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.

[EX Q]: This paper attempts to understand optimal ventilation rates at the national level across 26 European countries and to contrast the benefits of optimizing ventilation with filtration of outdoor air pollution and control of indoor sources. This is an important topic given the key role of the housing sector in tackling both air pollution and climate change. Although the methods used are relatively simplistic, they are appropriate for analyses performed at the scale presented in the paper. The findings and conclusions are well supported by the results. I would therefore support publication. However, I believe the manuscript would benefit from a stronger statement of the aims of the work and some clarifications regarding the methods (see below). My main concern relates to the assumption made by the authors that indoor-generated PM2.5 is equally as harmful to health as outdoor-generated PM2.5. There is little evidence to support this (though it is quite a commonly made assumption). I would like to see some form of sensitivity analysis in relation to this assumption, since it may have an impact on the final results (though probably not on the ultimate conclusions). More detailed comments can be found below. I consider the suggested revisions to be relatively minor. 1. Is the question posed original, important and well defined? The research question posed by the paper is important and I believe the methods used are appropriate to answer it. However, the aims of the paper are not currently well stated (in both the main text and in the abstract). The main statement of the aims comes towards the end of page 5, which states "This work aims to summarize the current understanding of the sources of health risks in indoor environments and their relationship to ventilation requirements". This doesn't really capture what the authors have actually done. There is a slightly better statement of the aims hidden in the Methods (top of page 7) but even this doesn't quite feel sufficient. 2. Are the data sound and well controlled? Yes, although the source of some of the input data can be made clearer in the text, especially in relation to Table 2 (see below) . 3. Is the interpretation (discussion and conclusion) well balanced and supported by the data? Yes. 4. Are the methods appropriate and well described, and are sufficient details provided to allow others to evaluate and/or replicate the work? The methods are generally well described. However, I have a few specific issues (see the additional comments below). The methods are based on relatively simplistic tools (both the mass-balance exposure model and the risk/health impact model). However, I think they are appropriate for the type of analysis presented in the paper. My main concern relates to the assumption of equal health risk associated with both outdoor-and indoor-generated PM2.5. The authors discuss this briefly in the Discussion section but this assumption is highly uncertain since almost all of the published epidemiology is based on outdoor PM2.5. The paper would benefit from greater emphasis on the sensitivity of the results to this assumption. Perhaps, the analysis (or part of it) could be repeated without the effects of indoorgenerated PM2.5 or with a reduced exposure-response coefficient? 6. Can the writing, organization, tables and figures be improved? Although the manuscript is generally well written, there are reoccurring problems, most importantly missing articles throughout the paper (e.g. a, the). For instance, in the abstract, "Based on measurements of the European Environment Agency (EEA),…" and "A framework for developing European health-based ventilation guidelines…" would be preferable. I realise that English is not the authors' first language (and, again, I should stress that most of the language used is very good). However, I think the paper would benefit from a thorough edit by a native English speaker. Also, the figures appear to be quite pixelated and may not be in an appropriate format for publication. 7. When revisions are requested. No preference. 8. Are there any ethical or competing interests issues you would like to raise? None. • I believe the abstract would benefit from a little editing. At present, the Background section feels unnecessarily long and there isn't enough detail in either the Methods or Results sections. The methods used for the health impact calculations aren't mentioned at all, despite being key to the paper. At the moment, I don't feel the main results are clearly stated in the abstract. • The paper refers throughout to "optimization". I think a mathematician might object to the use of the term because the method doesn't actually use a formal optimization process. I don't think this is too much of a problem but I do think a clear statement of what the authors mean by optimization would be helpful (e.g. in the Methods). As I understand it, the "optimal" ventilation rate is just taken to be the one for which the health burden is smallest.
[EX A]: Reducing burden of disease from residential indoor air exposures in Europe (HEALTHVENT project) Reducing burden of disease from residential indoor air exposures in Europe (HEALTHVENT project)

[EX Q]: Human coronavirus (HCoV) is one of the most common causes of respiratory tract infection throughout the world. To investigate the epidemiological and genetic variation of HCoV in Guangzhou, south China, we collected totally 13048 throat and nasal swab specimens from adults and children with fever and acute upper respiratory infection symptoms in Gunazhou, south China between July 2010 and June 2015, and the epidemiological features of HCoV and its species were studied. Specimens were screened for HCoV by real-time RT-PCR, and 7 other common respiratory viruses were tested simultaneously by PCR or real-time PCR. HCoV was detected in 294 cases (2.25%) of the 13048 samples, with most of them inpatients (251 cases, 85.4% of HCoV positive cases) and young children not in nursery (53.06%, 156 out of 294 HCoV positive cases). Four HCoVs, as OC43, 229E, NL63 and HKU1 were detected prevalent during 2010-2015 in Guangzhou, and among the HCoV positive cases, 60.20% were OC43, 16.67% were 229E, 14.97% were NL63 and 7.82% were HKU1. The month distribution showed that totally HCoV was prevalent in winter, but differences existed in different species. The 5 year distribution of HCoV showed a peak-valley distribution trend, with the detection rate higher in 2011 and 2013 whereas lower in 2010, 2012 and 2014. The age distribution revealed that children (especially those <3 years old) and old people (>50 years) were both high risk groups to be infected by HCoV. Of the 294 HCoV positive patients, 34.69% (101 cases) were co-infected by other common respiratory viruses, and influenza virus was the most common co-infecting virus (30/101, 29.70%). Fifteen HCoV-OC43 positive samples of 2013-2014 were selected for S gene sequencing PLOS ONE | https://doi., et al. (2018) Epidemiology characteristics of human coronaviruses in patients with respiratory infection symptoms and phylogenetic analysis of HCoV-OC43 during 2010-2015 in Guangzhou. PLoS ONE 13(1): e0191789. and phylogenetic analysis, and the results showed that the 15 strains could be divided into 2 clusters in the phylogenetic tree, 12 strains of which formed a separate cluster that was closer to genotype G found in Malaysia. It was revealed for the first time that genotype B and genotype G of HCoV-OC43 co-circulated and the newly defined genotype G was epidemic as a dominant genotype during 2013-2014 in Guanzhou, south China.
[EX A]: Epidemiology characteristics of human coronaviruses in patients with respiratory infection symptoms and phylogenetic analysis of HCoV-OC43 during 2010-2015 in Guangzhou

[EX Q]: Recent advances in nucleic acid diagnostic technologies have revolutionized microbiology by facilitating rapid, sensitive pathogen surveillance and differential diagnosis of infectious diseases. With the expansion and dissemination of genomic sequencing technology scientists are discovering new microbes at an accelerating pace. In this article we review recent progress in the fi eld of pathogen surveillance and discovery with a specifi c focus on applications in the fi eld of laboratory animal research. We discuss the challenges in proving a causal relationship between the presence of a candidate organism and disease. We also discuss the strengths and limitations of various assay platforms and describe a staged strategy for viral diagnostics. To illustrate the complexity of pursuing pathogen discovery research, we include examples from our own work that are intended to provide insights into the process that led to the selection of particular strategies.
[EX A]:
Microbe Hunting in Laboratory Animal Research