1
|
Li Y, Li J, Zhu Z, Zeng W, Zhu Q, Rong Z, Hu J, Li X, He G, Zhao J, Yin L, Quan Y, Zhang Q, Li M, Zhang L, Zhou Y, Liu T, Ma W, Zeng S, Chen Q, Sun L, Xiao J. Exposure-response relationship between temperature, relative humidity, and varicella: a multicity study in South China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:7594-7604. [PMID: 36044136 DOI: 10.1007/s11356-022-22711-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
Varicella is a rising public health issue. Several studies have tried to quantify the relationships between meteorological factors and varicella incidence but with inconsistent results. We aim to investigate the impact of temperature and relative humidity on varicella, and to further explore the effect modification of these relationships. In this study, the data of varicella and meteorological factors from 2011 to 2019 in 21 cities of Guangdong Province, China were collected. Distributed lag nonlinear models (DLNM) were constructed to explore the relationship between meteorological factors (temperature and relative humidity) and varicella in each city, controlling in school terms, holidays, seasonality, long-term trends, and day of week. Multivariate meta-analysis was applied to pool the city-specific estimations. And the meta-regression was used to explore the effect modification for the spatial heterogeneity of city-specific meteorological factors and social factors (such as disposable income per capita, vaccination coverage, and so on) on varicella. The results indicated that the relationship between temperature and varicella in 21 cities appeared nonlinear with an inverted S-shaped. The relative risk peaked at 20.8 ℃ (RR = 1.42, 95% CI: 1.22, 1.65). The relative humidity-varicella relationship was approximately L-shaped, with a peaking risk at 69.5% relative humidity (RR = 1.25, 95% CI: 1.04, 1.50). The spatial heterogeneity of temperature-varicella relationships may be caused by income or varicella vaccination coverage. And varicella vaccination coverage may contribute to the spatial heterogeneity of the relative humidity-varicella relationship. The findings can help us deepen the understanding of the meteorological factors-varicella association and provide evidence for developing prevention strategy for varicella epidemic.
Collapse
Affiliation(s)
- Yihan Li
- School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Jialing Li
- Institute of Immunization Program, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Zhihua Zhu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Weilin Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Qi Zhu
- Institute of Immunization Program, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Zuhua Rong
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Jianxiong Hu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Xing Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Guanhao He
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Jianguo Zhao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Lihua Yin
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Yi Quan
- School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Qian Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Manman Li
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Li Zhang
- School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Yan Zhou
- School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Tao Liu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, Guangdong, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, Guangdong, China
| | - Siqing Zeng
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Qing Chen
- School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China
| | - Limei Sun
- Institute of Immunization Program, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China
| | - Jianpeng Xiao
- School of Public Health, Southern Medical University, Guangzhou, 510515, Guangdong, China.
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, Guangdong, China.
| |
Collapse
|
2
|
Li M, Ma Y, Luo C, Lv Q, Liu Y, Zhang T, Yin F, Shui T. Modification effects of socioeconomic factors on associations between air pollutants and hand, foot, and mouth disease: A multicity time-series study based on heavily polluted areas in the basin area of Sichuan Province, China. PLoS Negl Trop Dis 2022; 16:e0010896. [PMID: 36413517 PMCID: PMC9681081 DOI: 10.1371/journal.pntd.0010896] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 10/14/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Hand, foot, and mouth disease (HFMD) is a serious threat among children in China. Some studies have found that air pollution is associated with HFMD incidence, but the results showed heterogeneity. In this study, we aimed to explore the heterogeneity of associations between air pollutants and the number of HFMD cases and to identify significant socioeconomic effect modifiers. METHODS We collected daily surveillance data on HFMD cases in those aged less than 15 years, air pollution variables and meteorological variables from 2015 to 2017 in the basin area of Sichuan Province. We also collected socioeconomic indicator data. We conducted a two-stage multicity time-series analysis. In the first stage, we constructed a distributed lag nonlinear model (DLNM) to obtain cumulative exposure-response curves between each air pollutant and the numbers of HFMD cases for every city. In the second stage, we carried out a multivariable meta-regression to merge the estimations in the first stage and to identify significant socioeconomic effect modifiers. RESULTS We found that PM10, NO2 and O3 concentrations were associated with the number of HFMD cases. An inverted V-shaped association between PM10 and the number of HFMD cases was observed. The overall NO2-HFMD association was a hockey-stick shape. For the relationships of PM10, SO2, NO2, O3 and CO with HFMD counts, approximately 58.5%, 48.4%, 51.0%, 55.6% and 52.5% of the heterogeneity could be explained, respectively. The proportion of primary school students, population density, urbanization rate, number of licensed physicians and number of hospital beds explained part of the heterogeneity and modified the relationships. CONCLUSION Our study explored the heterogeneity of associations between air pollutants and HFMD counts. The proportion of primary school students, population density, urbanization rate, number of licensed physicians and number of hospital beds could modify the relationships. The results can serve as a reference for relevant public health decision making.
Collapse
Affiliation(s)
- Mengyao Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Caiying Luo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Qiang Lv
- Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Yaqiong Liu
- Sichuan Center for Disease Control and Prevention, Chengdu, People’s Republic of China
| | - Tao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People’s Republic of China
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, People’s Republic of China
- * E-mail: (FY); (TS)
| | - Tiejun Shui
- Yunnan Center for Disease Control and Prevention, Kunming, People’s Republic of China
- * E-mail: (FY); (TS)
| |
Collapse
|
3
|
Wang Y, Wei Y, Li K, Jiang X, Li C, Yue Q, Zee BCY, Chong KC. Impact of extreme weather on dengue fever infection in four Asian countries: A modelling analysis. ENVIRONMENT INTERNATIONAL 2022; 169:107518. [PMID: 36155913 DOI: 10.1016/j.envint.2022.107518] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 08/04/2022] [Accepted: 09/10/2022] [Indexed: 06/16/2023]
Abstract
The rapid spread of dengue fever (DF) infection has posed severe threats to global health. Environmental factors, such as weather conditions, are believed to regulate DF spread. While previous research reported inconsistent change of DF risk with varying weather conditions, few of them evaluated the impact of extreme weather conditions on DF infection risk. This study aims to examine the short-term associations between extreme temperatures, extreme rainfall, and DF infection risk in South and Southeast Asia. A total of 35 locations in Singapore, Malaysia, Sri Lanka, and Thailand were included, and weekly DF data, as well as the daily meteorological data from 2012 to 2020 were collected. A two-stage meta-analysis was used to estimate the overall effect of extreme weather conditions on the DF infection risk. Location-specific associations were obtained by the distributed lag nonlinear models. The DF infection risk appeared to increase within 1-3 weeks after extremely high temperature (e.g. lag week 2: RR = 1.074, 95 % CI: 1.022-1.129, p = 0.005). Compared with no rainfall, extreme rainfall was associated with a declined DF risk (RR = 0.748, 95 % CI: 0.620-0.903, p = 0.003), and most of the impact was across 0-3 weeks lag. In addition, the DF risk was found to be associated with more intensive extreme weathers (e.g. seven extreme rainfall days per week: RR = 0.338, 95 % CI: 0.120-0.947, p = 0.039). This study provides more evidence in support of the impact of extreme weather conditions on DF infection and suggests better preparation of DF control measures according to climate change.
Collapse
Affiliation(s)
- Yawen Wang
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Yuchen Wei
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Kehang Li
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Xiaoting Jiang
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Conglu Li
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Qianying Yue
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region
| | - Benny Chung-Ying Zee
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China
| | - Ka Chun Chong
- Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region; Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China; Centre for Health Systems and Policy Research, The Chinese University of Hong Kong, Hong Kong Special Administrative Region.
| |
Collapse
|
4
|
Luo C, Qian J, Liu Y, Lv Q, Ma Y, Yin F. Long-term air pollution levels modify the relationships between short-term exposure to meteorological factors, air pollution and the incidence of hand, foot and mouth disease in children: a DLNM-based multicity time series study in Sichuan Province, China. BMC Public Health 2022; 22:1484. [PMID: 35927638 PMCID: PMC9351082 DOI: 10.1186/s12889-022-13890-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 07/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epidemiological studies have investigated the short-term effects of meteorological factors and air pollution on the incidence of hand, foot, and mouth disease (HFMD). Several meteorological indicators, such as relative humidity and the diurnal temperature range (DTR), significantly modify the relationship between short-term exposure to temperature and HFMD incidence. However, it remains unclear whether (and how) long-term air pollution levels modify the short-term relationships of HFMD incidence with meteorological factors and air pollution. METHODS We obtained daily data on meteorological factors, air pollutants, and HFMD counts in children from 21 prefecture-level cities in Sichuan Province in Southwest China from 2015 to 2017. First, we constructed a distributed lag nonlinear model (DLNM) at each prefecture-level site to evaluate the short-term impacts of meteorological variables and air pollutants on HFMD incidence. Then, we assessed the pooled effects of the exposures and incorporated long-term city-specific air pollutant indicators as meta-predictors to examine their potential modification effects by performing multivariate meta-regression models. RESULTS We found that long-term SO2 and CO concentrations significantly modified the short-term relationships between climatic variables and HFMD incidence. Specifically, high concentrations of CO (P = 0.027) and SO2 (P = 0.039) reduced the risk of HFMD at low temperatures. The relationship between relative humidity and HFMD incidence was weakened at high SO2 concentrations (P = 0.024), especially when the relative humidity was below the median level. When the minimum relative humidity (32%) was compared to the median relative humidity (77%), the risk ratio (RR) was 0.77 (95% CI: 0.51-1.17) in the 90th percentile of SO2 (19.6 μg/m3) and 0.41 (95% CI: 0.27-0.64) in the 10th percentile of SO2 (10.6 μg/m3). CONCLUSION Our results indicated that long-term SO2 and CO levels modified the short-term associations between HFMD incidence in children and meteorological variables. These findings may inform health authorities to optimize targeted public health policies including reducing ambient air pollution and reinforcing self-protective actions to weaken the adverse health impacts of environmental factors on HFMD incidence.
Collapse
Affiliation(s)
- Caiying Luo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Sichuan, Chengdu, China
| | - Jian Qian
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Sichuan, Chengdu, China
| | - Yaqiong Liu
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Qiang Lv
- Sichuan Center for Disease Control and Prevention, Chengdu, Sichuan, China
| | - Yue Ma
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Sichuan, Chengdu, China.
| | - Fei Yin
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Sichuan, Chengdu, China.
| |
Collapse
|
5
|
Shen L, Sun M, Song S, Hu Q, Wang N, Ou G, Guo Z, Jing D, Shao Z, Bai Y, Liu K. The impact of anti‐COVID‐19 non‐pharmaceutical interventions on hand, foot, and mouth disease—a spatiotemporal perspective in Xi'an, northwestern China. J Med Virol 2022; 94:3121-3132. [PMID: 35277880 PMCID: PMC9088661 DOI: 10.1002/jmv.27715] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/19/2022] [Accepted: 03/01/2022] [Indexed: 11/23/2022]
Abstract
Growing evidence has shown that anti‐COVID‐19 nonpharmaceutical interventions (NPIs) can support prevention and control of various infectious diseases, including intestinal diseases. However, most studies focused on the short‐term mitigating impact and neglected the dynamic impact over time. This study is aimed to investigate the dynamic impact of anti‐COVID‐19 NPIs on hand, foot, and mouth disease (HFMD) over time in Xi'an City, northwestern China. Based on the surveillance data of HFMD, meteorological and web search data, Bayesian Structural Time Series model and interrupted time series analysis were performed to quantitatively measure the impact of NPIs in sequent phases with different intensities and to predict the counterfactual number of HFMD cases. From 2013 to 2021, a total number of 172,898 HFMD cases were reported in Xi'an. In 2020, there appeared a significant decrease in HFMD incidence (−94.52%, 95% CI: −97.54% to −81.95%) in the first half of the year and the peak period shifted from June to October by a small margin of 6.74% compared to the previous years of 2013 to 2019. In 2021, the seasonality of HFMD incidence gradually returned to the bimodal temporal variation pattern with a significant average decline of 61.09%. In particular, the impact of NPIs on HFMD was more evident among young children (0–3 years), and the HFMD incidence reported in industrial areas had an unexpected increase of 51.71% in 2020 autumn and winter. Results suggested that both direct and indirect NPIs should be implemented as effective public health measures to reduce infectious disease and improve surveillance strategies, and HFMD incidence in Xi'an experienced a significant rebound to the previous seasonality after a prominent decline influenced by the anti‐COVID‐19 NPIs. HFMD transmission changed during the COVID‐19 pandemic; The impact of anti‐COVID‐19 NPIs on HFMD varied between different populations; The responsive NPIs indeed affected the HFMD incidence at different stages with potential long‐term impact.
Collapse
Affiliation(s)
- Li Shen
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Minghao Sun
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Shuxuan Song
- Department of EpidemiologyMinistry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical UniversityXi'anChina
| | - Qingwu Hu
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Nuoya Wang
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Guangyu Ou
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Zhaohui Guo
- School of Remote Sensing and Information EngineeringWuhan UniversityWuhanChina
| | - Du Jing
- School of Resource and Environmental ScienceWuhan UniversityWuhanChina
| | - Zhongjun Shao
- Department of EpidemiologyMinistry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical UniversityXi'anChina
| | - Yao Bai
- Department of Infectious Disease Control and PreventionXi'an Center for Disease Prevention and ControlXi'anChina
| | - Kun Liu
- Department of EpidemiologyMinistry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical UniversityXi'anChina
| |
Collapse
|
6
|
Zhang L, Jiang H, Wang K, Yuan Y, Fu Q, Jin X, Zhao N, Huang X, Wang S, Zhang T, Yao K, Chan TC, Xu W, Liu S. Long-term effects of weather condition and air pollution on acute hemorrhagic conjunctivitis in China: A nationalwide surveillance study in China. ENVIRONMENTAL RESEARCH 2021; 201:111616. [PMID: 34233156 DOI: 10.1016/j.envres.2021.111616] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 06/14/2021] [Accepted: 06/26/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Global climate change could have potential impact on enterovirus (EV)-induced infectious diseases. However, the environmental factors promoting acute hemorrhagic conjunctivitis (AHC) circulation remain inconclusive. This study aimed to quantify the relationship between the environment and AHC. METHODS We retrieved the monthly counts and incidence of AHC, meteorological variables and air quality in mainland China between 2013 and 2018. Exposure risks were evaluated by multivariate distributed lag nonlinear models. RESULTS A total of 219,599 AHC cases were reported in 31 provinces of China, predominantly in southern and central China, seasonally increased in summer. AHC incidence increased by 7% between 2013 and 2018, from 2.6873 to 2.7570 per 100,000 people. A moderate positive correlation was seen between AHC and monthly mean temperature, relative humidity (RH) and precipitation. Each unit increment was associated with a relative risk for AHC of 1.058 at 17°-32 °C at lag 0 months, 1.017 at 65-71% RH at lag 1.4 months, and 1.039 at 400-569 mm at lag 2.4 months. By contrast, a negative correlation was seen between monthly ambient NO2 and AHC. CONCLUSION Long-term exposure to higher mean temperature, RH and precipitation were associated with an increased risk of AHC. The general public, especially susceptible populations, should pay close attention to weather changes and take protective measures in advance to any AHC outbreak as the above situations occur.
Collapse
Affiliation(s)
- Li Zhang
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, 310009, China
| | - Hui Jiang
- Beijing Chest Hospital, Capital Medical University, Beijing, 101149, China; Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, 101149, China
| | - Kehan Wang
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, 100872, China
| | - Yuan Yuan
- Department of Geriatrics, Beijing Jishuitan Hospital, Beijing, 100035, China
| | - Qiuli Fu
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, 310009, China
| | - Xiuming Jin
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, 310009, China
| | - Na Zhao
- Collaborative Innovation Center of Recovery and Reconstruction of Degraded Ecosystem in Wanjiang Basin Co-founded by Anhui Province and Ministry of Education, School of Ecology and Environment, Anhui Normal University, Wuhu, Anhui Province, 241002, China
| | - Xiaodan Huang
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, 310009, China
| | - Supen Wang
- Anhui Provincial Key Laboratory of the Conservation and Exploitation of Biological Resources, College of Life Sciences, Anhui Normal University, Wuhu, Anhui Province, 241000, China
| | - Tao Zhang
- Nanjing Jiliang Information Technology Co., Ltd, Nanjing, Jiangsu Provice, 210002, China
| | - Ke Yao
- Eye Center of the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, 310009, China.
| | - Ta-Chien Chan
- Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, 115, Taiwan.
| | - Wangli Xu
- Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, 100872, China.
| | - Shelan Liu
- Department of Infectious Diseases, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, 310051, China.
| |
Collapse
|