Stay with your community: Bridges between clusters trigger expansion of COVID-19

Abstract

In this study, the spread of virus infection was simulated using artificial human networks. Here, real-space urban life was modeled as a modified scale-free network with constraints. To date, the scale-free network has been adopted for modeling online communities in several studies. However, in the present study, it has been modified to represent the social behaviors of people where the generated communities are restricted and reflect spatiotemporal constraints in real life. Furthermore, the networks have been extended by introducing multiple cliques in the initial step of network construction and enabling people to contact hidden (zero-degree) as well as popular (large-degree) people. Consequently, four findings and a policy proposal were obtained. First, “second waves” were observed in some cases of the simulations even without external influence or constraints on people’s social contacts or the releasing of the constraints. These waves tend to be lower than the first wave and occur in “fresh” clusters, that is, via the infection of people who are connected in the network but have not been infected previously. This implies that the bridge between infected and fresh clusters may trigger a new spread of the virus. Second, if the network changes its structure on the way of infection spread or after its suppression, a second wave larger than the first can occur. Third, the peak height in the time series of the number of infected cases depends on the difference between the upper bound of the number of people each member actually meets and the number of people they choose to meet during the period of infection spread. This tendency is observed for the two kinds of artificial networks introduced here and implies the impact of bridges between communities on the virus spreading. Fourth, the release of a previously imposed constraint may trigger a second wave higher than the peak of the time series without introducing any constraint so far previously, if the release is introduced at a time close to the peak. Thus, overall, both the government and individuals should be careful in returning to society where people enjoy free inter-community contact.

Estimation of Real-World Vaccination Effectiveness of mRNA COVID-19 Vaccines against Delta and Omicron Variants in Japan

“…Another reason for this discrepancy is the PEV for individuals ≥65 years of age, which was higher than that for individuals <65 years of age (see Figure 2 b). This different tendency can be hypothesized in terms of community [ 25 ]: the percentage of infected people ≥65 years would be lower due to a higher vaccination rate. Another potential bias is the population younger than 12 years, for whom the vaccination was not yet licensed.…”

Did the Tokyo Olympic Games enhance the transmission of COVID-19? An interpretation with machine learning

“…In Ref. [ 42 ], it has been modified to represent the social behaviors of people where the generated communities are restricted and reflect spatiotemporal constraints in real life. They concluded that the bridge between infected and fresh clusters may trigger new virus spread.…”

The Actual Conditions of Person-to-Object Contact and a Proposal for Prevention Measures During the COVID-19 Pandemic

“…However, locations with high ρ values-places with few users but many contact objects-are where users share the same spaces (locations and vehicles) both directly and indirectly, which increases the chances of contact with an unspecified number of people. From the perspective of remaining within an inter-community to prevent infection spread (Ohsawa and Tsubokura, 2020), we should avoid these places and refrain from contacting the objects there.…”

“…Third, this study detailed measures to be taken at each location through a discussion about the risk of infection through inanimate surfaces based on the objects that participants came into contact with. As with studies on the simulation of infection control (Ohsawa and Tsubokura, 2020) or measurement of household water insecurity (Stoler et al, 2020), this study does not investigate infected individuals or SARS-CoV-2 RNA directly, but provides useful insights into COVID-19 control and prevention measures.…”