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: We investigated the incidences and characteristics of pediatric traumatic injuries requiring emergency department visits, through a complementary approach using both nationwidesample and single-institutional data. Data for children (aged <15 years) identified with traumatic injuries during a 10-year period from the Korean National Health Insurance Sharing Service (n = 35,064 among 10,114,909 randomly sampled cases from the claim records of the National Health Insurance) and the authors' institute (n = 39,228) were retrospectively reviewed. The incidences and characteristics of the injuries were investigated using both datasets; additionally, detailed information regarding the injury environments was investigated using the single-institutional data. The findings were similar across both datasets. The incidence of injuries increased during the study period; the head was most commonly injured, whereas the trunk or proximal extremities were rarely injured; low-energy head injuries accounted for >50% of the cases in children aged <5 years, although the incidences of lowerextremity injuries and fractures increased in older children. Single-institutional data demonstrated that the proportion of indoor playground and trampoline-related injuries increased rapidly during the study period, and outdoor injuries and seasonal variation (with peak incidences in May and June) were more prominent in older children. Based on similarities between both datasets, the detailed results regarding pediatric traumatic injuries obtained from the singleinstitutional data could be generalized nationally with adequate external validity. To prevent traumatic injuries, it may be more effective to wear protective equipment covering the head and distal extremities rather than the trunk or proximal extremities; simple clothing, such as caps, could prevent many injuries in preschoolers. Among older children, safety guidelines for outdoor sports/leisure activities are needed. The increase in pediatric traumatic injuries may be partially explained by the increased availability of indoor playgrounds and installation of trampolines. Stricter adherence to the preventive guidelines is needed. Low-energy injuries (that is, superficial injuries such as abrasions or open wounds such as lacerations) were the most common injury type for children aged <5 years. Although fracture is a rare injury type in young children, it was relatively common in children aged >5 years and became the most common injury type in children aged >11 years (bold font). Data are presented as n (%).
Example Output: Characteristics and trends of traumatic injuries in children visiting emergency departments in South Korea: A retrospective serial cross-sectional study using both nationwide-sample and single-institutional data

Example Input: Background: With increasing international travel and historically high numbers of residents visiting friends and relatives overseas, travel-associated illnesses are frequent in Marseille, France. We report the changing epidemiology of travel-related illnesses over a 12-year period. Methods: A single site GeoSentinel surveillance analysis was undertaken for 3460 ill returned travellers presenting to two public hospitals in Marseille, France from March 2003 to October 2015, with travel-related illnesses. Demographic characteristics, travel history, presenting symptoms and information on pre-travel consultations were collected. Results: There was a predominance of travel to sub-Saharan Africa, in particular to Comoros archipelago. Tourism was the main reason for travel (1591/3460, 46%), followed by visiting friends or relatives (VFR) (895/3460, 26%), with a mean duration of 29 days; 35% (1212/3460) of travellers reported a pre-travel health consultation. The most common syndromic diagnoses were febrile systemic illness (1343, 39%), dermatologic (716, 21%), gastrointestinal (340, 10%) and respiratory/ear-nose-throat (331, ENT) (10%). Hospitalization rates were highest amongst travellers from sub-Saharan Africa (858/ 1632, 53%), and VFR (573/ 895, 64%, P < 0.001). Frequent diagnoses included malaria (797, 23%), dengue (96, 2.77%) and chikungunya (75, 2.17%), reflecting global trends. Comparison of two periods (2003-10 to 2011-15) demonstrated an increase in chikungunya and decrease in malaria and influenza-like illness. We report an increase in ill travellers from the Caribbean, Middle East and South-East Asia. Conclusion: Surveillance of travellers provides relevant sentinel information on the changing epidemiology of infectious diseases across the globe, most notably for malaria, dengue and chikungunya. We demonstrate the use of travel surveillance in improving pre-travel consultation needs and to address autochthonous vector-borne viral risks.
Example Output: Surveillance of travel-associated diseases at two referral centres in Marseille, France: a 12-year survey

Example Input: Backgrounds: An ongoing outbreak of a novel coronavirus (2019-nCoV) pneumonia hit a major city of China, Wuhan, December 2019 and subsequently reached other provinces/regions of China and countries. We present estimates of the basic reproduction number, R0, of 2019-nCoV in the early phase of the outbreak. Accounting for the impact of the variations in disease reporting rate, we modelled the epidemic curve of 2019-nCoV cases time series, in mainland China from January 10 to January 24, 2020, through the exponential growth. With the estimated intrinsic growth rate (γ), we estimated R0 by using the serial intervals (SI) of two other well-known coronavirus diseases, MERS and SARS, as approximations for the true unknown SI. The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 2.24 (95%CI: 1.96-2.55) to 3.58 (95%CI: 2.89-4.39) associated with 8-fold to 2-fold increase in the reporting rate. We demonstrated that changes in reporting rate substantially affect estimates of R0.
Example Output:
Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak