Behavioral manipulation-key to the successful global spread of the new coronavirus SARS-CoV-2?

Spatial risk for a superspreading environment: Insights from six urban facilities in six global cities across four continents

Introduction

This study sets out to provide scientific evidence on the spatial risk for the formation of a superspreading environment.

Methods

Focusing on six common types of urban facilities (bars, cinemas, gyms and fitness centers, places of worship, public libraries and shopping malls), it first tests whether visitors' mobility characteristics differ systematically for different types of facility and at different locations. The study collects detailed human mobility and other locational data in Chicago, Hong Kong, London, São Paulo, Seoul and Zurich. Then, considering facility agglomeration, visitors' profile and the density of the population, facilities are classified into four potential spatial risk (PSR) classes. Finally, a kernel density function is employed to derive the risk surface in each city based on the spatial risk class and nature of activities.

Results

Results of the human mobility analysis reflect the geographical and cultural context of various facilities, transport characteristics and people's lifestyle across cities. Consistent across the six global cities, geographical agglomeration is a risk factor for bars. For other urban facilities, the lack of agglomeration is a risk factor. Based on the spatial risk maps, some high-risk areas of superspreading are identified and discussed in each city.

Discussion

Integrating activity-travel patterns in risk models can help identify areas that attract highly mobile visitors and are conducive to superspreading. Based on the findings, this study proposes a place-based strategy of non-pharmaceutical interventions that balance the control of the pandemic and the daily life of the urban population.

A Simulation Study on Spread of Disease and Control Measures in Closed Population Using ABM

An infectious disease can cause a detrimental effect on national security. A group such as the military called a “closed population”, which is a subset of the general population but has many distinct characteristics, must survive even in the event of a pandemic. Hence, it requires its own distinct solution during a pandemic. In this study, we investigate a simulation analysis for implementing an agent-based model that reflects the characteristics of agents and the environment in a closed population and finds effective control measures for making the closed population functional in the course of disease spreading.

Non-pharmaceutical interventions during the COVID-19 pandemic: A review

Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travel bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.

Mass Events Trigger Malta's Second Peak After Initial Successful Pandemic Suppression

The second COVID-19 wave is sweeping the globe as restrictions are lifted. Malta, the ‘poster child of Europe’s COVID-19 first wave success’ also fell victim shortly after it welcomed the first tourists on 1st of July 2020. Only four positive cases were reported over the successive 15 days. Stability was disrupted when two major mass events were organized despite various health professional warnings. In a matter of few just days, daily cases rose to two-digit figures, with high community transmission, a drastic rise in active cases, and a rate per hundred thousand in Europe second only to Spain. Frontliners were swamped with swabbing requests while trying to sustain robust case management, contact tracing and follow-up. Indeed, the number of hospitalizations and the need for intensive ventilation increased. Despite the initial cases were among young adults, within weeks a small spill off on the more elderly population was observed. Restrictions were re-introduced including mandatory mask wearing in specific locations and capping of the total number of people in a single gathering. Malta is an island and the potential for containment would have been relatively simple and effective and permitting mass gatherings was unwise. Protecting the health of the population should take centre stage while carrying out extensive testing, contact tracing and surveillance. Containment and mitigation along with public cooperation is the key to curbing resurgences especially with the influenza season around the corner.