scholarly journals Tracking the spread of novel coronavirus (2019-nCoV) based on big data

Author(s):  
Xumao Zhao ◽  
Xiang Liu ◽  
Xinhai Li

AbstractThe novel coronavirus (2019-nCoV) appeared in Wuhan in late 2019 have infected 34,598 people, and killed 723 among them until 8th February 2020. The new virus has spread to at least 316 cities (until 1st February 2020) in China. We used the traffic flow data from Baidu Map, and number of air passengers who left Wuhan from 1st January to 26th January, to quantify the potential infectious people. We developed multiple linear models with local population and air passengers as predicted variables to explain the variance of confirmed cases in every city across China. We found the contribution of air passengers from Wuhan was decreasing gradually, but the effect of local population was increasing, indicating the trend of local transmission. However, the increase of local transmission is slow during the early stage of novel coronavirus, due to the super strict control measures carried out by government agents and communities.

Author(s):  
Ioanna A. Mitrofani ◽  
◽  
Vasilis P. Koutras

The novel coronavirus (covid-19) was initially identified at the end of 2019 and caused a global health care crisis. The increased transmissibility of the virus, that led to high mortality, raises the interest of scientists worldwide. Thus, various methods and models have been extensively discussed, so to study and control covid-19 transmission. Mathematical modeling constitutes an important tool to estimate key parameters of the transmission and predict the dynamic of the virus. More precisely, in the relevant literature, epidemiology is considered as a classical application area of branching processes, which are stochastic individual-based processes. In this paper, we develop a classical Galton-Watson branching process approach for the covid-19 spread in Greece at the early stage. This approach is structured in two parts, initial and latter transmission stages, so to provide a comprehensive view of the virus spread through basic and effective reproduction numbers respectively, along with the probability of an outbreak. Additionally, the effectiveness of control measures is discussed, based on a simple exponential smoothing model, which is used to build a non-mitigation scenario. Finally, our primary aim is to model all transmission stages through branching processes in order to analyze the first semiannual spread of the ongoing coronavirus pandemic in the region of Greece.


2020 ◽  
Vol 11 (SPL1) ◽  
pp. 462-468
Author(s):  
Latika kothari ◽  
Sanskruti Wadatkar ◽  
Roshni Taori ◽  
Pavan Bajaj ◽  
Diksha Agrawal

Coronavirus disease 2019 (COVID-19) is a communicable infection caused by the novel coronavirus resulting in severe acute respiratory syndrome coronavirus 2 (SARS-CoV). It was recognized to be a health crisis for the general population of international concern on 30th January 2020 and conceded as a pandemic on 11th March 2020. India is taking various measures to fight this invisible enemy by adopting different strategies and policies. To stop the COVID-19 from spreading, the Home Affairs Ministry and the health ministry, of India, has issued the nCoV 19 guidelines on travel. Screening for COVID-19 by asking questions about any symptoms, recent travel history, and exposure. India has been trying to get testing kits available. The government of India has enforced various laws like the social distancing, Janata curfew, strict lockdowns, screening door to door to control the spread of novel coronavirus. In this pandemic, innovative medical treatments are being explored, and a proper vaccine is being hunted to deal with the situation. Infection control measures are necessary to prevent the virus from further spreading and to help control the current situation. Thus, this review illustrates and explains the criteria provided by the government of India to the awareness of the public to prevent the spread of COVID-19.


2021 ◽  
Vol 9 ◽  
Author(s):  
Mohamed A. Daw

Background: Since the Arab uprising in 2011, Libya, Syria and Yemen have gone through major internal armed conflicts. This resulted in large numbers of deaths, injuries, and population displacements, with collapse of the healthcare systems. Furthermore, the situation was complicated by the emergence of COVID-19 as a global pandemic, which made the populations of these countries struggle under unusual conditions to deal with both the pandemic and the ongoing wars. This study aimed to determine the impact of the armed conflicts on the epidemiology of the novel coronavirus (SARS-CoV-2) within these war-torn countries and highlight the strategies needed to combat the spread of the pandemic and its consequences.Methods: Official and public data concerning the dynamics of the armed conflicts and the spread of SARS-COV-2 in Libya, Syria and Yemen were collected from all available sources, starting from the emergence of COVID-19 in each country until the end of December 2020. Datasets were analyzed by a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the conflict and the prevalence of COVID-19.Results: The data indicated that there was an increase in the intensity of the violence at an early stage from March to August 2020, when it approximately doubled in the three countries, particularly in Libya. During that period, few cases of COVID-19 were reported, ranging from 5 to 53 cases/day. From September to December 2020, a significant decline in the intensity of the armed conflicts was accompanied by steep upsurges in the rate of COVID-19 cases, which reached up to 500 cases/day. The accumulative cases vary from one country to another during the armed conflict. The highest cumulative number of cases were reported in Libya, Syria and Yemen.Conclusions: Our analysis demonstrates that the armed conflict provided an opportunity for SARS-CoV-2 to spread. The early weeks of the pandemic coincided with the most intense period of the armed conflicts, and few cases were officially reported. This indicates undercounting and hidden spread during the early stage of the pandemic. The pandemic then spread dramatically as the armed conflict declined, reaching its greatest spread by December 2020. Full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its consequences.


2020 ◽  
Vol 258 (5) ◽  
pp. 1049-1055 ◽  
Author(s):  
Tracy H. T. Lai ◽  
Emily W. H. Tang ◽  
Sandy K. Y. Chau ◽  
Kitty S. C. Fung ◽  
Kenneth K. W. Li

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Khosravi ◽  
R. Chaman ◽  
M. Rohani-Rasaf ◽  
F. Zare ◽  
S. Mehravaran ◽  
...  

Abstract The aim of this study was to estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The 30-day probable incidence and cumulative incidence were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using ‘earlyR’ and ‘projections’ packages in R software. The maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1−3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI 1.03–1.25) by the end of day 42. The expected average number of new cases in Shahroud was 9.0 ± 3.8 cases/day, which means an estimated total of 271 (95% CI: 178–383) new cases for the period between 02 April to 03 May 2020. By day 67 (27 April), the effective reproduction number (Rt), which had a descending trend and was around 1, reduced to 0.70. Based on the Rt for the last 21 days (days 46–67 of the epidemic), the prediction for 27 April to 26 May is a mean daily cases of 2.9 ± 2.0 with 87 (48–136) new cases. In order to maintain R below 1, we strongly recommend enforcing and continuing the current preventive measures, restricting travel and providing screening tests for a larger proportion of the population.


Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a fraction of unreported SARS-CoV-2 cases (18.4%; 95%CI = 0–34.0%) before 10 March lockdown. Interestingly, we estimated that transmission rate in the community was reduced by 32% (95%CI = 23–42%) after the first set of restrictions, and by 80% (95%CI = 70–89%) after those adopted on 23 March. Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Moreover, our findings suggested that transmission rates were reduced after the adoption of control measures. However, we cannot evaluate whether part of this reduction might be attributable to other unmeasured factors, and hence further research and more accurate data are needed to understand the extent to which restrictions contributed to the epidemic control.


2020 ◽  
Author(s):  
PATRÍCIA YOKOO ◽  
Eduardo Kaiser Ururahy Nunes Fonseca ◽  
Marcelo Oranges Filho ◽  
Rodrigo Caruso Chate ◽  
Gilberto Szarf ◽  
...  

Abstract The novel coronavirus (COVID-19) pandemic started in December 2019 in Wuhan (Hubei, China) and spread rapidly; therefore, it is essential to detect the disease at an early stage and immediately isolate the infected patients [1]. The most common symptoms of COVID-19 infection include fever, asthenia, cough and dyspnea [2]. However, some patients are asymptomatic from the respiratory symptoms, and may only present abdominal manifestations as an initial finding, what creates a diagnostic challenge.We describe two cases with diagnostic confirmations of COVID-19 who showed up at the Emergency Department with abdominal symptoms before presenting respiratory manifestations, and who had their initial suspicion based on the findings of the thoracoabdominal transition, demonstrating the importance of an adequate assessment of the lung base images.


2021 ◽  
Author(s):  
Dong Liu ◽  
Chi Kong Tse ◽  
Rosa H. M. Chan ◽  
Choujun Zhan

Abstract Approval of emergency use of the Novel Coronavirus Disease 2019 (COVID-19) vaccines in many countries has brought hope to ending the COVID-19 pandemic sooner. Considering the limited vaccine supply in the early stage of COVID-19 vaccination programs in most countries, a highly relevant question to ask is: who should get vaccinated first? In this article we propose a network information- driven vaccination strategy where a small number of people in a network (population) are categorized, according to a few key network properties, into priority groups. Using a network-based SEIR model for simulating the pandemic progression, the network information-driven vaccination strategy is compared with a random vaccination strategy. Results for both large-scale synthesized networks and real social networks have demonstrated that the network information-driven vaccination strategy can significantly reduce the cumulative number of infected individuals and lead to a more rapid containment of the pandemic. The results provide insight for policymakers in designing an effective early-stage vaccination plan.


2020 ◽  
Vol 63 (7) ◽  
pp. 239-250 ◽  
Author(s):  
Kyung-Yil Lee ◽  
Jung-Woo Rhim ◽  
Jin-Han Kang

The novel coronavirus disease 2019 (COVID-19) is spreading globally. Although its etiologic agent is discovered as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), there are many unsolved issues in COVID-19 and other infectious diseases. The causes of different clinical phenotypes and incubation periods among individuals, species specificity, and cytokine storm with lymphopenia as well as the mechanism of damage to organ cells are unknown. It has been suggested that in viral pneumonia, virus itself is not a direct cause of acute lung injury; rather, aberrant immune reactions of the host to the insults from viral infection are responsible. According to its epidemiological and clinical characteristics, SARS-CoV-2 may be a virus with low virulence in nature that has adapted to the human species. Current immunological concepts have limited ability to explain such unsolved issues, and a presumed immunopathogenesis of COVID-19 is presented under the proteinhomeostasis-system hypothesis. Every disease, including COVID-19, has etiological substances controlled by the host immune system according to size and biochemical properties. Patients with severe pneumonia caused by SARS-CoV-2 show more severe hypercytokinemia with corresponding lymphocytopenia than patients with mild pneumonia; thus, early immunomodulator treatment, including corticosteroids, has been considered. However, current guidelines recommend their use only for patients with advanced pneumonia or acute respiratory distress syndrome. Since the immunopathogenesis of pneumonia may be the same for all patients regardless of age or severity and the critical immune-mediated lung injury may begin in the early stage of the disease, early immunomodulator treatment, including corticosteroids and intravenous immunoglobulin, can help reduce morbidity and possibly mortality rates of older patients with underlying conditions.


Author(s):  
Abhijit Mohan Kanavaje ◽  
Vipul Ajit Sansare

Since the outbreak of the novel coronavirus disease COVID-19, caused by the SARS-CoV-2 virus, this disease has spread rapidly around the globe. On 11 March 2020, WHO declared Novel Coronavirus Disease (COVID-19) outbreak as a pandemic and reiterated the call for countries to take immediate actions and scale up the response to treat, detect and reduce transmission to save people’s lives. As of 3 April 2020, according to the Ministry of Health & Family Welfare (MoHFW), a total of 2301 COVID-19 cases (including 55 foreign nationals) have been reported in 29 states/union territories. These include 156 who have been cured/discharged,1 who has migrated, and 56 deaths in India. Considering the potential threat of a pandemic, scientists and physicians have been racing to understand this new virus and the pathophysiology of this disease to uncover possible treatment regimens and discover effective therapeutic agents and vaccines. The objective of this review article was to have a preliminary opinion about the disease, the ways of treatment, and prevention in this early stage of this outbreak.


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