Influenza Vaccination in the Elderly in Three Cities in China: Current Status and Influencing Factors Under Different Funding Policies

Comments 1: Title - Consider changing "of China" to "Across Several Cities in China"

Response 1: Thank you for this suggestion. We agree and have revised the title accordingly."Influenza Vaccination in the Elderly in Three Cities in China: Current Status and Influencing Factors Under Different Funding Policies"* (Page 1, Title)

Comments 2: Abstract Methods and Results - Multiple suggestions for improvement including study design clarification, data completeness, terminology definition, and conclusion moderation.

Response 2: Agree. We have, accordingly, revised the Abstract Methods and Results to emphasize this point.

- We have clarified the study design in the Methods section of the Abstract.

*"A cross-sectional, anonymous survey was conducted. A total of 2,265 elderly individuals... were recruited..."* (Page 1, Abstract, Methods section)

-We have rephrased this sentence to include specific willingness rates.

*"The intention to vaccinate for the 2024–2025 season was also highest in the free policy region (68.78%), followed by the partial reimbursement (47.71%) and self-paid (37.15%) regions (P < 0.001)."* (Page 1, Abstract, Results section)

-We have added the sample sizes for each policy group in the Results.

*”Among the 2,265 participants (free policy region: n = 426; partial reimbursement region: n = 633; and self-paid region: n = 1,206) “,* (Page 1, Abstract, Results section)

-We have provided definitions and examples for these terms.

*”Cues to action (e.g., healthcare worker or family member recommendations) positively influenced vaccinations across all of the regions. In the self-paid region, perceived barriers, such as vaccine cost and side effect concerns, significantly reduced both behaviors and the next-season intention to vaccinate.”* (Page 1, Abstract, Results section)

-We have added the P-value for the key comparison.

*"...compared to partial reimbursement (20.85%) and self-paid (13.60%) regions (P<0.001).""....followed by partial reimbursement (47.71%) and self-paid (37.15%) regions(P<0.001).”

* (Page 1, Abstract, Results section)

Comments 3: Abstract Conclusion - Consider revising since the conclusions were not clear and were overstated.  What did the authors mean by “financing policies” and “improving coverage”?  Consider removing or revising this conclusion as it does not appear to be supported by the evidence or is unclear: “Critical factors also include individual cognition and social support.”Given study limitations, consider removing “strongly” since more research is warranted to support the study findings.

Since it is unclear, please revise the statement beginning with “we commend optimizing subsidy strategies….”

Response 3: Thank you for this suggestion. We agree and have revised the Conclusion accordingly.

-We have softened the language and made the conclusions more specific.

*”Vaccination rates varied significantly across regions with different influenza vaccine subsidy policies. The free policy region demonstrated the highest coverage rate, while the self-paid region exhibited the lowest, suggesting that financial policies are a key determinant of vaccination uptake. Furthermore, free vaccination policies were associated with improved influenza vaccine knowledge among the elderly. Analysis of other influencing factors revealed that healthcare workers' recommendations played a crucial role across all policy regions, though their impact on current-season vaccination behavior and next-season vaccination intention differed by subsidy context. These findings highlight the need to optimize region-specific subsidy strategies, strengthen health education, and actively leverage healthcare providers to promote influenza vaccination among the elderly.”*(Page 2, Abstract, Conclusion section)

Comments 4: Introduction-Page 2, Second paragraph: consider changing “is a huge challenge” to “represents a significant challenge.”Page 2, Second paragraph: Consider changing “in order to inform targeted” to “establishing target intervention strategies.”

Response 4: Thank you for this suggestion. We agree and have revised the Introduction accordingly.

-We have replaced it with a more formal expression.

*”...the implementation of a nationwide free influenza vaccination policy represents a significant challenge due to...”

*”...partial reimbursement, and self-paid policies, establishing target intervention strategies.”*(Page 2-3, Introduction)

Comments 5: Materials and Methods -The authors should describe the overall study design and add the primary and secondary endpoints at the beginning of this section. The authors should consider stating in the text that the study was approved by IRB.

Response 5: Thank you for this suggestion. We agree and have revised the Materials and Methods accordingly.

-The following has shown the suggested changes.

*”This multi-center, cross-sectional study was conducted between May and August 2024 to investigate the influenza vaccination status, the next-season vaccination intention, and associated factors (based on the HBM) among the elderly under different funding policies. The study received approval from the Institutional Review Board of the Chinese CDC (Protocol Code 202320).”*(Page 3, Materials and Methods)

Comments 6: Study Population - Multiple formatting, terminology, and clarity improvements needed throughout the section.                

Response 6: Thank you for this suggestion.We have comprehensively revised the Study Population section to address all concerns:

-Added space between "region" and parentheses throughout

-Removed "entire" from cost descriptions for conciseness

-Simplified phrasing: "the vaccine cost is paid by participants and with no financial or insurance support"

-Defined "urban-rural interface": "(i.e., transitional areas between urban and rural settings)"

-Changed comma to semicolon: "communities were sampled as units; all communities were..."

-Completely revised the sampling methodology description for clarity: "The cumulative population of elderly individuals (aged ≥60 years) across all of the communities was calculated. A sampling interval was derived by dividing this cumulative total by the planned number of communities to be selected."

-Clarified subject selection: "simple random sampling was performed using the household registration list to identify potential subjects."

-Defined exclusion criteria: "individuals who did not agree to participate in the survey"

-Clarified replacement procedure: "were sequentially replaced by the next eligible individual on the sampling list"*(Page 3-4, Study Population)

Comments 7: Survey Methods and Content - Multiple definitions, details, and clarity improvements needed.

Response 7: Thank you for this suggestion.We have comprehensively revised the Survey Methods and Content section to address all concerns:

-Defined "basic health status": ".....basic health status, including the presence of chronic diseases (with simple hypertension excluded)."

-Added survey details: *"The questionnaire was composed of three sections (a total of 51 items):......", "including 6 dimensions (a total of 36 items), which employed 5-point Likert scales (from 1 = "strongly agree" to 5 = "strongly disagree",

-Improved conciseness: *"The second section focused on the respondent vaccination status for pneumococcus, COVID-19, and influenza during the 2023–2024 season, as well as the next-season vaccination intention (August 2024–April 2025). "*

-Clarified "perceived influenza severity": "(i.e., beliefs about the seriousness of influenza and its potential complications)"

-Revised terminology: "Perceived barriers to vaccination"

-Defined "cues to action" with examples: "(i.e., external triggers that prompt vaccination, such as advice from healthcare workers, reminders from family, or media campaigns)"

*(Page 4-5, Survey methods and content)

Comments 8: Statistical Processing - Terminology, conciseness, and methodological clarity improvements needed.

Response 8: Thank you for this suggestion.We have revised the Statistical Analysis section to address all concerns:

-Changed "Statistical Processing" to "Statistical Analysis" throughout

-Defined significance levels for machine learning metrics: "Finally, a random forest model was implemented to evaluate and rank the importance of each questionnaire item. Variable importance was ranked using the mean decrease in the Gini index, with higher values indicating greater importance for classifying the vaccination status/intention to vaccinate. "

*(Pages 5, Materials and Methods, Statistical Analysis section)

Comments 9: Results - Data completeness and figure presentation improvements needed.

Response 9:Thank you for this suggestion.We have thoroughly revised the Results section to address all concerns:

-Added exclusion data: "Nine of the 2,274 surveys were excluded due to a lack of basic information or duplicate records."

-Included basic health status data: Chronic disease prevalence data has been added to Table 1, “Notably, the chronic disease prevalence (excluding simple hypertension) was highest in the free policy region (45.31%), followed by the partial reimbursement (40.28%) and self-paid regions (38.97%), although this difference did not reach statistical significance (P = 0.072). “

-Completely revised Figures 1-3 to improve interpretability, including:Clearer labels and subheadings,

Added total N and group sample sizes, Enhanced readability and data presentation

(Pages 6-7, Results section, Table 1, and revised Figures 1-3)

Comments 10: Discussion - Comprehensive revisions needed including explanation of findings.(Discussion of income disparities across policy regions)

Response 10: Thanks for your comments. It’s a challenage for us to explain this disparities. Because the three cities we selected has different socioeconomic level. Our study was designed to compare the influence of finanical policy on vaccination. We intentionally selected cities that represent these distinct, real-world policy models.

Comments 11: Discussion - Comprehensive revisions needed including explanation of findings.(Discordance in pneumococcal vaccine rates across policy groups)

Response 11: We appreciate the reviewer's attention to this detail. Pneumococcal disease is   also a concern for elderly. Because this study mainly focused on influenza vaccination and influence about financial policy, so we didn’t collection any information such as finanical policy about pneumococcal vaccine, history of pneumococcal disease, except for the vaccination rate. So it’s difficult to analysis more details.

Comments 12: Discussion - Multiple language, clarity, and terminology improvements needed throughout the section.

Response 12: Thank you for this suggestion. We have comprehensively revised the Discussion section to address all language and clarity concerns:

-Improved sentence structure and conciseness:

*Changed to“These results agreed with observations from Beijing, where the implementation of a free vaccination policy for the elderly was followed by an increase in both influenza and vaccine knowledge scores”

*Revised to”Vaccine subsidy policies directly reduce out-of-pocket costs. Furthermore, through policy promotion and social mobilization, they may indirectly enhance vaccine knowledge among the elderly, thereby fostering a more favorable health belief structure.”

*Simplified lengthy sentences for better readability, ”...were among the top two determinants for both the current-season vaccination behavior and next-season intention.”, ”This result was consistent with numerous studies that have indicated that healthcare worker recommendations are among the most effective strategies for increasing vaccination rates among the elderly.”, ”Furthermore, prior research has suggested a positive dose-response relationship, where increased advice by healthcare workers is associated with higher vaccination rates. This underscores that under policy coverage, healthcare worker recommendations can be directly translated into vaccination action.”

-Corrected terminology and spelling:

*Changed "This sparity" to "These results"

*Corrected "signoficant" to "significant"

*Updated "Kroneman M's study" to "Kroneman et al."

-Enhanced clarity of key concepts:

*Improved explanation of healthcare workers' recommendation impacts, ”Conversely, in the partial reimbursement and self-paid regions, healthcare worker recommendations significantly influenced the next-season vaccination intention but showed no significant association with the current-season vaccination behavior, revealing a "current-season intervention gap.""

*Revised limitations section for better clarity, “This study has several limitations.”, “First, the inclusion of only one city per funding policy may have limited the generalizability of our findings and might not fully represent the diversity within similar policy contexts across China (e.g., ethnic minority areas and economically advanced eastern coastal regions).”,”Third, the data collected were based on a cross-sectional survey that reflected only the vaccination status and influencing factors for the 2023–2024 season. Consequently, it is difficult to elucidate the causal relationships between vaccination behavior and its influencing factors. “

-Restructured limitations and future directions:

*Added sample size limitation acknowledgment,”Second, although the total sample size was substantial, its distribution across the three distinct policy regions and the subsequent sub-analyses may have limited the statistical power of some comparisons.  “

-Changed "representativeness" to "generalizability"

-Added a dedicated "Future Research Directions" subsection following the limitations section, as suggested. “"The findings of this study highlighted several promising avenues for future research. First, longitudinal studies are warranted to track the dynamic evolution of vaccination behavior and its determinants over multiple influenza seasons, particularly in response to changes in subsidy policies. This would help establish causal relationships and assess the long-term impact of policy interventions. Second, future investigations should expand the geographical scope to include a more diverse range of regions, ......"(Page 13-15, Discussion)

Comments 13: Conclusions - Given the small sample size and other study limitations, the author’s strong conclusions are not fully supported by the evidence. Thus, the authors should revise the conclusions and indicate that the findings are preliminary and that future study is warranted to confirm the results. The authors should further revise the conclusions to enhance clarity, conciseness, and understanding

Response 13: Thank you for this suggestion.We have substantially revised the Conclusions section:

-Moderated conclusions to reflect study limitations

-Emphasized preliminary nature of findings

-Added explicit statement about need for future research

-Enhanced clarity and conciseness throughout

-Removed overly strong claims and tempered language

-Ensured conclusions are better supported by evidence

” This study was conducted across several Chinese cities, and it has underscored the profound impact of financial subsidy policies on influenza vaccination among the elderly. Our findings indicated that free vaccination policies were associated with coverage rates approximately four times higher than those in self-paid regions. Beyond financial mechanisms, the findings highlighted the critical role of socio-cognitive factors, with healthcare worker recommendations emerging as a pivotal cue to action across all policy contexts.

These insights suggest that a multi-pronged strategy that combines the strategic expansion of financial support, the strengthening of proactive recommendation systems within healthcare services, and targeted communication to address specific perceptual barriers holds promise for substantially improving vaccine uptake. Future longitudinal and more geographically diverse studies are required to confirm these relationships and explore the causal mechanisms that underlie them. Nonetheless, this study has provided valuable evidence to inform targeted public health strategies aimed at protecting the health of China's aging population.”*(Page 15-16, Conclusions)

Comments 14: Supplementary Materials - Addition of survey instruments.

Response 14: Thank you for this suggestion. We have added both the informed consent statement and the complete survey questionnaire as appendices to enhance methodological transparency and reproducibility.

(Pages 16-25, Appendices A and B)

Comments 1: The introduction lacks important information about how existing studies report vaccination behaviors and factors in the older group in China, as well as the knowledge gap identified after conducting a literature review. Suggest adding a short paragraph summarizing previous national or regional findings (e.g., knowledge, perceived barriers, and role of healthcare workers), and clarify what remains unknown

Response 1: We thank the reviewer for this valuable suggestion. We have now added a new paragraph in the Introduction summarizing previous national and regional findings on influenza vaccination among the elderly in China, including key factors such as knowledge levels, perceived barriers (e.g., cost and safety concerns), and the role of healthcare workers. We also explicitly state the research gap regarding the comparative influence of these factors under different funding policies, which our study aims to address.

“Previous studies conducted in specific Chinese provinces or cities have identified several key factors that influence influenza vaccination among the elderly. These factors include generally low levels of knowledge regarding influenza and its vaccine^[11], prevalent perceived barriers such as cost and concerns regarding safety^[12,13], and the crucial role of healthcare worker recommendations[14]. However, these studies were often limited to single provinces or specific policy contexts. A critical gap remains in the direct comparison of how these factors, particularly within a theoretical framework like the Health Belief Model (HBM), differentially influence vaccination behaviors and the next-season vaccination intention across districts concurrent with operational funding policies at the national level. The aim of this study is to fill this gap by systematically investigating and comparing the vaccination status and its cognitive determinants among the elderly under free, partial reimbursement, and self-paid policies, establishing target intervention strategies.”*（Page 2-3, Introduction section)

Comments 2: Please elaborate on sample size planning.

Response 2: We have expanded the description of sample size calculation in Section 2.2 (Page 4) to provide more detail. Specifically, we now include the formulas used for both univariate and multivariate logistic regression analyses, the parameter estimates (e.g., vaccination rates, ORs, R²), and the R package and function employed (SSizeLogisticBin in the powerMediation package). We also clarify the 20% allowance for attrition and the stratification by urban/rural areas.(Page 4, Sample size)

Comments 3: In the questionnaire section (2.3), clarify how vaccination status and willingness were coded for analysis.

Response 3: We have added a clarifying sentence in Section 2.3 (Page 4) to specify that vaccination status and intention to vaccinate were coded as binary variables: "Yes" = 1, and "No" or "Not sure" = 0.

“For statistical analysis, vaccination status and intention to vaccinate were coded as binary variables: responses of "Yes" were coded as 1, and responses of "No" or "Not sure" were coded as 0.”

Comments 4: In the statistical analysis, whether multicollinearity among independent variables was tested; Whether model fit was assessed; For the random forest model, specify a validation strategy, and whether variable importance ranking was checked for stability.

Response 4: We have updated Section 2.4 (Page 5) to include the following:

*Multicollinearity was assessed using Variance Inflation Factor (VIF), with all values below 1.61.

*Model fit for logistic regression was evaluated using the Likelihood Ratio Test (p < 0.001) and McFadden’s Pseudo R² (0.164).

*For the random forest model, we used out-of-bag (OOB) error estimation and 10-fold cross-validation. The stability of variable importance rankings was confirmed over 100 iterations with consistent results.

Comments 5: Figures 1 and 2 are visually dense and hard to interpret.

Response 5: We have revised Figures 1–3 to improve clarity and readability. The updated figures now use clearer labeling, simplified layouts, and enhanced color contrast to better communicate the top influencing factors identified by the random forest model.

Comment 6: In the discussion, add a short paragraph on future strategies to enhance influenza vaccine uptake among the elderly, integrate digital health interventions, such as chatbot-based education or reminder systems (DOI: 10.2196/76849). This addition would make the paper more policy-relevant and innovative.

Response 6: We appreciate this insightful suggestion. We have added a new paragraph in the Discussion (Page 15, Paragraph 2) discussing the potential of digital health interventions—such as chatbot-based education and reminder systems—to complement traditional strategies. We also cite the recommended reference to support this point.

”Furthermore, interventional studies evaluating the effectiveness of specific strategies—such as structured recommendation protocols for healthcare workers, targeted health communication campaigns, digital health interventions (e.g., chatbot-based education or reminder systems)[28], or integrated vaccination service delivery models—are needed to translate these findings into actionable public health practices.”

Comment 7: Replace “vaccination willingness” with “intention to vaccinate” throughout for a smoother academic tone.

Response 7: We have replaced “vaccination willingness” with “vaccination intention” throughout the manuscript to improve academic phrasing, as suggested.