Super-spreader

About: Super-spreader is a research topic. Over the lifetime, 4 publications have been published within this topic receiving 1931 citations.

Superspreading and the effect of individual variation on disease emergence

Abstract: Population-level analyses often use average quantities to describe heterogeneous systems, particularly when variation does not arise from identifiable groups. A prominent example, central to our current understanding of epidemic spread, is the basic reproductive number, R(0), which is defined as the mean number of infections caused by an infected individual in a susceptible population. Population estimates of R(0) can obscure considerable individual variation in infectiousness, as highlighted during the global emergence of severe acute respiratory syndrome (SARS) by numerous 'superspreading events' in which certain individuals infected unusually large numbers of secondary cases. For diseases transmitted by non-sexual direct contacts, such as SARS or smallpox, individual variation is difficult to measure empirically, and thus its importance for outbreak dynamics has been unclear. Here we present an integrated theoretical and statistical analysis of the influence of individual variation in infectiousness on disease emergence. Using contact tracing data from eight directly transmitted diseases, we show that the distribution of individual infectiousness around R(0) is often highly skewed. Model predictions accounting for this variation differ sharply from average-based approaches, with disease extinction more likely and outbreaks rarer but more explosive. Using these models, we explore implications for outbreak control, showing that individual-specific control measures outperform population-wide measures. Moreover, the dramatic improvements achieved through targeted control policies emphasize the need to identify predictive correlates of higher infectiousness. Our findings indicate that superspreading is a normal feature of disease spread, and to frame ongoing discussion we propose a rigorous definition for superspreading events and a method to predict their frequency.

Why is herd immunity so important

Abstract: Herd immunity, also called community immunity, occurs when a sufficient portion of a population is immune to a specific disease, thereby protecting individuals who have not developed immunity. The greater the proportion of a population that is immune or less susceptible to a disease, the lower the

A Framework for Sandboxing of Pandemic Spread

Abstract: Pandemic disease, like Corona spreading by social contacts, needs “lockdown”, a measure to limit the virus spread. But the measure is too expensive for a nation for its adverse impact on national economy. Sandboxing followed in system security is a proactive and resilient mechanism that allows a system to function either in full or partial capacity without compromising its security. Similarly, in order to limit a community spread with resilience, a proactive mechanism is required to predict and safeguard the area that is the most vulnerable to a pandemic disease infection and has the potential of a super spreader resulting to a community spread. The early care of the region may protect it from a community spread of an infection. Social analytics on immunity and connectivity are proposed in this research paper to predict the vulnerable regions. Based on this idea, a tool is under development and this paper presents a framework of the tool.