Pandemics are large-scale infectious disease outbreaks that can dramatically
increase morbidity and mortality over a wider geographic region and trigger substantial
economic, social, and political damage. Currently, the world is facing the coronavirus
(COVID-19) pandemic. COVID-19 is considered a dangerous disease affecting all
entire humanity and reports death cases in the thousands each day (as per the source
from Wikipedia, it is 3,690,000 deaths and 172,000,000 cases identified as COVID-19
positive as of 04-June-2021) and quietly throws dangerous bells on the entire humanity,
causing health emergencies in every country, worldwide. Due to the ongoing
pandemic, the healthcare infrastructure has been stretched. With the limited healthcare
infrastructure and the number of COVID-19 cases spiking up, many countries have
opted to treat their patients from the patient home, providing at-home medical facilities
and continuous monitoring by medical officials at regular intervals. Health is of
considerable importance in the new global situation. Providing smart healthcare is
important for all people to monitor continuously and maintain good health. A powerful
new mobile application and the usage of machine learning techniques can be an
innovative solution to the healthcare problems in these pandemic times for patient
management and disease management. This solution can directly impact clinical
decision-making. The proposed mobile application is a utility tool for COVID-19
patients during and after the quarantine period/home isolation. This application is
aimed at being a friendly interface that can record every detail of COVID-19 patient
activity from the day of admission to the day of discharge. This facilitates the proposed
system to record all symptoms, medication, responses to medicine, diet aspects, and
physical and mental aspects of the patients. The proposed system is designed in such a
way that we can get the data from the application that monitors the person’s health
activities, and that data will be used for the analysis to extract useful information by
using machine learning techniques. The data that is collected from each patient is
provided to the machine learning domain to find common features and patterns that
help us to gain further insights into the disease and could help to develop better
medications, vaccine development, immunisation knowledge base, recovery aspects, and symptomatic approaches for the future generation. This knowledge extracted from
the machine learning techniques can be used for better treatment and prediction of
disease at the initial stages, which could mitigate the life risk and help to stop the
spread of the disease.
Keywords: Coronavirus, CoviCare, COVID-19, Data Analysis, Data Collection, Machine Learning.
