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A model with six mutually-exclusive compartments related to Dengue disease is presented. In this model there are three vector control tools: insecticides (larvicide and adulticide) and mechanical control. The problem is studied using an…
The problems of selecting partial correlation and causality graphs for count data are considered. A parameter driven generalized linear model is used to describe the observed multivariate time series of counts. Partial correlation and…
Trending topics are the online conversations that grab collective attention on social media. They are continually changing and often reflect exogenous events that happen in the real world. Trends are localized in space and time as they are…
Bangladesh's worsening dengue crisis, fueled by its tropical climate, poor waste management infrastructure, rapid urbanization, and dense population, has led to increasingly deadly outbreaks, posing a significant public health threat. To…
Emerging wireless technologies, such as 5G and beyond, are bringing new use cases to the forefront, one of the most prominent being machine learning empowered health care. One of the notable modern medical concerns that impose an immense…
We analyze over 500 million Twitter messages from an eight month period and find that tracking a small number of flu-related keywords allows us to forecast future influenza rates with high accuracy, obtaining a 95% correlation with national…
Influenza, an infectious disease, causes many deaths worldwide. Predicting influenza victims during epidemics is an important task for clinical, hospital, and community outbreak preparation. On-line user-generated contents (UGC), primarily…
This paper presents a predictive model for Influenza-Like-Illness, based on Twitter traffic. We gather data from Twitter based on a set of keywords used in the Influenza wikipedia page, and perform feature selection over all words used in 3…
Many real networks are not isolated from each other but form networks of networks, often interrelated in non trivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop…
Background: Guillain-Barr\'e Syndrome (GBS) is a common type of severe acute paralytic neuropathy and associated with other virus infections such as dengue fever and Zika. This study investigate the relationship between GBS, dengue, local…
Online tracking has become of increasing concern in recent years, however our understanding of its extent to date has been limited to snapshots from web crawls. Previous at-tempts to measure the tracking ecosystem, have been done using…
Among all animals, mosquitoes are responsible for the most deaths worldwide. Interestingly, not all types of mosquitoes spread diseases, but rather, a select few alone are competent enough to do so. In the case of any disease outbreak, an…
`Tracking' is the collection of data about an individual's activity across multiple distinct contexts and the retention, use, or sharing of data derived from that activity outside the context in which it occurred. This paper aims to…
We construct an epidemic model for the transmission of dengue fever with an early-life stage in the vector dynamics and age-structure within hosts. The early-life stage of the vector is modeled via a general function that supports multiple…
Conventional surveillance systems for monitoring infectious diseases, such as influenza, face challenges due to shortage of skilled healthcare professionals, remoteness of communities and absence of communication infrastructures.…
Wandering is a problematic behavior in people with dementia that can lead to dangerous situations. To alleviate this problem we design an approach for the real-time automatic detection of wandering leading to getting lost. The approach…
The COVID-19 pandemic revealed that global health, social systems, and economies can be surprisingly fragile in an increasingly interconnected and interdependent world. Yet, during the last half of 2022, and quite remarkably, we began…
Previous research has demonstrated that various properties of infectious diseases can be inferred from online search behaviour. In this work we use time series of online search query frequencies to gain insights about the prevalence of…
Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and…
The Internet of Behavior is a research theme that aims to analyze human behavior data on the Internet from the perspective of behavioral psychology, obtain insights about human behavior, and better understand the intention behind the…