Global transmission network of SARS-CoV-2: from outbreak to pandemic

Uncovering COVID-19 transmission tree: identifying traced and untraced infections in an infection network

Introduction

This paper presents a comprehensive analysis of COVID-19 transmission dynamics using an infection network derived from epidemiological data in South Korea, covering the period from January 3, 2020, to July 11, 2021. The network illustrates infector-infectee relationships and provides invaluable insights for managing and mitigating the spread of the disease. However, significant missing data hinder conventional analysis of such networks from epidemiological surveillance.

Methods

To address this challenge, this article suggests a novel approach for categorizing individuals into four distinct groups, based on the classification of their infector or infectee status as either traced or untraced cases among all confirmed cases. The study analyzes the changes in the infection networks among untraced and traced cases across five distinct periods.

Results

The four types of cases emphasize the impact of various factors, such as the implementation of public health strategies and the emergence of novel COVID-19 variants, which contribute to the propagation of COVID-19 transmission. One of the key findings is the identification of notable transmission patterns in specific age groups, particularly in those aged 20-29, 40-69, and 0-9, based on the four type classifications. Furthermore, we develop a novel real-time indicator to assess the potential for infectious disease transmission more effectively. By analyzing the lengths of connected components, this indicator facilitates improved predictions and enables policymakers to proactively respond, thereby helping to mitigate the effects of the pandemic on global communities.

Conclusion

This study offers a novel approach to categorizing COVID-19 cases, provides insights into transmission patterns, and introduces a real-time indicator for better assessment and management of the disease transmission, thereby supporting more effective public health interventions.

Genomic and evolutionary study from SARS-CoV-2 virus isolates from Bangladesh during the early stage of pandemic strongly correlate with European origin and not with China

The goal of this study was to identify the genomic variants and determine molecular epidemiology of SARS-CoV-2 virus during the early pandemic stage in Bangladesh. Viral RNA was extracted, converted to cDNA, and amplified using Ion AmpliSeq™ SARS-CoV-2 Research Panel. 413 unique mutants from 151 viral isolates were identified. 80% of cases belongs to 8 mutants: 241C toT, 1163A toT, 3037C toT, 14408C toT, 23403A toG, 28881G toA, 28,882 G toA, and 28883G toC. Observed dominance of GR clade variants that have strong presence in Europe, suggesting European channel a possible entry route. Among 37 genomic mutants significantly associated with clinical symptoms, 3916CtoT (associated with sore-throat), 14408C to T (associated with cough-protection), 28881G to A, 28882G to A, and 28883G to C (associated with chest pain) were notable. These findings may inform future research platforms for disease management and epidemiological study.

Modeling COVID-19 Transmission Dynamics: A Bibliometric Review

A good amount of research has evolved just in three years in COVID-19 transmission, mortality, vaccination, and some socioeconomic studies. A few bibliometric reviews have already been performed in the literature, especially on the broad theme of COVID-19, without any particular area such as transmission, mortality, or vaccination. This paper fills this gap by conducting a bibliometric review on COVID-19 transmission as the first of its kind. The main aim of this study is to conduct a bibliometric review of the literature in the area of COVID-19 transmission dynamics. We have conducted bibliometric analysis using descriptive and network analysis methods to review the literature in this area using RStudio, Openrefine, VOSviewer, and Tableau. We reviewed 1103 articles published in 2020-2022. The result identified the top authors, top disciplines, research patterns, and hotspots and gave us clear directions for classifying research topics in this area. New research areas are rapidly emerging in this area, which needs constant observation by researchers to combat this global epidemic.

Modeling the Global Dynamic Contagion of COVID-19

The COVID-19 infections have profoundly and negatively impacted the whole world. Hence, we have modeled the dynamic spread of global COVID-19 infections with the connectedness approach based on the TVP-VAR model, using the data of confirmed COVID-19 cases during the period of March 23rd, 2020 to September 10th, 2021 in 18 countries. The results imply that, (i) the United States, the United Kingdom and Indonesia are global epidemic centers, among which the United States has the highest degree of the contagion of the COVID-19 infections, which is stable. South Korea, France and Italy are the main receiver of the contagion of the COVID-19 infections, and South Korea has been the most severely affected by the overseas epidemic; (ii) there is a negative correlation between the timeliness, effectiveness and mandatory nature of government policies and the risk of the associated countries COVID-19 epidemic affecting, as well as the magnitude of the net contagion of domestic COVID-19; (iii) the severity of domestic COVID-19 epidemics in the United States and Canada, Canada and Mexico, Indonesia and Canada is almost equivalent, especially for the United States, Canada and Mexico, whose domestic epidemics are with the same tendency; (iv) the COVID-19 epidemic has spread though not only the central divergence manner and chain mode of transmission, but also the way of feedback loop. Thus, more efforts should be made by the governments to enhance the pertinence and compulsion of their epidemic prevention policies and establish a systematic and efficient risk assessment mechanism for public health emergencies.

Gold-Nanostar-Chitosan-Mediated Delivery of SARS-CoV-2 DNA Vaccine for Respiratory Mucosal Immunization: Development and Proof-of-Principle

The COVID-19 pandemic is caused by the coronavirus SARS-CoV-2 (SC2). A variety of anti-SC2 vaccines have been approved for human applications, including those using messenger RNA (mRNA), adenoviruses expressing SC2 spike (S) protein, and inactivated virus. The protective periods of immunization afforded by these intramuscularly administered vaccines are currently unknown. An alternative self-administrable vaccine capable of mounting long-lasting immunity via sterilizing neutralizing antibodies would be hugely advantageous in tackling emerging mutant SC2 variants. This could also diminish the possibility of vaccinated individuals acting as passive carriers of COVID-19. Here, we investigate the potential of an intranasal (IN)-delivered DNA vaccine encoding the S protein of SC2 in BALB/c and C57BL/6J immunocompetent mouse models. The immune response to IN delivery of this SC2-spike DNA vaccine transported on a modified gold-chitosan nanocarrier shows a strong and consistent surge in antibodies (IgG, IgA, and IgM) and effective neutralization of pseudoviruses expressing S proteins of different SC2 variants (Wuhan, beta, and D614G). Immunophenotyping and histological analyses reveal chronological events involved in the recognition of SC2 S antigen by resident dendritic cells and alveolar macrophages, which prime the draining lymph nodes and spleen for peak SC2-specific cellular and humoral immune responses. The attainable high levels of anti-SC2 IgA in lung mucosa and tissue-resident memory T cells can efficiently inhibit SC2 and its variants at the site of entry and also provide long-lasting immunity.

A Global Mutational Profile of SARS-CoV-2: A Systematic Review and Meta-Analysis of 368,316 COVID-19 Patients

Since its first detection in December 2019, more than 232 million cases of COVID-19, including 4.7 million deaths, have been reported by the WHO. The SARS-CoV-2 viral genomes have evolved rapidly worldwide, causing the emergence of new variants. This systematic review and meta-analysis was conducted to provide a global mutational profile of SARS-CoV-2 from December 2019 to October 2020. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA), and a study protocol was lodged with PROSPERO. Data from 62 eligible studies involving 368,316 SARS-CoV-2 genomes were analyzed. The mutational data analyzed showed most studies detected mutations in the Spike protein (n = 50), Nucleocapsid phosphoprotein (n = 34), ORF1ab gene (n = 29), 5′-UTR (n = 28) and ORF3a (n = 25). Under the random-effects model, pooled prevalence of SARS-CoV-2 variants was estimated at 95.1% (95% CI; 93.3–96.4%; I² = 98.952%; p = 0.000) while subgroup meta-analysis by country showed majority of the studies were conducted ‘Worldwide’ (n = 10), followed by ‘Multiple countries’ (n = 6) and the USA (n = 5). The estimated prevalence indicated a need to continuously monitor the prevalence of new mutations due to their potential influence on disease severity, transmissibility and vaccine effectiveness.

A social network analysis of the spread of COVID-19 in South Korea and policy implications

This study estimates the COVID-19 infection network from actual data and draws on implications for policy and research. Using contact tracing information of 3283 confirmed patients in Seoul metropolitan areas from January 20, 2020 to July 19, 2020, this study created an infection network and analyzed its structural characteristics. The main results are as follows: (i) out-degrees follow an extremely positively skewed distribution; (ii) removing the top nodes on the out-degree significantly decreases the size of the infection network, and (iii) the indicators that express the infectious power of the network change according to governmental measures. Efforts to collect network data and analyze network structures are urgently required for the efficiency of governmental responses to COVID-19. Implications for better use of a metric such as R0 to estimate infection spread are also discussed.

The origin and early spread of SARS-CoV-2 in Europe

The investigation of migratory patterns during the SARS-CoV-2 pandemic before spring 2020 border closures in Europe is a crucial first step toward an in-depth evaluation of border closure policies. Here we analyze viral genome sequences using a phylodynamic model with geographic structure to estimate the origin and spread of SARS-CoV-2 in Europe prior to border closures. Based on SARS-CoV-2 genomes, we reconstruct a partial transmission tree of the early pandemic and coinfer the geographic location of ancestral lineages as well as the number of migration events into and between European regions. We find that the predominant lineage spreading in Europe during this time has a most recent common ancestor in Italy and was probably seeded by a transmission event in either Hubei, China or Germany. We do not find evidence for preferential migration paths from Hubei into different European regions or from each European region to the others. Sustained local transmission is first evident in Italy and then shortly thereafter in the other European regions considered. Before the first border closures in Europe, we estimate that the rate of occurrence of new cases from within-country transmission was within the bounds of the estimated rate of new cases from migration. In summary, our analysis offers a view on the early state of the epidemic in Europe and on migration patterns of the virus before border closures. This information will enable further study of the necessity and timeliness of border closures.

Transmission route and introduction of pandemic SARS-CoV-2 between China, Italy, and Spain

We present a phylodynamic and phylogeographic analysis of this new severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) virus in this report. A tree of maximum credibility was constructed using the 72 entire genome sequences of this virus, from the three countries (China, Italy, and Spain) available as of 26 March 2020 on the GISAID reference frame. To schematize the current SARS‐CoV‐2 migration scenario between and within the three countries chosen, using the multitype bearth‐death model implemented in BEAST2. Bayesian phylogeographic reconstruction shows that SARS‐CoV‐2 has a rate of evolution of 2.11 × 10⁻³ per sites per year (95% highest posterior density: 1.56 × 10⁻³ to 3.89 × 10⁻³), and a geographic origin in Shanghai, where time until the most recent common ancestor (tMRCA) emerged, according to the analysis of the molecular clock, around 13 November 2019. While for Italy and Spain, there are two tMRCA for each country, which agree with the assumption of several introductions for these countries. That explains also this very short period of subepidermal circulation before the recent events. A total of 8 (median) migration events occurred during this short period, the largest proportion of which (6 events [75%]) occurred from Shanghai (China) to Spain and from Italy to Spain. Such events are marked by speeds of migration that are comparatively lower as compared with that from Shanghai to Italy. Shanghai's R₀ and Italy's are closer to each other, though Spain's is slightly higher. All these results allow us to conclude the need for an automatic system of mixed, molecular and classical epidemiological surveillance, which could play a role in this global surveillance of public health and decision‐making.

The multitype bearth‐death model implemented in BEAST2 is used.

The aim of this study was to estimate the migration rate of the SRAS‐CoV‐2 between and within the three countries chosen (CHINA, ITALY and SPAIN).

Identifying the R0 for each subpopulation.

Analyzing the number of transmission between these three geographic locations.

Distribution of COVID-19 and Phylogenetic Tree Construction of SARS-CoV-2 in Indonesia

Coronavirus disease 2019 (COVID-19) is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 has spread quickly across the world and has been declared a pandemic. Indonesia has many COVID-19 cases, with a high mortality rate. This study aimed to describe the distribution of COVID-19 in Indonesia and constructed the SARS-CoV-2 phylogenetic tree from Indonesian isolates and those from other countries, including other CoVs to determine their relationship. The distribution data of COVID-19 in Indonesia were obtained from the COVID-19 Management Handling Unit and descriptively analyzed. SARS-CoV-2 isolates were retrieved from the GenBank® (National Center of Biotechnology Information, USA) and GISAID EpiCoV™ databases and were used to construct phylogenetic trees using MEGA X software. Of the 37 provinces in Indonesia, five provinces with the highest case fatality rates were DKI Jakarta, Jawa Barat, Jawa Timur, and Banten, and the five provinces with the highest cure rate were Kepulauan Riau, Bali, Aceh, Gorontalo, and DI Yogyakarta. SARS-CoV-2 Indonesian isolates were closely related to SARS-CoV-2 isolates from other countries. The rapid and widespread distribution of SARS-CoV-2 in Indonesia was caused by the lack of compliance with territorial restrictions and dishonesty with medical personnel. These data revealed that mutations can occur during the transmission process, which can be caused by a history of travel and increased patient immunity.

Evolving Transmission Network Dynamics of COVID-19 Cluster Infections in South Korea: a descriptive study

BACKGROUND

Extensive contact tracing and testing in South Korea allows us to investigate the transmission dynamics of the COVID-19 into diverse local communities.

OBJECTIVE

Understand the critical aspects of transmission dynamics in a different age, sex, and clusters with various activities.

METHODS

We conducted a retrospective observational study with 3,127 confirmed cases' contact tracing data from the Center for Disease and Prevention (CDC) of South Korea. We investigated network property concerning infected persons' demographics and different infection clusters.

FINDINGS

Overall, women had higher centrality scores than men after week four, when the confirmed cases rapidly increased. Older adults have higher centrality than young/middle-aged adults after week 9. In the infection clusters, young/middle-aged adults' infection clusters (such as religious gatherings and gym facilities) have higher average path lengths and diameter than older adults' nursing home infection clusters.

INTERPRETATION

Some women had higher reproduction numbers and bridged successive transmission than men when the confirmed cases rapidly increased. Similarly, some older adults (who were not residents of nursing homes) had higher reproduction numbers and bridged successive transmission than young/middle-aged adults after the peak has passed. The young/middle-aged adults' religious gatherings and group workout have caused long successive transmissions. In contrast, the older adults' nursing homes were a small world where the transmissions within a few steps can reach out to many persons.