In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Q: Coronaviruses strains 229E and OC43 have been associated with various respiratory illnesses ranging from the self-resolving common cold to severe pneumonia. Although chronic underlying conditions are major determinants of severe respiratory virus infections, few data about coronavirus-related pneumonia in immunocompromised patients are available. Here we report 2 well-documented cases of pneumonia related to coronavirus 229E, each with a different clinical presentation. Diagnosis was made on the basis of viral culture and electron microscopy findings that exhibited typical crown-like particles and through amplification of the viral genome by reverse transcriptase-polymerase chain reaction. On the basis of this report, coronaviruses should be considered as potential causative microorganisms of pneumonia in immunocompromised patients.

A: Coronavirus 229E-Related Pneumonia in Immunocompromised Patients
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Q: The Pneumonia Etiology Research for Child Health (PERCH) project is the largest multicountry etiology study of childhood pneumonia since the Board on Science and Technology in International Development studies of the 1980s. However, it is not the only recent or ongoing pneumonia etiology study, and even with seven sites, it cannot capture all epidemiologic settings in the developing world. Funding providers, researchers and policymakers rely on the best available evidence to strategically plan programs, new research directions and interventions. We aimed to describe the current landscape of recent pneumonia etiology studies in children under 5 years of age in the developed and developing world, as ascertained by a literature review of relevant studies with data since the year 2000 and a survey of researchers in the field of childhood pneumonia. We collected information on the study population, study design, case definitions, laboratory samples and methods and identified pathogens. A literature review identified 88 studies with child pneumonia etiology results. As of June 2010, our survey of researchers identified an additional 65 ongoing and recently completed child pneumonia etiology studies. This demonstrates the broad existing context into which the PERCH study must be placed. However, the landscape analysis also reveals a multiplicity of case definitions, levels of clinician involvement, facility types, specimen collection, and laboratory techniques. It reinforces the need for the standardization of methods and analyses for present and future pneumonia etiology studies in order to optimize their cumulative potential to accurately describe the microbial causes of childhood pneumonia. Each year, approximately 1.6 million children die from pneumonia [1]. The Pneumonia Etiology Research for Child Health (PERCH) study is the largest multisite study of childhood pneumonia since the Board of Science and Technology for International Development (BOSTID) studies were done in the 1980s [2] . The goal of PERCH is to identify the expected etiologies of pneumonia in 2015, a time when the burden of the major causes of bacterial pneumonia in the developing world, Streptococcus pneumoniae and Haemophilus influenzae type b (Hib), will likely be significantly reduced by widespread introduction and use of conjugate vaccines. Moreover, PERCH capitalizes upon new molecular diagnostic techniques that were not available 2 decades ago when the BOSTID studies were carried out. Another salient difference between PERCH and the BOSTID studies is that the 7 sites participating in PERCH will follow a highly standardized protocol, which includes standardization of enrollment criteria, specimen collection, and laboratory testing. Although PERCH is the largest multicountry, childhood pneumonia etiology study in developing countries that has been conducted in the past 2 decades, it is not the only contemporary pneumonia etiology study, and cannot capture the entire complexity of all epidemiologic settings. In recent years, many developed and developing country sites have initiated pneumonia studies that provide etiology data. These studies will

A: A Literature Review and Survey of Childhood Pneumonia Etiology Studies: 2000-2010
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Q: Relevant pandemic-spread scenario simulations provide guiding principles for containment and mitigation policy developments. Here we devise a simple model to predict the effectiveness of different mitigation strategies. The model consists of a set of simple differential equations considering the population size, reported and unreported infections, reported and unreported recoveries and the number of Covid-19-inflicted deaths. For simplification, we assume that Covid-19 survivors are immune (e.g. mutations are not considered) and that the virus can only be passed on by persons with undetected infections. While the latter assumption is a simplification (it is neglected that e.g. hospital staff may be infected by detected patients with symptoms), it was introduced here to keep the model as simple as possible. Moreover, the current version of the model does not account for age-dependent differences in the death rates, but considers higher mortality rates due to temporary shortage of intensive care units. Some of the model parameters have been fitted to the reported cases outside of China 1 from January 22 to March 12 of the 2020 Covid-19 pandemic. The other parameters were chosen in a plausible range to the best of our knowledge. We compared infection rates, the total number of people getting infected and the number of deaths in six different scenarios. Social distancing or increased testing can contain or drastically reduce the infections and the predicted number of deaths when compared to a situation without mitigation. We find that mass-testing alone and subsequent isolation of detected cases can be an effective mitigation strategy, alone and in combination with social distancing. However, unless one assumes that the virus can be globally defeated by reducing the number of infected persons to zero, testing must be upheld, albeit at reduced intensity, to prevent subsequent waves of infection. The model suggests that testing strategies can be equally effective as social distancing, though at much lower economical costs. We discuss how our mathematical model may help to devise an optimal mix of mitigation strategies against the Covid-19 pandemic. The website corona-lab.ch provides an interactive simulation tool based on the presented model. The Covid-19 pandemic is a serious threat that can be mitigated by different strategies. Social isolation is currently practiced in most countries in Europe, at least until alternative mitigation strategies can be implemented or therapies and vaccines become available. We have formulated a simple mathematical model to estimate how well social isolation or improved identification of Covid-19 infected people can slow down virus spread and reduce the death toll.

A:
Dynamic Modeling to Identify Mitigation Strategies for Covid-19 Pandemic
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