Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study
This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022. In this ecological and exploratory study, the microregions were used as...
Gespeichert in:
| Veröffentlicht in: | Journal of infection in developing countries 2024-07, Vol.18 (7), p.1124-1131 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1131 |
|---|---|
| container_issue | 7 |
| container_start_page | 1124 |
| container_title | Journal of infection in developing countries |
| container_volume | 18 |
| creator | Costa, Simone Bn Miranda, Claudia do Sc De Souza, Bruna C Guimarães, Heloisa Maria M E S Faria, Camylle Mc Da S Campos, Pedro S Koury, Taiana Ma Da Paixão, José Gabriel M Leal, Alessandra L Carrera, Maria de Fátima P De Brito, Silvana R Gonçalves, Nelson V |
| description | This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022.
In this ecological and exploratory study, the microregions were used as spatial units because they are formed by contiguous municipalities with similar characteristics. The epidemiological, environmental, socioeconomic, and public health policy data employed were obtained from the official information systems at the Ministry of Health, National Institute for Space Research, and Brazilian Institute of Geography and Statistics. A fuzzy system was developed to identify risk factors for the disease, using Python programming language. The results were analyzed with the bivariate Global Moran spatial analysis technique.
It was observed that the Altamira microregion had the highest risk percentage for the disease, while Breves had the lowest, with significant differences in the relevance of its conditioning factors, mainly related to land use and cover patterns, in addition to demography and living conditions index, education and public health policies.
The fuzzy system associated with the geostatistical technique was satisfactory for identifying areas with health vulnerability gradients related to deforestation, pasture, poverty, illiteracy, and health services coverage, as its conditioning variables. Thus, it was demonstrated that deforestation was the main risk factor for the disease. The system can also be used in environmental and epidemiological surveillance. |
| doi_str_mv | 10.3855/jidc.18639 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3086379073</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3131764320</sourcerecordid><originalsourceid>FETCH-LOGICAL-c240t-f9d325aadc438d9155222827a7e2e503920e884d97592bb4dc41ffa59b4612b73</originalsourceid><addsrcrecordid>eNpdkd9KHDEUh4O0uLp64wNIoDciHc2fyWTinS5uWxAq2F4PZyaZNktmsiYz4KxP02fpi5l1bSm9OgfOxw_O70PohJILXgpxubK6uaBlwdUeOqBKsowVJXn3zz5DhzGuCBGKC7qPZlwRWUqlDtDzctxsJgy9xnENgwWXdnBTtBH7FjfjAL3xY8TO2Pizg97C9mR7fA_h9y_8MMBgPuKbABvrLPT4uoON769SCjaNd_6HbV4zNTZPa-cDDD5MOA6jno7Q-xZcNMdvc46-L2-_LT5nd18_fVlc32UNy8mQtUpzJgB0k_NSKyoEY6xkEqRhRhCuGDFlmWslhWJ1nSeOti0IVecFZbXkc3S2y10H_ziaOFSdjY1xbvdaxUnqTqZKeEI__Ieu_BhSIYminMoi54wk6nxHNcHHGExbrYPtIEwVJdVWSbVVUr0qSfDpW-RYd0b_Rf844C8HKIhw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3131764320</pqid></control><display><type>article</type><title>Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Costa, Simone Bn ; Miranda, Claudia do Sc ; De Souza, Bruna C ; Guimarães, Heloisa Maria M E S ; Faria, Camylle Mc ; Da S Campos, Pedro S ; Koury, Taiana Ma ; Da Paixão, José Gabriel M ; Leal, Alessandra L ; Carrera, Maria de Fátima P ; De Brito, Silvana R ; Gonçalves, Nelson V</creator><creatorcontrib>Costa, Simone Bn ; Miranda, Claudia do Sc ; De Souza, Bruna C ; Guimarães, Heloisa Maria M E S ; Faria, Camylle Mc ; Da S Campos, Pedro S ; Koury, Taiana Ma ; Da Paixão, José Gabriel M ; Leal, Alessandra L ; Carrera, Maria de Fátima P ; De Brito, Silvana R ; Gonçalves, Nelson V</creatorcontrib><description>This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022.
In this ecological and exploratory study, the microregions were used as spatial units because they are formed by contiguous municipalities with similar characteristics. The epidemiological, environmental, socioeconomic, and public health policy data employed were obtained from the official information systems at the Ministry of Health, National Institute for Space Research, and Brazilian Institute of Geography and Statistics. A fuzzy system was developed to identify risk factors for the disease, using Python programming language. The results were analyzed with the bivariate Global Moran spatial analysis technique.
It was observed that the Altamira microregion had the highest risk percentage for the disease, while Breves had the lowest, with significant differences in the relevance of its conditioning factors, mainly related to land use and cover patterns, in addition to demography and living conditions index, education and public health policies.
The fuzzy system associated with the geostatistical technique was satisfactory for identifying areas with health vulnerability gradients related to deforestation, pasture, poverty, illiteracy, and health services coverage, as its conditioning variables. Thus, it was demonstrated that deforestation was the main risk factor for the disease. The system can also be used in environmental and epidemiological surveillance.</description><identifier>ISSN: 1972-2680</identifier><identifier>ISSN: 2036-6590</identifier><identifier>EISSN: 1972-2680</identifier><identifier>DOI: 10.3855/jidc.18639</identifier><identifier>PMID: 39078799</identifier><language>eng</language><publisher>Italy: Journal of Infection in Developing Countries</publisher><subject>Brazil - epidemiology ; Deforestation ; Fuzzy Logic ; Humans ; Leishmaniasis, Cutaneous - epidemiology ; Parasitic diseases ; Public health ; Risk Factors ; Socioeconomic Factors ; Spatial Analysis</subject><ispartof>Journal of infection in developing countries, 2024-07, Vol.18 (7), p.1124-1131</ispartof><rights>Copyright (c) 2024 Simone BN Costa, Claudia do SC Miranda, Bruna C de Souza, Heloisa Maria M e S Guimarães, Camylle MC Faria, Pedro S da S Campos, Taiana MA Koury, José Gabriel M da Paixão, Alessandra L Leal, Maria de Fátima P Carrera, Silvana R de Brito, Nelson V Gonçalves.</rights><rights>2024. This work is published under https://creativecommons.org/licenses/by/4.0/ (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><orcidid>0000-0002-5095-9629 ; 0000-0001-7202-1423 ; 0009-0009-5112-2060 ; 0009-0001-5967-7708 ; 0000-0003-1513-8144 ; 0000-0001-8476-5569</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39078799$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Costa, Simone Bn</creatorcontrib><creatorcontrib>Miranda, Claudia do Sc</creatorcontrib><creatorcontrib>De Souza, Bruna C</creatorcontrib><creatorcontrib>Guimarães, Heloisa Maria M E S</creatorcontrib><creatorcontrib>Faria, Camylle Mc</creatorcontrib><creatorcontrib>Da S Campos, Pedro S</creatorcontrib><creatorcontrib>Koury, Taiana Ma</creatorcontrib><creatorcontrib>Da Paixão, José Gabriel M</creatorcontrib><creatorcontrib>Leal, Alessandra L</creatorcontrib><creatorcontrib>Carrera, Maria de Fátima P</creatorcontrib><creatorcontrib>De Brito, Silvana R</creatorcontrib><creatorcontrib>Gonçalves, Nelson V</creatorcontrib><title>Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study</title><title>Journal of infection in developing countries</title><addtitle>J Infect Dev Ctries</addtitle><description>This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022.
In this ecological and exploratory study, the microregions were used as spatial units because they are formed by contiguous municipalities with similar characteristics. The epidemiological, environmental, socioeconomic, and public health policy data employed were obtained from the official information systems at the Ministry of Health, National Institute for Space Research, and Brazilian Institute of Geography and Statistics. A fuzzy system was developed to identify risk factors for the disease, using Python programming language. The results were analyzed with the bivariate Global Moran spatial analysis technique.
It was observed that the Altamira microregion had the highest risk percentage for the disease, while Breves had the lowest, with significant differences in the relevance of its conditioning factors, mainly related to land use and cover patterns, in addition to demography and living conditions index, education and public health policies.
The fuzzy system associated with the geostatistical technique was satisfactory for identifying areas with health vulnerability gradients related to deforestation, pasture, poverty, illiteracy, and health services coverage, as its conditioning variables. Thus, it was demonstrated that deforestation was the main risk factor for the disease. The system can also be used in environmental and epidemiological surveillance.</description><subject>Brazil - epidemiology</subject><subject>Deforestation</subject><subject>Fuzzy Logic</subject><subject>Humans</subject><subject>Leishmaniasis, Cutaneous - epidemiology</subject><subject>Parasitic diseases</subject><subject>Public health</subject><subject>Risk Factors</subject><subject>Socioeconomic Factors</subject><subject>Spatial Analysis</subject><issn>1972-2680</issn><issn>2036-6590</issn><issn>1972-2680</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNpdkd9KHDEUh4O0uLp64wNIoDciHc2fyWTinS5uWxAq2F4PZyaZNktmsiYz4KxP02fpi5l1bSm9OgfOxw_O70PohJILXgpxubK6uaBlwdUeOqBKsowVJXn3zz5DhzGuCBGKC7qPZlwRWUqlDtDzctxsJgy9xnENgwWXdnBTtBH7FjfjAL3xY8TO2Pizg97C9mR7fA_h9y_8MMBgPuKbABvrLPT4uoON769SCjaNd_6HbV4zNTZPa-cDDD5MOA6jno7Q-xZcNMdvc46-L2-_LT5nd18_fVlc32UNy8mQtUpzJgB0k_NSKyoEY6xkEqRhRhCuGDFlmWslhWJ1nSeOti0IVecFZbXkc3S2y10H_ziaOFSdjY1xbvdaxUnqTqZKeEI__Ieu_BhSIYminMoi54wk6nxHNcHHGExbrYPtIEwVJdVWSbVVUr0qSfDpW-RYd0b_Rf844C8HKIhw</recordid><startdate>20240729</startdate><enddate>20240729</enddate><creator>Costa, Simone Bn</creator><creator>Miranda, Claudia do Sc</creator><creator>De Souza, Bruna C</creator><creator>Guimarães, Heloisa Maria M E S</creator><creator>Faria, Camylle Mc</creator><creator>Da S Campos, Pedro S</creator><creator>Koury, Taiana Ma</creator><creator>Da Paixão, José Gabriel M</creator><creator>Leal, Alessandra L</creator><creator>Carrera, Maria de Fátima P</creator><creator>De Brito, Silvana R</creator><creator>Gonçalves, Nelson V</creator><general>Journal of Infection in Developing Countries</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8C1</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-5095-9629</orcidid><orcidid>https://orcid.org/0000-0001-7202-1423</orcidid><orcidid>https://orcid.org/0009-0009-5112-2060</orcidid><orcidid>https://orcid.org/0009-0001-5967-7708</orcidid><orcidid>https://orcid.org/0000-0003-1513-8144</orcidid><orcidid>https://orcid.org/0000-0001-8476-5569</orcidid></search><sort><creationdate>20240729</creationdate><title>Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study</title><author>Costa, Simone Bn ; Miranda, Claudia do Sc ; De Souza, Bruna C ; Guimarães, Heloisa Maria M E S ; Faria, Camylle Mc ; Da S Campos, Pedro S ; Koury, Taiana Ma ; Da Paixão, José Gabriel M ; Leal, Alessandra L ; Carrera, Maria de Fátima P ; De Brito, Silvana R ; Gonçalves, Nelson V</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c240t-f9d325aadc438d9155222827a7e2e503920e884d97592bb4dc41ffa59b4612b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Brazil - epidemiology</topic><topic>Deforestation</topic><topic>Fuzzy Logic</topic><topic>Humans</topic><topic>Leishmaniasis, Cutaneous - epidemiology</topic><topic>Parasitic diseases</topic><topic>Public health</topic><topic>Risk Factors</topic><topic>Socioeconomic Factors</topic><topic>Spatial Analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Costa, Simone Bn</creatorcontrib><creatorcontrib>Miranda, Claudia do Sc</creatorcontrib><creatorcontrib>De Souza, Bruna C</creatorcontrib><creatorcontrib>Guimarães, Heloisa Maria M E S</creatorcontrib><creatorcontrib>Faria, Camylle Mc</creatorcontrib><creatorcontrib>Da S Campos, Pedro S</creatorcontrib><creatorcontrib>Koury, Taiana Ma</creatorcontrib><creatorcontrib>Da Paixão, José Gabriel M</creatorcontrib><creatorcontrib>Leal, Alessandra L</creatorcontrib><creatorcontrib>Carrera, Maria de Fátima P</creatorcontrib><creatorcontrib>De Brito, Silvana R</creatorcontrib><creatorcontrib>Gonçalves, Nelson V</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Public Health Database</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Publicly Available Content Database</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><collection>MEDLINE - Academic</collection><jtitle>Journal of infection in developing countries</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Costa, Simone Bn</au><au>Miranda, Claudia do Sc</au><au>De Souza, Bruna C</au><au>Guimarães, Heloisa Maria M E S</au><au>Faria, Camylle Mc</au><au>Da S Campos, Pedro S</au><au>Koury, Taiana Ma</au><au>Da Paixão, José Gabriel M</au><au>Leal, Alessandra L</au><au>Carrera, Maria de Fátima P</au><au>De Brito, Silvana R</au><au>Gonçalves, Nelson V</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study</atitle><jtitle>Journal of infection in developing countries</jtitle><addtitle>J Infect Dev Ctries</addtitle><date>2024-07-29</date><risdate>2024</risdate><volume>18</volume><issue>7</issue><spage>1124</spage><epage>1131</epage><pages>1124-1131</pages><issn>1972-2680</issn><issn>2036-6590</issn><eissn>1972-2680</eissn><abstract>This study sought to analyze the relationships between cutaneous leishmaniasis and its epidemiological, environmental and socioeconomic conditions, in the 22 microregions of Pará state, Brazil, for the period from 2017 to 2022.
In this ecological and exploratory study, the microregions were used as spatial units because they are formed by contiguous municipalities with similar characteristics. The epidemiological, environmental, socioeconomic, and public health policy data employed were obtained from the official information systems at the Ministry of Health, National Institute for Space Research, and Brazilian Institute of Geography and Statistics. A fuzzy system was developed to identify risk factors for the disease, using Python programming language. The results were analyzed with the bivariate Global Moran spatial analysis technique.
It was observed that the Altamira microregion had the highest risk percentage for the disease, while Breves had the lowest, with significant differences in the relevance of its conditioning factors, mainly related to land use and cover patterns, in addition to demography and living conditions index, education and public health policies.
The fuzzy system associated with the geostatistical technique was satisfactory for identifying areas with health vulnerability gradients related to deforestation, pasture, poverty, illiteracy, and health services coverage, as its conditioning variables. Thus, it was demonstrated that deforestation was the main risk factor for the disease. The system can also be used in environmental and epidemiological surveillance.</abstract><cop>Italy</cop><pub>Journal of Infection in Developing Countries</pub><pmid>39078799</pmid><doi>10.3855/jidc.18639</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-5095-9629</orcidid><orcidid>https://orcid.org/0000-0001-7202-1423</orcidid><orcidid>https://orcid.org/0009-0009-5112-2060</orcidid><orcidid>https://orcid.org/0009-0001-5967-7708</orcidid><orcidid>https://orcid.org/0000-0003-1513-8144</orcidid><orcidid>https://orcid.org/0000-0001-8476-5569</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1972-2680 |
| ispartof | Journal of infection in developing countries, 2024-07, Vol.18 (7), p.1124-1131 |
| issn | 1972-2680 2036-6590 1972-2680 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_3086379073 |
| source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Brazil - epidemiology Deforestation Fuzzy Logic Humans Leishmaniasis, Cutaneous - epidemiology Parasitic diseases Public health Risk Factors Socioeconomic Factors Spatial Analysis |
| title | Fuzzy and spatial analysis of cutaneous leishmaniasis in Pará State, Brazilian Amazon: an ecological and exploratory study |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T20%3A54%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Fuzzy%20and%20spatial%20analysis%20of%20cutaneous%20leishmaniasis%20in%20Par%C3%A1%20State,%20Brazilian%20Amazon:%20an%20ecological%20and%20exploratory%20study&rft.jtitle=Journal%20of%20infection%20in%20developing%20countries&rft.au=Costa,%20Simone%20Bn&rft.date=2024-07-29&rft.volume=18&rft.issue=7&rft.spage=1124&rft.epage=1131&rft.pages=1124-1131&rft.issn=1972-2680&rft.eissn=1972-2680&rft_id=info:doi/10.3855/jidc.18639&rft_dat=%3Cproquest_cross%3E3131764320%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3131764320&rft_id=info:pmid/39078799&rfr_iscdi=true |