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Ge R, Zhu G, Tian M, Hou Z, Pan W, Feng H, Liu K, Xiao Q, Chen Z. Analysis on time delay of tuberculosis among adolescents and young adults in Eastern China. Front Public Health 2024; 12:1376404. [PMID: 38651131 PMCID: PMC11033351 DOI: 10.3389/fpubh.2024.1376404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 03/26/2024] [Indexed: 04/25/2024] Open
Abstract
Background Tuberculosis (TB) is recognized as a significant global public health concern. Still, there remains a dearth of comprehensive evaluation regarding the specific indicators and their influencing factors of delay for adolescents and young adults. Methods All notified pulmonary TB (PTB) patients in Jiaxing City were collected between 2005 and 2022 from China's TB Information Management System. Logistic regression models were conducted to ascertain the factors that influenced patient and health system delays for PTB cases, respectively. Furthermore, the impact of the COVID-19 pandemic on local delays has been explored. Results From January 1, 2005 to December 31, 2022, a total of 5,282 PTB cases were notified in Jiaxing City, including 1,678 adolescents and 3,604 young adults. For patient delay, female (AOR: 1.18, 95%CI: 1.05-1.32), PTB complicated with extra-pulmonary TB (AOR: 1.70, 95% CI: 1.28-2.26), passive case finding (AOR: 1.46, 95% CI: 1.07-1.98) and retreatment (AOR: 1.52, 95% CI: 1.11-2.09) showed a higher risk of delay. For health system delay, minorities (AOR: 0.69, 95% CI: 0.53-0.90) and non-students (AOR: 0.83, 95% CI: 0.71-0.98) experienced a lower delay. Referral (AOR: 1.46, 95% CI: 1.29-1.65) had a higher health system delay compared with clinical consultation. Furthermore, county hospitals (AOR: 1.47, 95% CI: 1.32-1.65) and etiological positive results (AOR: 1.46, 95% CI: 1.30-1.63) were associated with comparatively high odds of patient delay. Contrarily, county hospitals (AOR: 0.88, 95% CI: 0.78-1.00) and etiological positive results (AOR: 0.67, 95% CI: 0.59-0.74) experienced a lower health system delay. Besides, the median of patient delay, health system delay, and total delay during the COVID-19 pandemic were significantly lower than that before. Conclusion In general, there has been a noteworthy decline in the notification rate of PTB among adolescents and young adults in Jiaxing City while the declining trend was not obvious in patient delay, health system delay, and total delay, respectively. It also found factors such as gender, case-finding method, and the hospital level might influence the times of seeking health care and diagnosis in health agencies. These findings will provide valuable insights for refining preventive and treatment strategies for TB among adolescents and young adults.
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Affiliation(s)
- Rui Ge
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Guoying Zhu
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Min Tian
- Nanhu Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Zhigang Hou
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Weizhe Pan
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Hao Feng
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
| | - Kui Liu
- Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China
| | - Qinfeng Xiao
- The First Hospital of Jiaxing, Jiaxing, Zhejiang, China
| | - Zhongwen Chen
- Jiaxing Center for Disease Control and Prevention, Jiaxing, Zhejiang, China
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Ledesma JR, Basting A, Chu HT, Ma J, Zhang M, Vongpradith A, Novotney A, Dalos J, Zheng P, Murray CJL, Kyu HH. Global-, Regional-, and National-Level Impacts of the COVID-19 Pandemic on Tuberculosis Diagnoses, 2020-2021. Microorganisms 2023; 11:2191. [PMID: 37764035 PMCID: PMC10536333 DOI: 10.3390/microorganisms11092191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/28/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
Evaluating cross-country variability on the impact of the COVID-19 pandemic on tuberculosis (TB) may provide urgent inputs to control programs as countries recover from the pandemic. We compared expected TB notifications, modeled using trends in annual TB notifications from 2013-2019, with observed TB notifications to compute the observed to expected (OE) ratios for 170 countries. We applied the least absolute shrinkage and selection operator (LASSO) method to identify the covariates, out of 27 pandemic- and tuberculosis-relevant variables, that had the strongest explanatory power for log OE ratios. The COVID-19 pandemic was associated with a 1.55 million (95% CI: 1.26-1.85, 21.0% [17.5-24.6%]) decrease in TB diagnoses in 2020 and a 1.28 million (0.90-1.76, 16.6% [12.1-21.2%]) decrease in 2021 at a global level. India, Indonesia, the Philippines, and China contributed the most to the global declines for both years, while sub-Saharan Africa achieved pre-pandemic levels by 2021 (OE ratio = 1.02 [0.99-1.05]). Age-stratified analyses revealed that the ≥ 65-year-old age group experienced greater relative declines in TB diagnoses compared with the under 65-year-old age group in 2020 (RR = 0.88 [0.81-0.96]) and 2021 (RR = 0.88 [0.79-0.98]) globally. Covariates found to be associated with all-age OE ratios in 2020 were age-standardized smoking prevalence in 2019 (β = 0.973 [0.957-990]), school closures (β = 0.988 [0.977-0.998]), stay-at-home orders (β = 0.993 [0.985-1.00]), SARS-CoV-2 infection rate (β = 0.991 [0.987-0.996]), and proportion of population ≥65 years (β = 0.971 [0.944-0.999]). Further research is needed to clarify the extent to which the observed declines in TB diagnoses were attributable to disruptions in health services, decreases in TB transmission, and COVID-19 mortality among TB patients.
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Affiliation(s)
- Jorge R. Ledesma
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
- Department of Epidemiology, Brown University School of Public Health, 121 S Main St, Providence, RI 02912, USA
| | - Ann Basting
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
| | - Huong T. Chu
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
- Department of Health Metrics Sciences, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA
| | - Jianing Ma
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, 1800 Cannon Drive, Columbus, OH 43210, USA;
| | - Meixin Zhang
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
| | - Avina Vongpradith
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
| | - Amanda Novotney
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
| | - Jeremy Dalos
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
| | - Peng Zheng
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
- Department of Health Metrics Sciences, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA
| | - Christopher J. L. Murray
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
- Department of Health Metrics Sciences, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA
| | - Hmwe H. Kyu
- Institute for Health Metrics and Evaluation, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA; (J.R.L.); (A.B.); (H.T.C.); (M.Z.); (A.V.); (A.N.); (J.D.); (P.Z.); (C.J.L.M.)
- Department of Health Metrics Sciences, University of Washington, 3980 15th Ave. NE, Seattle, WA 98195, USA
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Li T, Du X, Kang J, Luo D, Liu X, Zhao Y. Patient, Diagnosis, and Treatment Delays Among Tuberculosis Patients Before and During COVID-19 Epidemic - China, 2018-2022. China CDC Wkly 2023; 5:259-265. [PMID: 37138894 PMCID: PMC10150750 DOI: 10.46234/ccdcw2023.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 03/22/2023] [Indexed: 05/05/2023] Open
Abstract
What is already known about this topic? The coronavirus disease (COVID-19) pandemic could have a damaging impact on access to tuberculosis (TB) diagnosis and treatment. What is added by this report? The overall delay experienced by TB patients during the COVID-19 pandemic has shown a modest decrease in comparison to the period before the pandemic. Notably, higher patient delays were observed among agricultural workers and those identified through passive case-finding methods. Furthermore, the patient delay in eastern regions was shorter compared to western and central regions. What are the implications for public health practice? The observed increase in patient delay in 2022 should be of concern for ongoing TB control efforts. Health education and active screening initiatives must be enhanced and broadened among high-risk populations and regions characterized by extended patient delays.
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Affiliation(s)
- Tao Li
- National Center for Tuberculosis Control and Prevention, China CDC, Beijing, China
- School of Public Health, Peking University, Beijing, China
| | - Xin Du
- National Center for Tuberculosis Control and Prevention, China CDC, Beijing, China
| | - Jiaojie Kang
- National Center for Tuberculosis Control and Prevention, China CDC, Beijing, China
| | - Dan Luo
- Department of Public Health, Hangzhou Medical College, Hangzhou City, Zhejiang Province, China
| | - Xiaoqiu Liu
- National Center for Tuberculosis Control and Prevention, China CDC, Beijing, China
| | - Yanlin Zhao
- National Center for Tuberculosis Control and Prevention, China CDC, Beijing, China
- Yanlin Zhao,
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Yang Y, Huang L, Yan H, Nicholas S, Maitland E, Bai Q, Shi X. Coping with COVID: Performance of China's hierarchical medical system during the COVID-19 pandemic. Front Public Health 2023; 11:1148847. [PMID: 37181683 PMCID: PMC10173579 DOI: 10.3389/fpubh.2023.1148847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 03/27/2023] [Indexed: 05/16/2023] Open
Abstract
Objective The COVID-19 pandemic has challenged the health system worldwide. This study aimed to assess how China's hierarchical medical system (HMS) coped with COVID-19 in the short-and medium-term. We mainly measured the number and distribution of hospital visits and healthcare expenditure between primary and high-level hospitals during Beijing's 2020-2021 pandemic relative to the 2017-2019 pre-COVID-19 benchmark period. Methods Hospital operational data were extracted from Municipal Health Statistics Information Platform. The COVID-19 period in Beijing was divided into five phases, corresponding to different characteristics, from January 2020 to October 2021. The main outcome measures in this study include the percentage change in inpatient and outpatient emergency visits, and surgeries, and changing distribution of patients between different hospital levels across Beijing's HMS. In addition, the corresponding health expenditure in each of the 5 phases of COVID-19 was also included. Results In the outbreak phase of the pandemic, the total visits of Beijing hospitals declined dramatically, where outpatient visits fell 44.6%, inpatients visits fell 47.9%; emergency visits fell 35.6%, and surgery inpatients fell 44.5%. Correspondingly, health expenditures declined 30.5% for outpatients and 43.0% for inpatients. The primary hospitals absorbed a 9.51% higher proportion of outpatients than the pre-COVID-19 level in phase 1. In phase 4, the number of patients, including non-local outpatients reached pre-pandemic 2017-2019 benchmark levels. The proportion of outpatients in primary hospitals was only 1.74% above pre-COVID-19 levels in phases 4 and 5. Health expenditure for both outpatients and inpatients reached the baseline level in phase 3 and increased nearly 10% above pre-COVID-19 levels in phases 4 and 5. Conclusion The HMS in Beijing coped with the COVID-19 pandemic in a relatively short time, the early stage of the pandemic reflected an enhanced role for primary hospitals in the HMS, but did not permanently change patient preferences for high-level hospitals. Relative to the pre-COVID-19 benchmark, the elevated hospital expenditure in phase 4 and phase 5 pointed to hospital over-treatment or patient excess treatment demand. We suggest improving the service capacity of primary hospitals and changing the preferences of patients through health education in the post-COVID-19 world.
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Affiliation(s)
- Yong Yang
- Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China
- Medical Device Regulatory Research and Evaluation Center, West China Hospital, Sichuan University, Chengdu, China
- School of Management, Beijing University of Chinese Medicine, Beijing, China
| | - Lieyu Huang
- Office of Policy and Planning Research, Chinese Center for Disease Control and Prevention (China CDC), Beijing, China
| | - Hao Yan
- School of Management, Beijing University of Chinese Medicine, Beijing, China
| | - Stephen Nicholas
- Australian National Institute of Management and Commerce, Sydney, NSW, Australia
- Guangdong Institute for International Strategies, Guangdong University of Foreign Studies, Guangzhou, China
- School of Economics and School of Management, Tianjin Normal University, Tianjin, China
- Newcastle Business School, University of Newcastle, Callaghan, NSW, Australia
| | - Elizabeth Maitland
- University of Liverpool Management School, University of Liverpool, Liverpool, United Kingdom
| | - Qian Bai
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macau, China
| | - Xuefeng Shi
- School of Management, Beijing University of Chinese Medicine, Beijing, China
- National Institute of Traditional Chinese Medicine Strategy and Development, Beijing University of Chinese Medicine, Beijing, China
- *Correspondence: Xuefeng Shi,
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Tuberculosis in the Russian Federation: Dynamics of the Epidemic Indicators before and after COVID-19 Pandemic. Life (Basel) 2022; 12:life12101468. [PMID: 36294903 PMCID: PMC9605375 DOI: 10.3390/life12101468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
The measures taken against tuberculosis (TB) in recent years in the Russian Federation have been highly effective. Unfortunately, the COVID-19 pandemic may seriously undermine the progress that has been made in the fight against TB. The aim of this study was to assess changes in the epidemiological rates of tuberculosis in the Russian Federation before and after the COVID-19 pandemic. Materials and methods. The analysis was conducted by considering the main epidemiological indicators of tuberculosis, according to the federal statistics for the period from 2017 to 2021. The parameters were estimated according to the data received from 11 areas in the North-Western region. Statistical analysis was carried out using the free software computing environment R (v.3.5.1) and the commercial software package Statistical Package for the Social Sciences (SPSS Statistics for Windows, version 24.0, IBM Corp., 2016). Research results. We found a positive correlation between the incidence among the overall population and the incidence among children aged 0–17, inclusively (r = 0.55 in 2017, r = 0.60 in 2020, and r = 0.53 in 2021). Along with the received regularities, a different trend is shown in the data analysis of general incidence and health X-ray examination for tuberculosis among the general population. The correlation has decreased threefold from 2017 (r = 0.72) to 2020 (r = 0.32); this negative trend might be the result of factors such as the quality of X-ray screening examinations among the general population, and the reduced assessment objectivity of the tuberculosis incidence rate. Conclusions. In assessing the correlation between general incidence and incidence in children under 17 years of age, as well as between incidence and mortality in the Russian Federation, a positive correlation was found with an increasing trend. Such a discrepancy might be due to decreases in the occupational health examination coverage among the general population. Therefore, in the years ahead, we can expect epidemiological indicators to increase incidence and mortality, including child mortality, associated with the insufficient detection of tuberculosis among the population during the COVID-19 pandemic.
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