In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Since the first imported case of Middle East respiratory syndrome coronavirus (MERS-CoV) infection was reported on May 20, 2015 in Korea, there have been 186 laboratoryconfirmed cases of MERS-CoV infection with 36 fatalities. Ninety-seven percent (181/186) of the cases had exposure to the health care facilities. We are reporting a superspreading event that transmitted MERS-CoV to 81 persons at a hospital emergency room (ER) during the Korean outbreak in 2015. The index case was a 35-yr-old man who had vigorous coughing while staying at the ER for 58 hr. As in severe acute respiratory syndrome outbreaks, superspreading events can cause a large outbreak of MERS in healthcare facilities with severe consequences. All healthcare facilities should establish and implement infection prevention and control measure as well as triage policies and procedures for early detection and isolation of suspected MERS-CoV cases.
Middle East Respiratory Syndrome Coronavirus Superspreading Event Involving 81 Persons, Korea 2015

Background: Disaster is a serious public health issue. Health professionals and community residents are main players in disaster responses but their knowledge levels of disaster medicine are not readily available. This study aimed to evaluate knowledge levels and training needs of disaster medicine among potential disaster responders and presented a necessity to popularize disaster medicine education. Methods: A self-reporting questionnaire survey on knowledge level and training needs of disaster medicine was conducted in Shanghai, China, in 2012. A total of randomly selected 547 health professionals, 456 medical students, and 1,526 local residents provided intact information. The total response rate was 93.7%. Results: Overall, 1.3% of these participants have received systematic disaster medicine training. News media (87.1%) was the most common channel to acquire disaster medicine knowledge. Although health professionals were more knowledgeable than community residents, their knowledge structure of disaster medicine was not intact. Medical teachers were more knowledgeable than medical practitioners and health administrators (p = 0.002). Clinicians performed better than public health physicians (p,0.001), whereas public health students performed better than clinical medical students (p,0.001). In community residents, education background significantly affected the knowledge level on disaster medicine (p,0.001). Training needs of disaster medicine were generally high among the surveyed. 'Lecture' and 'practical training' were preferred teaching methods. The selected key and interested contents on disaster medicine training were similar between health professionals and medical students, while the priorities chosen by local residents were quite different from health professionals and medical students (p,0.001). Conclusions: Traditional clinical-oriented medical education might lead to a huge gap between the knowledge level on disaster medicine and the current needs of disaster preparedness. Continuing medical education and public education plans on disaster medicine via media should be practice-oriented, and selectively applied to different populations and take the knowledge levels and training needs into consideration.
Knowledge Levels and Training Needs of Disaster Medicine among Health Professionals, Medical Students, and Local Residents in Shanghai, China

Contact networks are convenient models to investigate epidemics, with nodes and links representing potential hosts and infection pathways, respectively. The outcomes of outbreak simulations on networks are driven both by the underlying epidemic model, and by the networks' structural properties, so that the same pathogen can generate different epidemic dynamics on different networks. Here we ask whether there are general properties that make a contact network intrinsically vulnerable to epidemics (that is, regardless of specific epidemiological parameters). By conducting simulations on a large set of modelled networks, we show that, when a broad range of network topologies is taken into account, the effect of specific network properties on outbreak magnitude is stronger than that of fundamental pathogen features such as transmission rate, infection duration, and immunization ability. Then, by focusing on a large set of real world networks of the same type (potential contacts between field voles, Microtus agrestis), we showed how network structure can be used to accurately assess the relative, intrinsic vulnerability of networks towards a specific pathogen, even when those have limited topological variability. These results have profound implications for how we prevent disease outbreaks; in many real world situations, the topology of host contact networks can be described and used to infer intrinsic vulnerability. Such an approach can increase preparedness and inform preventive measures against emerging diseases for which limited epidemiological information is available, enabling the identification of priority targets before an epidemic event.

The intrinsic vulnerability of networks to epidemics