The Effect of Super-spreader Events in Epidemics
The spread of infectious epidemics is often accelerated by super-spreader events. Understanding their effect is important, particularly in the context of standard epidemiological models, which require estimates for parameters such as $R_0$. In this letter, we show that the effective value of $R_0$ in super-spreader situations is significantly large, of the order of hundreds, suggesting a delta-function-like behavior during the event. Use of a well-mixed room model supports these findings. They elucidate infection kinetic modeling in enclosed environments, which differ from the standard SIR model, and provide expressions for $R_0$ in terms of physical and operational parameters. The overall impact of super-spreader events can be significant, depending on the state of the epidemic and how the infections generated by the event subsequently spread in the community.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Contact Tracing & Super-Spreaders in the Branching-Process Model
In recent years, it became clear that super-spreader events play an important role, particularly in the spread of airborne infections. We investigate a novel model for super-spreader events, not based on a heterogeneous …
Top influencers can be identified universally by combining classical centralities
Information flow, opinion, and epidemics spread over structured networks. When using individual node centrality indicators to predict which nodes will be among the top influencers or spreaders in a large network, no sing…
Deep Demixing: Reconstructing the Evolution of Network Epidemics
We propose the deep demixing (DDmix) model, a graph autoencoder that can reconstruct epidemics evolving over networks from partial or aggregated temporal information. Assuming knowledge of the network topology but not of…
Modeling contact networks of patients and MRSA spread in Swedish hospitals
Methicillin-resistant Staphylococcus aureus (MRSA) is a difficult-to-treat infection that only in the European Union affects about 150,000 patients and causes extra costs of 380 million Euros annually to the health-care …
Propagation and mitigation of epidemics in a scale-free network
The epidemic curve and the final extent of the COVID-19 pandemic are usually predicted from the rate of early exponential raising using the SIR model. These predictions implicitly assume a full social mixing, which is no…