Prediction Models for COVID-19 Integrating Age Groups, Gender, and Underlying Conditions
نویسندگان
چکیده
The COVID-19 pandemic has caused hundreds of thousands deaths, millions infections worldwide, and the loss trillions dollars for many large economies. It poses a grave threat to human population with an excessive number patients constituting unprecedented challenge which health systems have cope. Researchers from domains devised diverse approaches timely diagnosis facilitate medical responses. In same vein, wide variety research studies investigated underlying conditions indicators suggesting severity mortality of, role age groups gender on, probability infection. This study aimed review, analyze, critically appraise published works that report on various factors explain their relationship COVID-19. Such span range, including descriptive analyses, ratio cohort, prospective retrospective studies. Various describe determine infection among general population, as well risk associated severe illness mortality, are analyzed these findings discussed in detail. A comprehensive analysis was conducted perceived differences vulnerability different genders outcomes Studies incorporating important demographic, health, socioeconomic characteristics highlighted emphasize importance. Predominantly, lack appropriated dataset contains personal information implicates efficacy efficiency methods. Results overstated part both exclusion quarantined mild symptoms inclusion data hospitals where majority cases potentially ill.
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ژورنال
عنوان ژورنال: Computers, materials & continua
سال: 2021
ISSN: ['1546-2218', '1546-2226']
DOI: https://doi.org/10.32604/cmc.2021.015140