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Preplanned Studies: Dengue Fever Screening Awareness and Capacity in Healthcare Facilities — Guangzhou City, Guangdong Province, China, 2024

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  • Summary

    What is already known about this topic?

    Dengue fever represents a significant public health challenge in tropical and subtropical regions globally, including China. The effective management of dengue cases depends critically on accurate and timely clinical and laboratory diagnosis, supported by well-coordinated healthcare services.

    What is added by this report?

    This survey revealed that healthcare facilities still needed to enhance dengue case screening and public health education initiatives. Polymerase chain reaction testing capacity was severely insufficient and inconsistent reimbursement rates across health insurance types and institutional levels. Notably, significant variations in dengue diagnostic awareness existed across hospital levels, departments, ages, and professional titles (P<0.05). Targeted training significantly enhanced diagnostic competence [odds ratio (OR)=13.78, 95% confidence interval (CI): 2.94–64.65].

    What are the implications for public health practice?

    Healthcare facilities must maintain heightened vigilance during dengue fever outbreaks. Robust screening and diagnostic capabilities are essential for early case detection and management. Understanding and addressing identified deficiencies and their contributing factors can strengthen the response capabilities while offering valuable lessons for other regions.

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  • Conflicts of interest: No conflicts of interest.
  • Funding: This work was supported by the National Key Research and Development Program of China (grant number 2024YFC2311500), The Key Project of Medicine Discipline of Guangzhou (No.2025-2027-11), and General Guidance Project for Health Science and Technology in Guangzhou (No. 20231A011069)
  • [1] World Health Organization. Dengue and severe dengue. 2024. https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue. [2024-7-14].
    [2] Lai SJ, Huang ZJ, Zhou H, Anders KL, Perkins TA, Yin WW, et al. The changing epidemiology of dengue in China, 1990-2014: a descriptive analysis of 25 years of nationwide surveillance data. BMC Med 2015;13:100. https://doi.org/10.1186/s12916-015-0336-1.
    [3] Luo L, Jiang LY, Xiao XC, Di B, Jing QL, Wang SY, et al. The dengue preface to endemic in mainland China: the historical largest outbreak by Aedes albopictus in Guangzhou, 2014. Infect Dis Poverty 2017;6(1):148. https://doi.org/10.1186/s40249-017-0352-9.
    [4] Li CX, Wang ZD, Yan Y, Qu YN, Hou LY, Li YJ, et al. Association between hydrological conditions and dengue fever incidence in coastal southeastern China From 2013 to 2019. JAMA Netw Open 2023;6(1):e2249440. https://doi.org/10.1001/jamanetworkopen.2022.49440.
    [5] Muller DA, Depelsenaire ACI, Young PR. Clinical and laboratory diagnosis of dengue virus infection. J Infect Dis 2017;215(S2):S89 − 95. https://doi.org/10.1093/infdis/jiw649.
    [6] Guangdong Provincial Health Commission. Guangdong Province dengue fever and other mosquito-borne infectious diseases surveillance program (2019). 2019. https://wsjkw.gd.gov.cn/gkmlpt/content/2/2484/%20post_2484867.html#2532. [2024-7-14]. (In Chinese).
    [7] Guangzhou Medical Security Bureau. Summary table of prices of basic medical service Items of public medical institutions in Guangzhou Area (September 2024). 2024. https://file.m12333.cn/upfile/download/46733976-85c6-cc7c-4d7d-bcccce4c65fa.pdf. [2024-11-25]. (In Chinese).
    [8] Guangzhou Medical Security Bureau, Guangzhou Finance Bureau, Guangzhou Health Commission. Notice on the standards of employee medical insurance and maternity insurance benefits in Guangzhou. 2022. https://www.gz.gov.cn/gzybj/gkmlpt/content/8/8689/post_8689749.html#14461. [2025-11-25]. (In Chinese).
    [9] Dong EH, Xu J, Sun XT, Xu T, Zhang LF, Wang T. Differences in regional distribution and inequality in health-resource allocation on institutions, beds, and workforce: a longitudinal study in China. Arch Public Health 2021;79(1):78. https://doi.org/10.1186/s13690-021-00597-1.
    [10] Tempark T, Whaidee K, Bongsebandhu-Phubhakdi C, Suteerojntrakool O. Prevalence of skin diseases in school-age children. Fam Pract 2022;39(3):340 − 5. https://doi.org/10.1093/fampra/cmab164.
    [11] Lee LK, Thein TL, Kurukularatne C, Gan VCH, Lye DC, Leo YS. Dengue knowledge, attitudes, and practices among primary care physicians in Singapore. Ann Acad Med Singap 2011;40(12):533 − 8. https://doi.org/10.47102/annals-acadmedsg.V40N12p533.
  • TABLE 1.  Basic survey of healthcare facilities.

    Variables Secondary and higher-level medical institutions [N, (%)] (N=11) Community health service centers [N, (%)] (N=11) Total[N, (%)] (N=22)
    Institution-building
    Work programme 11 (100) 10 (90.9) 21(95.5)
    Treatment-related procedures 10 (90.9) 11 (100.0) 21 (95.5)
    Relevant expert groups 9 (81.8) 8 (72.7) 17 (77.3)
    Serious illness/death reporting system 8 (72.7) 6 (54.5) 14 (63.6)
    laboratory test capacity
    NS1 test capacity 11 (100.0) 11 (100.0) 22 (100)
    NS1 test charge 11 (100.0) 8 (72.7) 19 (86.4)
    Antibody test capacity 9 (81.8) 1 (9.1) 10 (45.5)
    PCR test capacity 1 (9.1) 0 (0.0) 1 (4.5)
    NS1 examination of suspected patients (N=226) 24/113 (21.2) 34/113 (30.1) 58/226 (25.7)
    NS1 detection volume, Jan–June 2023 (N=102) 95/102 (93.1) 7/102 (6.9) 102/102 (100.0)
    NS1 detection volume, Jan–June 2024 (N=271) 207/271 (76.4) 64/271 (23.6) 271/271 (100.0)
    Patient admission conditions 10 (90.9) 4 (36.4) 14 (63.6)
    Breeding site clean-up
    1/week 10 (90.9) 10 (90.9) 20 (90.9)
    1/half month or longer 1 (9.1) 1 (9.1) 2 (9.1)
    Nosocomial mosquito control
    1/week 9 (81.8) 6 (54.5) 15 (68.2)
    1/half month 2 (18.2) 5 (45.5) 7 (31.8)
    Dengue-related training
    1/month 1 (9.1) 3 (27.2) 4 (18.2)
    1/half year or longer 10 (90.9) 8 (72.7) 18 (81.8)
    knowledge publicity
    Posters 8 (72.7) 10 (90.9) 18 (81.8)
    Distribution of folders 8 (72.7) 11 (100.0) 19 (86.4)
    Electronic screen publicity 6 (54.5) 10 (90.9) 16 (72.7)
    Broadcasting 0 (0.0) 2 (18.2) 2 (9.1)
    One-on-one consultation publicity 2 (18.2) 5 (45.5) 7 (31.8)
    With three or more publicity methods 4 (36.4) 10 (90.9) 14 (63.6)
    Abbreviation: N=number; NS1=nonstructural protein 1; PCR=polymerase chain reaction.
    Download: CSV

    TABLE 2.  Basic demographic characteristics of physicians by diagnostic awareness scores.

    Variable Qualified, N (%) Not qualified, N (%) χ2 /t P
    Location 0.300 0.584
    Central urban area 176 (61.1) 112 (38.9)
    Peripheral regions 125 (58.7) 88 (41.3)
    Hospital levels* 28.817 <0.001
    Secondary and higher-level medical institutions 246 (67.2) 120 (32.8)
    Community health service centers 55 (40.7) 80 (59.3)
    Department* 27.172 <0.001
    Pediatrics 56 (82.4) 12 (17.6)
    Fever clinic 91 (60.7) 59 (39.3)
    Internal medicine 109 (61.2) 69 (38.8)
    General practice 45 (42.9) 60 (57.1)
    Gender 0.033 0.855
    Male 151 (59.7) 102 (40.3)
    Female 150 (60.5) 98 (39.5)
    Age, mean±SD* 38.1±8.8 40.3±8.8 2.782 0.006
    Professional title* 12.468 0.002
    Physician 99 (66.9) 49 (33.1)
    Attending physician 160 (61.8) 99 (38.2)
    Chief physician 42 (44.7) 52 (55.3)
    Education 2.888 0.236
    Associate degree or below 26 (66.7) 13 (33.3)
    Bachelor’s degree 245 (60.8) 158 (39.2)
    Graduate degree or above 30 (50.8) 29 (49.2)
    Dengue-related training* 12.593 <0.001
    Yes 299 (61.4) 188 (38.6)
    No 2 (14.3) 12 (85.7)
    Abbreviation: SD=standard deviation.
    * P<0.05.
    Download: CSV

    TABLE 3.  Binary logistic regression analysis for physicians’ diagnostic awareness.

    Variable Comparison group Reference group β sx Wald χ2 P OR (95% CI)
    Hospital levels Secondary and higher-level medical institutions Community health service centers 1.013 0.289 12.243 <0.001 2.753 (1.565, 4.868)
    Department Pediatrics Fever clinic 0.951 0.368 6.661 0.010 2.588 (1.257, 5.328)
    Internal medicine 0.029 0.240 0.015 0.904 1.029 (0.644, 1.646)
    General practice −0.022 0.335 0.004 0.948 0.978 (0.507, 1.887)
    Age −0.024 0.014 3.002 0.083 0.976 (0.950, 1.003)
    Professional title Attending physician Physician −0.099 0.250 0.156 0.693 0.906 (0.555, 1.478)
    Chief physician −0.451 0.363 1.545 0.214 0.637 (0.313, 1.297)
    Dengue-related training Yes No 2.623 0.789 11.063 0.001 13.780 (2.937, 64.650)
    Abbreviation: β=regression coefficient; sx=Standard Error of the Coefficient; Wald χ2=Wald Chi-Squared; OR=odds ratio; CI=confidence interval.
    Download: CSV

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Dengue Fever Screening Awareness and Capacity in Healthcare Facilities — Guangzhou City, Guangdong Province, China, 2024

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Summary

What is already known about this topic?

Dengue fever represents a significant public health challenge in tropical and subtropical regions globally, including China. The effective management of dengue cases depends critically on accurate and timely clinical and laboratory diagnosis, supported by well-coordinated healthcare services.

What is added by this report?

This survey revealed that healthcare facilities still needed to enhance dengue case screening and public health education initiatives. Polymerase chain reaction testing capacity was severely insufficient and inconsistent reimbursement rates across health insurance types and institutional levels. Notably, significant variations in dengue diagnostic awareness existed across hospital levels, departments, ages, and professional titles (P<0.05). Targeted training significantly enhanced diagnostic competence [odds ratio (OR)=13.78, 95% confidence interval (CI): 2.94–64.65].

What are the implications for public health practice?

Healthcare facilities must maintain heightened vigilance during dengue fever outbreaks. Robust screening and diagnostic capabilities are essential for early case detection and management. Understanding and addressing identified deficiencies and their contributing factors can strengthen the response capabilities while offering valuable lessons for other regions.

  • 1. School of Public Health, Sun Yat-sen University, Guangzhou City, Guangdong Province, China
  • 2. Department of Communicable Disease Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou City, Guangdong Province, China
  • Corresponding authors:

    Pengzhe Qin, gzcdc_qinpz@gz.gov.cn

    Zhoubin Zhang, gzcdc_zhangzb@gz.gov.cn

  • Funding: This work was supported by the National Key Research and Development Program of China (grant number 2024YFC2311500), The Key Project of Medicine Discipline of Guangzhou (No.2025-2027-11), and General Guidance Project for Health Science and Technology in Guangzhou (No. 20231A011069)
  • Online Date: April 18 2025
    Issue Date: April 18 2025
    doi: 10.46234/ccdcw2025.087
    • Introduction: Dengue fever represents a significant public health challenge in tropical and subtropical regions worldwide, including China. This study aims to enhance early dengue detection and diagnosis by evaluating healthcare facilities’ diagnostic capacity and clinicians’ awareness.

      Methods: In June 2024, surveys were conducted in 11 secondary and higher-level hospitals and 11 community health centers. Data from facilities evaluations and clinician questionnaires were analyzed using chi-square tests and logistic regression.

      Results: Secondary and higher-level hospitals demonstrated more robust dengue-related institution-building but exhibited deficiencies in suspected case screening and public awareness efforts. Additionally, polymerase chain reaction (PCR) testing capacity was limited to one higher-level hospital, and nonstructural protein 1 (NS1) testing costs were high in secondary and higher-level hospitals, with varying reimbursement rates due to different insurance types and institutional levels. Significant disparities in diagnostic awareness were found across hospital levels, departments, ages, and professional titles (P<0.05). The regression analysis shows that education can significantly enhance diagnostic awareness [odds ratio (OR)=13.780, 95% confidence interval (CI): 2.937, 64.650].

      Conclusions: These findings underscore the need for dynamically adjust dengue testing strategies at different epidemic stages and improve NS1 testing cost reimbursement. Also, there should be more efforts in enhancing PCR testing in healthcare facilities and promoting health education.

    • Dengue fever, an acute infectious disease caused by the dengue virus, poses a significant global health threat in tropical and subtropical regions. With an estimated 100 million to 400 million infections annually, approximately half of the world’s population lives in at-risk areas (1). In China, Guangdong, Yunnan, and Hainan provinces represent high-prevalence regions, with Guangzhou City, the capital of Guangdong Province, emerging as a major dengue fever hotspot. The city experiences substantial numbers of both imported and locally transmitted cases, largely attributable to its subtropical climate, humid environment, and extensive international trade networks (2-4). While timely and accurate clinical and laboratory diagnosis, coupled with well-organized healthcare services, are fundamental to effective dengue management (5), significant disparities exist in screening and diagnostic capabilities among healthcare facilities, impacting early detection and case management. Therefore, a comprehensive assessment of diagnostic capabilities and awareness across medical institutions is essential for developing targeted improvement strategies.

      A cross-sectional study was conducted in June 2024 across 11 districts in Guangzhou using stratified random sampling. From each district, 1 secondary or higher-level medical institution and 1 Community Health Service Center were selected, resulting in 22 participating medical institutions. The study focused on relevant departments (pediatrics, internal medicine, fever clinics, and general practice), with 501 doctors completing the diagnostic awareness and capability survey, achieving a 92.3% response rate. Participants were required to be doctors from the selected institutions who voluntarily participated, while those from non-dengue-related departments or those who submitted incomplete electronic questionnaires were excluded.

      The survey consisted of two components. The first assessed institutional dengue prevention and control measures, including system infrastructure, epidemic reporting mechanisms, laboratory testing capabilities, treatment conditions, hospital infection control protocols, staff training, and public health education initiatives. The second component utilized a self-designed questionnaire to evaluate healthcare workers’ awareness of dengue diagnosis. This questionnaire gathered demographic information (including age, gender, education, and professional title) and assessed dengue knowledge through seven questions, with proficiency defined as correctly answering six or more questions.

      Statistical analysis employed categorical variables expressed as percentages and continuous variables as mean ± standard deviation. Chi-square tests were used to analyze differences in diagnostic awareness across demographic variables (age, education level, and professional title), while t-tests were applied for continuous variables. The relationship between various factors and diagnostic awareness was examined using binary logistic regression, calculating odds ratios (OR) and 95% confidence intervals (CI). All analyses were performed using IBM SPSS Statistics (version 27, IBM SPSS Inc., Chicago, USA), with statistical significance defined as P<0.05.

      This study encompassed 22 healthcare facilities and yielded 501 valid questionnaires from dengue-related healthcare workers. The facilities were evenly distributed between secondary or higher-level medical institutions (50.0%, n=11) and Community Health Service Centers (50.0%, n=11). The healthcare worker distribution included 68 pediatricians (13.6%), 150 fever clinic doctors (29.9%), 178 internal medicine doctors (35.5%), and 105 general practitioners (21.0%). Analysis revealed that secondary or higher-level medical institutions demonstrated superior performance in dengue-related system construction, environmental control, and detection capabilities compared to Community Health Service Centers, though they showed slight deficiencies in suspected case screening and dengue-related public education (Table 1). Significant variations in diagnostic awareness were identified across different institution levels, departments, ages, and professional titles (P<0.05) (Table 2). Binary logistic regression analysis revealed that higher hospital levels (OR=2.753, 95% CI: 1.565, 4.868) and participation in dengue training (OR=13.780, 95% CI: 2.937, 64.650) were positively associated with enhanced diagnostic awareness. Notably, compared to fever clinics, pediatric departments demonstrated higher diagnostic awareness (OR=2.588, 95% CI: 1.257, 5.328) (Table 3).

      Variables Secondary and higher-level medical institutions [N, (%)] (N=11) Community health service centers [N, (%)] (N=11) Total[N, (%)] (N=22)
      Institution-building
      Work programme 11 (100) 10 (90.9) 21(95.5)
      Treatment-related procedures 10 (90.9) 11 (100.0) 21 (95.5)
      Relevant expert groups 9 (81.8) 8 (72.7) 17 (77.3)
      Serious illness/death reporting system 8 (72.7) 6 (54.5) 14 (63.6)
      laboratory test capacity
      NS1 test capacity 11 (100.0) 11 (100.0) 22 (100)
      NS1 test charge 11 (100.0) 8 (72.7) 19 (86.4)
      Antibody test capacity 9 (81.8) 1 (9.1) 10 (45.5)
      PCR test capacity 1 (9.1) 0 (0.0) 1 (4.5)
      NS1 examination of suspected patients (N=226) 24/113 (21.2) 34/113 (30.1) 58/226 (25.7)
      NS1 detection volume, Jan–June 2023 (N=102) 95/102 (93.1) 7/102 (6.9) 102/102 (100.0)
      NS1 detection volume, Jan–June 2024 (N=271) 207/271 (76.4) 64/271 (23.6) 271/271 (100.0)
      Patient admission conditions 10 (90.9) 4 (36.4) 14 (63.6)
      Breeding site clean-up
      1/week 10 (90.9) 10 (90.9) 20 (90.9)
      1/half month or longer 1 (9.1) 1 (9.1) 2 (9.1)
      Nosocomial mosquito control
      1/week 9 (81.8) 6 (54.5) 15 (68.2)
      1/half month 2 (18.2) 5 (45.5) 7 (31.8)
      Dengue-related training
      1/month 1 (9.1) 3 (27.2) 4 (18.2)
      1/half year or longer 10 (90.9) 8 (72.7) 18 (81.8)
      knowledge publicity
      Posters 8 (72.7) 10 (90.9) 18 (81.8)
      Distribution of folders 8 (72.7) 11 (100.0) 19 (86.4)
      Electronic screen publicity 6 (54.5) 10 (90.9) 16 (72.7)
      Broadcasting 0 (0.0) 2 (18.2) 2 (9.1)
      One-on-one consultation publicity 2 (18.2) 5 (45.5) 7 (31.8)
      With three or more publicity methods 4 (36.4) 10 (90.9) 14 (63.6)
      Abbreviation: N=number; NS1=nonstructural protein 1; PCR=polymerase chain reaction.

      Table 1.  Basic survey of healthcare facilities.

      Variable Qualified, N (%) Not qualified, N (%) χ2 /t P
      Location 0.300 0.584
      Central urban area 176 (61.1) 112 (38.9)
      Peripheral regions 125 (58.7) 88 (41.3)
      Hospital levels* 28.817 <0.001
      Secondary and higher-level medical institutions 246 (67.2) 120 (32.8)
      Community health service centers 55 (40.7) 80 (59.3)
      Department* 27.172 <0.001
      Pediatrics 56 (82.4) 12 (17.6)
      Fever clinic 91 (60.7) 59 (39.3)
      Internal medicine 109 (61.2) 69 (38.8)
      General practice 45 (42.9) 60 (57.1)
      Gender 0.033 0.855
      Male 151 (59.7) 102 (40.3)
      Female 150 (60.5) 98 (39.5)
      Age, mean±SD* 38.1±8.8 40.3±8.8 2.782 0.006
      Professional title* 12.468 0.002
      Physician 99 (66.9) 49 (33.1)
      Attending physician 160 (61.8) 99 (38.2)
      Chief physician 42 (44.7) 52 (55.3)
      Education 2.888 0.236
      Associate degree or below 26 (66.7) 13 (33.3)
      Bachelor’s degree 245 (60.8) 158 (39.2)
      Graduate degree or above 30 (50.8) 29 (49.2)
      Dengue-related training* 12.593 <0.001
      Yes 299 (61.4) 188 (38.6)
      No 2 (14.3) 12 (85.7)
      Abbreviation: SD=standard deviation.
      * P<0.05.

      Table 2.  Basic demographic characteristics of physicians by diagnostic awareness scores.

      Variable Comparison group Reference group β sx Wald χ2 P OR (95% CI)
      Hospital levels Secondary and higher-level medical institutions Community health service centers 1.013 0.289 12.243 <0.001 2.753 (1.565, 4.868)
      Department Pediatrics Fever clinic 0.951 0.368 6.661 0.010 2.588 (1.257, 5.328)
      Internal medicine 0.029 0.240 0.015 0.904 1.029 (0.644, 1.646)
      General practice −0.022 0.335 0.004 0.948 0.978 (0.507, 1.887)
      Age −0.024 0.014 3.002 0.083 0.976 (0.950, 1.003)
      Professional title Attending physician Physician −0.099 0.250 0.156 0.693 0.906 (0.555, 1.478)
      Chief physician −0.451 0.363 1.545 0.214 0.637 (0.313, 1.297)
      Dengue-related training Yes No 2.623 0.789 11.063 0.001 13.780 (2.937, 64.650)
      Abbreviation: β=regression coefficient; sx=Standard Error of the Coefficient; Wald χ2=Wald Chi-Squared; OR=odds ratio; CI=confidence interval.

      Table 3.  Binary logistic regression analysis for physicians’ diagnostic awareness.

    • This cross-sectional survey evaluated the dengue fever screening awareness and capacity of healthcare facilities in Guangzhou. All 22 surveyed facilities demonstrated the capability to perform nonstructural protein 1 (NS1) antigen testing, with a notable increase in NS1 screenings from January to June 2024 (271 cases) compared to the same period in 2023 (102 cases). The diagnostic awareness assessment of clinicians revealed a 60.1% pass rate, indicating an overall improvement in dengue screening awareness compared to 2023, though certain areas still require enhancement.

      Notable deficiencies persist in healthcare facilities regarding the establishment of severe case and death reporting systems and the formation of dengue fever expert groups. According to the “Guangdong Province Dengue Fever and Other Mosquito-Borne Infectious Diseases Surveillance Program (2019)” Yue Wei Ban [2019] No. 10 (6), secondary and higher-level medical institutions are mandated to promote NS1 testing methods and, where feasible, implement polymerase chain reaction (PCR) testing to enhance early case detection capabilities. However, this study’s findings revealed that among the 11 surveyed secondary and higher-level medical institutions, only 1 had established PCR testing capabilities.

      Secondary and higher-level medical institutions demonstrate comparatively lower screening rates for suspected dengue fever cases and less frequent dissemination of dengue-related knowledge. This may be attributed to more selective patient screening protocols by medical staff or other institutional factors. The reduced health education efforts could be related to the distinct operational priorities of these institutions or limitations in health communication resources, though these associations require further investigation. Additionally, dengue NS1 testing fees vary by institutional tier, as established by the Medical Insurance Bureau (7). Secondary and higher-level institutions charge approximately 70 CNY (Chinese Yuan) compared to 50 CNY at community health service centers. While dengue NS1 screening is covered under Guangzhou’s medical insurance, reimbursement rates differ across insurance types and institutional levels (8), resulting in variable out-of-pocket expenses for patients. Community health service centers face their own challenges, with only 36.4% meeting dengue treatment facility requirements and conducting insufficient environmental mosquito control measures. These deficiencies likely stem from limited healthcare resource availability (9).

      This study’s survey of dengue fever diagnostic awareness among medical staff revealed higher competency levels in secondary and higher-level medical institutions, with pediatricians demonstrating superior diagnostic awareness compared to other departments and general practitioners showing the lowest levels. The enhanced awareness among pediatricians may reflect their extensive experience with childhood skin infections and associated conditions (10), particularly following dengue-specific training. Conversely, general practitioners, primarily working in community health centers, face substantial workloads that may contribute to their comparatively lower diagnostic awareness. Unlike Lee’s study (11), which found higher diagnostic competency among middle and senior-aged clinicians, this study’s findings showed enhanced dengue diagnostic awareness among younger and mid-career doctors with lower to middle-level professional titles, possibly due to their frontline roles and increased exposure to relevant training. Notably, medical staff who participated in dengue-specific training demonstrated significantly improved diagnostic awareness.

      This study has several limitations. First, as the sample was restricted to Guangzhou, the findings may not be generalizable to the national population, limiting the broader applicability of the results. Second, the cross-sectional design precludes causal inference. Additionally, regarding the low screening rates observed in secondary and higher-level medical institutions, the absence of comparative data from relevant secondary and tertiary institutions necessitates further investigation for a more comprehensive understanding.

      While prevention and control priorities may vary across different stages of dengue fever outbreaks, the diagnostic capabilities and screening awareness of healthcare facilities remain fundamental determinants of effective disease management. The findings of this study have significant implications for public health practice, leading to the following recommendations: 1) local Centers for Disease Control and Prevention should implement dynamic adjustments to case detection and management strategies based on epidemic status and medical resource allocation during different phases of local dengue outbreaks. During early epidemic stages, healthcare facilities in outbreak hotspots should implement a “test-upon-fever” approach, while areas without local cases should follow a “test-upon-suspicion” protocol. Hospitals should prioritize hospitalization and isolation for dengue patients to facilitate early detection and minimize transmission. As the epidemic progresses to middle and later stages with increased case numbers, the focus should shift to rational medical resource allocation to prevent healthcare system overcrowding and minimize severe and fatal cases. During these stages, dengue-specific testing should support clinical diagnosis of suspected cases, with hospitalization and isolation priorities focusing on high-risk populations, including elderly individuals, pregnant women, and children. 2) Healthcare facilities should strengthen their dengue fever testing capabilities through multiple approaches. These include expanding PCR testing capacity, implementing comprehensive IgM/IgG antibody and PCR testing protocols, maintaining adequate NS1 antigen reagent stockpiles, and enhancing early case detection systems. Additionally, facilities should intensify dengue awareness initiatives, particularly among general practitioners, through regular training on diagnostic criteria, epidemiological assessment, testing methodologies, and procedural protocols. Educational activities should be amplified during peak transmission seasons. Furthermore, healthcare facilities should implement systematic monitoring of outpatient records to ensure prompt sampling and testing of patients meeting suspected dengue case criteria. Community health centers must also improve their compliance with dengue fever admission and treatment environment standards. 3) The medical insurance department should conduct thorough feasibility studies regarding increasing the NS1 testing reimbursement rate to 60% under the “residents’ medical insurance” scheme. This adjustment would be particularly beneficial in community and outpatient settings during the early dengue fever season, typically occurring from May to August annually.

      Implementation of these comprehensive measures would significantly enhance early detection and accurate diagnosis of dengue fever cases, ultimately contributing to more effective control of dengue fever epidemics.

    • All research personnel from participating Centers for Disease Control and Prevention, hospitals, and healthcare facilities for their valuable contributions to this project.

    • This study did not involve human subjects or any intervention in clinical practice, as it focused on healthcare facilities’ diagnostic capacity and clinicians’ awareness of dengue early detection and diagnosis. Additionally, no personally identifiable information was collected or analyzed throughout the study.

  • Conflicts of interest: No conflicts of interest.
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