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[ARBOALVO: territorial stratification for definition of areas for prompt response by surveillance and timely control of urban arbovirus infections].

Jefferson Pereira Caldas Dos SantosHermano Gomes AlbuquerqueAlexandre San Pedro SiqueiraHeitor Levy Ferreira PraçaLeandro Vouga PereiraAlessandre de Medeiros TavaresEduardo Viana Vieira GusmãoPaulo Roberto de Abreu BrunoChristovam BarcellosMarília de Sá CarvalhoPaulo Chasgastelles SabrozaNildimar Alves Honório
Published in: Cadernos de saude publica (2022)
The study aimed to present the methodological proposal entitled "Prompt Response", modelled in the cities of Belo Horizonte (Minas Gerais State) and Natal (Rio Grande do Norte State), Brazil. The proposal aims to identify and demarcate priority areas for timely targeting of surveillance activities, aiming to reduce the intensity and velocity in the spread of epidemics in endemic urban areas. The methodology uses three variables that represent the necessary causes for the production and reproduction of dengue: notified cases (virus), Aedes eggs (vector), and population (host). This was an ecological study that used data from three information planes aggregated in finer temporal and spatial scales of 3 to 4 weeks and 400 to 600-meter grids, respectively. The prompt response areas were defined by Scan statistical analysis with definition of simultaneous spatial clusters for the three planes via the SaTScan program. In Natal, the areas defined as prompt response occupied, on average, 15.2% of the city's territory and concentrated 67.77% of the dengue cases in the period following demarcation of the prompt response areas. In Belo Horizonte, the observed proportions were 64.16% of cases in 23.23% of the territory. These results were obtained in two cities with different socioenvironmental and geographic realities and distinct epidemiological profiles, indicating that the methodology can be applied to different urban realities, allowing control programs to concentrate on reduced portions of the territory and impacting a high percentage of cases in timely fashion.
Keyphrases
  • aedes aegypti
  • south africa
  • zika virus
  • computed tomography
  • magnetic resonance
  • healthcare
  • quality improvement
  • risk assessment
  • deep learning