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".

Example input: Paragraph: The severe acute respiratory syndrome (SARS) epidemic originating from China in 2002 was caused by a previously uncharacterized coronavirus that could be identified by specific RT-PCR amplification. Efforts to control future SARS outbreaks depend on the accurate and early identification of SARS-CoV infected patients. A real-time fluorogenic RT-PCR assay based on the 3 -noncoding region (3 -NCR) of SARS-CoV genome was developed as a quantitative SARS diagnostic tool. The ideal amplification efficiency of a sensitive SARS-CoV RT-PCR assay should yield an E value (PCR product concentration increase per amplification cycle) equal to 2.0. It was demonstrated that the 3 -NCR SARS-CoV based RT-PCR reactions could be formulated to reach excellent E values of 1.81, or 91% amplification efficacy. The SARS-CoV cDNA preparations derived from viral RNA extract and the cloned recombinant plasmid both exhibit the identical amplification characteristics, i.e. amplification efficacy using the same PCR formulation developed in this study. The viral genomic copy (or genomic equivalences, GE) per infectious unit (GE/pfu) of SARS-CoV used in this study was also established to be approximate 1200-1600:1. The assay's detection sensitivity could reach 0.005 pfu or 6-8 GE per assay. It was preliminarily demonstrated that the assay could efficiently detect SARS-CoV from clinical specimens of SARS probable and suspected patients identified in Taiwan. The 3 -NCR based SARS-CoV assay demonstrated 100% diagnostic specificity testing samples of patients with acute respiratory disease from a non-SARS epidemic region.
Title: Development and evaluation of an efficient 3 -noncoding region-based SARS coronavirus (SARS-CoV) RT-PCR assay for detection of SARS-CoV
Example output: True
Example explanation: The answer is true because the title of the paragraph is correct where it described the development of 3 -noncoding region of SARS-CoV genome and assay efficiently detecting SARS-CoV from clinical specimens.
Q: Paragraph: Health-Emergency Disaster Risk Management (Health-EDRM) emerged as the latest knowledge, research and policy paradigm shift from response to preparedness and health risk management in non-emergency times [1] . This approach attempts to enlist and empower communities to invest and emphasize their disaster health risk reduction efforts, thereby strengthening health systems and supporting community health resilience building. This Special Issue has collected 20 scientific papers that attempt to examine the research frontier in Health-EDRM. Major Health-EDRM research evidence gaps were found during a global research agenda setting meeting of the 2018 WHO Health-EDRM global research group in Kobe. Kayano, Chan, Murry et al. [2] highlighted the development need for relevant research methodologies, risk communication approaches, health data management strategies, practical health emergency study ethical guidelines, bridging global research capacity disparities, and infrastructure constraints, to ensure knowledge advancement in Health-EDRM. The authors also pointed out the lack of understanding of psychosocial health risk profiling in population subgroups. Reifel's analysis showed a better understanding of current doctrines and practices in both clinical mental health practices and policy, which will help to bridge the conceptual interlinkages between the preventive-based disaster risk reduction policy agenda and the curative-focused disaster mental health discipline [3] . Genereux, Schluter, Tamahashi et al. [4] argued that standardizing psychometrically robust instruments would also be urgently needed to identify at-risk patients throughout-before, during, and after emergencies and disasters-to ensure that mental and social health needs are addressed throughout the pathway of care (prevention, screening, diagnosis, treatment, and rehabilitation). Aung, Murry and Kayano [5] discussed the need for new research and ethical guidelines to harmonize research efforts in Health-EDRM and Kubo, Yanasan, Herbosa et al. [6] described the challenges in the standardization of health data collection throughout the research processes. Existing surveillance databases, new study tools, and innovation methodologies may help to identify population health risks and support Health-EDRM policy development. Using a syndromic surveillance database in the Philippines, Salazar, Law, Winkler [7] showed how an existing clinical based database might be useful in assisting emergency health service planning decision making during outbreaks in armed conflict. Even with the database limitations to report injuries and death, this existing data system was nevertheless useful to support non-communicable diseases' service caseload planning. Using the computerized random digit dialling methods for rapid data collection after a major urban subway fire incident, Chan, Huang, Hung et al. [8] captured health risk perception, misconceptions, and community first-aid response knowledge in urban man-made emergency incidents. Using social media data from Twitter, Gruebner, Lowe, Sykora et al. [9] showed how the spatio-temporal distribution of Int.
Title: Environmental Research and Public Health Editorial Research Frontiers of Health Emergency and Disaster Risk Management: What Do We Know So Far?
A:
False