Related papers: Nowcasting Temporal Trends Using Indirect Surveys
The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is…
An information outbreak occurs on social media along with the COVID-19 pandemic and leads to infodemic. Predicting the popularity of online content, known as cascade prediction, allows for not only catching in advance hot information that…
Communication-enabled devices routinely carried by individuals have become pervasive, opening unprecedented opportunities for collecting digital metadata about the mobility of large populations. In this paper, we propose a novel methodology…
Implementing a lockdown for disease mitigation is a balancing act: Non-pharmaceutical interventions can reduce disease transmission significantly, but interventions also have considerable societal costs. Therefore, decision-makers need near…
The increasing availability of time --and space-- resolved data describing human activities and interactions gives insights into both static and dynamic properties of human behavior. In practice, nevertheless, real-world datasets can often…
The COVID-19 pandemic has created a sudden need for a wider uptake of home-based telework as means of sustaining the production. Generally, teleworking arrangements impacts directly worker's efficiency and motivation. The direction of this…
We address the problem of modeling constrained hospital resources in the midst of the COVID-19 pandemic in order to inform decision-makers of future demand and assess the societal value of possible interventions. For broad applicability, we…
Non-representative surveys are commonly used and widely available but suffer from selection bias that generally cannot be entirely eliminated using weighting techniques. Instead, we propose a Bayesian method to synthesize longitudinal…
Estimating the size of marginalized populations is a persistent challenge in survey statistics and public health, especially where stigma and legal restrictions exclude such groups from census and administrative data. Migrant domestic…
As the COVID-19 spread over the globe and new variants of COVID-19 keep occurring, reliable real-time forecasts of COVID-19 hospitalizations are critical for public health decision on medical resources allocations such as ICU beds,…
Analyzing large-scale time-series network data, such as social media and email communications, poses a significant challenge in understanding social dynamics, detecting anomalies, and predicting trends. In particular, the scalability of…
The ability to estimate current affective statuses of web users has considerable potential towards the realization of user-centric opportune services. However, determining the type of data to be used for such estimation as well as…
The unprecedented behavioural responses of societies have been evidently shaping the COVID-19 pandemic, yet it is a significant challenge to accurately monitor the continuously changing social mixing patterns in real-time. Contact matrices,…
As COVID-19 spread through the United States in 2020, states began to set up alert systems to inform policy decisions and serve as risk communication tools for the general public. Many of these systems, like in Ohio, included indicators…
As the interactions between people increases, the impending menace of COVID-19 outbreaks materialize, and there is an inclination to apply lockdowns. In this context, it is essential to have easy-to-use indicators for people to use as a…
All pandemics are local; so learning about the impacts of pandemics on public health and related societal issues at granular levels is of great interest. COVID-19 is affecting everyone in the globe and mask wearing is one of the few…
Respondent-Driven Sampling (RDS) is an approach to sampling design and inference in hard-to-reach human populations. Typically, a sampling frame is not available, and population members are difficult to identify or recruit from broader…
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…
Large quantities of social activity data, such as weekly web search volumes and the number of new infections with infectious diseases, reflect peoples' interests and activities. It is important to discover temporal patterns from such data…
Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national health authorities have set the 2-meter physical distancing as…