Transactions of the Royal Society of Tropical Medicine and Hygiene · 2023
Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Freitas Laís Picinini, Lowe Rachel, Koepp Andrew E, Alves Sandra Valongueiro, Dondero Molly, Marteleto Letícia J
Аннотация
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.
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.