Beyond comorbidities, sex and age have no effect on COVID-19 health care demand

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Abstract

This paper explores the associations between sex, age and hospital health care pressure in the context of the COVID-19 pandemic in Portuguese mainland municipalities. To represent the impact of sex and age, we calculated COVID-19 standardised incidence ratios (SIR) in Portuguese mainland municipalities over fourteen months daily, especially focusing on the Porto metropolitan area. A daily novel indicator was devised for hospital health care pressure, consisting of an approximation to the ratio of hospitalisations per available hospital medical doctor (HPI). In addition, 14-day incidence rates were also calculated daily (DIR14), both as an approach and an alternative to the current national pandemic surveillance indicator (which is not calculated with such regularity). Daily maps were first visualised to evaluate spatial patterns. Pearson's correlation coefficients were then calculated between each proposed surveillance indicator (SIR and DIR14) and the HPI. Our results suggest that hospital pressure is not strongly associated with SIR (r = 0.34, p value = 0.08). However, DIR14 bears a stronger correlation with hospital pressure (r = 0.84, p value < 0.001). By establishing the importance of tackling sex and age through the inclusion of these factors explicitly in an epidemiological monitoring indicator, and assessing its relationship with a hospital pressure indicator, our findings have public policy implications that could improve COVID-19 incidence surveillance in Portugal and elsewhere, contributing to advancing the management of potential pandemics in the near future, with a particular focus on local and regional territorial scales.
Original languageEnglish
Article number7356
Pages (from-to)1-12
Number of pages12
JournalScientific Reports
Volume12
Issue number1
Early online date1 May 2022
DOIs
Publication statusE-pub ahead of print - 1 May 2022

Keywords

  • Comorbidity
  • Delivery of Health Care
  • Hospitalization
  • Humans
  • Infant
  • Pandemics
  • COVID-19
  • Epidemiology

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