A data science-led strategy to assess the subnational burden of sepsis using official records: a longitudinal description and cross-sectional demonstration in Chile.

Sepsis is a life-threatening organ dysfunction caused by an aberrant host response to an infecting pathogen. Several international efforts have been launched to address its staggering burden and escalating costs. A disconnection occurs when translating current global, regional, and national estimates into local and subnational quantifications of their burden. Given the level of completeness of civil registration and vital statistics in Chile, an opportunity arose to calculate, rather than estimate, the burden of sepsis by subnational administrative division. Thus, for the first time, a data science-driven strategy is presented to quantify sepsis-related incidence and mortality from official datasets in this country. Moreover, given the high-throughput potential of the analysis, areas where sepsis-related mortality exceeded its incidence were identified by administrative division, age group, and individual cause of death, and ranked by the magnitude of the excess. Thus, a strategy to guide the efficient deployment of public health resources based on subnational burden is presented. Implementation of such a strategy may represent the key to tackling sepsis with a local-to-global perspective, especially in low- and middle-income countries.