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:
Objectives: We aimed to develop a prospective prediction tool on CrimeaneCongo haemorrhagic fever (CCHF) to identify geographic regions at risk. The tool could support public health decision-makers in implementation of an effective control strategy in a timely manner. Methods: We used monthly surveillance data between 2004 and 2015 to predict case counts between 2016 and 2017 prospectively. The Turkish nationwide surveillance data set collected by the Ministry of Health contained 10 411 confirmed CCHF cases. We collected potential explanatory covariates about climate, land use, and animal and human populations at risk to capture spatiotemporal transmission dynamics. We developed a structured Gaussian process algorithm and prospectively tested this tool predicting the future year's cases given past years' cases. Results: We predicted the annual cases in 2016 and 2017 as 438 and 341, whereas the observed cases were 432 and 343, respectively. Pearson's correlation coefficient and normalized root mean squared error values for 2016 and 2017 predictions were (0.83; 0.58) and (0.87; 0.52), respectively. The most important covariates were found to be the number of settlements with fewer than 25 000 inhabitants, latitude, longitude and potential evapotranspiration (evaporation and transpiration). Conclusions: Main driving factors of CCHF dynamics were human population at risk in rural areas, geographical dependency and climate effect on ticks. Our model was able to prospectively predict the numbers of CCHF cases. Our proof-of-concept study also provided insight for understanding possible mechanisms of infectious diseases and found important directions for practice and policy to combat against emerging infectious diseases. Ç. Ak, Clin Microbiol Infect 2020;26:123.e1e123.e7

Ex Output:
A prospective prediction tool for understanding CrimeaneCongo haemorrhagic fever dynamics in Turkey


Ex Input:
This article employs a state-of-the-art panel threshold model by allowing for regime intercepts, in order to shed new light on the asymmetric/ nonlinear effects of local and global sentiments on expected industry stock returns among 11 Asian countries during the period from 1996 to 2010. Empirical evidence demonstrates that once the regime intercept is included, the asymmetric effects of global sentiment on oil & gas, financials, and health care industry returns become less under optimism, as compared with under pessimism. More critically, the positive (negative) impact of global sentiment above (under) the threshold turns significant, indicating that global optimism leads industry returns to be overvalued, while pessimism leads them to be undervalued. For local market sentiment, our results support that higher local sentiment enhances the returns of basic materials, telecommunications, and utilities industries. The empirical results confirm that the nexus of industry returns and investor sentiments is subject to change between different sentimental intervals.

Ex Output:
Asymmetric effects of investor sentiment on industry stock returns: Panel data evidence


Ex Input:
Middle East respiratory syndrome coronavirus (MERS-CoV) infections continue to be a serious emerging disease problem internationally with well over 1000 cases and a major outbreak outside of the Middle East region. While the hypothesis that dromedary camels are the likely major source of MERS-CoV infection in humans is gaining acceptance, conjecture continues over the original natural reservoir host(s) and specifically the role of bats in the emergence of the virus. Dromedary camels were imported to Australia, principally between 1880 and 1907 and have since become a large feral population inhabiting extensive parts of the continent. Here we report that during a focussed surveillance study, no serological evidence was found for the presence of MERS-CoV in the camels in the Australian population. This finding presents various hypotheses about the timing of the emergence and spread of MERS-CoV throughout populations of camels in Africa and Asia, which can be partially resolved by testing sera from camels from the original source region, which we have inferred was mainly northwestern Pakistan. In addition, we identify bat species which overlap (or neighbour) the range of the Australian camel population with a higher likelihood of carrying CoVs of the same lineage as MERS-CoV. Both of these proposed follow-on studies are examples of "proactive surveillance", a concept that has particular relevance to a One Health approach to emerging zoonotic diseases with a complex epidemiology and aetiology.

Ex Output:

Absence of MERS-CoV antibodies in feral camels in Australia: Implications for the pathogen's origin and spread