Impact of COVID-19 on Cancer mortality and hospital care in the 133 intermediate geographic regions of Brazil and its relationship with socioeconomic conditions and provision of hospital structure

Abstract

The COVID-19 pandemic disrupted the provision of Cancer care around the world. This study starts from the hypothesis that this situation is causing delays in Cancer diagnoses and reflecting in less-than-ideal care for patients with this disease, outlining a scenario of latent impact on mortality. This impact - and its possible variations between different types of Cancer and populations - is still unknown. Objectives: To analyze the impact of the COVID-19 pandemic on mortality and hospital admissions for all types of Cancer and separately for the five most incidents and that cause most Cancer deaths in Brazil. Also, to analyze how socioeconomic factors and the structure of the hospital care influence this relationship. Methods: The units of analysis will be the 133 Intermediate Geographic Regions (IGRs) of Brazil. We will analyze the deaths and hospital admissions for all Cancers and separately for the five types of Cancer that are most incident and cause the most deaths in Brazil (trachea, bronchus, and lung; colon and rectum; female breast; prostate; and stomach), which will be further categorized as according to their prognosis - "treatable" or "non-treatable" Cancers. The Mortality Information System of Brazil will provide the mortality data, and the SUS Hospital Information System will provide data on hospital admissions - considering the period from 2014 to 2021. The Index of Human Development, the Brazilian Deprivation Index, and rates of hospital beds (by type) per inhabitant will characterize the IGRs. The calculation of death rates will have a previous stage of redistribution of ill-defined deaths, following two techniques recognized in the literature - the techniques of França and the Global Burden of Diseases. Rates of death and hospital admissions in the pre-pandemic period will be compared in different pandemic phases. We will estimate the impact of the COVID-19 pandemic on the outcome through the rates percentage change related to the control period. We will analyze the variation of this impact in the different RGIs, considering their socioeconomic and hospital care provision characteristics, by multiple regression models. (AU)