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This research is about the air pollutants and outpatient visits for influenza-like illness in Beijing, China. Although some studies have been conducted in this area, the different effects during the outbreak and non-outbreak seasons can provide some novel findings. One limitation of the study is the data only from one hospital, so caution is needed regarding the generalizability of the findings. Please see two reviewers’ reports for more details.
[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]
More literature review is needed, especially for the scenario of doing this analysis.
One concern of this study was including only one hospital in the analysis, which might lead to selection bias.
Another issue is blured in this manuscript, on the one hand, the authors claimed that they want to examine whether air polluction can contribute to the transmission of enfluenza, on the other hand, the analysis actually examined the association between daily air pollution and outpatients for enfluenza. In some extent, this can be two different study questions.
The observed negative association on some lag days during some special period needed caution to make any conclusion. This can be due to the data quality, for example only one hospital data were used, and adjustment of potential confounding factors.
Is it possible to include more hospitals for the analysis to make the analysis more robust.
• Criteria
o Clear, unambiguous, professional English language used throughout.
o Intro & background to show context. Literature well referenced & relevant.
o Structure conforms to PeerJ standards, discipline norm, or improved for clarity.
o Figures are relevant, high quality, well labelled & described.
o Raw data supplied (see PeerJ policy).
• Comments
o The structure conforms to PeerJ standards and is logically organized.
o The background can be strengthened by providing further rationale for the examination of the association between air pollution and influenza-like illness.
o The figures are mostly high quality but can be better labelled and captioned. Some data which would benefit the audience should be added (please see detailed comments below).
o Please review and revise work for irregularities in grammar and sentence structure.
o Unsure if raw data have been provided in the submission.
• Criteria
o Original primary research within Scope of the journal.
o Research question well defined, relevant & meaningful. It is stated how the research fills an identified knowledge gap.
o Rigorous investigation performed to a high technical & ethical standard.
o Methods described with sufficient detail & information to replicate.
• Comments
o Original primary research using administrative hospital data and environmental data.
o The research can have meaningful knowledge and policy implications; however, it is more preliminary or exploratory than explanatory.
o The authors are asked to specify or justify several methodological choices, such as the selected setting and time period for data extraction, the lag times, using single-pollutant model rather than a multi-pollutant. Further details are required to assess appropriateness of methods.
o The methods are described with sufficient detail to replicate.
• Criteria
o Impact and novelty not assessed. Negative/inconclusive results accepted. Meaningful replication encouraged where rationale & benefit to literature is clearly stated.
o All underlying data have been provided; they are robust, statistically sound, & controlled.
o Speculation is welcome, but should be identified as such.
o Conclusions are well stated, linked to original research question & limited to supporting results.
• Comments
o Similar studies have been conducted previously, as noted in the introduction and discussion, so the study is not entirely novel. However, the findings of different effects during the outbreak and non-outbreak seasons are of interest.
o The reported results are statistically significant. However, non-significant results should also be reported when relevant to the research question (for example, at different lag times).
o Conclusions are clearly stated and linked to the original research question.
1. Lines 57 and 58. Please express “less than” or “greater than” using words instead of the symbols. As well, please reword the sentence to clarify the DALYs; currently, it states PM exposure causes over 100 million DALYs, but I believe the authors mean that PM exposure causes a loss of over 100 million DALYs.
2. Line 59. Please correct exposured to exposed.
3. Line 60. Please correct the sentence to “high risks to their health” or “high health risks”.
4. To strengthen the background, please clarify the explanation of why PM2.5 concentrations might be associated with or increase the risk of exposure to influenza. What is the hypothesized underlying pathway from exposure to disease? Further, on Line 79, the authors state it is necessary to confirm the effects of influenza outbreaks on ILI outpatient visits. I believe it is important to clarify and close the paragraph with the main research question (effect of PM concentration on ILI). The last sentence is succinct and clear.
5. Lines 87 and 88. Why was this hospital and these dates chosen in particular?
6. Line 89. As above, please use “less than 15 years old”.
7. Lines 102 and 103. What constituted an outbreak period versus a non-outbreak period in this study?
8. Line 111. Why might including dummy variables for days of the week help control for confounders? More broadly, how did the authors choose the co-variates in their model?
9. Lines 112 to 113. Why did the authors choose the previous five days to control for lag effects?
10. Line 134. What is meant by “gross pollution” here?
11. Line 147. Why did the authors choose to use only a single-pollutant model and not a multi-pollutant model? Also, please consider including this information in the methods section.
12. For Figure 3, please clarify the differences between the plots A and B, between plots C and D, and so on. The axes and exposure for each pair are the same, so it is unclear how the two plots differ. Would it be possible to also report the point estimates, CIs, and p-values in a table, so that exact estimates are available for readers?
13. Line 175. Please clarify what is meant by “on the whole”.
14. Line 200. It may be more clear to state that the exposure is associated with an increase in risk of the outcome, rather than vice versa.
15. Line 209. Please clarify what is meant by “population specificities” and “a component of the complicated mixture”.
16. Lines 214 and 217. Did any of the lag times used in previous studies inform your study methods and choice of lag time? Why or why not? This question is similar to point #9 about why one to five days was chosen. The authors note that an Australian study used ten days.
17. Line 222. Interesting hypothesized mechanism. The authors suggest that the use of face masks is a mediator for the effect of air pollutants on ILI (good air quality -> less mask use -> higher ILI transmission)
18. Line 229. Please express symbols such as > in words.
19. Lines 241 to 244. The authors explain why children and elderly individuals might have lower exposure to air pollutants during an outbreak compared to middle-aged adults, but they do not explain why the association with ILI cases is less pronounced.
20. The limitations paragraph includes important limitations but is short/not comprehensive. Another potential limitation is that the study uses an ecological design, which may limit the ability to control for potentially relevant confounders, such as individual-level demographic or socio-economic factors.
21. The authors should also discuss suggestions for future research at the end of the discussion.
22. Table 3. Why did the authors exclude the RRs for Lag3, 4 and 5?
23. Figure 1. Please consider labelling the axes completely.
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