D2u4_R8-LuabZM1g_3q9ntOtGTjLWJzHWmFAAhFSmhyEEToBkwkymm6ZQrZXKgRmWck1IrQjSVPFdVwamKY5GN0cXQ2_j6o4PQim3deRefFGyaM8LZhPNI8YHSvg7BQyUab9_j5wUlohcsenei9yiiYEHFIDgG2RC0dfPX_E_oBxUjfpo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2572062466</pqid></control><display><type>article</type><title>Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging</title><source>Institute of Physics Open Access Journal Titles</source><source>EZB-FREE-00999 freely available EZB journals</source><source>IOPscience extra</source><source>Alma/SFX Local Collection</source><source>Free Full-Text Journals in Chemistry</source><creator>Prasetiyowati, S S ; Sibaroni, Y</creator><creatorcontrib>Prasetiyowati, S S ; Sibaroni, Y</creatorcontrib><description>Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time.</description><identifier>ISSN: 1742-6588</identifier><identifier>EISSN: 1742-6596</identifier><identifier>DOI: 10.1088/1742-6596/971/1/012010</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Dengue fever ; Dispersion ; Empirical analysis ; Epidemics ; Physics ; Social factors ; Viral diseases</subject><ispartof>Journal of physics. Conference series, 2018-03, Vol.971 (1), p.12010</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>2018. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c432t-a7c3bbee00f09e87ec0e13e2d3b2c156bbd7e1db36609cb00c1a67bf861bcb083</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1742-6596/971/1/012010/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,780,784,27924,27925,38868,38890,53840,53867</link.rule.ids></links><search><creatorcontrib>Prasetiyowati, S S</creatorcontrib><creatorcontrib>Sibaroni, Y</creatorcontrib><title>Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging</title><title>Journal of physics. Conference series</title><addtitle>J. Phys.: Conf. Ser</addtitle><description>Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time.</description><subject>Dengue fever</subject><subject>Dispersion</subject><subject>Empirical analysis</subject><subject>Epidemics</subject><subject>Physics</subject><subject>Social factors</subject><subject>Viral diseases</subject><issn>1742-6588</issn><issn>1742-6596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqFkE9LwzAYh4MoOKdfQQJeFKxN0i1tj7I5NxjoQfEY8uftzJxpTVrFb29KZR7NJXnJ8_slPAidU3JDSVGkNJ-whE9LnpY5TWlKKCOUHKDR_uJwfy6KY3QSwpaQLK58hMKjB2N1a2uH6wrPlwtsbAAZAIfGgzTWbXAj2xa8C7gL_WjdJ_gIRLCVTkPAX2A3ry0YfLmav1xd49rHnPTfWDqDO2d7Xu7wm7ebWHCKjiq5C3D2u4_R8-LuabZM1g_3q9ntOtGTjLWJzHWmFAAhFSmhyEEToBkwkymm6ZQrZXKgRmWck1IrQjSVPFdVwamKY5GN0cXQ2_j6o4PQim3deRefFGyaM8LZhPNI8YHSvg7BQyUab9_j5wUlohcsenei9yiiYEHFIDgG2RC0dfPX_E_oBxUjfpo</recordid><startdate>20180301</startdate><enddate>20180301</enddate><creator>Prasetiyowati, S S</creator><creator>Sibaroni, Y</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20180301</creationdate><title>Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging</title><author>Prasetiyowati, S S ; Sibaroni, Y</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c432t-a7c3bbee00f09e87ec0e13e2d3b2c156bbd7e1db36609cb00c1a67bf861bcb083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Dengue fever</topic><topic>Dispersion</topic><topic>Empirical analysis</topic><topic>Epidemics</topic><topic>Physics</topic><topic>Social factors</topic><topic>Viral diseases</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Prasetiyowati, S S</creatorcontrib><creatorcontrib>Sibaroni, Y</creatorcontrib><collection>Institute of Physics Open Access Journal Titles</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Journal of physics. Conference series</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Prasetiyowati, S S</au><au>Sibaroni, Y</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging</atitle><jtitle>Journal of physics. Conference series</jtitle><addtitle>J. Phys.: Conf. Ser</addtitle><date>2018-03-01</date><risdate>2018</risdate><volume>971</volume><issue>1</issue><spage>12010</spage><pages>12010-</pages><issn>1742-6588</issn><eissn>1742-6596</eissn><abstract>Dengue hemorrhagic disease, is a disease caused by the Dengue virus of the Flavivirus genus Flaviviridae family. Indonesia is the country with the highest case of dengue in Southeast Asia. In addition to mosquitoes as vectors and humans as hosts, other environmental and social factors are also the cause of widespread dengue fever. To prevent the occurrence of the epidemic of the disease, fast and accurate action is required. Rapid and accurate action can be taken, if there is appropriate information support on the occurrence of the epidemic. Therefore, a complete and accurate information on the spread pattern of endemic areas is necessary, so that precautions can be done as early as possible. The information on dispersal patterns can be obtained by various methods, which are based on empirical and theoretical considerations. One of the methods used is based on the estimated number of infected patients in a region based on spatial and time. The first step of this research is conducted by predicting the number of DHF patients in 2016 until 2018 based on 2010 to 2015 data using GSTAR (1, 1). In the second phase, the distribution pattern prediction of dengue disease area is conducted. Furthermore, based on the characteristics of DHF epidemic trends, i.e. down, stable or rising, the analysis of distribution patterns of dengue fever distribution areas with IDW and Kriging (ordinary and universal Kriging) were conducted in this study. The difference between IDW and Kriging, is the initial process that underlies the prediction process. Based on the experimental results, it is known that the dispersion pattern of epidemic areas of dengue disease with IDW and Ordinary Kriging is similar in the period of time.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1742-6596/971/1/012010</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1742-6588 |
ispartof | Journal of physics. Conference series, 2018-03, Vol.971 (1), p.12010 |
issn | 1742-6588 1742-6596 |
language | eng |
recordid | cdi_proquest_journals_2572062466 |
source | Institute of Physics Open Access Journal Titles; EZB-FREE-00999 freely available EZB journals; IOPscience extra; Alma/SFX Local Collection; Free Full-Text Journals in Chemistry |
subjects | Dengue fever Dispersion Empirical analysis Epidemics Physics Social factors Viral diseases |
title | Prediction of DHF disease spreading patterns using inverse distances weighted (IDW), ordinary and universal kriging |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T19%3A49%3A34IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_iop_j&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prediction%20of%20DHF%20disease%20spreading%20patterns%20using%20inverse%20distances%20weighted%20(IDW),%20ordinary%20and%20universal%20kriging&rft.jtitle=Journal%20of%20physics.%20Conference%20series&rft.au=Prasetiyowati,%20S%20S&rft.date=2018-03-01&rft.volume=971&rft.issue=1&rft.spage=12010&rft.pages=12010-&rft.issn=1742-6588&rft.eissn=1742-6596&rft_id=info:doi/10.1088/1742-6596/971/1/012010&rft_dat=%3Cproquest_iop_j%3E2572062466%3C/proquest_iop_j%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2572062466&rft_id=info:pmid/&rfr_iscdi=true |