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".

Q: Paragraph: Middle East respiratory syndrome coronavirus MERS Healthcare-associated outbreaks S U M M A R Y Middle East respiratory syndrome coronavirus (MERS-CoV) is capable of causing acute respiratory illness. Laboratory-confirmed MERS-CoV cases may be asymptomatic, have mild disease, or have a life-threatening infection with a high case fatality rate. There are three patterns of transmission: sporadic community cases from presumed non-human exposure, family clusters arising from contact with an infected family index case, and healthcareacquired infections among patients and from patients to healthcare workers. Healthcareacquired MERS infection has become a well-known characteristic of the disease and a leading means of spread. The main factors contributing to healthcare-associated outbreaks include delayed recognition, inadequate infection control measures, inadequate triaging and isolation of suspected MERS or other respiratory illness patients, crowding, and patients remaining in the emergency department for many days. A review of the literature suggests that effective control of hospital outbreaks was accomplished in most instances by the application of proper infection control procedures. Prompt recognition, isolation and management of suspected cases are key factors for prevention of the spread of MERS. Repeated assessments of infection control and monitoring of corrective measures contribute to changing the course of an outbreak. Limiting the number of contacts and hospital visits are also important factors to decrease the spread of infection.
Title: Healthcare-associated infections: the hallmark of Middle East respiratory syndrome coronavirus with review of the literature

A: True
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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

A: True
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Q: Paragraph: Dengue virus (DENV) emerged from the sylvatic environment and colonized urban settings, being sustained in a human-Aedes-human transmission chain, mainly by the bites of females of the anthropophilic species Aedes aegypti. Herein, we sought evidence for fine-tuning in viral codon usage, possibly due to viral adaptation to human transmission. We compared the codon adaptation of DENV serotype 2 (DENV-2) genotypes from urban and sylvatic habitats and tried to correlate the findings with key evolutionary determinants. We found that DENV-2 codons of urban and sylvatic genotypes had a higher CAI to humans than to Ae. aegypti. Remarkably, we found no significant differences in codon adaptation to human between urban American/Asian and sylvatic DENV-2 genotypes. Moreover, CAI values were significantly different, when comparing all genotypes to Ae. aegypti codon preferences, with lower values for sylvatic than urban genotypes. In summary, our findings suggest the presence of a molecular signature among the genotypes that circulate in sylvatic and urban environments, and may help explain the trafficking of DENV-2 strains to an urban cycle.
Title: Codon adaptation biases among sylvatic and urban genotypes of Dengue virus type 2

A:
False
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