The recent COVID-19 pandemic has propelled the field of aerosol science to the forefront, particularly the central role of virus-laden respiratory droplets and aerosols. The pandemic has also highlighted the critical need, and value for, an information bridge between epidemiological models (that inform policymakers to develop public health responses) and within-host models (that inform the public and health care providers how individuals develop respiratory infections). Here, we review existing data and models of generation of respiratory droplets and aerosols, their exhalation and inhalation, and the fate of infectious droplet transport and deposition throughout the respiratory tract. We then articulate how aerosol transport modeling can serve as a bridge between and guide calibration of within-host and epidemiological models, forming a comprehensive tool to formulate and test hypotheses about respiratory tract exposure and infection within and between individuals.
more »
« less
Physicochemical properties of respiratory droplets and their role in COVID-19 pandemics: a critical review
The ongoing coronavirus disease 2019 (COVID-19) pandemic is a serious challenge faced by the global community. Physical scientists can help medical workers and biomedical scientists, engineers, and practitioners, who are working on the front line, to slow down and eventually contain the spread of the COVID-19 virus. This review is focused on the physicochemical characteristics, including composition, aerodynamics, and drying behavior of respiratory droplets as a complex and multicomponent soft matter system, which are the main carrier of the virus for interpersonal transmission. The distribution and dynamics of virus particles within a droplet are also discussed. Understanding the characteristics of virus-laden respiratory droplets can lead to better design of personal protective equipment, frequently touched surfaces such as door knobs and touchscreens, and filtering equipment for indoor air circulation. Such an understanding also provides the scientific basis of public policy, including social distancing rules and public hygiene guidelines, implemented by governments around the world.
more »
« less
- Award ID(s):
- 1944887
- PAR ID:
- 10284302
- Date Published:
- Journal Name:
- Biomaterials translational
- Volume:
- 2
- Issue:
- 1
- ISSN:
- 2096-112X
- Page Range / eLocation ID:
- 10-18
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The COVID-19 pandemic has revealed critical knowledge gaps in our understanding of and a need to update the traditional view of transmission pathways for respiratory viruses. The long-standing definitions of droplet and airborne transmission do not account for the mechanisms by which virus-laden respiratory droplets and aerosols travel through the air and lead to infection. In this Review, we discuss current evidence regarding the transmission of respiratory viruses by aerosols—how they are generated, transported, and deposited, as well as the factors affecting the relative contributions of droplet-spray deposition versus aerosol inhalation as modes of transmission. Improved understanding of aerosol transmission brought about by studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection requires a reevaluation of the major transmission pathways for other respiratory viruses, which will allow better-informed controls to reduce airborne transmission.more » « less
-
At the end of 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel human coronavirus, emerged and rapidly caused a global pandemic. SARS-CoV-2 is the causative agent of coronavirus disease 2019 (COVID-19), which affects the respiratory tract and lungs of infected individuals. Due to the increased transmissibility of the SARS-CoV-2 virus compared to its previous versions, determining as fully as possible the various structural aspects of the virus became critical for the development of therapeutics and vaccines to combat this virus. Knowing the structures of viral proteins and their glycosylation is an essential foundation for the understanding of the mechanism of the disease. Glycopeptide analysis has been used to map the glycosylation of viral glycoproteins, including those of influenza and HIV. Thanks to the developments in the field over the last few decades, scientists were able to quickly develop therapeutics against SARS-CoV-2. This chapter discusses the four structural proteins of SARS-CoV-2, their glycosylation and modifications, and the techniques used to map SARS-CoV-2 glycosylation.more » « less
-
Abstract. The longer the COVID-19 pandemic lasts, the more apparent it becomes that understanding its social drivers may be as important as understanding the virus itself. One such social driver is misinformation and distrust in institutions. This is particularly interesting as the scientific process is more transparent than ever before. Numerous scientific teams have published datasets that cover almost any imaginable aspects of COVID-19 during the last two years. However, consistently and efficiently integrating and making sense of these separate data “silos” to scientists, decision makers, journalists, and more importantly the general public remain a key challenge with important implications for transparency. Several types of knowledge graphs have been published to tackle this issue and to enable data crosswalks by providing rich contextual information. Interestingly, none of these graphs has focused on COVID-19 forecasts despite them acting as the underpinning for decision making. In this work we motivate the need for exposing forecasts as a knowledge graph, showcase queries that run against the graph, and geographically interlink forecasts with indicators of economic impacts.more » « less
-
null (Ed.)The coronavirus disease 2019 (COVID-19) pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has placed epidemic modeling at the center of attention of public policymaking. Predicting the severity and speed of transmission of COVID-19 is crucial to resource management and developing strategies to deal with this epidemic. Based on the available data from current and previous outbreaks, many efforts have been made to develop epidemiological models, including statistical models, computer simulations, mathematical representations of the virus and its impacts, and many more. Despite their usefulness, modeling and forecasting the spread of COVID-19 remains a challenge. In this article, we give an overview of the unique features and issues of COVID-19 data and how they impact epidemic modeling and projection. In addition, we illustrate how various models could be connected to each other. Moreover, we provide new data science perspectives on the challenges of COVID-19 forecasting, from data collection, curation, and validation to the limitations of models, as well as the uncertainty of the forecast. Finally, we discuss some data science practices that are crucial to more robust and accurate epidemic forecasting.more » « less
An official website of the United States government

