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.

Example Input: The performance of the new ePlex Respiratory Pathogen (RP) panel (GenMark Diagnostics) for the simultaneous detection of 19 viruses (influenza A virus; influenza A H1 virus; influenza A 2009 H1 virus; influenza A H3 virus; influenza B virus; adenovirus; coronaviruses [HKU1, OC43, NL63, and 229E]; human rhinovirus/enterovirus; human metapneumovirus; parainfluenza viruses 1, 2, 3, and 4; and respiratory syncytial virus [RSV] [RSV subtype A and RSV subtype B] ) and 2 bacteria (Mycoplasma pneumoniae and Chlamydia pneumoniae) was evaluated. Prospectively and retrospectively collected nasopharyngeal swab (NPS) specimens (n 2,908) were evaluated by using the ePlex RP panel, with the bioMerieux/BioFire FilmArray Respiratory Panel (BioFire RP) as the comparator method. Discordance analysis was performed by using target-specific PCRs and bidirectional sequencing. The reproducibility of the assay was evaluated by using reproducibility panels comprised of 6 pathogens. The overall agreement between the ePlex RP and BioFire RP results was 95% for all targets. Positive percent agreement with the BioFire RP result for viruses ranged from 85.1% (95% confidence interval [CI], 80.2% to 88.9%) to 95.1% (95% CI, 89.0% to 97.9%), while negative percent agreement values ranged from 99.5% (95% CI, 99.1% to 99.7%) to 99.8% (95% CI, 99.5% to 99.9%). Additional testing of discordant targets (12%; 349/2,908) confirmed the results of ePlex RP for 38% (131/349) of samples tested. Reproducibility was 100% for all targets tested, with the exception of adenovirus, for which reproducibilities were 91.6% at low virus concentrations and 100% at moderate virus concentrations. The ePlex RP panel offers a new, rapid, and sensitive "sample-to-answer" multiplex panel for the detection of the most common viral and bacterial respiratory pathogens.
Example Output: Multicenter Evaluation of the ePlex Respiratory Pathogen Panel for the Detection of Viral and Bacterial Respiratory Tract Pathogens in Nasopharyngeal Swabs

Example Input: The spread of infectious disease epidemics is mediated by human travel. Yet human mobility patterns vary substantially between countries and regions. Quantifying the frequency of travel and length of journeys in well-defined population is therefore critical for predicting the likely speed and pattern of spread of emerging infectious diseases, such as a new influenza pandemic. Here we present the results of a large population survey undertaken in 2007 in two areas of China: Shenzhen city in Guangdong province, and Huangshan city in Anhui province. In each area, 10,000 randomly selected individuals were interviewed, and data on regular and occasional journeys collected. Travel behaviour was examined as a function of age, sex, economic status and home location. Women and children were generally found to travel shorter distances than men. Travel patterns in the economically developed Shenzhen region are shown to resemble those in developed and economically advanced middle income countries with a significant fraction of the population commuting over distances in excess of 50 km. Conversely, in the less developed rural region of Anhui, travel was much more local, with very few journeys over 30 km. Travel patterns in both populations were well-fitted by a gravity model with a lognormal kernel function. The results provide the first quantitative information on human travel patterns in modern China, and suggest that a pandemic emerging in a less developed area of rural China might spread geographically sufficiently slowly for containment to be feasible, while spatial spread in the more economically developed areas might be expected to be much more rapid, making containment more difficult.
Example Output: Travel Patterns in China

Example Input: Background: Low respiratory hygiene compliance among health care workers of emergency departments has become a major concern in the spread of respiratory infections. Our objective was to determine the compliance with respiratory hygiene of triage nurses at 2 university hospital centers and to identify factors influencing compliance to the respiratory hygiene principles of emergency health care workers. Methods: A 2-part, cross-sectional, descriptive study was conducted at 2 training centers. An anonymous observation of compliance with respiratory hygiene by triage emergency nurses was performed. A selfadministered, voluntary questionnaire on attitudes, perceptions, and knowledge of respiratory hygiene guidelines was distributed to the health care workers at the emergency department of the 2 hospital sites. Results: Median objective compliance with respiratory hygiene measures of triage nurses was 22% (interquartile range [IQR], 11%-33%). Median perceived compliance of the health care workers was 68% (IQR, 61%-79%). Median actual knowledge score was 75% (IQR, 75%-100%). Overall, 91.9% of respondents believed that the mask was an effective preventive measure. The main obstacles toward mask wearing by the health care worker were "tendency to forget" (37.8%) and "discomfort" (35.1%). Conclusion: The compliance rate at our institution is very low. We identified a few factors affecting adherence to respiratory hygiene measures that are of potential use in targeting groups and formulating recommendations.
Example Output:
Respiratory hygiene in emergency departments: Compliance, beliefs, and perceptions