The influence of the COVID-19 pandemic on identifying HIV/AIDS cases in China: an interrupted time series study

被引:18
作者
Zhao, Tianming [1 ,2 ]
Liu, Haixia [1 ]
Bulloch, Gabriella [3 ]
Jiang, Zhen [2 ]
Cao, Zhaobing [1 ,2 ]
Wu, Zunyou [1 ,2 ,4 ]
机构
[1] Anhui Med Univ, Sch Publ Hlth, Dept Epidemiol & Hlth Stat, Hefei, Peoples R China
[2] Chinese Ctr Dis Control & Prevent, Natl Ctr AIDS STD Control & Prevent, Beijing, Peoples R China
[3] Univ Melbourne, Fac Med Dent & Hlth Sci, Melbourne, Australia
[4] China CDC, Natl Ctr AIDS STD Control & Prevent, 155 Changbai Rd, Beijing 102206, Peoples R China
来源
LANCET REGIONAL HEALTH-WESTERN PACIFIC | 2023年 / 36卷
基金
美国国家卫生研究院;
关键词
COVID-19; Impact; HIV/AIDS; Identification; China; IMPACT;
D O I
10.1016/j.lanwpc.2023.100755
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background The COVID-19 pandemic has caused significant global public health challenges, and impacted HIV testing and reporting worldwide. We aimed to estimate the impact of COVID-19 polices on identifying HIV/AIDS cases in China from 2020 to 2022. Methods We used an interrupted time series (ITS) design and seasonal autoregressive integrated moving average intervention (SARIMA Intervention) model. Monthly reported data on HIV/AIDS cases were extracted from the National Bureau of Disease Control and Prevention of China from January 2004 to August 2022. Data on Stringency Index (SI) and Economic Support Index (ESI) from January 22, 2020 to August 31, 2022 were extracted from the Oxford COVID-19 Government Response Tracker (OxCGRT). Using these, a SARIMA-Intervention model was constructed to evaluate the association between COVID-19 polices and monthly reported HIV/AIDS case numbers from January 2004 to August 2022 using auto.arima () function from R. The absolute percentage errors (APEs) compared the expected numbers generated by the SARIMA-Intervention model with actual numbers of HIV/AIDS, and was the primary outcome of this study. A second counterfactual model estimated HIV/AIDS case numbers if COVID-19 hadn't occurred in December 2019, and the mean difference between actual and predicted numbers were calculated. All statistical analyses were performed in R software (version 4.2.1) and EmpowerStats 2.0 and a P < 0.05 was considered statistically significant. Findings The SARIMA-Intervention model indicated HIV/AIDS monthly reported cases were inversely and significantly correlated with stricter lockdown and COVID-19 related polices (Coefficient for SI = -231.24, 95% CI:-383.17, -79.32) but not with economic support polices (Coefficient for ESI = 124.27, 95% CI: -309.84, 558.38). APEs of the SARIMA-Intervention model for prediction of HIV/AIDS cases from January 2022 through August 2022, were -2.99, 5.08, -13.64, -34.04, -2.76, -1.52, -1.37 and -2.47 respectively, indicating good accuracy and underreporting of cases during COVID-19. The counterfactual model estimates between January 2020 and August 2022 an additional 1314 HIV/AIDS cases should have been established monthly if COVID-19 hadn't occurred. Interpretation The COVID-19 pandemic influenced the allocation and acquisition of medical resources which impacted accurate monthly reporting of HIV in China. Interventions that promote continuous HIV testing and ensure the adequate provision of HIV services including remote delivery of HIV testing services (HIV self-testing) and online sexual counseling services are necessary during pandemics in future. Copyright (c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页数:11
相关论文
共 41 条
[1]  
[Anonymous], 2014, Joint United Nations Programme on HIV/AIDS (UNAIDS). 90-90-90-An ambitious treatment target to help end the AIDS epidemic. In: UNAIDS Publications
[2]   The use of controls in interrupted time series studies of public health interventions [J].
Bernal, James Lopez ;
Cummins, Steven ;
Gasparrini, Antonio .
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2018, 47 (06) :2082-2093
[3]  
Chamie G, 2021, LANCET HIV, V8, pe225, DOI 10.1016/S2352-3018(21)00023-0
[4]   Associations of blood and urinary heavy metals with rheumatoid arthritis risk among adults in NHANES, 1999-2018 [J].
Chen, Li ;
Sun, Qiuzi ;
Peng, Shufen ;
Tan, Tianqi ;
Mei, Guibin ;
Chen, Huimin ;
Zhao, Ying ;
Yao, Ping ;
Tang, Yuhan .
CHEMOSPHERE, 2022, 289
[5]   Changing the Use of HIV Pre-exposure Prophylaxis Among Men Who Have Sex With Men During the COVID-19 Pandemic in Melbourne, Australia [J].
Chow, Eric P. F. ;
Hocking, Jane S. ;
Ong, Jason J. ;
Schmidt, Tina ;
Buchanan, Andrew ;
Rodriguez, Elena ;
Maddaford, Kate ;
Patel, Prital ;
Fairley, Christopher K. .
OPEN FORUM INFECTIOUS DISEASES, 2020, 7 (07)
[6]  
Cook Thomas D., 2002, EXPT QUASIEXPERIMENT
[7]   SARIMA Modelling Approach for Forecasting of Traffic Accidents [J].
Deretic, Nemanja ;
Stanimirovic, Dragan ;
Al Awadh, Mohammed ;
Vujanovic, Nikola ;
Djukic, Aleksandar .
SUSTAINABILITY, 2022, 14 (08)
[8]   SARIMA Model Forecasting Performance of the COVID-19 Daily Statistics in Thailand during the Omicron Variant Epidemic [J].
Duangchaemkarn, Khanita ;
Boonchieng, Waraporn ;
Wiwatanadate, Phongtape ;
Chouvatut, Varin .
HEALTHCARE, 2022, 10 (07)
[9]   Modeling malaria control intervention effect in KwaZulu-Natal, South Africa using intervention time series analysis [J].
Ebhuoma, Osadolor ;
Gebreslasie, Michael ;
Magubane, Lethumusa .
JOURNAL OF INFECTION AND PUBLIC HEALTH, 2017, 10 (03) :334-338
[10]   Medication Non-adherence and Condomless Anal Intercourse Increased Substantially During the COVID-19 Pandemic Among MSM PrEP Users: A Retrospective Cohort Study in Four Chinese Metropolises [J].
Gao, Yangyang ;
Hu, Qinghai ;
Leuba, Sequoia I. ;
Jia, Le ;
Wang, Hongyi ;
Huang, Xiaojie ;
Chen, Yaokai ;
Wang, Hui ;
Zhang, Jing ;
Chu, Zhenxing ;
Zhang, Lukun ;
Wang, Zixin ;
Shang, Hong ;
Xu, Junjie .
FRONTIERS IN MEDICINE, 2022, 9