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

• Published in: Einstein (São Paulo, Brazil) Vol. 22; p. eAO0931
• Main Authors: Martins, Felipe de Mello, Vidal, Alessandra Pinheiro, Giddaluru, Jeevan, da Silva, Bernardo Maia, Lee, Eva K, Zhang, Peijue, Cardozo, Lucas Esteves, Prete Junior, Carlos Augusto, Domingues, Helves Humberto, Sabino, Ester Cerdeira, Sampaio, Vanderson de Souza, Monteiro, Wuelton Marcelo, Nakaya, Helder I
• Format: Journal Article
• Language: English
• Published: Brazil Instituto Israelita de Ensino e Pesquisa Albert Einstein 01-01-2024
• Subjects: Age distribution; Brazil - epidemiology; Disease Outbreaks; Geographic information systems; Humans; Infant; Measles; Measles - epidemiology; MEDICINE, GENERAL & INTERNAL; Original; Prevalence; Spatial Analysis; Vaccination; Brazil; Prevalence; Measles; Disease outbreaks; Vaccination; Spatial analysis; Geographic information systems; Age distribution
• ISSN: 1679-4508; 2317-6385; 2317-6385
• DOI: 10.31744/einstein_journal/2024AO0931

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.
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.
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.
Understanding the spatial and temporal spread of measles outbreaks provides insights for decision-making regarding measures to mitigate future epidemics.