In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Ex Input:
Paragraph: Background: Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics. Results: The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources. The AsiaFluCap Simulator is freely available software (www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software. 
 Title: Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator

Ex Output:
True


Ex Input:
Paragraph: MRNA2 of the arteriviruses lactate dehydrogenase-elevating virus (LDV) and equine arteritis virus (EAV) encodes two proteins that are read in different frames, an about 26 kDa minor envelope glycoprotein and an about 8 kDa protein that lacks N-glycosylation sites and a signal peptide, but possesses a central hydrophobic segment. Recent studies have shown that both proteins of EAV are translated from mRNA 2 in EAV infected BHK cells, that the 8 kDa protein is membrane associated and that small amounts of it are recovered in purified virions (Snijder, E.J., van Tol, H., Pederson, K.W., Raamsman, M.J.B., de Vries, A.A.F., 1999. Identification of a novel structural protein of arteriviruses. J. Virol. 73, 6335-6345). The authors concluded that the 8 kDa protein is another arterivirus envelope protein and designated it E protein. However, we have not detected a significant level of an 8 kDa protein in LDV virions and thus conclude that it is not a structural virion component. 
 Title: An ORF-2a protein is not present at a significant level in virions of the arterivirus lactate dehydrogenase-elevating virus

Ex Output:
True


Ex Input:
Paragraph: The impact of COVID-19 pandemic on the global health and world's economy have been profound and unseen since the Spanish flu of 1918-19. As of now, many countries have been severely affected, partly because of slow responses to the crisis, ill-preparedness of their health system, and the fragile health infrastructure and the shortage of protective equipment. This note evaluates various scenarios, based on an estimation of number of identified and unidentified infected cases, and examines the effectiveness of different policy responses to contain this pandemic. Our result, based on an estimation of the model for Iran, show that in many instances the number of unidentified cases, including asymptomatic individuals, could be much bigger than the reported numbers. The results confirm that in such circumstances, social distancing alone cannot be an effective policy unless a large portion of the population confine themselves for an extended period of time, which is not only difficult to implement, but it could also prove extremely costly and damaging to the economy. An alternative policy, this note argues, is to couple effective social distancing with extensive testing, even to those who are asymptomatic, and isolate the identified cases actively. Otherwise, many lives will be lost, and the health system will collapse, adding to the ongoing economic troubles that many countries have started to encounter. JEL classification: I10, I18, I19. 
 Title: Modeling of COVID-19 Pandemic and Scenarios for Containment *

Ex Output:

False