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]: 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.
[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)


[Q]: We describe the first genome isolation of Middle East respiratory syndrome coronavirus (MERS-CoV) in Kenya. This fatal zoonotic pathogen was first described in the Kingdom of Saudi Arabia in 2012. Epidemiological and molecular evidence revealed zoonotic transmission from camels to humans and between humans. Currently, MERS-CoV is classified by the WHO as having high pandemic potential requiring greater surveillance. Previous studies of MERS-CoV in Kenya mainly focused on site-specific and archived camel and human serum samples for antibodies. We conducted active nationwide cross-sectional surveillance of camels and humans in Kenya, targeting both nasal swabs and plasma samples from 1,163 camels and 486 humans collected from January 2016 to June 2018. A total of 792 camel plasma samples were positive by ELISA. Seroprevalence increased with age, and the highest prevalence was observed in adult camels (82.37%, 95% confidence interval (CI) 79.50-84.91). More female camels were significantly seropositive (74.28%, 95% CI 71.14-77.19) than male camels (P \ 0.001) (53.74%, 95% CI 48.48-58.90). Only 11 camel nasal swabs were positive for MERS-CoV by reverse transcription-quantitative PCR. Phylogenetic analysis of whole genome sequences showed that Kenyan MERS-CoV clustered within sub-clade C2, which is associated with the African clade, but did not contain signature deletions of orf4b in African viruses. None of the human plasma screened contained neutralizing antibodies against MERS-CoV. This study confirms the geographically widespread occurrence of MERS-CoV in Kenyan camels. Further one-health surveillance approaches in camels, wildlife, and human populations are needed.
[A]: Genetic Evidence of Middle East Respiratory Syndrome Coronavirus (MERS-Cov) and Widespread Seroprevalence among Camels in Kenya


[Q]: According to recent statistics, 96 million apparent dengue infections were estimated worldwide in 2010. This figure is by far greater than the WHO prediction which indicates the rapid spread of this disease posing a growing threat to the economy and a major challenge to clinicians and health care services across the globe particularly in the affected areas. This article aims at bringing to light the current epidemiological and clinical status of the dengue fever. The relationship between genetic mutations, single nucleotide polymorphism (SNP) and the pathophysiology of disease progression will be put into perspective. It will also highlight the recent advances in dengue vaccine development. Thus far, a significant progress has been made in unraveling the risk factors and understanding the molecular pathogenesis associated with the disease. However, further insights in molecular features of the disease and the development of animal models will enormously help improving the therapeutic interventions and potentially contribute to finding new preventive measures for population at risk.
[A]:
Tackling dengue fever: Current status and challenges