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Wastewater-based epidemiology (WBE) is currently used to monitor not only the spread of the viral SARS-CoV-2 pandemic but also that of other viruses in endemic conditions, particularly in the absence of syndromic surveillance. The continuous monitoring of sewage requires high expenditure and significant time investments, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Tuscany (Italy) and targeted human adenovirus (HAdV), norovirus genogroup II (NoVggII), enterovirus (EV), and SARS-CoV-2. Samples were collected at the entrances of treatment plants and concentrated using PEG/NaCl precipitation, and viral nucleic acids were extracted and detected through real-time reverse transcription qPCR. NoVggII was the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. Compared with data that were previously collected in the same study area (from February 2021 to September 2021), the results for SARS-CoV-2 revealed a shift from an epidemic to an endemic pattern, at least in the region under investigation, which was likely due to viral mutations that led to the spreading of new variants with increased resistance to summer environmental conditions. In conclusion, using standardized methods and an efficient monitoring strategy, WBE proves valuable for viral surveillance in pandemic and epidemic scenarios, enabling the identification of temporal–local distribution patterns that are useful for making informed public health decisions. [ABSTRACT FROM AUTHOR]

Background: Public health measures for COVID-19 mitigation influenced the circulation of Respiratory Syncytial Virus (RSV) during the 2020–2021 winter season. In the following autumn, an unprecedented resurgence of RSV occurred. Our study monitored RSV pediatric infections one and two years after the relaxation of containment measures for the COVID-19 pandemic. Methods: We analyzed diagnostic molecular data for SARS-CoV-2, flu, and RSV infections and clinical data from children with respiratory symptoms referring to our hospital during the 2021–2022 and 2022–2023 seasons. Results: In the 2021–2022 season, the number of RSV-affected children was very high, especially for babies <1 year. The outbreak appeared in a shorter interval of time, with a high clinical severity. In the 2022–23 season, a reduced number of infected pediatric patients were detected, with a similar hospitalization rate (46% vs. 40%), and RSV accounted for 12% of the infections. Coinfections were observed in age <2 years. In RSV patients, symptoms were similar across the two seasons. Conclusions: The clinical presentation of RSV in the two post-COVID seasons suggests that the pathophysiology of the virus did not change across these two years. Further studies are needed to continuously monitor RSV to support an effective prevention strategy. [ABSTRACT FROM AUTHOR]

The comparison of the development of the SARS-CoV-2 epidemic in several neighboring regions can help researchers to assess the risks and develop more effective strategies and approaches in the field of preventive medicine. We analyzed the infection and mortality statistics for the 2020–2022 period in ten individual regions of the Siberian Federal District of Russia. We also sequenced complete genomes, which allowed us to analyze the genetic diversity of SARS-CoV-2 circulated in each of the ten regions and to build a phylogenetic dendrogram for the virus variants. The ParSeq v.1.0 software was developed to automate and speed up the processing and analysis of viral genomes. At the beginning of the pandemic, in the first two waves, the B.1.1 variant (20B) dominated in all regions of the Siberian Federal District. The third and fourth waves were caused by the Delta variant. Mortality during this period was at a maximum; the incidence was quite high, but the number of deposited genomes with GISAID during this period was extremely low. The maximum incidence was at the beginning of 2022, which corresponds to the arrival of the Omicron variant in the region. The BA.5.2 variant became the dominant one. In addition, by using NextClade, we identified three recombinants in the most densely populated areas. [ABSTRACT FROM AUTHOR]

All four serotypes of the dengue virus (DENV1–4) cause a phenotypically similar illness, but serial infections from different serotypes increase the risk of severe disease. Thus, genomic surveillance of circulating viruses is important to detect serotype switches that precede community outbreaks of disproportionate magnitude. A phylogenetic analysis was conducted on near full length DENV genomes sequenced from serum collected from a prospective cohort study from the Colombo district, Sri Lanka during a 28-month period using Oxford nanopore technology, and the consensus sequences were analyzed using maximum likelihood and Bayesian evolutionary analysis. From 523 patients, 328 DENV sequences were successfully generated (DENV1: 43, DENV2: 219, DENV3:66). Most circulating sequences originated from a common ancestor that was estimated to have existed from around 2010 for DENV2 and around 2015/2016 for DENV1 and DENV3. Four distinct outbreaks coinciding with monsoon rain seasons were identified during the observation period mostly driven by DENV2 cosmopolitan genotype, except for a large outbreak in 2019 contributed by DENV3 genotype I. This serotype switch did not result in a more clinically severe illness. Phylogeographic analyses showed that all outbreaks started within Colombo city and then spread to the rest of the district. In 2019, DENV3 genotype I, previously, rarely reported in Sri Lanka, is likely to have contributed to a disease outbreak. However, this did not result in more severe disease in those infected, probably due to pre-existing DENV3 immunity in the community. Targeted vector control within Colombo city before anticipated seasonal outbreaks may help to limit the geographic spread of outbreaks. [ABSTRACT FROM AUTHOR]

To face the COVID-19 outbreak, a wide range of non-pharmaceutical interventions (NPIs) aimed at limiting the spread of the virus in communities, such as mask-wearing, hand hygiene, social distancing, travel restrictions, and school closures, were introduced in most countries. Thereafter, a significant reduction of new asymptomatic and symptomatic COVID-19 cases occurred, although there were differences between countries according to the type and duration of the NPIs. In addition, the COVID-19 pandemic has been accompanied by significant variations in the global incidence of diseases due to the most common non-SARS-CoV-2 respiratory viruses and some bacteria. In this narrative review, the epidemiology of the most common non-SARS-CoV-2 respiratory infections during the COVID-19 pandemic is detailed. Moreover, factors that could have had a role in modifying the traditional circulation of respiratory pathogens are discussed. A literature analysis shows that NPIs were the most important cause of the general reduction in the incidence of influenza and respiratory syncytial virus infection in the first year of the pandemic, although the different sensitivity of each virus to NPIs, the type and duration of measures used, as well as the interference among viruses may have played a role in modulating viral circulation. Reasons for the increase in the incidences of Streptococcus pneumoniae and group A Streptococcus infections seem strictly linked to immunity debt and the role played by NPIs in reducing viral infections and limiting bacterial superimposed infections. These results highlight the importance of NPIs during pandemics, the need to monitor the circulation of infectious agents that cause diseases similar to those caused by pandemic agents, and the need to make efforts to improve coverage with available vaccines. [ABSTRACT FROM AUTHOR]

The transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is known to be overdispersed, meaning that only a fraction of infected cases contributes to super-spreading. While cluster interventions are an effective measure for controlling pandemics due to the viruses' overdispersed nature, a quantitative assessment of the risk of clustering has yet to be sufficiently presented. Using systematically collected cluster surveillance data for coronavirus disease 2019 (COVID-19) from June 2020 to June 2021 in Japan, we estimated the activity-dependent risk of clustering in 23 establishment types. The analysis indicated that elderly care facilities, welfare facilities for people with disabilities, and hospitals had the highest risk of clustering, with 4.65 (95% confidence interval [CI]: 4.43–4.87), 2.99 (2.59–3.46), and 2.00 (1.88–2.12) cluster reports per million event users, respectively. Risks in educational settings were higher overall among older age groups, potentially being affected by activities with close and uncontrollable contact during extracurricular hours. In dining settings, drinking and singing increased the risk by 10- to 70-fold compared with regular eating settings. The comprehensive analysis of the COVID-19 cluster records provides an additional scientific basis for the design of customized interventions. [ABSTRACT FROM AUTHOR]

There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19. [ABSTRACT FROM AUTHOR]

Background: After its initial detection in Wuhan, China, in December 2019, SARS-CoV-2 has spread rapidly, causing successive epidemic waves worldwide. This study aims to provide a genomic epidemiology of SARS-CoV-2 in Burkina Faso. Methods: Three hundred and seventy-seven SARS-CoV-2 genomes obtained from PCR-positive nasopharyngeal samples (PCR cycle threshold score < 35) collected between 5 May 2020, and 31 January 2022 were analyzed. Genomic sequences were assigned to phylogenetic clades using NextClade and to Pango lineages using pangolin. Phylogenetic and phylogeographic analyses were performed to determine the geographical sources and time of virus introduction in Burkina Faso. Results: The analyzed SARS-CoV-2 genomes can be assigned to 10 phylogenetic clades and 27 Pango lineages already described worldwide. Our analyses revealed the important role of cross-border human mobility in the successive SARS-CoV-2 introductions in Burkina Faso from neighboring countries. Conclusions: This study provides additional insights into the genomic epidemiology of SARS-CoV-2 in West Africa. It highlights the importance of land travel in the spread of the virus and the need to rapidly implement preventive policies. Regional cross-border collaborations and the adherence of the general population to government policies are key to prevent new epidemic waves. [ABSTRACT FROM AUTHOR]

Many approaches using compartmental models have been used to study the COVID-19 pandemic, with machine learning methods applied to these models having particularly notable success. We consider the Susceptible–Infected–Confirmed–Recovered–Deceased (SICRD) compartmental model, with the goal of estimating the unknown infected compartment I, and several unknown parameters. We apply a variation of a "Physics Informed Neural Network" (PINN), which uses knowledge of the system to aid learning. First, we ensure estimation is possible by verifying the model's identifiability. Then, we propose a wavelet transform to process data for the network training. Finally, our central result is a novel modification of the PINN's loss function to reduce the number of simultaneously considered unknowns. We find that our modified network is capable of stable, efficient, and accurate estimation, while the unmodified network consistently yields incorrect values. The modified network is also shown to be efficient enough to be applied to a model with time-varying parameters. We present an application of our model results for ranking states by their estimated relative testing efficiency. Our findings suggest the effectiveness of our modified PINN network, especially in the case of multiple unknown variables. [ABSTRACT FROM AUTHOR]

Since its emergence in 2019, SARS-CoV-2 has spread and evolved globally, with newly emerged variants of concern (VOCs) accounting for more than 500 million COVID-19 cases and 6 million deaths. Continuous surveillance utilizing simple genetic tools is needed to measure the viral epidemiological diversity, risk of infection, and distribution among different demographics in different geographical regions. To help address this need, we developed a proof-of-concept multilocus genotyping tool and demonstrated its utility to monitor viral populations sampled in 2020 and 2021 across six continents. We sampled globally 22,164 SARS-CoV-2 genomes from GISAID (inclusion criteria: available clinical and demographic data). They comprised two study populations, "2020 genomes" (N = 5959) sampled from December 2019 to September 2020 and "2021 genomes" (N = 16,205) sampled from 15 January to 15 March 2021. All genomes were aligned to the SARS-CoV-2 reference genome and amino acid polymorphisms were called with quality filtering. Thereafter, 74 codons (loci) in 14 genes including orf1ab polygene (N = 9), orf3a, orf8, nucleocapsid (N), matrix (M), and spike (S) met the 0.01 minimum allele frequency criteria and were selected to construct multilocus genotypes (MLGs) for the genomes. At these loci, 137 mutant/variant amino acids (alleles) were detected with eight VOC-defining variant alleles, including N KR203&204, orf1ab (I265, F3606, and L4715), orf3a H57, orf8 S84, and S G614, being predominant globally with > 35% prevalence. Their persistence and selection were associated with peaks in the viral transmission and COVID-19 incidence between 2020 and 2021. Epidemiologically, older patients (≥20 years) compared to younger patients (<20 years) had a higher risk of being infected with these variants, but this association was dependent on the continent of origin. In the global population, the discriminant analysis of principal components (DAPC) showed contrasting patterns of genetic clustering with three (Africa, Asia, and North America) and two (North and South America) continental clusters being observed for the 2020 and 2021 global populations, respectively. Within each continent, the MLG repertoires (range 40–199) sampled in 2020 and 2021 were genetically differentiated, with ≤4 MLGs per repertoire accounting for the majority of genomes sampled. These data suggested that the majority of SARS-CoV-2 infections in 2020 and 2021 were caused by genetically distinct variants that likely adapted to local populations. Indeed, four GISAID clade-defined VOCs - GRY (Alpha), GH (Beta), GR (Gamma), and G/GK (Delta variant) were differentiated by their MLG signatures, demonstrating the versatility of the MLG tool for variant identification. Results from this proof-of-concept multilocus genotyping demonstrates its utility for SARS-CoV-2 genomic surveillance and for monitoring its spatiotemporal epidemiology and evolution, particularly in response to control interventions including COVID-19 vaccines and chemotherapies. [ABSTRACT FROM AUTHOR]

In view of the grave situation during the first two waves of SARS-CoV-2 virus (severe acute respiratory syndrome coronavirus-2), nursing homes (NHs) were prioritised for vaccination once vaccines became available in Belgium. The aim of this study was to assess the effect of the COVID-19 (Coronavirus Disease 2019) vaccination campaign on COVID-19 cases, hospital admissions, and deaths among residents living in Belgian NHs. All 1545 Belgian NHs were invited to participate in a COVID-19 surveillance program. In Belgium, before vaccination, COVID-19 morbidity and mortality rates were driven by the situation in the NHs. Shortly after the COVID-19 vaccination campaign, and later the booster campaign, the number of hospital admissions and deaths among NH residents dropped, while clear peaks could be observed among the general population. The impact of vaccination on virus circulation was less effective than expected. However, due to the high vaccination coverage, NH residents remain well protected against hospital admission and death due to COVID-19 more than one year after being vaccinated. [ABSTRACT FROM AUTHOR]

In February 2020, the municipality of Vo', a small town near Padua (Italy) was quarantined due to the first coronavirus disease 19 (COVID-19)-related death detected in Italy. To investigate the viral prevalence and clinical features, the entire population was swab tested in two sequential surveys. Here we report the analysis of 87 viral genomes, which revealed that the unique ancestor haplotype introduced in Vo' belongs to lineage B, carrying the mutations G11083T and G26144T. The viral sequences allowed us to investigate the viral evolution while being transmitted within and across households and the effectiveness of the non-pharmaceutical interventions implemented in Vo'. We report, for the first time, evidence that novel viral haplotypes can naturally arise intra-host within an interval as short as two weeks, in approximately 30% of the infected individuals, regardless of symptom severity or immune system deficiencies. Moreover, both phylogenetic and minimum spanning network analyses converge on the hypothesis that the viral sequences evolved from a unique common ancestor haplotype that was carried by an index case. The lockdown extinguished both the viral spread and the emergence of new variants. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 pandemic has mobilized many efforts worldwide to curb its impact on morbidity and mortality. Vaccination of the general population has resulted in the administration of more than 6,700,000,000 doses by the end of October 2021, which is the most effective method to prevent hospitalization and death. Among the adverse effects described, myocarditis and pericarditis are low-frequency events (less than 10 per 100,000 people), mainly observed with messenger RNA vaccines. The mechanisms responsible for these effects have not been specified, considering an exacerbated and uncontrolled immune response and an autoimmune response against specific cardiomyocyte proteins. This greater immunogenicity and reactogenicity is clinically manifested in a differential manner in pediatric patients, adults, and the elderly, determining specific characteristics of its presentation for each age group. It generally develops as a condition of mild to moderate severity, whose symptoms and imaging findings are self-limited, resolving favorably in days to weeks and, exceptionally, reporting deaths associated with this complication. The short- and medium-term prognosis is favorable, highlighting the lack of data on long-term evolution, which should be determined in longer follow-ups. [ABSTRACT FROM AUTHOR]

The outbreak of emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) in China has been brought to global attention and declared a pandemic by the World Health Organization (WHO) on March 11, 2020. Scientific advancements since the pandemic of severe acute respiratory syndrome (SARS) in 2002~2003 and Middle East respiratory syndrome (MERS) in 2012 have accelerated our understanding of the epidemiology and pathogenesis of SARS-CoV-2 and the development of therapeutics to treat viral infection. As no specific therapeutics and vaccines are available for disease control, the epidemic of COVID-19 is posing a great threat for global public health. To provide a comprehensive summary to public health authorities and potential readers worldwide, we detail the present understanding of COVID-19 and introduce the current state of development of measures in this review. [ABSTRACT FROM AUTHOR]