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.
ABSTRACT
A identificação de focos de transmissão pode ser de grande utilidade no controle da malária. Por esse motivo, hospitais em regiões endêmicas buscam saber os locais que foram visitados anteriormente por pacientes. No entanto, tais informações, obtidas através de questionários fornecidos aos pacientes, são geralmente vagas e muitas vezes imprecisas. Isto torna o processo manual, lento e de pouca valia em estudos epidemiológicos de larga escala. Baseando-se no fato de que uma parcela significativa da população possui celulares com GPS, o objetivo deste projeto é melhorar a acurácia, organização e dinâmica do processo de coleta de dados de geolocalização de pacientes infectados. Um sistema (https://sipos.fcf.usp.br) foi desenvolvido para que pacientes que chegam aos hospitais possam, sob consentimento voluntário, fornecer os dados de GPS dos seus celulares. Os dados dos usuários, que são tratados de forma anônima, são automaticamente processados e armazenados de forma segura. Através do sistema SiPoS Explorer, epidemiologistas e especialistas em saúde pública podem explorar e analisar os dados de geolocalização, permitindo, desta forma, que regiões vulneráveis sejam priorizadas durante campanhas de controle
The identification of regions with high rates of infection can be of great use in the control of malaria. For this reason, hospitals in endemic regions seek to know the places previously visited by patients. However, such information, obtained through questionnaires provided to patients, is usually vague, inaccurate and not integrated into databases. This makes the process manual, slow and of little value in large-scale epidemiological studies. Based on the fact that a significant portion of the population has smartphones equipped with GPS, this project aims to improve the accuracy and organization of the process of collecting geolocation data from infected patients. The Sickness Positioning System (https://sipos.fcf.usp.br) was developed so that patients who arrive at hospitals can, with voluntary consent, provide the GPS data collected by their smartphones. User data, which is handled anonymously, is automatically processed and securely stored. Through the SiPoS Explorer system (https://sipos.fcf.usp.br/explorer), epidemiologists and public health experts can explore and analyze geolocation data, thereby allowing vulnerable regions to be prioritized during control campaigns