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.

Input: Consider Input: The Tasmanian devil (Sarcophilus harrisii), so named for its blood-curdling, nocturnal shrieks and snarls, is the largest of the carnivorous marsupials. Although once widely persecuted, concerted efforts are now being made to save the devil from extinction following the emergence of a fatal transmissible malignancy known as devil facial tumour disease (DFTD). DFTD is unusual in that the infectious agent is the cancer cell itself. This chapter discusses the aetiology and pathogenesis of DFTD as well as the profound impact the spread of DFTD has had on the devil's conservation status. Strategies for managing DFTD and conserving the devil will be explored and the contribution of new sequencing technology to the field of conservation genetics and genomics will be examined with regard to the Tasmanian devil and DFTD.

Output: Devil Facial Tumour Disease (DFTD): Using Genetics and Genomics to Investigate Infectious Disease in an Endangered Marsupial

Input: Consider Input: Most pandemics-eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenzaoriginate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption.

Output: Prediction and prevention of the next pandemic zoonosis

Input: Consider Input: A review of some methods for analysis of space-time disease surveillance data is presented. Increasingly, surveillance systems are capturing spatial and temporal data on disease and health outcomes in a variety of public health contexts. A vast and growing suite of methods exists for detection of outbreaks and trends in surveillance data and the selection of appropriate methods in a given surveillance context is not always clear. While most reviews of methods focus on algorithm performance, in practice, a variety of factors determine what methods are appropriate for surveillance. In this review, we focus on the role of contextual factors such as scale, scope, surveillance objective, disease characteristics, and technical issues in relation to commonly used approaches to surveillance. Methods are classified as testing-based or model-based approaches. Reviewing methods in the context of factors other than algorithm performance highlights important aspects of implementing and selecting appropriate disease surveillance methods.
Output: Review of methods for space-time disease surveillance