III: Statistical and Mathematical Model-Based Solutions

Analysis of Epidemiology: Integrating Computational Models

DEEPAK KUMAR1’, VINOD KUMAR2, and POOJA KHURANA1

department of Mathematics, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana 121004, India

department of Mathematics, University College of Basic Science and Humanities, Guru Kashi University, Talwandi Sabo, Punjab 151302, India

*Corresponding author. E-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

ABSTRACT

An epidemiology is very serious situation, in which epidemic disease spreads animal to animal, person to person, animal to person through inhaling of the vims liable to spread it to healthy person. The human society has suffering from epidemic diseases for thousands of years because of viral infection. Viral infection transmits from birds or animals like hens, ducks, pigs, swine, turkeys, and many other species of warm-blooded vertebrates. In the study of epidemic diseases, computational modeling approaches to be progressively abundant in epidemiology research. The complex nature of the study of epidemics is appropriate to quantitative techniques as it gives challenges and opportunities to new advancements. The practical implementation of the computational modeling must rely on an epidemiological model. Computational models can supplement test and clinical investigations, social media users, and yet additionally challenge current paradigms, redefine our understanding of mechanism driving epidemic and shape future research in public health policies, and to provide the number of techniques to control all kinds of epidemic diseases.

INTRODUCTION

Epidemiology is a veiy dire situation, in which epidemic disease spreads from animal to animal, person to person, and animal to person through inhaling of the virus. The human society has suffered from epidemic diseases for thousands of years because of viral infection. Viral infections transmit from buds or animals such as hens, ducks, pigs, swine, turkeys, and many other species of warm-blooded vertebrates, hi the study of epidemic diseases, computational modeling approaches to be progr essively abundant in epidemiology research. The complex nature of the study of epidemics is appropriate for quantitative techniques as it gives challenges and opportunities to new advancements. The practical implementation of computational modeling must rely on an epidemiological model. Computational models can supplement test and clinical investigations, social media users, and yet additionally challenge current paradigms, redefine our understanding of mechanism driving epidemic, and shape future research in public health policies, and provide the number of techniques to contr ol all kinds of epidemic diseases.

The study of epidemic disease is the investigation and examination of the distribution determining the factors of epidemic diseases in a population. This way, computational modeling demonstrates to epidemiology explore by helping to elucidate the mechanism and by giving quantitative predictions that can be validated.

9.1.1 INTRODUCTION TO COMPUTATIONAL MODELING

GTA, Need for Speed, Counter-Strike, PUBG, Call of Duty; Don’t these names sound familiar to you? Yes, these are among the top-most games played in the world, which almost everyone knows. These games somewhat give us the “Reality Experience!” We all enjoy playing these, don’t we, but have you ever pondered on this fact, that ‘How?’ How are these games so well built? How is everything made in an organized manner? How is the reflex action taking place when you enter a command? Well, these games use computational modeling and are examples of the same. Not just these, there are a lot many things that use this method. So, what is computational modeling?

Well, these games use computational modeling and are perfect examples of the same. Not just these, there are a lot of many things that use this method. So, what is computational modeling? A computational model, computer- based system that forms a direct link or a joint between mathematics and computer science, used to cany out the complex operations of mathematics with the help of computer simulation. Computational modeling is about two critical topics, which are vital for the functioning of the computational model: mathematics and computer.

“For the things of this world cannot be made without a knowledge of mathematics”—Roger Bacon Mathematics, veiy well known, an integral part of modem civilization, is a subject that nurtures a lot, many qualities of a person like a way of thinking, understanding, logical reasoning, creativity, problem-solving skills, spatial thinking, social experiences, and many more.

In simple terms, representation of the problems in mathematics to know the behavior of that problem quantitatively is mathematical modeling.

“The computer was bom to solve problems that did not exist before”— Bill Gates. Computer technology makes business and other fields faster and easier. It also provided all the students (needy ones and the disabled ones) a better tool to become familiar with the various skills (basic, master, and advanced) required for performing the tasks. Due to this, computational science has reached its height where understanding and solution of complex problems become veiy easy with the help of advanced computing capabilities. It is an interdisciplinary approach, including mathematics, computer science, biology, and psychology, forming a core link between the model development and simulation to understand the behavior of natural systems. Now, corning back, as said earlier, the computational modeling method is a way we interconnect technology with mathematics to solve real-life problems.

9.1.2 INTRODUCTION TO EPIDEMIOLOGY AND IMPORTANCE

Epidemiology is a Greek word derived from “epi,” which means on or upon, “demos,” which means people, and “logos,” which means the study of, provided the meaning of the word as the study of study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems [1]. To determine the number of disease cases in a particular area during a specific period is the main aim of epidemiology [2]. Frequency and the health events pattern in a population are the main determinants of epidemiology. It means how often disease occurs in a community to that of the size of the people.

Pattern refers to the happening of a series of health-related events by time, person, and place. Epidemiology is an essential part of the fundamental illustration of a particular disease. Epidemiological studies are used as a template description to prevent illness. It also helps in the management of a patient, who has already developed an infection. Risk factor identification in the food production system by representing critical control points is the importance of epidemiology [3]. One more impact factor of epidemiology is high accuracy in the diagnostic procedures helpful to both the patient for the reduction in risk factors and also to the physician for providing the appropriate medication [4].

9.1.3 INTRODUCTION TO SOCIAL NETWORKS

Social networking is a relatively modem advancement in science. A social network is a chain of entities (such as friends, colleagues, and partners) connected by antisocial connections. Social networking is an excellent form of fun, is a place for finding and meeting human beings with similar interests and ideas, and is useful for connecting and staying in touch with old friends/colleagues. It is also a usefiil promotional tool because of businesspeople, entrepreneurs, writers, actors, musicians, and artists. It is a committed Internet site, which permits users after talking together with every other by way of posting information, comments, messages, images, etc. It is the use of Internet-based social media applications to rearrange connections with friends, family, classmates, and clients. Social networking can occur for social purposes, business purposes or both through sites such as Facebook, Twitter, Linkedln, Bebo, Classmates, Instagrarn, MySpace, Path, Pinterest, Reddit, Stumble Upon, Tumblr, Yik Yak, YouTube, and Yelp. Perhaps, the easiest way to understand social networking is to think of it like high school. An online social network is a meeting place for individuals to expand their range and remain in contact with their associations. Person- to-person communication is not a static thing. Systems are developing and constantly changing, with new ones flying up at a quick rate. Many systems’ administration sites are outfitted toward users with particular interests and needs, while others wish everybody to join. Many individuals join a social network as long as their loved ones are utilizing the application, and they need to remain in contact. Once you have been using a social network site for some time, you will undoubtedly interact with other individuals you know or knew long before. These networks are fantastic spots to make up for lost tune with old companions and to share current and old photographs, and find different companions whom you may have lost contact with a journey. Experts have dependably organized somehow. Regardless of whether it is a conference, a gathering, or a significant industry occasion, meeting other individuals facing a similar situation is a need. Social networks, particularly those like Linkedln that take into account organizations and experts, give another stage to meet carriers and compelling individuals in the business. Given the fast growth over conventional networks within the advent years, the gradual increase regarding the Internet is now forming itself around the characteristics of associative networks.

LITERATURE REVIEW

In today’s world, the healthcare environment needs experimentally proved evidence for better decision making process. The literature review provides a fundamental background knowledge that answers many health-related questions. It includes the prevalence of particular in the next upcoming years, cause of illness, risk factors associated with the disease, treatment patterns, and the effectiveness of treatment.

Kumar et al. [53], done a meta-analysis of 233 studies on Dengue and reported 180 reviews as a confirmed Dengue infection and 77 as a fatal case. Harder et al. [54] performed 12 studies, of which six were applicable for meta-analysis, and the conclusion drawn was the significant increase in the chickenpox of those cases that have not done any prior vaccination of varicella. Likewise, many more diseases were reviewed and analyzed. Even the process of study of disease is continuing, the prevention and cure of different types of conditions, including rare diseases, makes the entire world foil of healthy people.

Thakare et al. [44] explained the improved SIR model for epidemic control in a social network. It gives better realistic simulation results by considering crowding or protective effect. The efficiency of the model can be analyzed in social subnetworks with some potential immunization strategies. It includes a random set immunization, dominating set immunization, and high degree set immunization. Woo et al. [40] presented the SIR model of diffusion in web forums. It is used to analyze disease outbreaks. Evaluation of model occurs on a large longitudinal dataset from the web forum of a major retail company. The fitting results showed that the SIR model is a plausible model to describe the diffusion process of a topic. The research showed that epidemic models could expand their application areas to topic discussion on the web, particularly social media such as web forums. Wang and Wang [41] proposed a novel SIR model to study minor spreading. They did by taking the influence of the social network into consideration. They found that the influence of the network medium on homogeneous networks is greater than on inhomogeneous networks. They performed numerical simulations which showed that minor spreading accelerates with an increase of the infectivity between persons and the network medium. Cannarella and Spechler [55] applied a modified epidemiological model to outline the acceptance and disused progress of online social networks by active users. They validated the proposed infectious recovery SIR model (irSIR model). In addition, the usage of publicly available Google enquires question facts for MySpace. Then, that applies the irSIR model in conformity with ask query data because of “Facebook,” which confirmed the instance regarding a disused phase. Extrapolating the superior in shape model predicts a rapid decline in Facebook recreation into the next few years. Sotoodeh et al. [46] proposed a general compaitmental information diffusion model and extracted some of the parameters which are beneficial to analyze the model. To the acceptance of a deterministic maimer to stochastic one, the Markovian property has been used to find out transition probability. Then, the probability obtained has been applied to get the mean value of the population per each group. Wei et al. [47] proposed a general compaitmental information diffusion model and extracted some of the parameters that are beneficial to analyze the model. To the acceptance of a deterministic maimer to stochastic one, the Markovian property has been used to find out transition probability. Then, the probability obtained has been applied to get the mean value of the population per each group. Medianama [56] calculated that WhatsApp customers in India use the video calling feature for a complete of 50 million minutes per day, the highest aggregate usage inside the global, in keeping with the enterprise. Singh [57] told about WhatsApp users in India that about 200 million people are actively using this app in India.

 
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