La cisticercosis humana es una zoonosis desatendida cuya manifestación más grave, la neurocisticercosis (NCC) es considerada la principal enfermedad parasitaria que afecta al sistema nervioso central en humanos, además de una importante causa de epilepsia³ , ⁴ . Sus manifestaciones más graves se relacionan con discapacidad, discriminación, altos costos médicos, pérdida de productividad, complejos procedimientos quirúrgicos, deterioro de la calidad de vida e incluso la muerte⁵ . Solo en 2010 la carga global de la enfermedad asociada a las complicaciones neurológicas por NCC se valoró en 2,8 millones de años de vida ajustados por discapacidad (AVAD)⁶ .

Automatic geocoding methods have become popular in recent years, facilitating the study of the association between health outcomes and the place of living. However, rather few studies have evaluated geocoding quality, with most of them being performed in the US and Europe. This article aims to compare the quality of three automatic online geocoding tools against a reference method. A subsample of 300 handwritten addresses from hospital records was geocoded using Bing, Google Earth, and Google Maps. Match rates were higher (> 80%) for Google Maps and Google Earth compared with Bing. However, the accuracy of the addresses was better for Bing with a larger proportion (> 70%) of addresses with positional errors below 20m. Generally, performance did not vary for each method for different socioeconomic status. Overall, the methods showed an acceptable, but heterogeneous performance, which may be a warning against the use of automatic methods without assessing quality in other municipalities, particularly in Chile and Latin America.