Decrease in overdispersed secondary transmission of COVID-19 over time in Japan.

Coronavirus disease 2019 (COVID-19) has been described as having an overdispersed offspring distribution, i.e. high variation in the number of secondary transmissions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) per single primary COVID-19 case. Accordingly, countermeasures focused on high-risk settings and contact tracing could efficiently reduce secondary transmissions. However, as variants of concern with elevated transmissibility continue to emerge, controlling COVID-19 with such focused approaches has become difficult. It is vital to quantify temporal variations in the offspring distribution dispersibility. Here, we investigated offspring distributions for periods when the ancestral variant was still dominant (summer, 2020; wave 2) and when Alpha variant (B.1.1.7) was prevailing (spring, 2021; wave 4). The dispersion parameter (k) was estimated by analysing contact tracing data and fitting a negative binomial distribution to empirically observed offspring distributions from Nagano, Japan. The offspring distribution was less dispersed in wave 4 (k = 0.32; 95% confidence interval (CI) 0.24-0.43) than in wave 2 (k = 0.21 (95% CI 0.13-0.36)). A high proportion of household transmission was observed in wave 4, although the proportion of secondary transmissions generating more than five secondary cases did not vary over time. With this decreased variation, the effectiveness of risk group-focused interventions may be diminished.

SARS-CoV-2 outbreak investigation in a German meat processing plant.

We describe a multifactorial investigation of a SARS-CoV-2 outbreak in a large meat processing complex in Germany. Infection event timing, spatial, climate and ventilation conditions in the processing plant, sharing of living quarters and transport, and viral genome sequences were analyzed. Our results suggest that a single index case transmitted SARS-CoV-2 to co-workers over distances of more than 8 m, within a confined work area in which air is constantly recirculated and cooled. Viral genome sequencing shows that all cases share a set of mutations representing a novel sub-branch in the SARS-CoV-2 C20 clade. We identified the same set of mutations in samples collected in the time period between this initial infection cluster and a subsequent outbreak within the same factory, with the largest number of confirmed SARS-CoV-2 cases in a German meat processing facility reported so far. Our results indicate climate conditions, fresh air exchange rates, and airflow as factors that can promote efficient spread of SARS-CoV-2 via long distances and provide insights into possible requirements for pandemic mitigation strategies in industrial workplace settings.

Detection of modified measles and super-spreader using a real-time reverse transcription PCR in the largest measles outbreak, Yamagata, Japan, 2017 in its elimination era.

We aimed to verify the effectiveness of real-time reverse transcription (rRT) polymerase chain reaction (PCR) for detecting cases of modified measles (M-Me) and for predicting super-spreader candidates through the experience of a measles outbreak dominated by M-Me in Yamagata, Japan, during March-April 2017. We applied rRT-PCR to specimens from 35 cases of M-Me, nine cases of typical measles (T-Me) and nine cases of prodromal stage of T-Me (P-Me). From rRT-PCR among the M-Me cases, peripheral blood mononuclear cells (PBMC) showed the highest positive rate (80.0%), followed by throat swab (48.6%), urine (33.3%) and serum (3.1%). The negative result of PBMC in M-Me cases was recovered by the result of a throat swab. In specimens of PBMC, throat swab and urine, M-Me group showed the significantly higher cycle of threshold (i.e., lower viral load) in the rRT-PCR than T-Me and P-Me groups, respectively. Furthermore, three super-spreaders in T-Me or P-Me showed an extremely low cycle of threshold in their throat swab specimens. rRT-PCR using PBMC and throat swab might be helpful for clinical management and measles control by certain detection of M-Me cases and by predicting super-spreading events resulting from measles cases with the high viral load.

Risk factors for transmission of Middle East respiratory syndrome coronavirus infection during the 2015 outbreak in South Korea.

Background: Transmission heterogeneity was observed during the 2015 South Korean outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection. Only 22 of 186 cases transmitted the infection, and 5 super-spreading events caused 150 transmissions. We investigated the risk factors for MERS-CoV transmission. Methods: Epidemiological reports were used to classify patients as non-spreaders, spreaders (1-4 transmission), or those associated with super-spreading event (≥4 transmissions). Logistic regression analyses were used to evaluate the factors that influenced MERS-CoV transmission. Results: Compared to non-spreaders, spreaders exhibited a longer interval from symptom onset to isolation (7 days vs. 3 days) and more frequent pre-isolation pneumonia diagnoses (68.2% vs. 17.1%). Spreaders also exhibited higher values for pre-isolation contacts (149 vs. 17.5), pre-isolation hospitalization (68.2% vs. 16.5%), and emergency room visits (50% vs. 7.3%). Spreaders exhibited lower cycle thresholds for the upE and ORF1a genes (22.7 vs. 27.2 and 23.7 vs. 27.9, respectively). Transmission was independently associated with the cycle threshold (odds ratio [OR]: 0.84, 95% confidence interval [CI]: 0.75-0.96) and pre-isolation hospitalization or emergency room visits (OR: 6.82, 95% CI: 2.06-22.84). The spreaders with ≥4 transmissions exhibited higher values for pre-isolation contacts (777 vs. 78), pre-isolation emergency room visits (100% vs. 35.3%), and doctor-shopping (100% vs. 47.1%), compared to other spreaders. Conclusions: These findings indicate that transmission is determined by host infectivity and the number of contacts, whereas super-spreading events were determined by the number of contacts and hospital visits. These relationships highlight the importance of rapidly enforcing infection control measures to prevent outbreaks.