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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Temporal and spatial analysis of over 7,000 measles cases outbreak from 2018 to 2019 in the Brazilian Amazon

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Felipe de Mello Martins ; Alessandra Pinheiro Vidal ; Jeevan Giddaluru [3] ; Bernardo Maia da Silva ; Eva K. Lee [5] ; Peijue Zhang [6] ; Lucas Esteves Cardozo [7] ; Carlos Augusto Prete Junior [8] ; Helves Humberto Domingues [9] ; Ester Cerdeira Sabino [10] ; Vanderson de Souza Sampaio ; Wuelton Marcelo Monteiro ; Helder I Nakaya
Total Authors: 13
Document type: Journal article
Source: Einstein (São Paulo); v. 22, 2024-03-29.
Abstract

ABSTRACT Objective: This study aimed to present a temporal and spatial analysis of the 2018 measles outbreak in Brazil, particularly in the metropolitan city of Manaus in the Amazon region, and further introduce a new tool for spatial analysis. Methods: We analyzed the geographical data of the residences of over 7,000 individuals with measles in Manaus during 2018 and 2019. Spatial and temporal analyses were conducted to characterize various aspects of the outbreak, including the onset and prevalence of symptoms, demographics, and vaccination status. A visualization tool was also constructed to display the geographical and temporal distribution of the reported measles cases. Results: Approximately 95% of the included participants had not received vaccination within the past decade. Heterogeneity was observed across all facets of the outbreak, including variations in the incubation period and symptom presentation. Age distribution exhibited two peaks, occurring at one year and 18 years of age, and the potential implications of this distribution on predictive analysis were discussed. Additionally, spatial analysis revealed that areas with the highest case densities tended to have the lowest standard of living. Conclusion: Understanding the spatial and temporal spread of measles outbreaks provides insights for decision-making regarding measures to mitigate future epidemics. (AU)

FAPESP's process: 19/21858-0 - Bayesian models for estimating the attack rate of epidemics
Grantee:Carlos Augusto Prete Junior
Support Opportunities: Scholarships in Brazil - Doctorate