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:
This study shows that the disease free equilibrium ( ) for COVID-19 coronavirus does not satisfy the criteria for a locally or globally asymptotic stability. This implies that as a pandemic as declared by WHO (2020) the COVID-19 coronavirus does not have a curative vaccine yet and precautionary measures are advised through quarantine and observatory procedures. Also, the Basic Reproductive number ( 0 < 1) by Equation (33) shows that there is a chance of decline of secondary infections when the ratio between the incidence rate in the population and the total number of infected population quarantined with observatory procedure. The effort to evaluate the disease equilibrium shows that unless there is a dedicated effort from government, decision makers and stakeholders, the world would hardly be reed of the COVID-19 coronavirus and further spread is eminent and the rate of infection will continue to increase despite the increased rate of recovery because of the absence of vaccine at the moment.

Ex Output:
MATHEMATICAL PREDICTIONS FOR COVID-19 AS A GLOBAL PANDEMIC

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:
A major hallmark of the autoimmune demyelinating disease multiple sclerosis (MS) is immune cell infiltration into the brain and spinal cord resulting in myelin destruction, which not only slows conduction of nerve impulses, but causes axonal injury resulting in motor and cognitive decline. Current treatments for MS focus on attenuating immune cell infiltration into the central nervous system (CNS). These treatments decrease the number of relapses, improving quality of life, but do not completely eliminate relapses so long-term disability is not improved. Therefore, therapeutic agents that protect the CNS are warranted. In both animal models as well as human patients with MS, T cell entry into the CNS is generally considered the initiating inflammatory event. In order to assess if a drug protects the CNS, any potential effects on immune cell infiltration or proliferation in the periphery must be ruled out. This protocol describes how to determine whether CNS protection observed after drug intervention is a consequence of attenuating CNS-infiltrating immune cells or blocking death of CNS cells during inflammatory insults. The ability to examine MS treatments that are protective to the CNS during inflammatory insults is highly critical for the advancement of therapeutic strategies since current treatments reduce, but do not completely eliminate, relapses (i.e., immune cell infiltration), leaving the CNS vulnerable to degeneration.

Ex Output:
Determining Immune System Suppression versus CNS Protection for Pharmacological Interventions in Autoimmune Demyelination