Predicting Grocery Store Visits During the Early Outbreak of COVID-19 with Machine Learning.

While non-essential travel was canceled during the coronavirus infectious disease (COVID-19) pandemic, grocery shopping was essential. The objectives of this study were to: 1) examine how grocery store visits changed during the early outbreak of COVID-19, and 2) estimate a model to predict the change of grocery store visits in the future, within the same phase of the pandemic. The study period (February 15-May 31, 2020) covered the outbreak and phase-one re-opening.

How do Parents Manage Symptomatic Children? Social-Distancing Insights for COVID-19 and Seasonal Influenza.

Strategies for controlling pandemics include social distancing. Using data from a 2016 nation-wide survey pertaining to influenza, (generalized) ordered logit models are developed to identify the factors associated with the relative frequency (never/sometimes/always) a household (a) isolates a sick child from others in the household, (b) keeps the sick child out of school/daycare, (c) stops the child's social activities, (d) has a parent stay home to care for the child, and (e) has another adult care for the child. Marital status is non-significant for isolation practices but is significant in caregiving.

Influenza risk perception and travel-related health protection behavior in the US: Insights for the aftermath of the COVID-19 outbreak.

Influenza is a contagious virus affecting both one's health and economic productivity. This study evaluates uses a survey of 2168 individuals across the U.S.

Critical Time, Space, and Decision-Making Agent Considerations in Human-Centered Interdisciplinary Hurricane-Related Research.

In hazard and disaster contexts, human-centered approaches are promising for interdisciplinary research since humans and communities feature prominently in many definitions of disaster and the built environment is designed and constructed by humans to serve their needs. With a human-centered approach, the decision-making agent becomes a critical consideration. This article discusses and illustrates the need for alignment of decision-making agents, time, and space for interdisciplinary research on hurricanes, particularly evacuation and the immediate aftermath.

The Frontiers of Uncertainty Estimation in Interdisciplinary Disaster Research and Practice.

Conceptualizing, assessing, and managing disaster risks involve collecting and synthesizing pluralistic information-from natural, built, and human systems-to characterize disaster impacts and guide policy on effective resilience investments. Disaster research and practice, therefore, are highly complex and inherently interdisciplinary endeavors. Characterizing the uncertainties involved in interdisciplinary disaster research is imperative, since misrepresenting uncertainty can lead to myopic decisions and suboptimal societal outcomes.

Impact of demographic disparities in social distancing and vaccination on influenza epidemics in urban and rural regions of the United States.

Background: Self-protective behaviors of social distancing and vaccination uptake vary by demographics and affect the transmission dynamics of influenza in the United States. By incorporating the socio-behavioral differences in social distancing and vaccination uptake into mathematical models of influenza transmission dynamics, we can improve our estimates of epidemic outcomes. In this study we analyze the impact of demographic disparities in social distancing and vaccination on influenza epidemics in urban and rural regions of the United States.

Building an Interdisciplinary Team for Disaster Response Research: A Data-Driven Approach.

Building an interdisciplinary team is critical to disaster response research as it often deals with acute onset events, short decision horizons, constrained resources, and uncertainties related to rapidly unfolding response environments.  This article examines three teaming mechanisms for interdisciplinary disaster response research, including ad hoc and/or grant proposal driven teams, research center or institute based teams, and teams oriented by matching expertise toward long-term collaborations. Using hurricanes as the response context, it further examines several types of critical data that require interdisciplinary collaboration on collection, integration, and analysis.

The dynamic nature of risk perceptions after a fatal transit accident.

In 2009, two trains of Washington, DC's Metrorail system collided, resulting in nine deaths and 50 serious injuries. Based on a multiwave survey of Metrorail users in the months after the crash, this article reports how the accident appears to have (1) changed over time the tradeoffs among safety, speed, frequency of service, cost, and reliability that the transit users stated they were willing to make in the postaccident period and (2) altered transit users' concerns about safety as a function of time and distance from the accident site. We employ conditional logit models to examine tradeoffs among stated preferences for system performance measures after the accident, as well as the influence that respondent characteristics of transit use, location, income, age, and gender have on these preference tradeoffs.

Uniting multi-adult households during emergency evacuation planning.

When a no-notice emergency prompts an evacuation, family members in different locations throughout a city may unite so that they can evacuate as a group. This paper draws on data from more than 300 interviews conducted in the metropolitan area of Chicago, Illinois, United States. The study uses discrete choice models to analyse the expectations of respondents regarding whether their likely plans for evacuation involve gathering spouses, parents, adult-age children, and/or non-family members.