To predict the clinical outcome of coronavirus disease-2019 (COVID-19), we examined relationships among epidemiological data, viral load, and disease severity. We examined viral loads of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) in fatal (15 cases), symptomatic/survived (133 cases), and asymptomatic cases (138 cases) using reverse transcription quantitative real-time PCR (RT-qPCR). We examined 5768 nasopharyngeal swabs (NPS) and attempted to detect the SARS-CoV-2 genome using RT-qPCR. Among them, the viral genome was detected using the method for the 370 NPS samples with a positive rate of 6.4%. A comparison of each age showed that the fatal case was higher than the survived case and asymptomatic patients. Survived cases were older than asymptomatic patients. Notably, the viral load in the fatal cases was significantly higher than in symptomatic or asymptomatic cases (p < 0.05). These results suggested that a high viral load of the SARS-CoV-2 in elderly patients at an early stage of the disease results in a poor outcome. We should, therefore, intervene early to prevent a severe stage of the disease in such cases.

Acute respiratory illness (ARI) due to various viruses is not only the most common cause of upper respiratory infection in humans but is also a major cause of morbidity and mortality, leading to diseases such as bronchiolitis and pneumonia. Previous studies have shown that respiratory syncytial virus (RSV), human rhinovirus (HRV), human metapneumovirus (HMPV), human parainfluenza virus (HPIV), and human enterovirus (HEV) infections may be associated with virus-induced asthma. For example, it has been suggested that HRV infection is detected in the acute exacerbation of asthma and infection is prolonged. Thus it is believed that the main etiological cause of asthma is ARI viruses. Furthermore, the number of asthma patients in most industrial countries has greatly increased, resulting in a morbidity rate of around 10-15% of the population. However, the relationships between viral infections, host immune response, and host factors in the pathophysiology of asthma remain unclear. To gain a better understanding of the epidemiology of virus-induced asthma, it is important to assess both the characteristics of the viruses and the host defense mechanisms. Molecular epidemiology enables us to understand the pathogenesis of microorganisms by identifying specific pathways, molecules, and genes that influence the risk of developing a disease. However, the epidemiology of various respiratory viruses associated with virus-induced asthma is not fully understood. Therefore, in this article, we review molecular epidemiological studies of RSV, HRV, HPIV, and HMPV infection associated with virus-induced asthma.

We performed evolution, phylodynamics, and reinfection-related antigenicity analyses of respiratory syncytial virus subgroup A (RSV-A) fusion (F) gene in globally collected strains (1465 strains) using authentic bioinformatics methods. The time-scaled evolutionary tree using the Bayesian Markov chain Monte Carlo method estimated that a common ancestor of the RSV-A, RSV-B, and bovine-RSV diverged at around 450 years ago, and RSV-A and RSV-B diverged around 250 years ago. Finally, the RSV-A F gene formed eight genotypes (GA1-GA7 and NA1) over the last 80 years. Phylodynamics of RSV-A F gene, including all genotype strains, increased twice in the 1990s and 2010s, while patterns of each RSV-A genotype were different. Phylogenetic distance analysis suggested that the genetic distances of the strains were relatively short (less than 0.05). No positive selection sites were estimated, while many negative selection sites were found. Moreover, the F protein 3D structure mapping and conformational epitope analysis implied that the conformational epitopes did not correspond to the neutralizing antibody binding sites of the F protein. These results suggested that the RSV-A F gene is relatively conserved, and mismatches between conformational epitopes and neutralizing antibody binding sites of the F protein are responsible for the virus reinfection.

Streptococcus suis (S. suis) is an important emerging zoonotic agent. Here, we report two cases of S. suis infection in pig farmers in Gunma Prefecture, Japan. We conducted a high-resolution molecular epidemiologic analysis on the basis of whole-genome sequencing data of each isolate using next-generation sequencing (NGS). NGS analysis revealed that the two S. suis clinical isolates were belonged to serotype 2 ST28. Phylogenetic analysis showed that two isolates were closely related to S. suis strains isolated from pigs in Japan at least until 1995. Since 41 nucleotide substitutions were found between the two strains, these strains might be derived from the same genetic lineage but distinct sporadic cases. NGS analysis is a powerful diagnostic tool for analysing bacterial infections. The database is more fulfilling, and more detailed analysis will become possible in the near future. Attention should be paid to S. suis infections, especially if the patient works on a livestock farm.

Background: After the first case of COVID-19 in Japan on 15 January 2020, multiple nationwide COVID-19 clusters were identified by the end of February. The Japanese government focused on mitigating emerging COVID-19 clusters by conducting active nationwide epidemiological surveillance. However, an increasing number of cases appeared until early April, many with unclear infection routes exhibiting no recent history of travel outside Japan. We aimed to evaluate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequences from COVID-19 cases until early April and characterise the genealogical networks to demonstrate possible routes of spread in Japan. Methods: Nasopharyngeal specimens were collected from patients and a quantitative reverse transcription polymerase chain reaction testing for SARS-CoV-2 was performed. Positive RNA samples were subjected whole genome sequencing and a haplotype network analysis was performed. Findings: Some of the primary clusters identified during January and February in Japan directly descended from Wuhan-Hu-1-related isolates in China and other distinct clusters. Clusters were almost contained until mid-March; the haplotype network analysis demonstrated that COVID-19 cases from late March through early April may have caused an additional large cluster related to the outbreak in Europe, leading to additional spread within Japan. National self-restraint during February was effective in mitigating the COVID-19 spread, but late action on stopping immigration and declaring national emergency in Japan might be involved in the later increase in cases. Interpretation: Genome surveillance suggested that at least two distinct SARS-CoV-2 introductions from China and other countries occurred. Funding: Japan Agency for Medical Research and Development.