1
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Winalai C, Anupong S, Modchang C, Chadsuthi S. LSTM-Powered COVID-19 prediction in central Thailand incorporating meteorological and particulate matter data with a multi-feature selection approach. Heliyon 2024; 10:e30319. [PMID: 38711630 PMCID: PMC11070856 DOI: 10.1016/j.heliyon.2024.e30319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 04/23/2024] [Accepted: 04/23/2024] [Indexed: 05/08/2024] Open
Abstract
The COVID-19 pandemic has significantly impacted public health and necessitated urgent actions to mitigate its spread. Monitoring and predicting the outbreak's progression have become vital to devise effective strategies and allocate resources efficiently. This study presents a novel approach utilizing Multivariate Long Short-Term Memory (LSTM) to analyze and predict COVID-19 trends in Central Thailand, particularly emphasizing the multi-feature selection process. To consider a comprehensive view of the pandemic's dynamics, our research dataset encompasses epidemiological, meteorological, and particulate matter features, which were gathered from reliable sources. We propose a multi-feature selection technique to identify the most relevant and influential features that significantly impact the spread of COVID-19 in the region to enhance the model's performance. Our results highlight that relative humidity is the key factor driving COVID-19 transmission in Central Thailand. The proposed multi-feature selection technique significantly improves the model's accuracy, ensuring that only the most informative variables contribute to the predictions, avoiding the potential noise or redundancy from less relevant features. The proposed LSTM model demonstrates its capability to forecast COVID-19 cases, facilitating informed decision-making for public health authorities and policymakers.
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Affiliation(s)
- Chanidapa Winalai
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
| | - Suparinthon Anupong
- Department of Chemistry, Mahidol Wittayanusorn School (MWIT), Salaya, Nakhon Pathom 73170, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand
- Centre of Excellence in Mathematics, CHE, Bangkok 10400, Thailand
- Thailand Center of Excellence in Physics, CHE, 328 Si Ayutthaya Road, Bangkok 10400, Thailand
| | - Sudarat Chadsuthi
- Department of Physics, Faculty of Science, Naresuan University, Phitsanulok 65000, Thailand
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2
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Rybarczyk Y, Zalakeviciute R, Ortiz-Prado E. Causal effect of air pollution and meteorology on the COVID-19 pandemic: A convergent cross mapping approach. Heliyon 2024; 10:e25134. [PMID: 38322928 PMCID: PMC10844283 DOI: 10.1016/j.heliyon.2024.e25134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 01/15/2024] [Accepted: 01/22/2024] [Indexed: 02/08/2024] Open
Abstract
Environmental factors have been suspected to influence the propagation and lethality of COVID-19 in the global population. However, most of the studies have been limited to correlation analyses and did not use specific methods to address the dynamic of the causal relationship between the virus and its external drivers. This work focuses on inferring and understanding the causal effect of critical air pollutants and meteorological parameters on COVID-19 by using an Empirical Dynamic Modeling approach called Convergent Cross Mapping. This technique allowed us to identify the time-delayed causation and the sign of interactions. Considering its remarkable urban environment and mortality rate during the pandemic, Quito, Ecuador, was chosen as a case study. Our results show that both urban air pollution and meteorology have a causal impact on COVID-19. Even if the strength and the sign of the causality vary over time, a general trend can be drawn. NO2, SO2, CO and PM2.5 have a positive causation for COVID-19 infections (ρ > 0.35 and ∂ > 9.1). Contrary to current knowledge, this study shows a rapid effect of pollution on COVID-19 cases (1 < lag days <24) and a negative impact of O3 on COVID-19-related deaths (ρ = 0.53 and ∂ = -0.3). Regarding the meteorology, temperature (ρ = 0.24 and ∂ = -0.4) and wind speed (ρ = 0.34 and ∂ = -3.9) tend to mitigate the epidemiological consequences of SARS-CoV-2, whereas relative humidity seems to increase the excess deaths (ρ = 0.4 and ∂ = 0.05). A causal network is proposed to synthesize the interactions between the studied variables and to provide a simple model to support the management of coronavirus outbreaks.
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Affiliation(s)
- Yves Rybarczyk
- School of Information and Engineering, Dalarna University, Falun, Sweden
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3
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Harapan H, Johar E, Maroef CN, Sriyani IY, Iqhrammullah M, Kusuma HI, Syukri M, Razali R, Hamdani H, Kurniawan R, Irwansyah I, Sofyan SE, Myint KS, Mahlia TI, Rizal S. Effect of elevated temperature on SARS-CoV-2 viability. F1000Res 2023; 11:403. [PMID: 37745627 PMCID: PMC10517306 DOI: 10.12688/f1000research.110305.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/06/2023] [Indexed: 09/26/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide disruption of global health putting healthcare workers at high risk. To reduce the transmission of SARS-CoV-2, in particular during treating the patients, our team aims to develop an optimized isolation chamber. The present study was conducted to evaluate the role of temperature elevation against SARS-CoV-2 viability, where the information would be used to build the isolation chamber. 0.6 mL of the Indonesian isolate of SARS-CoV-2 strain 20201012747 (approximately 10 13 PFU/mL) was incubated for one hour with a variation of temperatures: 25, 30, 35, 40, 45, 50, 55, 60, and 65°C in digital block heater as well as at room temperature (21-23°C) before used to infect Vero E6 cells. The viability was determined using a plaque assay. Our data found a significant reduction of the viral viability from 10 13 PFU/mL to 10 9 PFU/mL after the room temperature was increase to 40°C. Further elevation revealed that 55°C and above resulted in the total elimination of the viral viability. Increasing the temperature 40°C to reduce the SARS-CoV-2 survival could create mild hyperthermia conditions in a patient which could act as a thermotherapy. In addition, according to our findings, thermal sterilization of the vacant isolation chamber could be conducted by increasing the temperature to 55°C. In conclusion, elevating the temperature of the isolation chamber could be one of the main variables for developing an optimized isolation chamber for COVID-19 patients.
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Affiliation(s)
- Harapan Harapan
- Department of Microbiology, School of Medicine, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
- Tropical Disease Centre, School of Medicine, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
- Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Edison Johar
- Eijkman Institute for Molecular Biology, Jakarta, 10430, Indonesia
| | | | - Ida Yus Sriyani
- Eijkman Institute for Molecular Biology, Jakarta, 10430, Indonesia
| | - Muhammad Iqhrammullah
- Graduate School of Mathematics and Applied Sciences, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Hendrix Indra Kusuma
- Medical Research Unit, School of Medicine, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
- Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Maimun Syukri
- Department of Internal Medicine, School of Medicine, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Razali Razali
- Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Hamdani Hamdani
- Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Rudi Kurniawan
- Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Irwansyah Irwansyah
- Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Sarwo Edhy Sofyan
- Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
| | - Khin Saw Myint
- Eijkman Institute for Molecular Biology, Jakarta, 10430, Indonesia
| | - T.M. Indra Mahlia
- School of Civil and Environmental Engineering, University of Technology Sydney, Ultimo, Sydney, NSW 2007, Australia
| | - Samsul Rizal
- Department of Mechanical and Industrial Engineering, Faculty of Engineering, Universitas Syiah Kuala, Banda Aceh, 23111, Indonesia
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Necesito IV, Velasco JMS, Jung J, Bae YH, Yoo Y, Kim S, Kim HS. Predicting COVID-19 Cases in South Korea Using Stringency and Niño Sea Surface Temperature Indices. Front Public Health 2022; 10:871354. [PMID: 35719622 PMCID: PMC9204014 DOI: 10.3389/fpubh.2022.871354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
Most coronavirus disease 2019 (COVID-19) models use a combination of agent-based and equation-based models with only a few incorporating environmental factors in their prediction models. Many studies have shown that human and environmental factors play huge roles in disease transmission and spread, but few have combined the use of both factors, especially for SARS-CoV-2. In this study, both man-made policies (Stringency Index) and environment variables (Niño SST Index) were combined to predict the number of COVID-19 cases in South Korea. The performance indicators showed satisfactory results in modeling COVID-19 cases using the Non-linear Autoregressive Exogenous Model (NARX) as the modeling method, and Stringency Index (SI) and Niño Sea Surface Temperature (SST) as model variables. In this study, we showed that the accuracy of SARS-CoV-2 transmission forecasts may be further improved by incorporating both the Niño SST and SI variables and combining these variables with NARX may outperform other models. Future forecasting work by modelers should consider including climate or environmental variables (i.e., Niño SST) to enhance the prediction of transmission and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
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Affiliation(s)
- Imee V. Necesito
- Department of Civil Engineering, Inha University, Incheon, South Korea
- *Correspondence: Imee V. Necesito
| | - John Mark S. Velasco
- Department of Clinical Epidemiology, College of Medicine, University of the Philippines, Manila, Philippines
- Institute of Molecular Biology and Biotechnology, National Institutes of Health, University of the Philippines, Manila, Philippines
| | - Jaewon Jung
- Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology, Gyeonggi-do, South Korea
| | - Young Hye Bae
- Department of Civil Engineering, Inha University, Incheon, South Korea
| | - Younghoon Yoo
- Department of Civil Engineering, Inha University, Incheon, South Korea
| | - Soojun Kim
- Department of Civil Engineering, Inha University, Incheon, South Korea
| | - Hung Soo Kim
- Department of Civil Engineering, Inha University, Incheon, South Korea
- Hung Soo Kim
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5
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Yu H, Du R, Wang M, Yu F, Yang J, Jiao L, Wang Z, Liu H, Wu P, Bärnighausen T, Xue L, Wang C, McMahon S, Geldsetzer P, Chen S. The provision of COVID-19 vaccines developed in China to other countries: A cross-sectional online survey on the views of the Chinese public. JMIR Public Health Surveill 2022; 8:e33484. [PMID: 35483084 PMCID: PMC9177168 DOI: 10.2196/33484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 02/22/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND COVID-19 vaccines are in short supply globally. China was among the first countries to pledge supplies of the COVID-19 vaccine as a global public product, and to date the country has provided more than 600 million vaccines to more than 200 countries and regions with low COVID-19 vaccination rates. Understanding the public's attitude in China towards the global distribution of COVID-19 vaccines could inform global and national decisions, policies and debates. OBJECTIVE The aim of this study was to determine the attitudes of adults living in China regarding the global allocation of COVID-19 vaccines developed in China, and how these attitudes vary across provinces and by sociodemographic characteristics. METHODS We conducted a cross-sectional online survey among adults registered with the survey company KuRunData. The survey asked participants 31 questions on their attitudes regarding the global allocation of COVID-19 vaccines developed in China. We disaggregated responses by province and sociodemographic characteristics. All analyses used survey sampling weights. RESULTS A total of 10,000 participants completed the questionnaire. Participants generally favored providing COVID-19 vaccines to foreign countries before fully fulfilling domestic needs (75.6%, 95% CI: 74.6% - 76.5%). Women (76.8%, OR = 1.18, 95% CI: 1.07 - 1.32, P = .002) and those living in rural areas (76.8%, OR = 1.13, 95% CI: 1.01 - 1.27, P = .03) were especially likely to hold this opinion. Most respondents preferred providing financial support through international platforms rather than directly offering support to individual countries (72.1%, 95% CI: 71.0% - 73.1%), while for vaccine products they preferred direct provision to relevant countries instead of via a delivery platform such as COVAX (77.3%, 95% CI: 76.3% - 78.2%). CONCLUSIONS Among our survey sample, we find that adults are generally supportive of the international distribution of COVID-19 vaccines, which may encourage policy makers to support and implement the distribution of COVID-19 vaccines developed in China globally. Conducting similar surveys in other countries could help align policymakers' actions on COVID-19 vaccine distribution with the preferences of their constituencies. CLINICALTRIAL
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Affiliation(s)
- Hanzhi Yu
- School of Public Affairs, Zhejiang University, Hangzhou, CN
| | - Runming Du
- Department of Global Health, School of Public Health, Peking University, Beijing, CN
| | - Minmin Wang
- Peking University Cancer Hospital & Institute, Beijing, CN
| | - Fengyun Yu
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, CN
| | - Juntao Yang
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, CN
| | | | - Zhuoran Wang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CN
| | - Haitao Liu
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CN
| | - Peixin Wu
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CN
| | - Till Bärnighausen
- Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg University, Postfach 10 57 60 69047 Heidelberg, Heidelberg, DE
| | - Lan Xue
- School of Public Policy and Management, Tsinghua University, Beijing, CN
| | - Chen Wang
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, CN
| | - Shannon McMahon
- Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg University, Postfach 10 57 60 69047 Heidelberg, Heidelberg, DE
| | - Pascal Geldsetzer
- Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, US
| | - Simiao Chen
- Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg University, Postfach 10 57 60 69047 Heidelberg, Heidelberg, DE
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6
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Affiliation(s)
- Ji-Ming Chen
- School of Life Science and Engineering, Foshan University, Foshan, China.
| | - Yi-Qing Chen
- School of Life Sciences, Tsinghua University, Beijing, China
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7
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Mandal CC, Panwar MS, Yadav CP, Tripathi V, Bandyopadhayaya S. Combinatorial influence of environmental temperature, obesity and cholesterol on SARS-CoV-2 infectivity. Sci Rep 2022; 12:4796. [PMID: 35314722 PMCID: PMC8935894 DOI: 10.1038/s41598-022-08485-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 03/03/2022] [Indexed: 01/27/2023] Open
Abstract
The continuing evolution of SARS-CoV-2 variants not only causes a long-term global health concerns but also encounters the vaccine/drug effectiveness. The degree of virus infectivity and its clinical outcomes often depend on various biological parameters (e.g., age, genetic factors, diabetes, obesity and other ailments) of an individual along with multiple environmental factors (e.g., air temperature, humidity, seasons). Thus, despite the extensive search for and use of several vaccine/drug candidates, the combinative influence of these various extrinsic and intrinsic risk factors involved in the SARS-CoV-2 virus infectivity has yet to be explored. Previous studies have reported that environment temperature is negatively associated with virus infectivity for SARS-CoV-2. This study elaborates on our previous findings, investigating the link between environmental temperature and other metabolic parameters, such as average total cholesterol and obesity, with the increase in COVID-19 cases. Statistical analysis conducted on a per country basis not only supports the existence of a significant negative correlation between environmental temperature and SARS-CoV-2 infections but also found a strong positive correlation between COVID-19 cases and these metabolic parameters. In addition, a multiphase growth curve model (GCM) was built to predict the contribution of these covariates in SARS-CoV-2 infectivity. These findings, for first time, support the idea that there might be a combinatorial impact of environmental temperature, average total cholesterol, and obesity in the inflation of the SARS-CoV-2 infectivity.
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Affiliation(s)
- Chandi C Mandal
- Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, NH-8, Bandarsindri, Kishangarh, Ajmer, Rajasthan, 305817, India.
| | - Mahaveer S Panwar
- Department of Statistics, Banaras Hindu University, Varanasi, Uttar Pradesh, India
| | - Chandra P Yadav
- Department of Statistics, Banaras Hindu University, Varanasi, Uttar Pradesh, India
| | - Vaishnavi Tripathi
- Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, NH-8, Bandarsindri, Kishangarh, Ajmer, Rajasthan, 305817, India
| | - Shreetama Bandyopadhayaya
- Department of Biochemistry, School of Life Sciences, Central University of Rajasthan, NH-8, Bandarsindri, Kishangarh, Ajmer, Rajasthan, 305817, India
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Irfan M, Ikram M, Ahmad M, Wu H, Hao Y. Does temperature matter for COVID-19 transmissibility? Evidence across Pakistani provinces. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021. [PMID: 34143386 DOI: 10.1007/s11356-021-14875-6/tables/1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
The outbreak of novel coronavirus (COVID-19) has become a global concern that is deteriorating environmental quality and damaging human health. Though some researchers have investigated the linkage between temperature and COVID-19 transmissibility across different geographical locations and over time, yet these studies are scarce. This study aims to bridge this gap using daily temperature and COVID-19 cases (transmissibility) by employing grey incidence analysis (GIA) models (i.e., Deng's grey incidence analysis (DGIA), the absolute degree GIA (ADGIA), the second synthetic degree GIA (SSDGIA), the conservative (maximin) model) and correlation analysis. Data on temperature are accessed from the NASA database, while the data on COVID-19 cases are collected from the official website of the government of Pakistan. Empirical results reveal the existence of linkages between temperature and COVID-19 in all Pakistani provinces. These linkages vary from a relatively stronger to a relatively weaker linkage. Based on calculated weights, the strength of linkages is ranked across provinces as follows: Gilgit Baltistan (0.715301) > Baluchistan (0.675091) > Khyber Pakhtunkhwa (0.619893) > Punjab (0.619286) > Sindh (0.601736). The disparity in the strength of linkage among provinces is explained by the discrepancy in the intensity of temperature. Besides, the diagrammatic correlation analysis shows that temperature is inversely linked to COVID-19 cases (per million persons) over time, implying that low temperatures are associated with high COVID-19 transmissibility and vice versa. This study is among the first of its kind to consider the linkages between temperature and COVID-19 transmissibility for a tropical climate country (Pakistan) using the advanced GIA models. Research findings provide an up-to-date glimpse of the outbreak and emphasize the need to raise public awareness about the devastating impacts of the COVID-19. The educational syllabus should provide information on the causes, signs, and precautions of the pandemic. Additionally, individuals should practice handwashing, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to ensure a secure and supportive atmosphere for preventing and controlling the current pandemic.
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Affiliation(s)
- Muhammad Irfan
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
| | - Muhammad Ikram
- Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Shenzhen, China.
| | - Munir Ahmad
- School of Economics, Zhejiang University, Hangzhou, 310058, China
| | - Haitao Wu
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China
| | - Yu Hao
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China.
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China.
- Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China.
- Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081, China.
- Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, 100081, China.
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Irfan M, Ikram M, Ahmad M, Wu H, Hao Y. Does temperature matter for COVID-19 transmissibility? Evidence across Pakistani provinces. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:59705-59719. [PMID: 34143386 PMCID: PMC8211721 DOI: 10.1007/s11356-021-14875-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Accepted: 06/09/2021] [Indexed: 05/03/2023]
Abstract
The outbreak of novel coronavirus (COVID-19) has become a global concern that is deteriorating environmental quality and damaging human health. Though some researchers have investigated the linkage between temperature and COVID-19 transmissibility across different geographical locations and over time, yet these studies are scarce. This study aims to bridge this gap using daily temperature and COVID-19 cases (transmissibility) by employing grey incidence analysis (GIA) models (i.e., Deng's grey incidence analysis (DGIA), the absolute degree GIA (ADGIA), the second synthetic degree GIA (SSDGIA), the conservative (maximin) model) and correlation analysis. Data on temperature are accessed from the NASA database, while the data on COVID-19 cases are collected from the official website of the government of Pakistan. Empirical results reveal the existence of linkages between temperature and COVID-19 in all Pakistani provinces. These linkages vary from a relatively stronger to a relatively weaker linkage. Based on calculated weights, the strength of linkages is ranked across provinces as follows: Gilgit Baltistan (0.715301) > Baluchistan (0.675091) > Khyber Pakhtunkhwa (0.619893) > Punjab (0.619286) > Sindh (0.601736). The disparity in the strength of linkage among provinces is explained by the discrepancy in the intensity of temperature. Besides, the diagrammatic correlation analysis shows that temperature is inversely linked to COVID-19 cases (per million persons) over time, implying that low temperatures are associated with high COVID-19 transmissibility and vice versa. This study is among the first of its kind to consider the linkages between temperature and COVID-19 transmissibility for a tropical climate country (Pakistan) using the advanced GIA models. Research findings provide an up-to-date glimpse of the outbreak and emphasize the need to raise public awareness about the devastating impacts of the COVID-19. The educational syllabus should provide information on the causes, signs, and precautions of the pandemic. Additionally, individuals should practice handwashing, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to ensure a secure and supportive atmosphere for preventing and controlling the current pandemic.
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Affiliation(s)
- Muhammad Irfan
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081 China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081 China
| | - Muhammad Ikram
- Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Shenzhen, China
| | - Munir Ahmad
- School of Economics, Zhejiang University, Hangzhou, 310058 China
| | - Haitao Wu
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081 China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081 China
| | - Yu Hao
- School of Management and Economics, Beijing Institute of Technology, Beijing, 100081 China
- Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081 China
- Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081 China
- Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081 China
- Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, 100081 China
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10
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Chen S, Prettner K, Kuhn M, Bloom DE. The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach. JOURNAL OF THE ECONOMICS OF AGEING 2021; 20:100328. [PMID: 34123719 PMCID: PMC8186726 DOI: 10.1016/j.jeoa.2021.100328] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
OBJECTIVES To assess the economic burden of COVID-19 that would arise absent behavioral or policy responses under the herd immunity approach in the United States and compare it to the total burden that also accounts for estimates of the value of lives lost. METHODS We use the trajectories of age-specific human and physical capital in the production process to calculate output changes based on a human capital-augmented production function. We also calculate the total burden that results when including the value of lives lost as calculated from mortality rates of COVID-19 and estimates for the value of a statistical life in the United States based on studies assessing individual's willingness to pay to avoid risks. RESULTS Our results indicate that the GDP loss associated with unmitigated COVID-19 would amount to a cumulative US$1.4 trillion by 2030 assuming that 60 percent of the population is infected over three years. This is equivalent to around 7.7 percent of GDP in 2019 (in constant 2010 US$) or an average tax on yearly output of 0.6 percent. After applying the value of a statistical life to account for the value of lives lost, our analyses show that the total burden can mount to between US$17 and 94 trillion over the next decade, which is equivalent to an annual tax burden between 8 and 43 percent. CONCLUSION Our results show that the United States would incur a sizeable burden if it adopted a non-interventionist herd immunity approach. FUNDING Research reported in this paper was supported by the Alexander von Humboldt Foundation, the Bill & Melinda Gates Foundation (Project INV-006261), and the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG) and the National Natural Science Foundation of China (NSFC). Preparation of this article was also supported by the Value of Vaccination Research Network (VoVRN) through a grant from the Bill & Melinda Gates Foundation (Grant OPP1158136). The content is solely the responsibility of the authors.
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Affiliation(s)
- Simiao Chen
- Heidelberg Institute of Global Health (HIGH), Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany
- Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Klaus Prettner
- Vienna University of Economics and Business (WU), Department of Economics, Vienna, Austria
- Wittgenstein Centre (IIASA, OeAW, University of Vienna), Vienna Institute of Demography, Vienna, Austria
| | - Michael Kuhn
- Wittgenstein Centre (IIASA, OeAW, University of Vienna), Vienna Institute of Demography, Vienna, Austria
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
| | - David E Bloom
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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11
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Kircheis R, Schuster M, Planz O. COVID-19: Mechanistic Model of the African Paradox Supports the Central Role of the NF-κB Pathway. Viruses 2021; 13:1887. [PMID: 34578468 PMCID: PMC8473087 DOI: 10.3390/v13091887] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 09/16/2021] [Accepted: 09/17/2021] [Indexed: 12/24/2022] Open
Abstract
The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has expanded into a global pandemic, with more than 220 million affected persons and almost 4.6 million deaths by 8 September 2021. In particular, Europe and the Americas have been heavily affected by high infection and death rates. In contrast, much lower infection rates and mortality have been reported generally in Africa, particularly in the sub-Saharan region (with the exception of the Southern Africa region). There are different hypotheses for this African paradox, including less testing, the young age of the population, genetic disposition, and behavioral and epidemiological factors. In the present review, we address different immunological factors and their correlation with genetic factors, pre-existing immune status, and differences in cytokine induction patterns. We also focus on epidemiological factors, such as specific medication coverage, helminth distribution, and malaria endemics in the sub-Saharan region. An analysis combining different factors is presented that highlights the central role of the NF-κB signaling pathway in the African paradox. Importantly, insights into the interplay of different factors with the underlying immune pathological mechanisms for COVID-19 can provide a better understanding of the disease and the development of new targets for more efficient treatment strategies.
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Affiliation(s)
| | | | - Oliver Planz
- Institute of Cell Biology and Immunology, Eberhard Karls University Tuebingen, 72076 Tuebingen, Germany
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12
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Wang X, Wang J, Shen J, Ji JS, Pan L, Liu H, Zhao K, Li L, Ying B, Fan L, Zhang L, Wang L, Shi X. Facilities for Centralized Isolation and Quarantine for the Observation and Treatment of Patients with COVID-19. ENGINEERING (BEIJING, CHINA) 2021; 7:908-913. [PMID: 33903828 PMCID: PMC8061092 DOI: 10.1016/j.eng.2021.03.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 02/25/2021] [Accepted: 04/22/2021] [Indexed: 05/26/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic increased the burden on many healthcare systems and in the process, exposed the need for medical resources and physical space. While few studies discussed the efficient utilization of medical resources and physical space so far. Therefore, this study aimed to summarize experiences related to facilities used for centralized isolation for medical observation and treatment during the COVID-19 pandemic in China and to provide suggestions to further improve the management of confirmed cases, suspected cases, and close contacts. In China, three types of facilities for centralized isolation (Fangcang shelter hospitals, refitted non-designated hospitals, and quarantine hotels) underwent retrofitting for the treatment and isolation of confirmed and suspected cases. These facilities mitigated the immediate high demand for space. Moreover, in order to minimize infection risks in these facilities, regulators and governmental agencies implemented new designs, management measures, and precautionary measures to minimize infection risk. Other countries and regions could refer to China's experience in optimally allocating social resources in response to the COVID-19 pandemic. As a conclusion, government should allocate social resources and construct centralized isolation and quarantine facilities for an emergency response, health authorities should issue regulations for centralized isolation facilities and pay strict attention to the daily management of these facilities, a multidisciplinary administration team is required to support the daily operation of a centralized isolation facility, in-depth studies and international collaboration on the centralized isolation policy are encouraged.
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Affiliation(s)
- Xianliang Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiao Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jin Shen
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - John S Ji
- Environmental Research Center, Duke Kunshan University, Kunshan 215316, China
- Nicholas School of the Environment, Duke University, Durham, NC 27708, USA
| | - Lijun Pan
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Hang Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Kangfeng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Li Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Bo Ying
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Lin Fan
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Liubo Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Lin Wang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
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13
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Abstract
Visual inspection of world maps shows that coronavirus disease 2019 (COVID-19) is less prevalent in countries closer to the equator, where heat and humidity tend to be higher. Scientists disagree how to interpret this observation because the relationship between COVID-19 and climatic conditions may be confounded by many factors. We regress the logarithm of confirmed COVID-19 cases per million inhabitants in a country against the country’s distance from the equator, controlling for key confounding factors: air travel, vehicle concentration, urbanization, COVID-19 testing intensity, cell phone usage, income, old-age dependency ratio, and health expenditure. A one-degree increase in absolute latitude is associated with a 4.3% increase in cases per million inhabitants as of January 9, 2021 (p value < 0.001). Our results imply that a country, which is located 1000 km closer to the equator, could expect 33% fewer cases per million inhabitants. Since the change in Earth’s angle towards the sun between equinox and solstice is about 23.5°, one could expect a difference in cases per million inhabitants of 64% between two hypothetical countries whose climates differ to a similar extent as two adjacent seasons. According to our results, countries are expected to see a decline in new COVID-19 cases during summer and a resurgence during winter. However, our results do not imply that the disease will vanish during summer or will not affect countries close to the equator. Rather, the higher temperatures and more intense UV radiation in summer are likely to support public health measures to contain SARS-CoV-2.
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Mukherjee UK, Bose S, Ivanov A, Souyris S, Seshadri S, Sridhar P, Watkins R, Xu Y. Evaluation of reopening strategies for educational institutions during COVID-19 through agent based simulation. Sci Rep 2021; 11:6264. [PMID: 33731722 PMCID: PMC7969783 DOI: 10.1038/s41598-021-84192-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 02/12/2021] [Indexed: 12/26/2022] Open
Abstract
Many educational institutions have partially or fully closed all operations to cope with the challenges of the ongoing COVID-19 pandemic. In this paper, we explore strategies that such institutions can adopt to conduct safe reopening and resume operations during the pandemic. The research is motivated by the University of Illinois at Urbana-Champaign’s (UIUC’s) SHIELD program, which is a set of policies and strategies, including rapid saliva-based COVID-19 screening, for ensuring safety of students, faculty and staff to conduct in-person operations, at least partially. Specifically, we study how rapid bulk testing, contact tracing and preventative measures such as mask wearing, sanitization, and enforcement of social distancing can allow institutions to manage the epidemic spread. This work combines the power of analytical epidemic modeling, data analysis and agent-based simulations to derive policy insights. We develop an analytical model that takes into account the asymptomatic transmission of COVID-19, the effect of isolation via testing (both in bulk and through contact tracing) and the rate of contacts among people within and outside the institution. Next, we use data from the UIUC SHIELD program and 85 other universities to estimate parameters that describe the analytical model. Using the estimated parameters, we finally conduct agent-based simulations with various model parameters to evaluate testing and reopening strategies. The parameter estimates from UIUC and other universities show similar trends. For example, infection rates at various institutions grow rapidly in certain months and this growth correlates positively with infection rates in counties where the universities are located. Infection rates are also shown to be negatively correlated with testing rates at the institutions. Through agent-based simulations, we demonstrate that the key to designing an effective reopening strategy is a combination of rapid bulk testing and effective preventative measures such as mask wearing and social distancing. Multiple other factors help to reduce infection load, such as efficient contact tracing, reduced delay between testing and result revelation, tests with less false negatives and targeted testing of high-risk class among others. This paper contributes to the nascent literature on combating the COVID-19 pandemic and is especially relevant for educational institutions and similarly large organizations. We contribute by providing an analytical model that can be used to estimate key parameters from data, which in turn can be used to simulate the effect of different strategies for reopening. We quantify the relative effect of different strategies such as bulk testing, contact tracing, reduced infectivity and contact rates in the context of educational institutions. Specifically, we show that for the estimated average base infectivity of 0.025 (\documentclass[12pt]{minimal}
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\begin{document}$$R_0 = 1.82$$\end{document}R0=1.82), a daily number of tests to population ratio T/N of 0.2, i.e., once a week testing for all individuals, is a good indicative threshold. However, this test to population ratio is sensitive to external infectivities, internal and external mobilities, delay in getting results after testing, and measures related to mask wearing and sanitization, which affect the base infection rate.
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Affiliation(s)
- Ujjal K Mukherjee
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA.
| | - Subhonmesh Bose
- Department of Electrical and Computer Engineering, Grainger College of Engineering, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Anton Ivanov
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Sebastian Souyris
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Sridhar Seshadri
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Padmavati Sridhar
- School of Information, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Ronald Watkins
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Yuqian Xu
- Department of Business Administration, Gies College of Business, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
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15
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Wang Q, Zhao Y, Zhang Y, Qiu J, Li J, Yan N, Li N, Zhang J, Tian D, Sha X, Jing J, Yang C, Wang K, Xu R, Zhang Y, Yang H, Zhao S, Zhao Y. Could the ambient higher temperature decrease the transmissibility of COVID-19 in China? ENVIRONMENTAL RESEARCH 2021; 193:110576. [PMID: 33279494 PMCID: PMC7713592 DOI: 10.1016/j.envres.2020.110576] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 11/17/2020] [Accepted: 11/30/2020] [Indexed: 05/11/2023]
Abstract
BACKGROUND Existing literatures demonstrated that meteorological factors could be of importance in affecting the spread patterns of the respiratory infectious diseases. However, how ambient temperature may influence the transmissibility of COVID-19 remains unclear. OBJECTIVES We explore the association between ambient temperature and transmissibility of COVID-19 in different regions across China. METHODS The surveillance data on COVID-19 and meteorological factors were collected from 28 provincial level regions in China, and estimated the instantaneous reproductive number (Rt). The generalized additive model was used to assess the relationship between mean temperature and Rt. RESULTS There were 12,745 COVID-19 cases collected in the study areas. We report the associated effect of temperature on Rt is likely to be negative but not of statistical significance, which holds for most Chinese regions. CONCLUSIONS We found little statistical evidence for that the higher temperature may reduce the transmissibility of COVID-19. Since intensive control measures against the COVID-19 epidemics were implemented in China, we acknowledge this may impact the underlying effect size estimation, and thus cautiousness should be taken when interpreting our findings.
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Affiliation(s)
- Qingan Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Yu Zhao
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Yajuan Zhang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Jiangwei Qiu
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Juan Li
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Ni Yan
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Nan Li
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Jiaxing Zhang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Di Tian
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Xiaolan Sha
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Jinyun Jing
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Chan Yang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Kairong Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Rongbin Xu
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia
| | - Yuhong Zhang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Huifang Yang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China
| | - Shi Zhao
- JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong SAR, China; CUHK Shenzhen Research Institute, Shenzhen, China.
| | - Yi Zhao
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750001, Ningxia, China; The Key Laboratory of Environmental Factors and Chronic Disease Control of Ningxia, Yinchuan, 750001, Ningxia, China.
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Hu CY, Xiao LS, Zhu HB, Zhu H, Liu L. Correlation Between Local Air Temperature and the COVID-19 Pandemic in Hubei, China. Front Public Health 2021; 8:604870. [PMID: 33537279 PMCID: PMC7848168 DOI: 10.3389/fpubh.2020.604870] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 12/14/2020] [Indexed: 12/23/2022] Open
Abstract
Objective: To clarify the correlation between temperature and the COVID-19 pandemic in Hubei. Methods: We collected daily newly confirmed COVID-19 cases and daily temperature for six cities in Hubei Province, assessed their correlations, and established regression models. Results: For temperatures ranging from −3.9 to 16.5°C, daily newly confirmed cases were positively correlated with the maximum temperature ~0–4 days prior or the minimum temperature ~11–14 days prior to the diagnosis in almost all selected cities. An increase in the maximum temperature 4 days prior by 1°C was associated with an increase in the daily newly confirmed cases (~129) in Wuhan. The influence of temperature on the daily newly confirmed cases in Wuhan was much more significant than in other cities. Conclusion: Government departments in areas where temperatures range between −3.9 and 16.5°C and rise gradually must take more active measures to address the COVID-19 pandemic.
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Affiliation(s)
- Cheng-Yi Hu
- Department of Medical Quality Management, Nanfang Hospital, Southern Medical University, Guangzhou, China.,Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Lu-Shan Xiao
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Hong-Bo Zhu
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China.,Department of Oncology, The First Affiliated Hospital, University of South China, Hengyang, China
| | - Hong Zhu
- Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Li Liu
- Department of Medical Quality Management, Nanfang Hospital, Southern Medical University, Guangzhou, China.,Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, China
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