Network model findings could shape public health policy for airborne viruses – sciencedaily

Studies show that wearing masks and social distancing can contain the spread of the COVID-19 virus, but their combined effectiveness is not precisely known.

In chaos, by AIP Publishing, researchers at New York University and Politecnico di Torino in Italy have developed a network model to study the effects of these two measures on the spread of airborne diseases like COVID-19. The model shows that viral outbreaks can be prevented if at least 60% of the population comply with both measures.

“Neither social distancing nor wearing a mask alone is probably enough to stop the spread of COVID-19, unless almost all of the population adhere to the measure alone,” the said. author Maurizio Porfiri. “But if a significant fraction of the population adheres to both measures, the spread of the virus can be prevented without mass vaccination.”

A network model encompasses nodes, or data points, and edges or links between nodes. These models are used in applications ranging from marketing to monitoring bird migration. In the researchers’ model, based on a sensitive, exposed, infected or removed (recovered or deceased) framework, each node represents a person’s state of health. The edges represent potential contacts between pairs of individuals.

The model takes into account the variability of activity, which means that a few very active nodes are responsible for a large part of the network contacts. This reflects the validated hypothesis that most people have few interactions and only a few interact with many others. Scenarios involving social distancing without wearing a mask and vice versa were also tested by defining the measures as separate variables.

The model was inspired by cell phone mobility data and Facebook surveys obtained from the Institute for Health Metrics and Evaluation at the University of Washington. Data has shown that people who wear masks are also the ones who tend to reduce their mobility. Based on this premise, the knots were divided into individuals who regularly wear masks and socially distanced and those whose behavior remains largely unaffected by an outbreak or pandemic.

Using data collected by the New York Times to assess the effectiveness of the model, researchers analyzed cumulative cases per capita in all 50 states and the District of Columbia between July 14, 2020, when the Centers for Disease Control and Prevention officially recommended wearing a mask, until December 10.

In addition to showing the effects of the combination of mask wearing and social distancing, the model shows the critical need for widespread adherence to public health measures.

“The US states that suffered the most from infections last fall are also the states where people complied the least with public health guidelines, falling well above the epidemic threshold predicted by our model.” , said Porfiri.

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