Human bocavirus (HBoV) is a new parvovirus associated with acute respiratory tract infection (ARTI). In order to evaluate HBoV significance as an agent of acute respiratory disease, we screened 1,135 respiratory samples from children and adults with and without symptoms during two complete calendar years. HBoV1 prevalence in patients with ARTI was 6.33 % in 2011 and 11.64 % in 2012, including neonatal and adult patients. HBoV1 was also detected in 3.77 % of asymptomatic individuals. The co-detection rate was 78.1 %. Among children, 87 % were clinically diagnosed with lower respiratory infection (no significant differences between patients with and without coinfection), and 31 % exhibited comorbidities. Pediatric patients with comorbidities were significantly older than patients without comorbidities. Patients with ARTI had either high or low viral load, while controls had only low viral load, but there were no clinical differences between patients with high or low viral load. In conclusion, we present evidence of the pathogenic potential of HBoV1 in young children with ARTI. Since patients with HBoV1-single infection are not significantly different from those with coinfection with respect to clinical features, the virus can be as pathogenic by itself as other respiratory agents are. Furthermore, an association between high HBoV1 load and disease could not be demonstrated in this study, but all asymptomatic individuals had low viral loads. Also, children with comorbidities are susceptible to HBoV1 infection at older ages than previously healthy children. Thus, the clinical presentation of infection may occur depending on both viral load and the particular interaction between the HBoV1 and the host.

Highlights This study with MALDI-TOF comprises, as far as we know, the first report describing the performance of this technology with COVID-19 diagnosis. This work would encourage researchers to explore the potential of MALDI-TOF MS to assess the feasibility of this technology, as a rapid and reproducible screening tool for diagnosis of SARS-CoV-2. According to our preliminary results, mass spectrometry-based methods combined with multivariate analysis showed potential as a complementary diagnostic tool.

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Coronavirus disease 2019 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid, sensitive and specific diagnosis of SARS-CoV-2 by fast and unambiguous testing is widely recognized to be critical in responding to the ongoing outbreak. Since the current testing capacity of RT-PCR-based methods is being challenged due to the extraordinary demand of supplies, such as RNA extraction kits and PCR reagents worldwide, alternative and/or complementary testing assays should be developed. Here, we exploit the potential of mass spectrometry technology combined with machine learning algorithms as an alternative fast tool for SARS-CoV-2 detection from nasopharyngeal swabs samples. According to our preliminary results, mass spectrometry-based methods combined with multivariate analysis showed an interesting potential as a complementary diagnostic tool and further steps should be focused on sample preparation protocols and the improvement of the technology applied.was not certified by peer review)