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Zonglin He
International School, Jinan University, Guangzhou 510632, China

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Journal article
Published: 14 June 2021 in Vaccines
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Objectives: To investigate the differences in vaccine hesitancy and preference of the currently available COVID-19 vaccines between two countries, namely, China and the United States (U.S.). Method: A cross-national survey was conducted in both China and the United States, and discrete choice experiments, as well as Likert scales, were utilized to assess vaccine preference and the underlying factors contributing to vaccination acceptance. Propensity score matching (PSM) was performed to enable a direct comparison between the two countries. Results: A total of 9077 (5375 and 3702 from China and the United States, respectively) respondents completed the survey. After propensity score matching, over 82.0% of respondents from China positively accepted the COVID-19 vaccination, while 72.2% of respondents from the United States positively accepted it. Specifically, only 31.9% of Chinese respondents were recommended by a doctor to have COVID-19 vaccination, while more than half of the U.S. respondents were recommended by a doctor (50.2%), local health board (59.4%), or friends and families (64.8%). The discrete choice experiments revealed that respondents from the United States attached the greatest importance to the efficacy of COVID-19 vaccines (44.41%), followed by the cost of vaccination (29.57%), whereas those from China held a different viewpoint, that the cost of vaccination covered the largest proportion in their trade-off (30.66%), and efficacy ranked as the second most important attribute (26.34%). Additionally, respondents from China tended to be much more concerned about the adverse effect of vaccination (19.68% vs. 6.12%) and have a lower perceived severity of being infected with COVID-19. Conclusion: Although the overall acceptance and hesitancy of COVID-19 vaccination in both countries are high, underpinned distinctions between these countries were observed. Owing to the differences in COVID-19 incidence rates, cultural backgrounds, and the availability of specific COVID-19 vaccines in the two countries, vaccine rollout strategies should be nation-dependent.

ACS Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola Akinwunmi; Babatunde Akinwunmi; Casper Zhang; Yibo Wu; Wai-Kit Ming. A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States. Vaccines 2021, 9, 649 .

AMA Style

Taoran Liu, Zonglin He, Jian Huang, Ni Yan, Qian Chen, Fengqiu Huang, Yuejia Zhang, Omolola Akinwunmi, Babatunde Akinwunmi, Casper Zhang, Yibo Wu, Wai-Kit Ming. A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States. Vaccines. 2021; 9 (6):649.

Chicago/Turabian Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola Akinwunmi; Babatunde Akinwunmi; Casper Zhang; Yibo Wu; Wai-Kit Ming. 2021. "A Comparison of Vaccine Hesitancy of COVID-19 Vaccination in China and the United States." Vaccines 9, no. 6: 649.

Review
Published: 13 May 2021 in Pediatric Pulmonology
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Objectives To provide an updated review and meta‐analysis on the efficacy and safety of sildenafil for treating persistent pulmonary hypertension in neonates (PPHN). Methods PubMed/Medline, SCOPUS, Cochrane Central Register of Controlled Trials, and Web of Science were searched from the inception of publication to January 2021. The principal outcomes include oxygenation parameters, hemodynamic metrics and echocardiographic measurements, as well as adverse outcomes. Results A total of eight studies were included with 216 term and premature neonates with PPHN. Compelling evidence showed the use of sildenafil could improve the prognosis of PPHN neonates, compared with baseline or placebo in neonates with PPHN, and a time‐dependent pattern of the improvements can be observed. After 24 h of treatment, the Oxygenation index suggested a steady decrease (SD: −1.80, 95% confidence interval [CI]: −2.92, −0.67) and sildenafil exerted peak effects after 72 h of treatment (SD: −4.02, 95% CI: −5.45, −2.59). No clinically significant side effects were identified. Egger's test and funnel plots of the major outcomes were performed, and the publication bias was not significant. Conclusion Improvements were shown in oxygenation index, pulmonary arterial pressure, and adverse outcomes after using sildenafil for PPHN in neonates. However, future research with robust longitudinal or randomized controlled design is still needed.

ACS Style

Zonglin He; Sui Zhu; Kai Zhou; Ya Jin; Longkai He; Weipeng Xu; CheokUn Lao; Guosheng Liu; Shasha Han. Sildenafil for pulmonary hypertension in neonates: An updated systematic review and meta‐analysis. Pediatric Pulmonology 2021, 1 .

AMA Style

Zonglin He, Sui Zhu, Kai Zhou, Ya Jin, Longkai He, Weipeng Xu, CheokUn Lao, Guosheng Liu, Shasha Han. Sildenafil for pulmonary hypertension in neonates: An updated systematic review and meta‐analysis. Pediatric Pulmonology. 2021; ():1.

Chicago/Turabian Style

Zonglin He; Sui Zhu; Kai Zhou; Ya Jin; Longkai He; Weipeng Xu; CheokUn Lao; Guosheng Liu; Shasha Han. 2021. "Sildenafil for pulmonary hypertension in neonates: An updated systematic review and meta‐analysis." Pediatric Pulmonology , no. : 1.

Preprint content
Published: 02 May 2021
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Objectives To investigate the differences in vaccine hesitancy and preference of the currently available COVID-19 vaccines between two countries, viz. China and the United States (US). Method A cross-national survey was conducted in both China and the US, and discrete choice experiments as well as Likert scales were utilized to assess vaccine preference and the underlying factors contributing to the vaccination acceptance. A propensity score matching (PSM) was performed to enable a direct comparison between the two countries. Results A total of 9,077 (5,375 and 3,702, respectively, from China and the US) respondents have completed the survey. After propensity score matching, over 82.0% respondents from China positively accept the COVID-19 vaccination, while 72.2% respondents form the US positively accept it. Specifically, only 31.9% of Chinese respondents were recommended by a doctor to have COVID-19 vaccination, while more than half of the US respondents were recommended by a doctor (50.2%), local health board (59.4%), or friends and families (64.8%). The discrete choice experiments revealed that respondents from the US attached the greatest importance to the efficacy of COVID-19 vaccines (44.41%), followed by the cost of vaccination (29.57%), whereas those from China held a different viewpoint that the cost of vaccination covers the largest proportion in their trade-off (30.66%), and efficacy ranked as the second most important attribute (26.34%). Also, respondents from China tend to concerned much more about the adverse effect of vaccination (19.68% vs 6.12%) and have lower perceived severity of being infected with COVID-19. Conclusion While the overall acceptance and hesitancy of COVID-19 vaccination in both countries are high, underpinned distinctions between countries are observed. Owing to the differences in COVID-19 incidence rates, cultural backgrounds, and the availability of specific COVID-19 vaccines in two countries, the vaccine rollout strategies should be nation-dependent.

ACS Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola M Akinwunmi; Babatunde Akinwunmi; Casper J.P Zhang; Yibo Wu; Wai-Kit Ming. The comparison of vaccine hesitancy of COVID-19 vaccination in China and the United States. 2021, 1 .

AMA Style

Taoran Liu, Zonglin He, Jian Huang, Ni Yan, Qian Chen, Fengqiu Huang, Yuejia Zhang, Omolola M Akinwunmi, Babatunde Akinwunmi, Casper J.P Zhang, Yibo Wu, Wai-Kit Ming. The comparison of vaccine hesitancy of COVID-19 vaccination in China and the United States. . 2021; ():1.

Chicago/Turabian Style

Taoran Liu; Zonglin He; Jian Huang; Ni Yan; Qian Chen; Fengqiu Huang; Yuejia Zhang; Omolola M Akinwunmi; Babatunde Akinwunmi; Casper J.P Zhang; Yibo Wu; Wai-Kit Ming. 2021. "The comparison of vaccine hesitancy of COVID-19 vaccination in China and the United States." , no. : 1.

Journal article
Published: 25 January 2021 in JMIR Public Health and Surveillance
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Background The influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated. Objective This study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities. Methods Pearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available. Results The Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=–0.565, P<.001), Shanghai (r=–0.47, P<.001), and Guangzhou (r=–0.53, P<.001). In Japan, however, a positive correlation was observed (r=0.416, P<.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, P<.001) in the lagged 3-day model. Conclusions The findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.

ACS Style

Zonglin He; Yiqiao Chin; Shinning Yu; Jian Huang; Casper J P Zhang; Ke Zhu; Nima Azarakhsh; Jie Sheng; Yi He; Pallavi Jayavanth; Qian Liu; Babatunde O Akinwunmi; Wai-Kit Ming. The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis. JMIR Public Health and Surveillance 2021, 7, e20495 .

AMA Style

Zonglin He, Yiqiao Chin, Shinning Yu, Jian Huang, Casper J P Zhang, Ke Zhu, Nima Azarakhsh, Jie Sheng, Yi He, Pallavi Jayavanth, Qian Liu, Babatunde O Akinwunmi, Wai-Kit Ming. The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis. JMIR Public Health and Surveillance. 2021; 7 (1):e20495.

Chicago/Turabian Style

Zonglin He; Yiqiao Chin; Shinning Yu; Jian Huang; Casper J P Zhang; Ke Zhu; Nima Azarakhsh; Jie Sheng; Yi He; Pallavi Jayavanth; Qian Liu; Babatunde O Akinwunmi; Wai-Kit Ming. 2021. "The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis." JMIR Public Health and Surveillance 7, no. 1: e20495.

Research article
Published: 31 December 2020 in PLOS ONE
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Purpose To evaluate the efficacy and safety of methylprednisolone in treating the coronavirus disease 2019 (COVID-19) patients. Methods A retrospective cohort study was conducted, and all COVID-19 patients were recruited who were admitted to the Yichang Third People’s Hospital from February 1st to March 31st, 2020. One-to-one propensity score matching (PSM) was used for minimizing confounding effects. The primary outcome was hospital mortality, with the secondary outcomes being the time needed for a positive SARS-CoV-2 nucleic acid test to turn negative and the length of hospital stay. Results Totaling 367 patients with COVID-19 hospitalized at the Yichang Third People’s Hospital were identified, of whom 276 were mild or stable COVID-19, and 67 were serious or critically ill. Among them, 255 patients were treated using methylprednisolone, and 188 did not receive any corticosteroid-related treatment. After PSM, no statistically significant difference was found in the baseline characteristics between the two groups. Regarding the outcomes, there also were no statistically significant difference between the two groups. Patients without the use of methylprednisolone were more quickly to obtain negative results of their nasopharyngeal swab tests of SARS-CoV-2 nucleic acid after treatment, compared to those receiving methylprednisolone. Conclusion Methylprednisolone could not improve the prognosis of patients with COVID-19, and the efficacy and safety of the use of methylprednisolone in patients with COVID-19 still remain uncertain, thus the use of corticosteroids clinically in patients with COVID-19 should be with cautions.

ACS Style

Xiang You; Chao-Hui Wu; Ya-Nan Fu; Zonglin He; Pin-Fang Huang; Gong-Ping Chen; Cui-Hong Lin; Wai-Kit Ming; Rong-Fang Lin. The use of methylprednisolone in COVID-19 patients: A propensity score matched retrospective cohort study. PLOS ONE 2020, 15, e0244128 .

AMA Style

Xiang You, Chao-Hui Wu, Ya-Nan Fu, Zonglin He, Pin-Fang Huang, Gong-Ping Chen, Cui-Hong Lin, Wai-Kit Ming, Rong-Fang Lin. The use of methylprednisolone in COVID-19 patients: A propensity score matched retrospective cohort study. PLOS ONE. 2020; 15 (12):e0244128.

Chicago/Turabian Style

Xiang You; Chao-Hui Wu; Ya-Nan Fu; Zonglin He; Pin-Fang Huang; Gong-Ping Chen; Cui-Hong Lin; Wai-Kit Ming; Rong-Fang Lin. 2020. "The use of methylprednisolone in COVID-19 patients: A propensity score matched retrospective cohort study." PLOS ONE 15, no. 12: e0244128.

Viewpoint
Published: 17 September 2020 in Journal of Medical Internet Research
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A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

ACS Style

Zonglin He; Casper J P Zhang; Jian Huang; Jingyan Zhai; Shuang Zhou; Joyce Wai-Ting Chiu; Jie Sheng; Winghei Tsang; Babatunde O Akinwunmi; Wai-Kit Ming. A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China. Journal of Medical Internet Research 2020, 22, e21685 .

AMA Style

Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China. Journal of Medical Internet Research. 2020; 22 (9):e21685.

Chicago/Turabian Style

Zonglin He; Casper J P Zhang; Jian Huang; Jingyan Zhai; Shuang Zhou; Joyce Wai-Ting Chiu; Jie Sheng; Winghei Tsang; Babatunde O Akinwunmi; Wai-Kit Ming. 2020. "A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China." Journal of Medical Internet Research 22, no. 9: e21685.

Cover
Published: 15 September 2020 in Pediatric Pulmonology
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Cover Caption: The cover image is based on the Review The association between secondhand smoke and childhood asthma: A systematic review and meta‐analysis by Zonglin He et al., https://doi.org/10.1002/ppul.24961.

ACS Style

Zonglin He; Huailiang Wu; Siyu Zhang; Yuchen Lin; Rui Li; Lijie Xie; Zibo Li; Weiwei Sun; Xinyu Huang; Casper J. P. Zhang; Wai‐Kit Ming. Cover Image, Volume 55, Number 10, October 2020. Pediatric Pulmonology 2020, 55, 1 .

AMA Style

Zonglin He, Huailiang Wu, Siyu Zhang, Yuchen Lin, Rui Li, Lijie Xie, Zibo Li, Weiwei Sun, Xinyu Huang, Casper J. P. Zhang, Wai‐Kit Ming. Cover Image, Volume 55, Number 10, October 2020. Pediatric Pulmonology. 2020; 55 (10):1.

Chicago/Turabian Style

Zonglin He; Huailiang Wu; Siyu Zhang; Yuchen Lin; Rui Li; Lijie Xie; Zibo Li; Weiwei Sun; Xinyu Huang; Casper J. P. Zhang; Wai‐Kit Ming. 2020. "Cover Image, Volume 55, Number 10, October 2020." Pediatric Pulmonology 55, no. 10: 1.

Journal article
Published: 15 September 2020 in Journal of Medical Internet Research
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Background Gestational diabetes mellitus (GDM) can cause adverse consequences to both mothers and their newborns. However, pregnant women living in low- and middle-income areas or countries often fail to receive early clinical interventions at local medical facilities due to restricted availability of GDM diagnosis. The outstanding performance of artificial intelligence (AI) in disease diagnosis in previous studies demonstrates its promising applications in GDM diagnosis. Objective This study aims to investigate the implementation of a well-performing AI algorithm in GDM diagnosis in a setting, which requires fewer medical equipment and staff and to establish an app based on the AI algorithm. This study also explores possible progress if our app is widely used. Methods An AI model that included 9 algorithms was trained on 12,304 pregnant outpatients with their consent who received a test for GDM in the obstetrics and gynecology department of the First Affiliated Hospital of Jinan University, a local hospital in South China, between November 2010 and October 2017. GDM was diagnosed according to American Diabetes Association (ADA) 2011 diagnostic criteria. Age and fasting blood glucose were chosen as critical parameters. For validation, we performed k-fold cross-validation (k=5) for the internal dataset and an external validation dataset that included 1655 cases from the Prince of Wales Hospital, the affiliated teaching hospital of the Chinese University of Hong Kong, a non-local hospital. Accuracy, sensitivity, and other criteria were calculated for each algorithm. Results The areas under the receiver operating characteristic curve (AUROC) of external validation dataset for support vector machine (SVM), random forest, AdaBoost, k-nearest neighbors (kNN), naive Bayes (NB), decision tree, logistic regression (LR), eXtreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT) were 0.780, 0.657, 0.736, 0.669, 0.774, 0.614, 0.769, 0.742, and 0.757, respectively. SVM also retained high performance in other criteria. The specificity for SVM retained 100% in the external validation set with an accuracy of 88.7%. Conclusions Our prospective and multicenter study is the first clinical study that supports the GDM diagnosis for pregnant women in resource-limited areas, using only fasting blood glucose value, patients’ age, and a smartphone connected to the internet. Our study proved that SVM can achieve accurate diagnosis with less operation cost and higher efficacy. Our study (referred to as GDM-AI study, ie, the study of AI-based diagnosis of GDM) also shows our app has a promising future in improving the quality of maternal health for pregnant women, precision medicine, and long-distance medical care. We recommend future work should expand the dataset scope and replicate the process to validate the performance of the AI algorithms.

ACS Style

Jiayi Shen; Jiebin Chen; Zequan Zheng; Jiabin Zheng; Zherui Liu; Jian Song; Sum Yi Wong; Xiaoling Wang; Mengqi Huang; Po-Han Fang; Bangsheng Jiang; Winghei Tsang; Zonglin He; Taoran Liu; Babatunde Akinwunmi; Chi Chiu Wang; Casper J P Zhang; Jian Huang; Wai-Kit Ming. An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study. Journal of Medical Internet Research 2020, 22, e21573 .

AMA Style

Jiayi Shen, Jiebin Chen, Zequan Zheng, Jiabin Zheng, Zherui Liu, Jian Song, Sum Yi Wong, Xiaoling Wang, Mengqi Huang, Po-Han Fang, Bangsheng Jiang, Winghei Tsang, Zonglin He, Taoran Liu, Babatunde Akinwunmi, Chi Chiu Wang, Casper J P Zhang, Jian Huang, Wai-Kit Ming. An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study. Journal of Medical Internet Research. 2020; 22 (9):e21573.

Chicago/Turabian Style

Jiayi Shen; Jiebin Chen; Zequan Zheng; Jiabin Zheng; Zherui Liu; Jian Song; Sum Yi Wong; Xiaoling Wang; Mengqi Huang; Po-Han Fang; Bangsheng Jiang; Winghei Tsang; Zonglin He; Taoran Liu; Babatunde Akinwunmi; Chi Chiu Wang; Casper J P Zhang; Jian Huang; Wai-Kit Ming. 2020. "An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study." Journal of Medical Internet Research 22, no. 9: e21573.

Journal article
Published: 26 August 2020 in BMJ Open Diabetes Research & Care
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Introduction The International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria for gestational diabetes mellitus (GDM) increased the morbidity significantly, but the cost and effectiveness of its application are still unclear. This study aimed to analyze the impact of the IADPSG criteria for diagnosing GDM in China on the perinatal outcomes, and medical expenditure of GDM women versus those with normal glucose tolerance (NGT). Research design and methods We conducted a retrospective cohort study involving 7794 women admitted at the First Affiliated Hospital of Jinan University (Guangzhou, China), from November 1, 2010 to October 31, 2017. The perinatal outcomes and medical expenditure were retrieved from the electronic medical records in the hospital. Propensity score matching (PSM, in a 1:1 ratio) algorithm was used to minimize confounding effects on the difference in the two cohorts. Results PSM minimized the difference of baseline characteristics between women with and without GDM. Of 7794 pregnant women, half (n=3897) were all of the pregnant women with GDM admitted to the hospital during the period, the other half women had NGT and were selected randomly to match with their counterparts. Adopting the IADPSG criteria was associated with reduced risk of emergency cesarean section, polyhydramnios, turbid amniotic fluid and perineal injury (p<0.01 for all) and having any one of the adverse fetal outcomes (p<0.01), including fetal distress, umbilical cord around the neck, neonatal encephalopathy, admission to neonatal intensive care unit, birth trauma, neonatal hypoglycemia and fetal death. After PSM, the median total medical expenditure by the GDM women was ¥912.9 (US$140.7 in 2015) more than that of the the NGT women (p=0.09). Conclusions Despite the increasing medical expenditure, screening at 24–28 gestational weeks under the IADPSG guidelines with the 2-hour, 75 g oral glucose tolerance test can improve short-term maternal and neonatal outcomes.

ACS Style

Zonglin He; Yuan Tang; Huatao Xie; Yuchen Lin; Shangqiang Liang; Yuyuan Xu; Zhili Chen; Liang-Zhi Wu; Jie Sheng; Xiaoyu Bi; Muyi Pang; Babatunde Akinwunmi; Xiaomin Xiao; Wai-Kit Ming. Economic burden of IADPSG gestational diabetes diagnostic criteria in China: propensity score matching analysis from a 7-year retrospective cohort. BMJ Open Diabetes Research & Care 2020, 8, e001538 .

AMA Style

Zonglin He, Yuan Tang, Huatao Xie, Yuchen Lin, Shangqiang Liang, Yuyuan Xu, Zhili Chen, Liang-Zhi Wu, Jie Sheng, Xiaoyu Bi, Muyi Pang, Babatunde Akinwunmi, Xiaomin Xiao, Wai-Kit Ming. Economic burden of IADPSG gestational diabetes diagnostic criteria in China: propensity score matching analysis from a 7-year retrospective cohort. BMJ Open Diabetes Research & Care. 2020; 8 (1):e001538.

Chicago/Turabian Style

Zonglin He; Yuan Tang; Huatao Xie; Yuchen Lin; Shangqiang Liang; Yuyuan Xu; Zhili Chen; Liang-Zhi Wu; Jie Sheng; Xiaoyu Bi; Muyi Pang; Babatunde Akinwunmi; Xiaomin Xiao; Wai-Kit Ming. 2020. "Economic burden of IADPSG gestational diabetes diagnostic criteria in China: propensity score matching analysis from a 7-year retrospective cohort." BMJ Open Diabetes Research & Care 8, no. 1: e001538.

Review
Published: 15 July 2020 in Pediatric Pulmonology
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Background Secondhand smoke (SHS) exposure can trigger asthma exacerbations in children. Different studies have linked increased asthma symptoms and even deaths in children with SHS, but the risk has not been quantified uniformly across studies. We aimed to investigate the role of SHS exposure as a risk factor of asthma among children. Methods We performed a systematic review in PubMed, Scopus, and Google Scholar from June 1975 to 10 March 2020. We included cohort, case‐control, and cross‐sectional studies reporting odds ratio (OR) or relative risk estimates and confidence intervals of all types of SHS exposure and childhood asthma. Results Of the 26 970 studies identified, we included 93 eligible studies (42 cross‐sectional, 41 cohort, and 10 case‐control) in the meta‐analysis. There were significantly positive associations between SHS exposure and doctor‐diagnosed asthma (OR = 1.24; 95% confidence interval (CI) = 1.20‐1.28), wheezing (OR = 1.27; 95% CI = 1.23‐1.32) and asthma‐like syndrome (OR = 1.34; 95% CI = 1.34‐1.64). The funnel plots of all three outcomes skewed to the right, indicating that the studies generally favor a positive association of the disease with tobacco exposure. Subgroup analysis demonstrated that younger children tended to suffer more from developing doctor‐diagnosed asthma, but older children (adolescents) suffered more from wheezing. There was no evidence of significant publication or small study bias using Egger's and Begg's tests. Conclusion The results show a positive association between prenatal and postnatal secondhand smoking exposure and the occurrence of childhood asthma, asthma‐like syndrome, and wheezing. These results lend support to continued efforts to reduce childhood exposure to secondhand smoke.

ACS Style

Zonglin He; Huailiang Wu; Siyu Zhang; Yuchen Lin; Rui Li; Lijie Xie; Zibo Li; Weiwei Sun; Xinyu Huang; Casper J. P. Zhang; Wai‐Kit Ming. The association between secondhand smoke and childhood asthma: A systematic review and meta‐analysis. Pediatric Pulmonology 2020, 55, 2518 -2531.

AMA Style

Zonglin He, Huailiang Wu, Siyu Zhang, Yuchen Lin, Rui Li, Lijie Xie, Zibo Li, Weiwei Sun, Xinyu Huang, Casper J. P. Zhang, Wai‐Kit Ming. The association between secondhand smoke and childhood asthma: A systematic review and meta‐analysis. Pediatric Pulmonology. 2020; 55 (10):2518-2531.

Chicago/Turabian Style

Zonglin He; Huailiang Wu; Siyu Zhang; Yuchen Lin; Rui Li; Lijie Xie; Zibo Li; Weiwei Sun; Xinyu Huang; Casper J. P. Zhang; Wai‐Kit Ming. 2020. "The association between secondhand smoke and childhood asthma: A systematic review and meta‐analysis." Pediatric Pulmonology 55, no. 10: 2518-2531.

Review
Published: 15 July 2020 in Neurochemical Research
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Inflammation secondary to tissue injuries serves as a double-edged sword that determines the prognosis of tissue repair. As one of the most important enzymes controlling the inflammation process by producing leukotrienes, 5-lipoxygenase (5-LOX, also called 5-LO) has been one of the therapeutic targets in regulating inflammation for a long time. Although a large number of 5-LOX inhibitors have been explored, only a few of them can be applied clinically. Surprisingly, phosphorylation of 5-LOX reveals great significance in regulating the subcellular localization of 5-LOX, which has proven to be an important mechanism underlying the enzymatic activities of 5-LOX. There are at least three phosphorylation sites in 5-LOX jointly to determine the final inflammatory outcomes, and adjustment of phosphorylation of 5-LOX at different phosphorylation sites brings hope to provide an unrecognized means to regulate inflammation. The present review intends to shed more lights into the set-point-like mechanisms of phosphorylation of 5-LOX and its possible clinical application by summarizing the biological properties of 5-LOX, the relationship of 5-LOX with neurodegenerative diseases and brain injuries, the phosphorylation of 5-LOX at different sites, the regulatory effects and mechanisms of phosphorylated 5-LOX upon inflammation, as well as the potential anti-inflammatory application through balancing the phosphorylation-depended set-point.

ACS Style

Zonglin He; Di Tao; Jiaming Xiong; Fangfang Lou; Jiayuan Zhang; Jinxia Chen; Weixi Dai; Jing Sun; Yuechun Wang. Phosphorylation of 5-LOX: The Potential Set-point of Inflammation. Neurochemical Research 2020, 45, 2245 -2257.

AMA Style

Zonglin He, Di Tao, Jiaming Xiong, Fangfang Lou, Jiayuan Zhang, Jinxia Chen, Weixi Dai, Jing Sun, Yuechun Wang. Phosphorylation of 5-LOX: The Potential Set-point of Inflammation. Neurochemical Research. 2020; 45 (10):2245-2257.

Chicago/Turabian Style

Zonglin He; Di Tao; Jiaming Xiong; Fangfang Lou; Jiayuan Zhang; Jinxia Chen; Weixi Dai; Jing Sun; Yuechun Wang. 2020. "Phosphorylation of 5-LOX: The Potential Set-point of Inflammation." Neurochemical Research 45, no. 10: 2245-2257.

Preprint content
Published: 22 June 2020
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UNSTRUCTURED A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.

ACS Style

Zonglin He; Casper J P Zhang; Jian Huang; Jingyan Zhai; Shuang Zhou; Joyce Wai-Ting Chiu; Jie Sheng; Winghei Tsang; Babatunde O Akinwunmi; Wai-Kit Ming. A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China (Preprint). 2020, 1 .

AMA Style

Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China (Preprint). . 2020; ():1.

Chicago/Turabian Style

Zonglin He; Casper J P Zhang; Jian Huang; Jingyan Zhai; Shuang Zhou; Joyce Wai-Ting Chiu; Jie Sheng; Winghei Tsang; Babatunde O Akinwunmi; Wai-Kit Ming. 2020. "A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China (Preprint)." , no. : 1.

Preprint content
Published: 18 June 2020
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BACKGROUND Gestational diabetes mellitus (GDM) can cause adverse consequences to both mothers and their newborns. However, pregnant women living in low- and middle-income areas or countries often fail to receive early clinical interventions at local medical facilities due to restricted availability of GDM diagnosis. The outstanding performance of artificial intelligence (AI) in disease diagnosis in previous studies demonstrates its promising applications in GDM diagnosis. OBJECTIVE This study aims to investigate the implementation of a well-performing AI algorithm in GDM diagnosis in a setting, which requires fewer medical equipment and staff and to establish an app based on the AI algorithm. This study also explores possible progress if our app is widely used. METHODS An AI model that included 9 algorithms was trained on 12,304 pregnant outpatients with their consent who received a test for GDM in the obstetrics and gynecology department of the First Affiliated Hospital of Jinan University, a local hospital in South China, between November 2010 and October 2017. GDM was diagnosed according to American Diabetes Association (ADA) 2011 diagnostic criteria. Age and fasting blood glucose were chosen as critical parameters. For validation, we performed k-fold cross-validation (k=5) for the internal dataset and an external validation dataset that included 1655 cases from the Prince of Wales Hospital, the affiliated teaching hospital of the Chinese University of Hong Kong, a non-local hospital. Accuracy, sensitivity, and other criteria were calculated for each algorithm. RESULTS The areas under the receiver operating characteristic curve (AUROC) of external validation dataset for support vector machine (SVM), random forest, AdaBoost, k-nearest neighbors (kNN), naive Bayes (NB), decision tree, logistic regression (LR), eXtreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT) were 0.780, 0.657, 0.736, 0.669, 0.774, 0.614, 0.769, 0.742, and 0.757, respectively. SVM also retained high performance in other criteria. The specificity for SVM retained 100% in the external validation set with an accuracy of 88.7%. CONCLUSIONS Our prospective and multicenter study is the first clinical study that supports the GDM diagnosis for pregnant women in resource-limited areas, using only fasting blood glucose value, patients’ age, and a smartphone connected to the internet. Our study proved that SVM can achieve accurate diagnosis with less operation cost and higher efficacy. Our study (referred to as GDM-AI study, ie, the study of AI-based diagnosis of GDM) also shows our app has a promising future in improving the quality of maternal health for pregnant women, precision medicine, and long-distance medical care. We recommend future work should expand the dataset scope and replicate the process to validate the performance of the AI algorithms.

ACS Style

Jiayi Shen; Jiebin Chen; Zequan Zheng; Jiabin Zheng; Zherui Liu; Jian Song; Sum Yi Wong; Xiaoling Wang; Mengqi Huang; Po-Han Fang; Bangsheng Jiang; Winghei Tsang; Zonglin He; Taoran Liu; Babatunde Akinwunmi; Chi Chiu Wang; Casper J P Zhang; Jian Huang; Wai-Kit Ming. An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study (Preprint). 2020, 1 .

AMA Style

Jiayi Shen, Jiebin Chen, Zequan Zheng, Jiabin Zheng, Zherui Liu, Jian Song, Sum Yi Wong, Xiaoling Wang, Mengqi Huang, Po-Han Fang, Bangsheng Jiang, Winghei Tsang, Zonglin He, Taoran Liu, Babatunde Akinwunmi, Chi Chiu Wang, Casper J P Zhang, Jian Huang, Wai-Kit Ming. An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study (Preprint). . 2020; ():1.

Chicago/Turabian Style

Jiayi Shen; Jiebin Chen; Zequan Zheng; Jiabin Zheng; Zherui Liu; Jian Song; Sum Yi Wong; Xiaoling Wang; Mengqi Huang; Po-Han Fang; Bangsheng Jiang; Winghei Tsang; Zonglin He; Taoran Liu; Babatunde Akinwunmi; Chi Chiu Wang; Casper J P Zhang; Jian Huang; Wai-Kit Ming. 2020. "An Innovative Artificial Intelligence–Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study (Preprint)." , no. : 1.

Preprint content
Published: 08 June 2020
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BACKGROUND The influence of meteorological factors on the transmission and spread of COVID-19 is of interest and has not been investigated. OBJECTIVE This study aimed to investigate the associations between meteorological factors and the daily number of new cases of COVID-19 in 9 Asian cities. METHODS Pearson correlation and generalized additive modeling (GAM) were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available. RESULTS The Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=–0.565, P<.001), Shanghai (r=–0.47, P<.001), and Guangzhou (r=–0.53, P<.001). In Japan, however, a positive correlation was observed (r=0.416, P<.001). In most of the cities (Shanghai, Guangzhou, Hong Kong, Seoul, Tokyo, and Kuala Lumpur), GAM analysis showed the number of daily new confirmed cases to be positively associated with both average temperature and relative humidity, especially using lagged 3D modeling where the positive influence of temperature on daily new confirmed cases was discerned in 5 cities (exceptions: Beijing, Wuhan, Korea, and Malaysia). Moreover, the sensitivity analysis showed, by incorporating the city grade and public health measures into the model, that higher temperatures can increase daily new case numbers (beta=0.073, Z=11.594, P<.001) in the lagged 3-day model. CONCLUSIONS The findings suggest that increased temperature yield increases in daily new cases of COVID-19. Hence, large-scale public health measures and expanded regional research are still required until a vaccine becomes widely available and herd immunity is established.

ACS Style

Zonglin He; Yiqiao Chin; Shinning Yu; Jian Huang; Casper J P Zhang; Ke Zhu; Nima Azarakhsh; Jie Sheng; Yi He; Pallavi Jayavanth; Qian Liu; Babatunde O Akinwunmi; Wai-Kit Ming. The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis (Preprint). 2020, 1 .

AMA Style

Zonglin He, Yiqiao Chin, Shinning Yu, Jian Huang, Casper J P Zhang, Ke Zhu, Nima Azarakhsh, Jie Sheng, Yi He, Pallavi Jayavanth, Qian Liu, Babatunde O Akinwunmi, Wai-Kit Ming. The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis (Preprint). . 2020; ():1.

Chicago/Turabian Style

Zonglin He; Yiqiao Chin; Shinning Yu; Jian Huang; Casper J P Zhang; Ke Zhu; Nima Azarakhsh; Jie Sheng; Yi He; Pallavi Jayavanth; Qian Liu; Babatunde O Akinwunmi; Wai-Kit Ming. 2020. "The Influence of Average Temperature and Relative Humidity on New Cases of COVID-19: Time-Series Analysis (Preprint)." , no. : 1.

Other
Published: 18 April 2020
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AIMTo investigate the associations of meteorological factors and the daily new cases of coronavirus disease (COVID-19) in nine Asian cities.METHODPearson’s correlation and generalized additive modeling were performed to assess the relationships between daily new COVID-19 cases and meteorological factors (daily average temperature and relative humidity) with the most updated data currently available.RESULTSThe Pearson correlation showed that daily new confirmed cases of COVID-19 were more correlated with the average temperature than with relative humidity. Daily new confirmed cases were negatively correlated with the average temperature in Beijing (r=-0.565, PCONCLUSIONThe associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and lagged time. Large-scale public health measures and expanded regional research are still required until a vaccine becomes available and herd immunity is established.Significance statementWith increasing COVID-19 cases across China and the world, and previous studies showing that meteorological factors may be associated with infectious disease transmission, the saying has it that when summer comes, the epidemic of COVID-19 may simultaneously fade away. We demonstrated the influence of meteorological factors on the daily domestic new cases of coronavirus disease (COVID-19) in nine Asian cities. And we found that the associations between meteorological factors and the number of COVID-19 daily cases are inconsistent across cities and time. We think this important topic may give better clues on prevention, management, and preparation for new events or new changes that could happen in the COVID-19 epidemiology in various geographical regions and as we move towards Summer.

ACS Style

Zonglin He; Yiqiao Chin; Jian Huang; Yi He; Babatunde O. Akinwunmi; Shinning Yu; Casper J.P. Zhang; Wai-Kit Ming. Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis. 2020, 1 .

AMA Style

Zonglin He, Yiqiao Chin, Jian Huang, Yi He, Babatunde O. Akinwunmi, Shinning Yu, Casper J.P. Zhang, Wai-Kit Ming. Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis. . 2020; ():1.

Chicago/Turabian Style

Zonglin He; Yiqiao Chin; Jian Huang; Yi He; Babatunde O. Akinwunmi; Shinning Yu; Casper J.P. Zhang; Wai-Kit Ming. 2020. "Meteorological factors and domestic new cases of coronavirus disease (COVID-19) in nine Asian cities: A time-series analysis." , no. : 1.

Journal article
Published: 02 April 2020 in EClinicalMedicine
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Abstract Background A novel coronavirus disease (COVID-19) outbreak due to the severe respiratory syndrome coronavirus (SARS-CoV-2) infection occurred in China in late December 2019. Facemask wearing with proper hand hygiene is considered an effective measure to prevent SARS-CoV-2 transmission, but facemask wearing has become a social concern due to the global facemask shortage. China is the major facemask producer in the world, contributing to 50% of global production. However, a universal facemask wearing policy would put an enormous burden on the facemask supply. Methods We performed a policy review concerning facemasks using government websites and mathematical modelling shortage analyses based on data obtained from the National Health Commission (NHC), the Ministry of Industry and Information Technology (MIIT), the Centre for Disease Control and Prevention (CDC), and General Administration of Customs (GAC) of the People's Republic of China. Three scenarios with respect to wearing facemasks were considered: (1) a universal facemask wearing policy implementation in all regions of mainland China; (2) a universal facemask wearing policy implementation only in the epicentre (Hubei province, China); and (3) no implementation of a universal facemask wearing policy. Findings Regardless of different universal facemask wearing policy scenarios, facemask shortage would occur but eventually end during our prediction period (from 20 Jan 2020 to 30 Jun 2020). The duration of the facemask shortage described in the scenarios of a country-wide universal facemask wearing policy, a universal facemask wearing policy in the epicentre, and no universal facemask wearing policy were 132, seven, and four days, respectively. During the prediction period, the largest daily facemask shortages were predicted to be 589·5, 49·3, and 37·5 million in each of the three scenarios, respectively. In any scenario, an N95 mask shortage was predicted to occur on 24 January 2020 with a daily facemask shortage of 2·2 million. Interpretation Implementing a universal facemask wearing policy in the whole of China could lead to severe facemask shortage. Without effective public communication, a universal facemask wearing policy could result in societal panic and subsequently, increase the nationwide and worldwide demand for facemasks. These increased demands could cause a facemask shortage for healthcare workers and reduce the effectiveness of outbreak control in the affected regions, eventually leading to a pandemic. To fight novel infectious disease outbreaks, such as COVID-19, governments should monitor domestic facemask supplies and give priority to healthcare workers. The risk of asymptomatic transmission and facemask shortages should be carefully evaluated before introducing a universal facemask wearing policy in high-risk regions. Public health measures aimed at improving hand hygiene and effective public communication should be considered along with the facemask policy.

ACS Style

Huai-Liang Wu; Jian Huang; Casper J.P. Zhang; Zonglin He; Wai-Kit Ming. Facemask shortage and the novel coronavirus disease (COVID-19) outbreak: Reflections on public health measures. EClinicalMedicine 2020, 21, 1 .

AMA Style

Huai-Liang Wu, Jian Huang, Casper J.P. Zhang, Zonglin He, Wai-Kit Ming. Facemask shortage and the novel coronavirus disease (COVID-19) outbreak: Reflections on public health measures. EClinicalMedicine. 2020; 21 ():1.

Chicago/Turabian Style

Huai-Liang Wu; Jian Huang; Casper J.P. Zhang; Zonglin He; Wai-Kit Ming. 2020. "Facemask shortage and the novel coronavirus disease (COVID-19) outbreak: Reflections on public health measures." EClinicalMedicine 21, no. : 1.

Other
Published: 12 February 2020
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BackgroundA novel coronavirus disease (COVID-19) outbreak due to SARS-CoV-2 infection occurred in China in late-December 2019. Facemask wearing is considered as one of the most cost-effective and important measures to prevent the transmission of SARS-CoV-2, but it became a social concern due to the recent global facemask shortage. China is the major facemask producer in the world, contributing to 50% of global production. However, even full productivity (20 million facemasks per day) does not seem to meet the need of a population of 1.4 billion in China.MethodsPolicy review using government websites and shortage analysis using mathematical modelling based on data obtained from the National Health Commission (NHC), the Ministry of Industry and Information Technology (MIIT), the Center for Disease Control and Prevention (CDC) of the People’s Republic of China, and Wuhan Bureau of Statistics.FindingsSupplies of facemasks in the whole of China would have been sufficient for both healthcare workers and the general population if the COVID-19 outbreak only occurred in Wuhan city or Hubei province. However, if the outbreak occurred in the whole of China, facemask supplies in China could last for 5 days if under the existing public health measures and a shortage of 853 million facemasks is expected by 30 Apr 2020. Assuming a gradually decreased import volume, we estimated that dramatic increase in productivity (42.7 times of the usual level) is needed to mitigate the facemask crisis by the end of April.InterpretationIn light of the COVID-19 outbreak in China, a shortage of facemasks and other medical resources can considerably compromise the efficacy of public health measures. Effective public health measures should also consider the adequacy and affordability of medical resources. Global collaboration should be strengthened to prevent the development of a global pandemic from a regional epidemic via easing the medical resources crisis in the affected countries.Research in contextEvidence before this studyWe searched PubMed and Web of Science for articles in English, between 1 Jan 1980, and 1 Jan 2020, using the search terms 1) (infection OR infectious disease* OR outbreaks) AND (modelling); and 2) (mask* OR facemask* OR medical resource*) AND (infection OR infectious disease* OR outbreaks). Most relevant studies identified were performed to predict diseases spread and to determine the original infection source of previous epidemics like SARS and H7N9. However, few studies focused on the medical resources crisis during the outbreaks.Added value of this studyTo the best of our knowledge, this is the first study to investigate the facemask shortage during the novel coronavirus pneumonia (COVID-19) outbreak in China. We have summarized in detail the management strategies implemented by the Chinese governments during the outbreaks. By considering three scenarios for the outbreak development, we simulated the facemasks availability from late-December 2019 to late-April 2020 and estimated the duration of sufficient facemask supplies. Our findings showed that if the COVID-19 outbreak occurred only in Wuhan city or Hubei province, facemask shortage would not appear with the existing public health measures. However, if the outbreak occurred in the whole of China, a shortage of facemask could be substantial assuming no alternative public health measures.Implications of all the available evidenceOur findings provide insight into the public health measures to confront medical resources crisis during infectious disease outbreaks. Effective public health measures should consider the adequacy and affordability of existing medical resources. Governments across the world should revisit their emergency plans for controlling infectious disease outbreaks by taking into account the supply of and demand for the medical resource. Global collaboration should be strengthened to prevent the development of a global pandemic from a regional epidemic via easing the medical resources crisis in the affected countries.

ACS Style

Huailiang Wu; Jian Huang; Casper J. P. Zhang; Zonglin He; Wai-Kit Ming. Facemask shortage and the coronavirus disease (COVID-19) outbreak: Reflection on public health measures. 2020, 1 .

AMA Style

Huailiang Wu, Jian Huang, Casper J. P. Zhang, Zonglin He, Wai-Kit Ming. Facemask shortage and the coronavirus disease (COVID-19) outbreak: Reflection on public health measures. . 2020; ():1.

Chicago/Turabian Style

Huailiang Wu; Jian Huang; Casper J. P. Zhang; Zonglin He; Wai-Kit Ming. 2020. "Facemask shortage and the coronavirus disease (COVID-19) outbreak: Reflection on public health measures." , no. : 1.

Review
Published: 16 August 2019 in JMIR Medical Informatics
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Background Artificial intelligence (AI) has been extensively used in a range of medical fields to promote therapeutic development. The development of diverse AI techniques has also contributed to early detections, disease diagnoses, and referral management. However, concerns about the value of advanced AI in disease diagnosis have been raised by health care professionals, medical service providers, and health policy decision makers. Objective This review aimed to systematically examine the literature, in particular, focusing on the performance comparison between advanced AI and human clinicians to provide an up-to-date summary regarding the extent of the application of AI to disease diagnoses. By doing so, this review discussed the relationship between the current advanced AI development and clinicians with respect to disease diagnosis and thus therapeutic development in the long run. Methods We systematically searched articles published between January 2000 and March 2019 following the Preferred Reporting Items for Systematic reviews and Meta-Analysis in the following databases: Scopus, PubMed, CINAHL, Web of Science, and the Cochrane Library. According to the preset inclusion and exclusion criteria, only articles comparing the medical performance between advanced AI and human experts were considered. Results A total of 9 articles were identified. A convolutional neural network was the commonly applied advanced AI technology. Owing to the variation in medical fields, there is a distinction between individual studies in terms of classification, labeling, training process, dataset size, and algorithm validation of AI. Performance indices reported in articles included diagnostic accuracy, weighted errors, false-positive rate, sensitivity, specificity, and the area under the receiver operating characteristic curve. The results showed that the performance of AI was at par with that of clinicians and exceeded that of clinicians with less experience. Conclusions Current AI development has a diagnostic performance that is comparable with medical experts, especially in image recognition-related fields. Further studies can be extended to other types of medical imaging such as magnetic resonance imaging and other medical practices unrelated to images. With the continued development of AI-assisted technologies, the clinical implications underpinned by clinicians’ experience and guided by patient-centered health care principle should be constantly considered in future AI-related and other technology-based medical research.

ACS Style

Jiayi Shen; Casper J P Zhang; Bangsheng Jiang; Jiebin Chen; Jian Song; Zherui Liu; Zonglin He; Chayakrit Krittanawong; Po-Han Fang; Wai-Kit Ming. Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review. JMIR Medical Informatics 2019, 7, e10010 .

AMA Style

Jiayi Shen, Casper J P Zhang, Bangsheng Jiang, Jiebin Chen, Jian Song, Zherui Liu, Zonglin He, Chayakrit Krittanawong, Po-Han Fang, Wai-Kit Ming. Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review. JMIR Medical Informatics. 2019; 7 (3):e10010.

Chicago/Turabian Style

Jiayi Shen; Casper J P Zhang; Bangsheng Jiang; Jiebin Chen; Jian Song; Zherui Liu; Zonglin He; Chayakrit Krittanawong; Po-Han Fang; Wai-Kit Ming. 2019. "Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review." JMIR Medical Informatics 7, no. 3: e10010.

Original article
Published: 21 January 2019 in Journal of Diabetes Investigation
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Aims To summarize the development of the criteria for diagnosing gestational diabetes mellitus (GDM) in China and investigate how different GDM diagnostic criteria influence the national prevalence of GDM, the national health system, and the economic burden of GDM in China. Method Retrospectively using data from women undergoing a 2‐h, 75‐g oral glucose tolerance test at 24–28 gestational weeks in the First Affiliated Hospital of Jinan University (Guangzhou, Guangdong, China) from January 2011 to December 2017, the prevalence rate of GDM and its impacts on the national health system were evaluated using different criteria (the 7th edition textbook criteria, NDDG 1979, WHO 1985, EASD 1996, Japan 2002, ADA 2011 (IADPSG), and NICE 2015). Results The incidence rates of GDM based on the ADA 2011 and NICE 2015 were respectively 22.94% (p<0.01) and 21.72% (p<0.01), over three‐fold higher than implementing the 7th edition textbook criteria (p<0.001). On the contrary, the incidence rates of GDM diagnosed with the NDDG 1979 and WHO 1985 guidelines were significantly less than the 7th edition textbook criteria (p<0.001). From 2001–2016, the estimated national cost of treating GDM rose from 3.9 billion yuan to 27.4 billion yuan after implementing the ADA 2011 guidelines. Conclusions With the implementation of ADA 2011 (IADPSG) guidelines, there are less adverse perinatal outcomes and T2DM in the long run, but the medical costs increased significantly, and the cost‐effectiveness of diagnostic criteria in China is still yet to be confirmed. This article is protected by copyright. All rights reserved.

ACS Style

Zonglin He; Huatao Xie; Shangqiang Liang; Yuan Tang; Wenjing Ding; Yanxin Wu; Wai‐Kit Ming. Influence of different diagnostic criteria on gestational diabetes mellitus incidence and medical expenditures in China. Journal of Diabetes Investigation 2019, 10, 1347 -1357.

AMA Style

Zonglin He, Huatao Xie, Shangqiang Liang, Yuan Tang, Wenjing Ding, Yanxin Wu, Wai‐Kit Ming. Influence of different diagnostic criteria on gestational diabetes mellitus incidence and medical expenditures in China. Journal of Diabetes Investigation. 2019; 10 (5):1347-1357.

Chicago/Turabian Style

Zonglin He; Huatao Xie; Shangqiang Liang; Yuan Tang; Wenjing Ding; Yanxin Wu; Wai‐Kit Ming. 2019. "Influence of different diagnostic criteria on gestational diabetes mellitus incidence and medical expenditures in China." Journal of Diabetes Investigation 10, no. 5: 1347-1357.

Review
Published: 01 February 2018
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BACKGROUND Artificial intelligence (AI) has been extensively used in a range of medical fields to promote therapeutic development. The development of diverse AI techniques has also contributed to early detections, disease diagnoses, and referral management. However, concerns about the value of advanced AI in disease diagnosis have been raised by health care professionals, medical service providers, and health policy decision makers. OBJECTIVE This review aimed to systematically examine the literature, in particular, focusing on the performance comparison between advanced AI and human clinicians to provide an up-to-date summary regarding the extent of the application of AI to disease diagnoses. By doing so, this review discussed the relationship between the current advanced AI development and clinicians with respect to disease diagnosis and thus therapeutic development in the long run. METHODS We systematically searched articles published between January 2000 and March 2019 following the Preferred Reporting Items for Systematic reviews and Meta-Analysis in the following databases: Scopus, PubMed, CINAHL, Web of Science, and the Cochrane Library. According to the preset inclusion and exclusion criteria, only articles comparing the medical performance between advanced AI and human experts were considered. RESULTS A total of 9 articles were identified. A convolutional neural network was the commonly applied advanced AI technology. Owing to the variation in medical fields, there is a distinction between individual studies in terms of classification, labeling, training process, dataset size, and algorithm validation of AI. Performance indices reported in articles included diagnostic accuracy, weighted errors, false-positive rate, sensitivity, specificity, and the area under the receiver operating characteristic curve. The results showed that the performance of AI was at par with that of clinicians and exceeded that of clinicians with less experience. CONCLUSIONS Current AI development has a diagnostic performance that is comparable with medical experts, especially in image recognition-related fields. Further studies can be extended to other types of medical imaging such as magnetic resonance imaging and other medical practices unrelated to images. With the continued development of AI-assisted technologies, the clinical implications underpinned by clinicians’ experience and guided by patient-centered health care principle should be constantly considered in future AI-related and other technology-based medical research.

ACS Style

Jiayi Shen; Casper J P Zhang; Bangsheng Jiang; Jiebin Chen; Jian Song; Zherui Liu; Zonglin He; Sum Yi Wong; Po-Han Fang; Wai-Kit Ming. Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review (Preprint). 2018, 1 .

AMA Style

Jiayi Shen, Casper J P Zhang, Bangsheng Jiang, Jiebin Chen, Jian Song, Zherui Liu, Zonglin He, Sum Yi Wong, Po-Han Fang, Wai-Kit Ming. Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review (Preprint). . 2018; ():1.

Chicago/Turabian Style

Jiayi Shen; Casper J P Zhang; Bangsheng Jiang; Jiebin Chen; Jian Song; Zherui Liu; Zonglin He; Sum Yi Wong; Po-Han Fang; Wai-Kit Ming. 2018. "Artificial Intelligence Versus Clinicians in Disease Diagnosis: Systematic Review (Preprint)." , no. : 1.