Related papers: A Visual Analytics Based Decision Making Environme…

In response to the ongoing pandemic and health emergency of COVID-19, several models have been used to understand the dynamics of virus spread. Some employ mathematical models like the compartmental SEIHRD approach and others rely on…

The emergence of Covid-19 requires new effective tools for epidemiological surveillance. Spatio-temporal disease mapping models, which allow dealing with highly disaggregated spatial and temporal units of analysis, are a priority in this…

The coronavirus disease 2019 (COVID-19) pandemic has been ongoing for around 3 years, and has infected over 750 million people and caused over 6 million deaths worldwide at the time of writing. Throughout the pandemic, several strategies…

Raw data on the cumulative number of deaths at a country level generally indicate a spatially variable distribution of the incidence of COVID-19 disease. An important issue is to determine whether this spatial pattern is a consequence of…

For hospitals, realistic forecasting of bed demand during impending epidemics of infectious diseases is essential to avoid being overwhelmed by a potential sudden increase in the number of admitted patients. Short-term forecasting can aid…

We apply topological data analysis, specifically the Mapper algorithm, to the U.S. COVID-19 data. The resulting Mapper graphs provide visualizations of the pandemic that are more complete than those supplied by other, more standard methods.…

Objective. The COVID-19 pandemic has threatened to collapse hospital and ICU services, and it has affected the care programs for non-COVID patients. The objective was to develop a mathematical model designed to optimize predictions related…

What is the impact of COVID-19 on South Africa? This paper envisages assisting researchers and decision-makers in battling the COVID-19 pandemic focusing on South Africa. This paper focuses on the spread of the disease by applying heatmap…

This regularly updated survey provides an overview of public resources that offer medical images and metadata of COVID-19 cases. The purpose of this survey is to simplify the access to open COVID-19 image data resources for all scientists…

Pandemic control measures like lock-down, restrictions on restaurants and gatherings, social-distancing have shown to be effective in curtailing the spread of COVID-19. However, their sustained enforcement has negative economic effects. To…

The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and containment strategies.…

Policy responses to COVID-19, particularly those related to non-pharmaceutical interventions, are unprecedented in scale and scope. Epidemiologists are more involved in policy decisions and evidence generation than ever before. However,…

During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although…

Maps have played an important role in epidemiology and public health since the beginnings of these disciplines. With the advent of geographical information systems and advanced information visualization techniques, interactive maps have…

The visual modeling method enables flexible interactions with rich graphical depictions of data and supports the exploration of the complexities of epidemiological analysis. However, most epidemiology visualizations do not support the…

The COVID-19 pandemic and the implementation of social distancing policies have rapidly changed people's visiting patterns, as reflected in mobility data that tracks mobility traffic using location trackers on cell phones. However, the…

Dashboards have arguably been the most used visualizations during the COVID-19 pandemic. They were used to communicate its evolution to national governments for disaster mitigation, to the public domain to inform about its status, and to…

Phenomenological and deterministic models are often used for the estimation of transmission parameters in an epidemic and for the prediction of its growth trajectory. Such analyses are usually based on single peak outbreak dynamics. In…

The COVID-19 pandemic prompted a surge in computational models to simulate disease dynamics and guide interventions. Agent-based models (ABMs) are well-suited to capture population and environmental heterogeneity, but their rapid deployment…

To mitigate the spread of COVID-19 pandemic, decision-makers and public authorities have announced various non-pharmaceutical policies. Analyzing the causal impact of these policies in reducing the spread of COVID-19 is important for future…