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.

Ex Input:
Introduction: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response. Methods: We assessed how the machine learning LASSO method may be useful in providing useful forecasts for different pathogens in countries with different climates. Separate LASSO models were constructed for different disease/country/forecast window with different model complexity by including different sets of predictors to assess the importance of different predictors under various conditions. Results: There was a more apparent cyclicity for both climatic variables and incidence in regions further away from the equator. For most diseases, predictions made beyond 4 weeks ahead were increasingly discrepant from the actual scenario. Prediction models were more accurate in capturing the outbreak but less sensitive to predict the outbreak size. In different situations, climatic variables have different levels of importance in prediction accuracy. Conclusions: For LASSO models used for prediction, including different sets of predictors has varying effect in different situations. Short term predictions generally perform better than longer term predictions, suggesting public health agencies may need the capacity to respond at short-notice to early warnings.

Ex Output:
The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison


Ex 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.

Ex Output:
Surveillance of travel-associated diseases at two referral centres in Marseille, France: a 12-year survey


Ex Input:
Respiratory viruses of human origin infect wild apes across Africa, sometimes lethally. Here we report simultaneous outbreaks of two distinct human respiratory viruses, human metapneumovirus (MPV; Pneumoviridae: Metapneumovirus) and human respirovirus 3 (HRV3; Paramyxoviridae; Respirovirus, formerly known as parainfluenza virus 3), in two chimpanzee (Pan troglodytes schweinfurthii) communities in the same forest in Uganda in December 2016 and January 2017. The viruses were absent before the outbreaks, but each was present in ill chimpanzees from one community during the outbreak period. Clinical signs and gross pathologic changes in affected chimpanzees closely mirrored symptoms and pathology commonly observed in humans for each virus. Epidemiologic modelling showed that MPV and HRV3 were similarly transmissible (R 0 of 1.27 and 1.48, respectively), but MPV caused 12.2% mortality mainly in infants and older chimpanzees, whereas HRV3 caused no direct mortality. These results are consistent with the higher virulence of MPV than HRV3 in humans, although both MPV and HRV3 cause a significant global disease burden. Both viruses clustered phylogenetically within groups of known human variants, with MPV closely related to a lethal 2009 variant from mountain gorillas (Gorilla beringei beringei), suggesting two independent and simultaneous reverse zoonotic origins, either directly from humans or via intermediary hosts. These findings expand our knowledge of human origin viruses threatening wild chimpanzees and suggest that such viruses might be differentiated by their comparative epidemiological dynamics and pathogenicity in wild apes. Our results also caution against assuming common causation in coincident outbreaks.

Ex Output:

Simultaneous outbreaks of respiratory disease in wild chimpanzees caused by distinct viruses of human origin