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 Q]: Paragraph: Using sequence data to infer population dynamics is playing an increasing role in the analysis of outbreaks. The most common methods in use, based on coalescent inference, have been widely used but not extensively tested against simulated epidemics. Here, we use simulated data to test the ability of both parametric and non-parametric methods for inference of effective population size (coded in the popular BEAST package) to reconstruct epidemic dynamics. We consider a range of simulations centred on scenarios considered plausible for pandemic influenza, but our conclusions are generic for any exponentially growing epidemic. We highlight systematic biases in non-parametric effective population size estimation. The most prominent such bias leads to the false inference of slowing of epidemic spread in the recent past even when the real epidemic is growing exponentially. We suggest some sampling strategies that could reduce (but not eliminate) some of the biases. Parametric methods can correct for these biases if the infected population size is large. We also explore how some poor sampling strategies (e.g. that over-represent epidemiologically linked clusters of cases) could dramatically exacerbate bias in an uncontrolled manner. Finally, we present a simple diagnostic indicator, based on coalescent density and which can easily be applied to reconstructed phylogenies, that identifies time-periods for which effective population size estimates are less likely to be biased. We illustrate this with an application to the 2009 H1N1 pandemic. Pandemic growth rates from sequences E. de Silva et al. 1799 Pandemic growth rates from sequences E. de Silva et al. 1807  
 Title: Inferring pandemic growth rates from sequence data
[EX A]: True

[EX Q]: Paragraph: Vaccination programs against infectious bronchitis virus (IBV) in Egypt depend on both classical and/or imported variant IBV strain vaccines. However, many IBV outbreaks associated with respiratory distress, nephropathy, and high mortalities were attributed to the circulation of both classical and new nephropathogenic IBV variant 2 strains. In the present study, we report the development of attenuated IBV candidate vaccines using the classic IBV strains (IBM41 and IB2) and a nephropathogenic strain (IBvar2). The wild-type (WT) viruses were attenuated through serial passages in embryonated specific pathogen free (SPF) chicken eggs. Virulence of the attenuated viruses was then tested via the ocular route inoculation and the in vivo back passage in day-old SPF chickens. Efficacy against homologous challenge was investigated also in day-old SPF chickens. Results showed that the viruses were successfully adapted to the embryo by the 100th (IBM41 and IB2) and 110th passages (IBvar2). The attenuated viruses were safe and showed no change of virulence in day-old SPF chickens up to the 10th back passages. The efficacy experiment showed that the attenuated vaccines showed 90 to 100% protection against the homologous challenge based on ciliostasis score and protection percent. The att-IBM41 and att-IB2 vaccines were able to reduce the shedding of the challenge at 3 days post-infection (DPI) and no virus shedding was detected in both vaccinated groups by 5 DPI. In the att-IBvar2 vaccinated birds, only 20% of vaccinated birds shed the challenge virus with low titers (10 2.10±0.3 EID 50 /mL) at 3 DPI. In conclusion, the attenuated strains IBM41, IB2, and IBvar2 are efficient vaccine candidates against currently circulating classic and variant IB viruses, respectively. Further studies to evaluate the field efficacy and combining these attenuated IBV strains to induce a wider protection against heterologous IBV challenge are suggested. 
 Title: Safety and efficacy of attenuated classic and variant 2 infectious bronchitis virus candidate vaccines
[EX A]: False

[EX Q]: Paragraph: Gulf Cooperation Council (GCC) countries bear the heaviest brunt of MERS-CoV. This study aims to compare public awareness and practice around MERS-CoV across GCC countries. A cross-sectional survey was conducted using the Gulf Indicators (GI) smartphone app among people in the six GCC countries, namely Saudi Arabia, Kuwait, the United Arab Emirates, Qatar, Bahrain, and Oman. A total of 1812 participants recruited. All were aware of MERS-CoV, yet the perception and practice around MERS-CoV varied widely between countries. Over two thirds were either "not concerned" or "slightly concerned" about contracting MERS-CoV; believing that they were under Allah's (God's) protection (40%) was the most cited reason. While 79% were aware that the disease can transmit through droplet from infected person, only 12% stated that MERS-CoV transmits via camels; people in Saudi Arabia were better aware of the transmission. Nevertheless, only 22% of respondents believed that camels are the zoonotic reservoir of MERS-CoV. Those who were concerned about contracting MERS-CoV (aOR: 1.6, 95% CI: 1.2-2.1, p < 0.01) and those who thought MERS-CoV to be a severe disease only for those with high-risk conditions (aOR: 1.5, 95% CI: 1.1-2.1, p < 0.01) were more likely to believe that camels are the zoonotic source. However, residents of KSA (aOR: 0.03, 95% CI: 0.01-0.07, p < 0.01), UAE (aOR: 0.01, 95% CI: 0.004-0.02, p < 0.01) and Kuwait (aOR: 0.03, 95% CI: 0.01-0.07, p < 0.01) were less likely to believe that camels are the main zoonotic source compared to respondents from the other countries. Hygienic measures were more commonly adopted than avoidance of camels or their raw products, yet there was a discrepancy between the countries. This study highlights that despite being aware of the ongoing MERS-CoV epidemic; many people lack accurate understanding about MERS-CoV transmission, prevention, and are not fully compliant with preventive measures. 
 Title: Public response to MERS-CoV in the Middle East: iPhone survey in six countries
[EX A]:
False