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Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis
Abstract Background Northeast Brazil has the world's highest rate of Zika-related microcephaly. However, Zika case counts cannot accurately describe burden because mandatory reporting was only established when the epidemic was declining in the region. Methods To advance the study of the Zika ep...
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Published in: | Transactions of the Royal Society of Tropical Medicine and Hygiene 2023-03, Vol.117 (3), p.189-196 |
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creator | Freitas, Laís Picinini Lowe, Rachel Koepp, Andrew E Alves, Sandra Valongueiro Dondero, Molly Marteleto, Letícia J |
description | Abstract
Background
Northeast Brazil has the world's highest rate of Zika-related microcephaly. However, Zika case counts cannot accurately describe burden because mandatory reporting was only established when the epidemic was declining in the region.
Methods
To advance the study of the Zika epidemic, we identified hotspots of Zika in Pernambuco state, Northeast Brazil, using Aedes-borne diseases (dengue, chikungunya and Zika) and microcephaly data. We used Kulldorff's Poisson purely spatial scan statistic to detect low- and high-risk clusters for Aedes-borne diseases (2014–2017) and for microcephaly (2015–2017), separately. Municipalities were classified according to a proposed gradient of Zika burden during the epidemic, based on the combination of cluster status in each analysis and considering the strength of the evidence.
Results
We identified 26 Aedes-borne diseases clusters (11 high-risk) and 5 microcephaly clusters (3 high-risk) in Pernambuco. According to the proposed Zika burden gradient, our results indicate that the northeast of Pernambuco and the Sertão region were hit hardest by the Zika epidemic. The first is the most populous area of Pernambuco, while the second has one of the highest rates of social and economic inequality in Brazil.
Conclusion
We successfully identified possible hidden Zika hotspots using a simple methodology combining Aedes-borne diseases and microcephaly information. |
doi_str_mv | 10.1093/trstmh/trac099 |
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Background
Northeast Brazil has the world's highest rate of Zika-related microcephaly. However, Zika case counts cannot accurately describe burden because mandatory reporting was only established when the epidemic was declining in the region.
Methods
To advance the study of the Zika epidemic, we identified hotspots of Zika in Pernambuco state, Northeast Brazil, using Aedes-borne diseases (dengue, chikungunya and Zika) and microcephaly data. We used Kulldorff's Poisson purely spatial scan statistic to detect low- and high-risk clusters for Aedes-borne diseases (2014–2017) and for microcephaly (2015–2017), separately. Municipalities were classified according to a proposed gradient of Zika burden during the epidemic, based on the combination of cluster status in each analysis and considering the strength of the evidence.
Results
We identified 26 Aedes-borne diseases clusters (11 high-risk) and 5 microcephaly clusters (3 high-risk) in Pernambuco. According to the proposed Zika burden gradient, our results indicate that the northeast of Pernambuco and the Sertão region were hit hardest by the Zika epidemic. The first is the most populous area of Pernambuco, while the second has one of the highest rates of social and economic inequality in Brazil.
Conclusion
We successfully identified possible hidden Zika hotspots using a simple methodology combining Aedes-borne diseases and microcephaly information.</description><identifier>ISSN: 0035-9203</identifier><identifier>ISSN: 1878-3503</identifier><identifier>EISSN: 1878-3503</identifier><identifier>DOI: 10.1093/trstmh/trac099</identifier><identifier>PMID: 36326785</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Aedes ; Animals ; Brazil - epidemiology ; Humans ; Microcephaly - epidemiology ; Original ; Spatial Analysis ; Zika Virus ; Zika Virus Infection - epidemiology</subject><ispartof>Transactions of the Royal Society of Tropical Medicine and Hygiene, 2023-03, Vol.117 (3), p.189-196</ispartof><rights>The Author(s) 2022. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. 2022</rights><rights>The Author(s) 2022. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-23fccd4bafc760314fd1366b698821d22c8f2b96769608499c18172f13a54b83</citedby><cites>FETCH-LOGICAL-c424t-23fccd4bafc760314fd1366b698821d22c8f2b96769608499c18172f13a54b83</cites><orcidid>0000-0001-9012-9382</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36326785$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Freitas, Laís Picinini</creatorcontrib><creatorcontrib>Lowe, Rachel</creatorcontrib><creatorcontrib>Koepp, Andrew E</creatorcontrib><creatorcontrib>Alves, Sandra Valongueiro</creatorcontrib><creatorcontrib>Dondero, Molly</creatorcontrib><creatorcontrib>Marteleto, Letícia J</creatorcontrib><title>Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis</title><title>Transactions of the Royal Society of Tropical Medicine and Hygiene</title><addtitle>Trans R Soc Trop Med Hyg</addtitle><description>Abstract
Background
Northeast Brazil has the world's highest rate of Zika-related microcephaly. However, Zika case counts cannot accurately describe burden because mandatory reporting was only established when the epidemic was declining in the region.
Methods
To advance the study of the Zika epidemic, we identified hotspots of Zika in Pernambuco state, Northeast Brazil, using Aedes-borne diseases (dengue, chikungunya and Zika) and microcephaly data. We used Kulldorff's Poisson purely spatial scan statistic to detect low- and high-risk clusters for Aedes-borne diseases (2014–2017) and for microcephaly (2015–2017), separately. Municipalities were classified according to a proposed gradient of Zika burden during the epidemic, based on the combination of cluster status in each analysis and considering the strength of the evidence.
Results
We identified 26 Aedes-borne diseases clusters (11 high-risk) and 5 microcephaly clusters (3 high-risk) in Pernambuco. According to the proposed Zika burden gradient, our results indicate that the northeast of Pernambuco and the Sertão region were hit hardest by the Zika epidemic. The first is the most populous area of Pernambuco, while the second has one of the highest rates of social and economic inequality in Brazil.
Conclusion
We successfully identified possible hidden Zika hotspots using a simple methodology combining Aedes-borne diseases and microcephaly information.</description><subject>Aedes</subject><subject>Animals</subject><subject>Brazil - epidemiology</subject><subject>Humans</subject><subject>Microcephaly - epidemiology</subject><subject>Original</subject><subject>Spatial Analysis</subject><subject>Zika Virus</subject><subject>Zika Virus Infection - epidemiology</subject><issn>0035-9203</issn><issn>1878-3503</issn><issn>1878-3503</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkMtLAzEQxoMotlavHiVHBbfmsZuHB0GLj0pBDz15Cdnsbhvdl8muUP96I61FTx6GYZjffN_wAXCM0RgjSS8657tqGZo2SModMMSCi4gmiO6CIUI0iSRBdAAOvH9FiCQ4kftgQBkljItkCB6nWV53tljZegGXNgsTfLFvGi6bzrehoK3hc-5qXaW9ac7hjdOftryEGvpWd1aXUNe6XHnrD8FeoUufH236CMzvbueTh2j2dD-dXM8iE5O4iwgtjMniVBeGM0RxXGSYMpYyKQTBGSFGFCSVjDPJkIilNFhgTgpMdRKngo7A1Vq27dMqz0x43-lStc5W2q1Uo636u6ntUi2aDyUl5wSTIHC6EXDNe5_7TlXWm7wsdZ03vVeEU8xxsE8COl6jxjXeu7zY2mCkvvNX6_zVJv9wcPL7uS3-E3gAztZA07f_iX0BR5GS8w</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Freitas, Laís Picinini</creator><creator>Lowe, Rachel</creator><creator>Koepp, Andrew E</creator><creator>Alves, Sandra Valongueiro</creator><creator>Dondero, Molly</creator><creator>Marteleto, Letícia J</creator><general>Oxford University Press</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>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-9012-9382</orcidid></search><sort><creationdate>20230301</creationdate><title>Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis</title><author>Freitas, Laís Picinini ; Lowe, Rachel ; Koepp, Andrew E ; Alves, Sandra Valongueiro ; Dondero, Molly ; Marteleto, Letícia J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-23fccd4bafc760314fd1366b698821d22c8f2b96769608499c18172f13a54b83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aedes</topic><topic>Animals</topic><topic>Brazil - epidemiology</topic><topic>Humans</topic><topic>Microcephaly - epidemiology</topic><topic>Original</topic><topic>Spatial Analysis</topic><topic>Zika Virus</topic><topic>Zika Virus Infection - epidemiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Freitas, Laís Picinini</creatorcontrib><creatorcontrib>Lowe, Rachel</creatorcontrib><creatorcontrib>Koepp, Andrew E</creatorcontrib><creatorcontrib>Alves, Sandra Valongueiro</creatorcontrib><creatorcontrib>Dondero, Molly</creatorcontrib><creatorcontrib>Marteleto, Letícia J</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Transactions of the Royal Society of Tropical Medicine and Hygiene</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Freitas, Laís Picinini</au><au>Lowe, Rachel</au><au>Koepp, Andrew E</au><au>Alves, Sandra Valongueiro</au><au>Dondero, Molly</au><au>Marteleto, Letícia J</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis</atitle><jtitle>Transactions of the Royal Society of Tropical Medicine and Hygiene</jtitle><addtitle>Trans R Soc Trop Med Hyg</addtitle><date>2023-03-01</date><risdate>2023</risdate><volume>117</volume><issue>3</issue><spage>189</spage><epage>196</epage><pages>189-196</pages><issn>0035-9203</issn><issn>1878-3503</issn><eissn>1878-3503</eissn><abstract>Abstract
Background
Northeast Brazil has the world's highest rate of Zika-related microcephaly. However, Zika case counts cannot accurately describe burden because mandatory reporting was only established when the epidemic was declining in the region.
Methods
To advance the study of the Zika epidemic, we identified hotspots of Zika in Pernambuco state, Northeast Brazil, using Aedes-borne diseases (dengue, chikungunya and Zika) and microcephaly data. We used Kulldorff's Poisson purely spatial scan statistic to detect low- and high-risk clusters for Aedes-borne diseases (2014–2017) and for microcephaly (2015–2017), separately. Municipalities were classified according to a proposed gradient of Zika burden during the epidemic, based on the combination of cluster status in each analysis and considering the strength of the evidence.
Results
We identified 26 Aedes-borne diseases clusters (11 high-risk) and 5 microcephaly clusters (3 high-risk) in Pernambuco. According to the proposed Zika burden gradient, our results indicate that the northeast of Pernambuco and the Sertão region were hit hardest by the Zika epidemic. The first is the most populous area of Pernambuco, while the second has one of the highest rates of social and economic inequality in Brazil.
Conclusion
We successfully identified possible hidden Zika hotspots using a simple methodology combining Aedes-borne diseases and microcephaly information.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>36326785</pmid><doi>10.1093/trstmh/trac099</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-9012-9382</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aedes Animals Brazil - epidemiology Humans Microcephaly - epidemiology Original Spatial Analysis Zika Virus Zika Virus Infection - epidemiology |
title | Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis |
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