COVID-19, trabalho e limitação de dados de ocupação: a morbidade entre trabalhadores da saúde na Bahia

Abstract

Introduction: in the COVID-19 Pandemic Brazil needed to produce information quickly. The high demands on health services exposed Health Personnel (HP) in particular. To investigate this occupational group, the availability of quality, accessible and reliable data is necessary to produce indicators and information on worker health. Objectives: The objective of this study was to estimate the incidence of COVID-19 cases in HP and discuss the availability and quality of data from different health information systems and other data sources. Method: This is a study of the incidence of COVID-19 in HP in Bahia, with data available in DATASUS and other sources from 2020 to 2022. Results: Only 2.8% (2,252) of 81,497 accumulated cases of the syndrome Severe Acute Respiratory due to COVID-19 had the occupation field filled in, and for Flu Syndrome cases, 5.3% (80,994) of the 1,521,313 had this field filled in. Of these cases, 59,185 (73.1%) corresponded to HP, 61.1% (36,650) were female, with the predominant age group of 20-39 years making up 54.8% of cases (27,653); 71.4% (36,078) variety among TS of black or brown race/color. The results with denominators from the National Immunization Program Information System have the highest incidence among nurses, 325.5/1000, followed by nursing assistants/technicians, with 269.9/1000 and receptionists with 78.5/1000. Nurse was the occupation with the highest relative risk at 15.5. Discussion: Health workers are those with the highest incidence of COVID-19, but little is known about occupations not directly linked to care. The absence of this data compromises the quality of the information produced and consequently the construction of indicators. Conclusion: Information on workers' health through secondary data presents challenges to be overcome, one of which is the establishment of appropriate denominators, which depends on the recording of the variable occupation in the Health Information Systems.