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Objective: Fangcang shelter hospital is a form of large temporary hospital developed in China to tackle public health events. Through the case study and analysis of managing a nursing unit in a huge Fangcang shelter hospital transformed from the National Exhibition and Convention Center during the Omicron wave in Shanghai, China between April 9, 2022 and May 24, 2022, this paper aimed to highlight critical implications of public health nurses in health emergencies. Design: A case study was conducted using data collected from a nursing unit with 570 beds. The five characteristics of management were organized as follows: human resource management, establishment and optimization of the core workflow, safety management of high‐risk patients, the grid cooperation mechanism with patient volunteers, as well as humanistic nursing. Results: Analysis of the data of the nursing unit indicated close team cooperation, efficient and orderly process scheduling, good outcomes of patients, and the indispensable role of volunteers. Conclusion: Practice indicated that nursing unit management in a large Fangcang shelter hospital is important to ensure medical order and efficiency. This practical experience can provide valuable reference and data to support for the nursing management of large‐scale public health events, such as infectious disease epidemics. [ABSTRACT FROM AUTHOR]

Significant and composite indices for infectious disease can have implications for developing interventions and public health. This paper presents an investment for developing access to further analysis of the incidence of individual and multiple diseases. This research mainly comprises two steps: first, an automatic and reproducible procedure based on functional data analysis techniques was proposed for analyzing the dynamic properties of each disease; second, orthogonal transformation was adopted for the development of composite indices. Between 2000 and 2019, nineteen class B notifiable diseases in China were collected for this study from the National Bureau of Statistics of China. The study facilitates the probing of underlying information about the dynamics from discrete incidence rates of each disease through the procedure, and it is also possible to obtain similarities and differences about diseases in detail by combining the derivative features. There has been great success in intervening in the majority of notifiable diseases in China, like bacterial or amebic dysentery and epidemic cerebrospinal meningitis, while more efforts are required for some diseases, like AIDS and virus hepatitis. The composite indices were able to reflect a more complex concept by combining individual incidences into a single value, providing a simultaneous reflection for multiple objects, and facilitating disease comparisons accordingly. For the notifiable diseases included in this study, there was superior management of gastro-intestinal infectious diseases and respiratory infectious diseases from the perspective of composite indices. This study developed a methodology for exploring the prevalent properties of infectious diseases. The development of effective and reliable analytical methods provides special insight into infectious diseases' common dynamics and properties and has implications for the effective intervention of infectious diseases. [ABSTRACT FROM AUTHOR]

Aim: To investigate the current condition and degree of fear of disease progression and associated factors in patients with mild or common type COVID‐19. Background: At the end of 2019, COVID‐19 spread from Wuhan in Hubei Province throughout China. Confirmed cases and deaths have since been reported in many countries around the world. However, fear of progression in these patients has been poorly explored. Methods: During February 2020, we recruited 114 patients with mild or common type COVID‐19 admitted to a Fangcang shelter hospital. We assessed patients' degree of fear using the simplified Fear of Progression Questionnaire (Chinese version). Multiple regression analysis was applied to explore potential factors. Results: The fear of disease progression scores of patients with mild or common COVID‐19 was at the low‐to‐moderate level. Current unemployment, disease duration of 28 days or more and not having a spouse diagnosed with COVID‐19 were factors potentially associated with fear of progression. Conclusion: With a high prevalence of fear of disease progression in patients with COVID‐19, the risk of psychological effects from the pandemic is significant and fear of progression is one of the manifestations. The need for psychological support services for patients should be included in all pandemic and disaster planning. Summary statement: What is already known about this topic? Fear of progression is a common bio‐socio‐psychological consequence that widespread in cancer patients as well as chronic diseases.Very few studies focus on fear of progression in patients with major infectious disease, not to mention coronavirus disease (COVID‐19). What this paper adds? The present study surveys fear of progression in patients with mild or common type COVID‐19 and revealed a low‐to‐moderate level overall.Being unemployed, having no spouse diagnosed with COVID‐19, and a disease duration of 28 days or more are potential factors associated to patients' fear of the disease progression. The implications of this paper: The COVID‐19 outbreak has been declared as a public health emergency of international concern. Mental health problems such as fear of disease progression might need more attention beyond medical treatment.Future mental health nursing practice and research need to focus on those potential factors or patients with specific characteristics. [ABSTRACT FROM AUTHOR]

The novel coronavirus disease (SARS-CoV-2) has caused many infections and deaths throughout the world; the spread of the coronavirus pandemic is still ongoing and continues to affect healthcare systems and economies of countries worldwide. Mathematical models are used in many applications for infectious diseases, including forecasting outbreaks and designing containment strategies. In this paper, we study two types of SIR and SEIR models for the coronavirus. This study focuses on the discrete-time and fractional-order of these models; we study the stability of the fixed points and orbits using the Jacobian matrix and the eigenvalues and eigenvectors of each case; moreover, we estimate the parameters of the two systems in fractional order. We present a statistical study of the coronavirus model in two countries: Saudi Arabia, which has successfully recovered from the SARS-CoV-2 pandemic, and China, where the number of infections remains significantly high. [ABSTRACT FROM AUTHOR]

Since December 2019, the COVID-19 pandemic has quickly spread across the world. The traditional understanding of the relationship between wealth and the spread of contagious diseases is that similar to many precedent epidemics, the pandemic spread easily in poor neighborhoods in many countries. The environmental and socioeconomic implications of the COVID-19 pandemic are still poorly understood, thus this paper examines the relationship between neighborhood characteristics and the spread of the pandemic through a case study of Shenzhen, a Chinese megacity with many low-income rural migrants. The major finding is that wealthier and larger neighborhoods in Shenzhen were more likely to be infected in the first wave of the pandemic in 2020. This spread pattern is likely to result from China's strict control to prevent the pandemic, human mobility, and demographic characteristics such as income. This finding reveals a new phenomenon that contrasts with the traditional understanding of the influence of wealth on the spread of epidemics. This paper enriches the understanding of the role of neighborhoods in the spread of the pandemic, and it has important public policy implications. [ABSTRACT FROM AUTHOR]

Since the infectious coronavirus disease (COVID-19) was first reported in Wuhan, it has become a public health problem in China and even around the world. This pandemic is having devastating effects on societies and economies around the world. The increase in the number of COVID-19 tests gives more information about the epidemic spread, which may lead to the possibility of surrounding it to prevent further infections. However, wearing a face mask that prevents the transmission of droplets in the air and maintaining an appropriate physical distance between people, and reducing close contact with each other can still be beneficial in combating this pandemic. Therefore, this research paper focuses on implementing a Face Mask and Social Distancing Detection model as an embedded vision system. The pretrained models such as the MobileNet, ResNet Classifier, and VGG are used in our context. People violating social distancing or not wearing masks were detected. After implementing and deploying the models, the selected one achieved a confidence score of 100%. This paper also provides a comparative study of different face detection and face mask classification models. The system performance is evaluated in terms of precision, recall, F1-score, support, sensitivity, specificity, and accuracy that demonstrate the practical applicability. The system performs with F1-score of 99%, sensitivity of 99%, specificity of 99%, and an accuracy of 100%. Hence, this solution tracks the people with or without masks in a real-time scenario and ensures social distancing by generating an alarm if there is a violation in the scene or in public places. This can be used with the existing embedded camera infrastructure to enable these analytics which can be applied to various verticals, as well as in an office building or at airport terminals/gates. [ABSTRACT FROM AUTHOR]

Objective: COVID-19, a contagious disease which is caused by novel coronavirus (SARS-CoV-2), is still spreading globally. Bibliometric analyses assess the current status and trends in a spesific research domain by using several (Scopus, PubMed, Web of Science) databases. The aim of present study is to evaluate the scientific activities in the first year of the COVID-19 pandemic on scientific output. Method: Web of Science software was used for the search and the analysis. All scientific papers published about COVID-19 included in Science Citation Index Expanded (SCI-E) from January 1st to December 13th 2020; the date of the study, were searched by using the terms of "COVID-19", "2019-n-CoV", "SARS-CoV-2", "Coronavirus disease 19" and "2019 novel coronavirus" as scientific nomenclatures of COVID-19 in the topic search section of the software. Results:Overall; 47368 scientific papers related to COVID-19, indexed by SCI-E, were found related to COVID-19 between January 1, 2020 to December 13, 2020. The biggest contribution for publications was from United States of America, the most of the publications was articles, the authors that contribute to the literature = 150 papers were all from China and the journal that published the most paper was British Medical Journal. Conclusions: The present analyse reports an overview of the literature on COVID-19 since the beginning. These kind of periodic analysis provides interesting insights regarding the past and progress of each area of scientific knowledge and also can guide the rethinking of scientific data. [ABSTRACT FROM AUTHOR]

The rate of infectious disease outbreaks has been accelerating over the past two decades, from the SARS epidemic in 2003 to COVID-19 in 2020. Termed by some as the twenty-first century's first pandemic, SARS originated in China and alerted the country to the importance of public health and epidemic response. After SARS, China improved its health infrastructure and reformed its political and legal health governance system. The emergence of COVID-19 from Wuhan in late 2019 put those reforms to the test. This paper analyses China's public health and epidemic response policies from a historical perspective, tracing the evolution of Chinese public health policies after the SARS outbreak in 2003. This paper assesses China's response to COVID-19 and how post-SARS policy reforms, particularly in epidemic response, played out on the ground in Wuhan. What policies worked well? What were the challenges faced? Based on the policy analysis, this paper presents recommendations for how China can improve its epidemic response through strengthened infectious disease surveillance, more transparent political coordination, and expanded public health infrastructure. [ABSTRACT FROM AUTHOR]

The paper presents a analysis of quantitative and qualitative dimensions of global research output (3488 records) on "Impact of COVID-19 on Children and Adolescents", based on indexed publications in Scopus database. The global publications on this theme averaged 8.31 citations per paper. About 1.49% share of its total publications in this area received external funding support. The 145 countries partcipitated in global research output on "Impact of COVID-19 on Children and Adults", of which the top 10 countries accounted for 85.21% and more than 100% share of global publications and citations. The USA, U.K. and Italy leads in global publications ranking and productivity as against China (3.16), U.K (1.28) and USA (1.27) leading in terms of relative of relative citation index. The 412 organizations and 661 authors participated in global research on this theme, with top 15 most productive organizations and authors contributing 21.07% and 4.30% global publications share and 38.05% and 12.98% global citations share. Harvard Medical School, USA, Huazhong University of Science and Technology, China and Tongji Medical College, China leads the world as the most productive organizatons (with 480, 67 and 63 publications) and Huazhong University of Science and Technology, China (31.97 and 3.85), Tongji Medical College, China (19.92 and 2.40) and Children Hospital of Philadelphia, USA (19.30 and 2.32) leading as the most impactful organizations in the world in terms of citation per paper and relative citation index. D.Buonsensov, C.Calvo and X. Lu were the most productive authors (with 15, 12 and 12 papers) and X.Lu (103.83 and 12.49), A. Licari ( 40.11 and 4.83) and G.L. Marseglia( 34.09 and 4.1) were the most impactful authors. JAMA Pediatrics, Pediatrics Infectious Disease Journal and Acta Paediatrica International Journal of Pediatrics were the most productive journals (with 71, 60 and 58 papers) and Pediatrics (36.59, JAMA Pediatrics (19.49) and Acta Paediatrica International Journal of Pediatrics (14.93) were the most impactful journals. [ABSTRACT FROM AUTHOR]

At the moment, the shortcomings in the system of responding to crises in the health sector lie in the imperfection of the response order and management mechanisms. The purpose of the paper is to investigate the legal regulation and reflection of public health emergencies in China, as exemplified by the case of 2019 coronavirus. The paper discusses the legal framework for the regulation of emergency situations in public health in China for the period from the end of 2019. The importance of preventing and controlling the epidemic is substantiated, and shortcomings in the work to combat the epidemic are analysed. Particular attention is paid to issues of informing the public and the rule of law in emergency situations in public health. The provisions of the legislation of the People's Republic of China in public health emergencies were also examined. The paper is of practical importance not only for China, but for the entire world in the prevention and control of coronavirus. [ABSTRACT FROM AUTHOR]

Objective: Coronavirus disease 19 (COVID-19) is a highly contagious disease characterized by severe respiratory infection by SARS-CoV-2 virus. COVID-19 was first appeared in Wuhan, China, in December 2019 and then rapidly became a global pandemic from a local outbreak. The present study aims to present the rapid increase of scientific productivity on COVID-19 by comparing publications of the first quarter with the first half of 2020. Materials and Methods: Web of Science (WoS) software was used for the search and the analysis. To compare scientific productivity of two periods as the first quarter and the first half of the pandemic era, all scientific papers published about COVID-19 included in Science Citation Index Expanded (SCI-E) from January 1st to April 5th and from January 1st to July 9th of 2020 were searched using the following terms: "COVID-19","2019-n-CoV","SARS-CoV-2","Coronavirus disease 19" and "2019 novel coronavirus" as nomenclatures of COVID-19. Results: Overall, 337 and 11.704 scientific papers related to COVID-19, indexed by SCI-E, were found in the first quarter and the first half of 2020, respectively. While the biggest contribution for publications was from People's Republic of China (PRC) in the first quarter and was from the USA in the first half of 2020 for COVID-19. Conclusion: We found a close correlation between the rapid acceleration of scientific papers and turning the disease from a local outbreak to a global pandemic. Since sharing experiences is as important as struggling with these kinds of novel diseases, we believe that encouraging researchers to make scientific publications for others is more important than ever in the circumstances like this. [ABSTRACT FROM AUTHOR]

• This study applied a logistic growth model with parameters estimated by a non-linear least squares (NLS) method to daily new COVID-19 cases. • The model fitted time-series data exceedingly well for the whole of China, eleven selected Chinese provinces and municipalities, South Korea and Iran. • This study provided key estimates and a 95% confidence interval for parameters K , r, and P 0. • This study found that the growth rates of outbreaks differed between provinces in China and between South Korea and Iran. • As of March 13, 2020, this study's model suggested that countries such as the U.S.A., France, Italy, and Spain were still in the early stages of outbreaks. As the coronavirus disease 2019 (COVID-19) pandemic continues to proliferate globally, this paper shares the findings of modelling the outbreak in China at both provincial and national levels. This paper examines the applicability of the logistic growth model, with implications for the study of the COVID-19 pandemic and other infectious diseases. An NLS (Non-Linear Least Squares) method was employed to estimate the parameters of a differentiated logistic growth function using new daily COVID-19 cases in multiple regions in China and in other selected countries. The estimation was based upon training data from January 20, 2020 to March 13, 2020. A restriction test was subsequently implemented to examine whether a designated parameter was identical among regions or countries, and the diagnosis of residuals was also conducted. The model's goodness of fit was checked using testing data from March 14, 2020 to April 18, 2020. The model presented in this paper fitted time-series data exceedingly well for the whole of China, its eleven selected provinces and municipalities, and two other countries - South Korea and Iran - and provided estimates of key parameters. This study rejected the null hypothesis that the growth rates of outbreaks were the same among ten selected non-Hubei provinces in China, as well as between South Korea and Iran. The study found that the model did not provide reliable estimates for countries that were in the early stages of outbreaks. Furthermore, this study concured that the R 2 values might vary and mislead when compared between different portions of the same non-linear curve. In addition, the study identified the existence of heteroskedasticity and positive serial correlation within residuals in some provinces and countries. The findings suggest that there is potential for this model to contribute to better public health policy in combatting COVID-19. The model does so by providing a simple logistic framework for retrospectively analyzing outbreaks in regions that have already experienced a maximal proliferation in cases. Based upon statistical findings, this study also outlines certain challenges in modelling and their implications for the results. [ABSTRACT FROM AUTHOR]

Narrow and closed spaces like high-speed train cabins are at great risk for airborne infectious disease transmission. With the threat of COVID-19 as well as other potential contagious diseases, it is necessary to protect passengers from infection. Except for the traditional preventions such as increasing ventilation or wearing masks, this paper proposes a novel measurement that optimizes passenger-to-car assignment schemes to reduce the infection risk for high-speed railway passengers. First, we estimated the probability of an infected person boarding the train at any station. Once infectors occur, the non-steady-state Wells–Riley equation is used to model the airborne transmission intercar cabin. The expected number of susceptible passengers infected on the train can be calculated, which is the so-called overall infection risk. The model to minimize overall infection risk, as a pure integer quadratic programming problem, is solved by LINGO software and tested on several scenarios compared with the classical sequential and discrete assignment strategies used in China. The results show that the proposed model can reduce 67.6% and 56.8% of the infection risk in the base case compared to the sequential and discrete assignment, respectively. In other scenarios, the reduction lies mostly between 10% and 90%. The optimized assignment scheme suggests that the cotravel itinerary among passengers from high-risk and low-risk areas should be reduced, as well as passengers with long- and short-distance trips. Sensitivity analysis shows that our model works better when the incidence is higher at downstream or low-flow stations. Increasing the number of cars and car service capacity can also improve the optimization effect. Moreover, the model is applicable to other epidemics since it is insensitive to the Wells–Riley equation parameters. The results can provide a guideline for railway operators during the post-COVID-19 and other epidemic periods. [ABSTRACT FROM AUTHOR]

The new coronavirus infection (COVID-19) has spread to numerous countries around the world since several cases of the disease were first reported in late December 2019 in China. Currently, the WHO strongly recommends infection prevention measures such as wearing masks, hand washing, and frequent disinfection of high-touch surfaces, but there were many arguments against infection prevention policy in March 2020. For example, the WHO did not recommend the use of masks for the healthy general public. In Japan, wearing a mask was required before the habit of wearing a mask was established, which gave additional works of checking whether customer was wearing a mask to the employees. To reduce the workloads of employee and ensure mask-wearing, we started providing the mask-wearing system free of charge on March 5, 2020. We also developed hand washing time estimation and disinfection support system. It is useful to accumulate data on the status of implementation of countermeasures by our application, which leads to gain useful knowledge regarding countermeasures against COVID-19 as well as other infectious diseases. In this paper, we describe the development and introduction impacts of these systems in a pandemic emergencies. In addition, because of the security and privacy issues in running these image analysis applications, we discuss the delivery methods suitable for each service. [ABSTRACT FROM AUTHOR]

We aimed to examine the rate and characteristics of retracted articles in infectious diseases and clinical microbiology. Using the Retraction Watch Database, we conducted a cross-sectional study for retracted publications categorized as 'Infectious Disease' or 'Microbiology' until June 30 2022. We included publications for which citation information was available through the Web of Science database. Study characteristics, retraction trends and number of citations before and after the retraction year were analysed. Overall, 1004 retracted publications were included, retracted between August 1968 and June 2022. The number of retractions climbed through the years, peaking in 2020–2021. A total of 614 retractions originated from USA, China, and India, of total 183 736 PubMed publications from these countries. Overall, 378 (38%) were retracted because of errors; 182 (18%) because of plagiarism; and 142 (14%) because of falsification/fabrication. Specific reasons included 'concerns/issues about data' (158, 16%); 'duplication of image' (127, 13%); and 'unreliable results' (116, 12%). Of the 347 retractions during 2020 to June 2022, 91 (26%) were COVID-19 related. Fifty of 895 (5.6%) first authors had two retracted papers, and 14 (1.6%) had ≥2 retractions. Of 824 publications cited at least once, 466 (57%) were cited more often after retraction. Retractions of infectious diseases and clinical microbiology publications are increasing. Concerning reasons such as plagiarism, falsification/fabrication and errors are not uncommon. Nonetheless, these publications continue to be commonly cited after being retracted. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with the COVID-19 virus will experience mild to moderate respiratory illness and recover without requiring special treatment. People in extremes of age and those having pre-existing disease are more prone to the infection. Transmission is by droplet/contact route or by airborne transmission in special circumstances i.e endotracheal intubation, bronchoscopy, tracheostomy, cardiopulmonary resuscitation etc. Not only the treatment of living infected subjects, handling of COVID-19 dead bodies is also having utmost importance to prevent the transmission of deadly virus to the body handlers (hospital staff/cremation staff/family members) in the hospital or at the cremation/burial site. Here in this review paper, we have discussed about the pros and cons of the cremation and burial of the body keeping in mind that no further spread of the virus could occur to the community. However for eg China and Sri Lankan authorities made cremation compulsory by official order while WHO, India and many other did not objected to either of them. In our opinion, cremation should be preferred for complete elimination of chances of infection. However keeping in mind the religious views of the family, if the burial of the body is requested, then it should be assured that the body is buried in a thick, air tight coffin and placed at normal depth of about 2 meter. It is recommended that the area above and adjacent to the grave should be cemented immediately as an additional precautionary to avoid scavenging by animal. [ABSTRACT FROM AUTHOR]

Wuhan, a city of China, is the epicenter for the pandemic outbreak of coronavirus disease‐2019 (COVID‐19). It has become a severe public health challenge to the world and established a public health emergency of international worry. This infectious disease has pulled down the economy of almost all top developed nations. The coronaviruses (CoVs) known for various epidemics caused time to time. Infectious diseases such as severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS), followed by COVID‐19, are all coronaviruses led outbreaks that scourged the history of mankind. CoVs evolved themselves to more infectious, transmissible, and more pandemic with time. To prevent the spread of the SARS‐CoV‐2, many countries have ordered the complete lockdown to combat the outbreak. This paper briefly discussed the historical background of CoVs and the evolution of human coronaviruses (HCoVs), the case studies and the development of their antiviral medications. The viral infection encountered with present‐day challenges and futuristic approaches with the help of nanotechnology to minimize the spread of infectious viruses. The antiviral drugs and their clinical advances, along with herbal medicines for viral inhibition and immunity boosters, are described. Elaboration of tables related to CoVs for the compilation of the literature has been adopted for the better understanding. [ABSTRACT FROM AUTHOR]

Pneumonia caused by SARS-CoV-2 infection emerged in Wuhan City, Hubei Province, China in December 2019. Widespread outbreaks of infectious disease are associated with psychological distress and symptoms of mental illness. The COVID-19 outbreak has caused a public health crisis. In response to the rapidly increasing number of publications on this subject, this article attempts to provide a comprehensive review of early reports that appeared in the international literature until the beginning of May 2020. This paper details the effects on the general population as medical staff are exposed to different, specific stressors. The available literature has emerged from only a few of the most affected countries; therefore, there is a need for more representative research from other affected regions. The majority of studies focus on depression, anxiety, insomnia and distress. Subsyndromal mental health problems are a common response to the COVID-19 pandemic. There is a huge need for further research. In particular, attention must be paid to the potentially devastating effects on population-wide mental health. Pandemic crisis shifts from acute to protracted, and the long-term mental-health consequences of the pandemic will manifest themselves in the future. [ABSTRACT FROM AUTHOR]

We propose a varying coefficient Susceptible-Infected-Removal (vSIR) model that allows changing infection and removal rates for the latest corona virus (COVID-19) outbreak in China. The vSIR model together with proposed estimation procedures allow one to track the reproductivity of the COVID-19 through time and to assess the effectiveness of the control measures implemented since Jan 23 2020 when the city of Wuhan was lockdown followed by an extremely high level of self-isolation in the population. Our study finds that the reproductivity of COVID-19 had been significantly slowed down in the three weeks from January 27th to February 17th with 96.3% and 95.1% reductions in the effective reproduction numbers R among the 30 provinces and 15 Hubei cities, respectively. Predictions to the ending times and the total numbers of infected are made under three scenarios of the removal rates. The paper provides a timely model and associated estimation and prediction methods which may be applied in other countries to track, assess and predict the epidemic of the COVID-19 or other infectious diseases. [ABSTRACT FROM AUTHOR]

Infectious diseases, such as the current COVID-19, have a huge economic and societal impact. The ability to model its transmission characteristics is critical to minimize its impact. In fact, predicting how fast an infection is spreading could be a major factor in deciding on the severity, extent and strictness of the applied mitigation measures, such as the recent lockdowns. Even though modelling epidemics is a well studied subject, usually models do not include quarantine or other social measures, such as those imposed in the recent pandemic. The current work builds upon a recent paper by Maier and Brockmann (2020), where a compartmental SIRX model was implemented. That model included social or individual behavioural changes during quarantine, by introducing state X , in which symptomatic quarantined individuals are not transmitting the infection anymore, and described well the transmission in the initial stages of the infection. The results of the model were applied to real data from several provinces in China, quite successfully. In our approach we use a Monte-Carlo simulation model on networks. Individuals are network nodes and the links are their contacts. We use a spreading mechanism from the initially infected nodes to their nearest neighbours, as has been done previously. Initially, we find the values of the rate constants (parameters) the same way as in Maier and Brockmann (2020) for the confirmed cases of a country, on a daily basis, as given by the Johns Hopkins University. We then use different types of networks (random Erdős–Rényi, Small World, and Barabási–Albert Scale-Free) with various characteristics in an effort to find the best fit with the real data for the same geographical regions as reported in Maier and Brockmann (2020). Our simulations show that the best fit comes with the Erdős–Rényi random networks. We then apply this method to several other countries, both for large-size countries, and small size ones. In all cases investigated we find the same result, i.e. best agreement for the evolution of the pandemic with time is for the Erdős–Rényi networks. Furthermore, our results indicate that the best fit occurs for a random network with an average degree of the order of 〈 k 〉 ≈ 10–25, for all countries tested. Scale Free and Small World networks fail to fit the real data convincingly. • Monte-Carlo simulation model for the spread of COVID-19 in the early days of the pandemic. • Spreading of the virus is done on networks. Several different types of networks are tested. • The best fit with the real-world data is with Erdős–Rényi type of network. • We find that the average degree for several different countries in the world is in the range ∼ 10–25. [ABSTRACT FROM AUTHOR]