Assessing the Pre-Vaccination Anti-SARS-CoV-2 IgG Seroprevalence among Residents and Staff in Nursing Home in Niigata, Japan, November 2020.

An outbreak of coronavirus disease 2019 (COVID-19) occurred in a nursing home in Niigata, Japan, November 2020, with an attack rate of 32.0% (63/197). The present study was aimed at assessing the pre-vaccination seroprevalence almost half a year after the COVID-19 outbreak in residents and staff in the facility, along with an assessment of the performance of the enzyme-linked immunosorbent assay (ELISA) and the chemiluminescent immunoassay (CLIA), regarding test seropositivity and seronegativity in detecting immunoglobulin G (IgG) anti-severe acute respiratory syndrome 2 (SARS-CoV-2) antibodies (anti-nucleocapsid (N) and spike (S) proteins). A total of 101 people (30 reverse transcription PCR (RT-PCR)-positive and 71 RT-PCR-negative at the time of the outbreak in November 2020) were tested for anti-IgG antibody titers in April 2021, and the seroprevalence was approximately 40.0-60.0% for residents and 10.0-20.0% for staff, which was almost consistent with the RT-PCR test results that were implemented during the outbreak. The seropositivity for anti-S antibodies showed 90.0% and was almost identical to the RT-PCR positives even after approximately six months of infections, suggesting that the anti-S antibody titer test is reliable for a close assessment of the infection history. Meanwhile, seropositivity for anti-N antibodies was relatively low, at 66.7%. There was one staff member and one resident that were RT-PCR-negative but seropositive for both anti-S and anti-N antibody, indicating overlooked infections despite periodical RT-PCR testing at the time of the outbreak. Our study indicated the impact of transmission of SARS-CoV-2 in a vulnerable elderly nursing home in the pre-vaccination period and the value of a serological study to supplement RT-PCR results retrospectively.

Genomic Epidemiology Reveals Multiple Introductions of Severe Acute Respiratory Syndrome Coronavirus 2 in Niigata City, Japan, Between February and May 2020.

The coronavirus disease 2019 (COVID-19) has caused a serious disease burden and poses a tremendous public health challenge worldwide. Here, we report a comprehensive epidemiological and genomic analysis of SARS-CoV-2 from 63 patients in Niigata City, a medium-sized Japanese city, during the early phase of the pandemic, between February and May 2020. Among the 63 patients, 32 (51%) were female, with a mean (±standard deviation) age of 47.9 ± 22.3 years. Fever (65%, 41/63), malaise (51%, 32/63), and cough (35%, 22/63) were the most common clinical symptoms. The median C t value after the onset of symptoms lowered within 9 days at 20.9 cycles (interquartile range, 17-26 cycles), but after 10 days, the median C t value exceeded 30 cycles (p < 0.001). Of the 63 cases, 27 were distributed in the first epidemic wave and 33 in the second, and between the two waves, three cases from abroad were identified. The first wave was epidemiologically characterized by a single cluster related to indoor sports activity spread in closed settings, which included mixing indoors with families, relatives, and colleagues. The second wave showed more epidemiologically diversified events, with most index cases not related to each other. Almost all secondary cases were infected by droplets or aerosols from closed indoor settings, but at least two cases in the first wave were suspected to be contact infections. Results of the genomic analysis identified two possible clusters in Niigata City, the first of which was attributed to clade S (19B by Nexstrain clade) with a monophyletic group derived from the Wuhan prototype strain but that of the second wave was polyphyletic suggesting multiple introductions, and the clade was changed to GR (20B), which mainly spread in Europe in early 2020. These findings depict characteristics of SARS-CoV-2 transmission in the early stages in local community settings during February to May 2020 in Japan, and this integrated approach of epidemiological and genomic analysis may provide valuable information for public health policy decision-making for successful containment of chains of infection.