Interessados em mensurar a criminalidade violenta utilizam o número de homicídios, a partir de hipótese, nunca verificada, de que a gravidade do crime implica subnotificação desprezível. No Brasil, o Sistema de Informações sobre Mortalidade (SIM) é fonte habitualmente utilizada na aferição do número de homicídio. Entre 1996 e 2021, dentre as mortes por causa externa, 8,2% são classificadas como mortes por causa externa de intenção indeterminada (MVCI), indicando possibilidade de subnotificação de homicídios. A partir dos microdados sobre morte por causa externa registradas no SIM, algoritmo de aprendizado supervisionado aprende as características de homicídios, acidentes e suicídios e estima probabilidade de as MVCIs serem na realidade homicídio incorretamente registrados como MVCI, permitindo-nos estimar o número de homicídios ocultos no SIM. O resultado encontrado sugere que, entre 1996 e 2021, não foram contabilizados 128.567 homicídios ocultos ou 43,6% das MVCI são na realidade homicídios. Evidência contrária à hipótese de reduzida subnotificação, implicando impactos significativos em avaliações de políticas públicas, procedimentos econométricos e necessidade de contabilização destes homicídios ocultos em medições da criminalidade.
Palavras-chave:
Aprendizado de Maquinas; Homicídio; Crime; Subnotificação; DATASUS
Abstract:
Those interested in measuring violent crime use the number of homicides, based on the never-verified assumption that the seriousness of the crime implies negligible underreporting. In Brazil, the Mortality Information System (SIM) is the source usually used to measure the number of homicides. Between 1996 and 2021, among deaths from external causes, 8.2% were classified as deaths from external causes of undetermined intent (MVCI), indicating the possibility of homicide underreporting. From the microdata on external cause deaths recorded in the SIM, a supervised learning algorithm learns the characteristics of homicides, accidents and suicides and estimates the probability that MVCIs are homicides incorrectly recorded as MVCI, allowing us to estimate the number of shadow homicides in the SIM. The result suggests that between 1996 and 2021, 128,567 shadow homicides were not accounted for, or 43.6% of MVCI s are actually homicides. Evidence contrary to the hypothesis of reduced underreporting, implying significant impacts on public policy evaluations, econometric procedures and the need to account for these hidden homicides in crime measurements.
The map of hidden homicides in Brazil between 1996 and 2021
Resumo (abstract):
Those interested in measuring violent crime use the number of homicides, based on the never-verified assumption that the seriousness of the crime implies negligible underreporting. In Brazil, the Mortality Information System (SIM) is the source usually used to measure the number of homicides. Between 1996 and 2021, among deaths from external causes, 8.2% were classified as deaths from external causes of undetermined intent (MVCI), indicating the possibility of homicide underreporting. From the microdata on external cause deaths recorded in the SIM, a supervised learning algorithm learns the characteristics of homicides, accidents and suicides and estimates the probability that MVCIs are homicides incorrectly recorded as MVCI, allowing us to estimate the number of shadow homicides in the SIM. The result suggests that between 1996 and 2021, 128,567 shadow homicides were not accounted for, or 43.6% of MVCI s are actually homicides. Evidence contrary to the hypothesis of reduced underreporting, implying significant impacts on public policy evaluations, econometric procedures and the need to account for these hidden homicides in crime measurements.
Cerqueira, DRC, Lins, GOA. Mapa dos homicídios ocultos no Brasil entre 1996 e 2021. Cien Saude Colet [periódico na internet] (2025/ago). [Citado em 05/12/2025].
Está disponível em: http://cienciaesaudecoletiva.com.br/artigos/mapa-dos-homicidios-ocultos-no-brasil-entre-1996-e-2021/19787
