Stochastic modeling, analysis, and simulation of the COVID-19 pandemic with explicit behavioral changes in Bogotá: A case study.

In this paper, a stochastic epidemiological model is presented as an extension of a compartmental SEIR model with random perturbations to analyze the dynamics of the COVID-19 pandemic in the city of Bogotá D.C., Colombia. This model incorporates the spread of COVID-19 impacted by social behaviors in the population and allows for projecting the number of infected, recovered, and deceased individuals considering the mitigation measures, namely confinement and partial relaxed restrictions. Also, the role of randomness using the concept of Brownian motion is emphasized to explain the behavior of the population. Computational experiments for the stochastic model with random perturbations were performed, and the model is validated through numerical simulations for actual data from Bogotá D.C.

The Hard Lessons and Shifting Modeling Trends of COVID-19 Dynamics: Multiresolution Modeling Approach.

The COVID-19 pandemic has placed epidemiologists, modelers, and policy makers at the forefront of the global discussion of how to control the spread of coronavirus. The main challenges confronting modelling approaches include real-time projections of changes in the numbers of cases, hospitalizations, and fatalities, the consequences of public health policy, the understanding of how best to implement varied non-pharmaceutical interventions and potential vaccination strategies, now that vaccines are available for distribution. Here, we: (i) review carefully selected literature on COVID-19 modeling to identify challenges associated with developing appropriate models along with collecting the fine-tuned data, (ii) use the identified challenges to suggest prospective modeling frameworks through which adaptive interventions such as vaccine strategies and the uses of diagnostic tests can be evaluated, and (iii) provide a novel Multiresolution Modeling Framework which constructs a multi-objective optimization problem by considering relevant stakeholders' participatory perspective to carry out epidemic nowcasting and future prediction. Consolidating our understanding of model approaches to COVID-19 will assist policy makers in designing interventions that are not only maximally effective but also economically beneficial.

When Triggers Become Tigers: Taming the Autonomic Nervous System via Sensory Support System Modulation.

Personalized recovery technologies may enable individuals with Substance Use Disorder (SUD) to monitor and manage acute craving and drug use urges in ways that improve drug-seeking decisions in real-time. Direct and indirect regulation of the autonomic nervous system through sensory input monitoring and modulation may enhance control over behavioral decisions and prevent relapse. A personalized sensory support system that monitors neurophysiological reactivity and offers non-pharmacological point-in-time personalized digital interventions may increase awareness of and control over craving reactivity. It is critical to be able to detect these warning signs and intervene early and effectively. The use of wearable technologies that assess point-in-time neurophysiological escalation and shape behavioral response through personalized interventions could be transformative in allowing individuals to better manage their recovery as they transition out of institutions and move back into community settings.

Challenges and Opportunities From COVID-19 for Global Sustainable Development.

We live in unprecedented times, faced with a pandemic of monumental proportions. Not only has COVID-19 wreaked havoc across the world, it also has exposed fundamental weaknesses in healthcare systems in a number of countries. We identify challenges and opportunities that COVID-19 presents by connecting the immediate need to curb the spread of the disease to the United Nations sustainable development goals (SDGs). Considering broad social, political, and economic impacts, we focus on health disparities and the severe effects of the crisis on some populations, especially disadvantaged and underserved ones, and countries relative to others. In particular, we identify key targets for achieving SDG-3 (Good Health and Wellbeing) that will help strengthen capacities for scaling up healthcare and policy responses to understand, combat, and control COVID-19.