A hybrid deep learning model for predicting and targeting the less immunized area to improve childrens vaccination rate

Abstract

In the past few years, there has been a significantly growing interest among the developing nations to increase vaccination coverage for all group of people to make their nation healthy and safe. India has launched a mission called Indradhanush which aims to bring 100% vaccinated rate across the country in the coming years. District Level Household Survey (DLHS) is conducted to determine the percentage of immunized children in different regions of India. The data collected through this survey has been used and evaluated by various researchers and the findings have been presented in three different categories, such as Fully Vaccinated, Partially Vaccinated and Non-Vaccinated, based on the percentage of vaccination rates. Several scholars relate the low rate of vaccination across India, with low literacy rates and inequities between boys and girls. Some studies have examined the socio-demographic variables that mainly affect the rate of vaccination. newlineYet they have not predicted whether the vaccination rate will stay as it is, or whether or not the proportion of partially immunized and non-immunized will decline in the future. Nor have they talked about the non-availability of health services and inadequate public infrastructure resources. It will be very helpful for healthcare organizations if the rate of vaccination of a particular sate in India is analysed and the rate of vaccination for the future is predicted. Based on the results, the same process will be extended in the other states of India to improve the rate of vaccination. In order to eradicate the diseases by administering different vaccines, it is necessary to predict the coverage rate of all vaccines in a particular region newline