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".

Input: Consider Input: Paragraph: Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps in the decision making process by using available data to provide quantitative estimates of outbreak trajectories. Effective reduction of the spread of infectious diseases can be achieved through collaboration between the modeling community and public health policy community. However, such collaboration is rare, resulting in a lack of models that meet the needs of the public health community. Here we show a Susceptible-Infectious-Recovered (SIR) model modified to include control measures that allows parameter ranges, rather than parameter point estimates, and includes a web user interface for broad adoption. We apply the model to three diseases, measles, norovirus and influenza, to show the feasibility of its use and describe a research agenda to further promote interactions between decision makers and the modeling community. Despite substantial public health improvements in the last century, infectious diseases remain one of the leading causes of both morbidity and mortality 1,2 . When confronted with an infectious disease outbreak, public health officials typically work to control the outbreak by performing assessments, analyzing surveillance data, identifying resources and interacting with subject mater experts 2-4 . Control measures are then implemented based on the cumulative information collected. These approaches rely heavily on good surveillance systems, access to experts, and good intuition about which control measures to use. As such, they are largely subjective, time consuming, and the infrastructure required is often not present in high disease burden areas. Modeling is an attractive supplemental method because of the ability to estimate an outbreak's trajectory and the effects of possible control measures in a timely manner. Compartmental models are historically common; they divide individuals into categories based on their disease status. The most common variant is the SIR model, named after the categories used-"susceptible", "infectious" and "recovered". Models of this nature have small computational requirements, and are thus commonly used as first pass attempts to characterize outbreaks or infections quickly 5 . For example, after the sudden emergence of Severe Acute Respiratory Syndrome (SARS) in the early 2000s, researchers used modeling to characterize the virus' epidemiology. Several used compartmental models with control measures like quarantine or isolation in various settings (e.g., hospitals or cities) to describe effects of possible interventions 6-9 . Similar work exists for essentially all well known infectious diseases. For example, Mandal et al. provide a review of models used for malaria 10 and Bauch et al. explore model use with respect to SARS and other emerging infectious diseases 6 . Methods among these groups are often similar, but tend to focus on specific diseases and locations of interest. In contrast, agent-based models use a bottom-up approach where the agents (these are often people) interact with particular rules to simulate outbreaks 11 . This allows simulations at high resolutions, but requires large amounts of data to parameterize the models, as well as substantial computational power. It is thought that they may reflect real world scenarios more accurately, but the lack of available epidemiological data necessitates assumptions that are difficult or impossible to test 11 . These models further require computational resources inaccessible to an average health department. Both agent-based and compartmental models exhibit additional features that are problematic to wide-spread model adoption. The first is the focus on particular disease-location pairs. This emphasis precludes application to 
 Title: An approach to and web-based tool for infectious disease outbreak intervention analysis OPEN

Output: False


Input: Consider Input: Paragraph: Immaturity of the neonatal immune system is causative for high morbidity in calves and colostrum intake is crucial for acquiring passive immunity. Pathogenesis is promoted by reactive oxygen species accumulating at birth if counter-regulation is inadequate. The flavonol quercetin exerts antioxidative and anti-inflammatory effects that may enhance neonatal health. The aim of this work was to study effects of quercetin feeding on metabolic, antioxidative and inflammatory parameters in neonatal calves to investigate whether quercetin could compensate for insufficient colostrum supply. Twenty-eight newborn calves were assigned to two dietary groups fed colostrum or milk-based formula on day 1 and 2 and milk replacer thereafter. From day 2 onwards, 7 calves per diet group were additionally fed quercetin aglycone (50 mg/(kg body weight × day)). Blood samples were taken repeatedly to measure plasma concentrations of flavonols, glucose, lactate, total protein, albumin, urea, non-esterified fatty acids, triglycerides, cholesterol, insulin, glucagon, cortisol, immunoglobulins, fibrinogen, haptoglobin and serum amyloid A. Trolox equivalent antioxidative capacity, ferric reducing ability of plasma, thiobarbituric acid reactive species and F2isoprostanes were analyzed to evaluate plasma antioxidative status. Expression of tumor necrosis factor, interleukin-1α, interleukin-1β, serum amyloid A, haptoglobin, fibrinogen, Creactive protein, catalase, glutathione peroxidase and superoxide dismutase mRNA were measured in liver tissue on day 8. Plasma flavonol concentrations were detectable only after quercetin-feeding without differences between colostrum and formula feeding. Plasma glucose, lactate, total protein, immunoglobulins, triglycerides, cholesterol, trolox equivalent antioxidative capacity and thiobarbituric acid reactive species were higher after colostrum feeding. Body temperature, fecal fluidity and plasma concentrations of cortisol and PLOS ONE | Competing Interests: The authors have declared that no competing interests exist. haptoglobin were higher in formula-than in colostrum-fed groups. Hepatic mRNA expression of tumor necrosis factor was higher after quercetin feeding and expression of C-reactive protein was higher after formula feeding. Data confirm that colostrum improves neonatal health and indicate that quercetin feeding cannot compensate for insufficient colostrum supply. Quercetin Supplementation in Neonatal Calves with Respect to Different Diet PLOS ONE | 
 Title: Quercetin Feeding in Newborn Dairy Calves Cannot Compensate Colostrum Deprivation: Study on Metabolic, Antioxidative and Inflammatory Traits

Output: True


Input: Consider Input: Paragraph: The remarkable capacity of some viruses to adapt to new hosts and environments is highly dependent on their ability to generate de novo diversity in a short period of time. Rates of spontaneous mutation vary amply among viruses. RNA viruses mutate faster than DNA viruses, single-stranded viruses mutate faster than doublestrand virus, and genome size appears to correlate negatively with mutation rate. Viral mutation rates are modulated at different levels, including polymerase fidelity, sequence context, template secondary structure, cellular microenvironment, replication mechanisms, proofreading, and access to post-replicative repair. Additionally, massive numbers of mutations can be introduced by some virus-encoded diversity-generating elements, as well as by host-encoded cytidine/adenine deaminases. Our current knowledge of viral mutation rates indicates that viral genetic diversity is determined by multiple virus-and host-dependent processes, and that viral mutation rates can evolve in response to specific selective pressures. 
 Title: Mechanisms of viral mutation


Output: True