Beclin1 is essential for the pancreas development.

Beclin1 (Becn1) is a multifunctional protein involved in autophagy regulation, membrane trafficking, and tumor suppression. In this study, we examined the roles of Becn1 in the pancreas development by generating mice with conditional deletion of Becn1 in the pancreas using pancreatic transcriptional factor 1a (Ptf1a)-Cre mice (Becn1f/f; Ptf1aCre/+). Surprisingly, loss of Becn1 in the pancreas resulted in severe pancreatic developmental defects, leading to insufficient exocrine and endocrine pancreatic function. Approximately half of Becn1f/f; Ptf1aCre/+ mice died immediately after birth. However, duodenum and neural tissue development were almost normal, indicating that pancreatic insufficiency was the cause of death. These findings demonstrated a novel role for Becn1 in pancreas morphogenesis, differentiation, and growth, and suggested that loss of this factor leaded to pancreatic agenesis at birth.

Decomposing mechanisms of COVID-19 mortality in empirical datasets: A modeling study.

Our objective was to decompose mortality mechanisms during the coronavirus disease 2019 (COVID-19) pandemic to estimate direct, indirect, and associated deaths from COVID-19. Given the confirmatory diagnosis of COVID-19, a death event that was not necessarily caused by respiratory complications but stemmed from other complications was categorized as an indirect death from COVID-19. Associated deaths occurred in patients who did not have COVID-19 but died during the surge in COVID-19 cases when overwhelming pressure was exerted on the healthcare system. Analyzing the sixth wave (i.e., the first epidemic wave of the Omicron B.1.1.529 variant from January to May 2022), decomposition was achieved using the binomial and Poisson sampling process models fitted to two pieces of data (i.e., COVID-19 death certificate and excess data by major cause of death). The total numbers of direct, indirect, and associated deaths during the sixth wave in Osaka were estimated at 1,071; 948; and 2,157; respectively. The number of associated deaths was greater than the sum of direct and indirect deaths. We further observed that the composition of indirect and associated deaths differed by major cause of death, and deaths caused by circulatory disease included a greater proportion of indirect deaths compared with deaths by other causes. The goals of healthcare services for endemic COVID-19 include the sustainable provision of services to avoid preventable deaths. Therefore, gaining an in-depth understanding of mechanisms that lead to excess death is vital for improving future pandemic response efforts.

Reconstructing the COVID-19 incidence in India using airport screening data in Japan.

BACKGROUND: A major epidemic of COVID-19 caused by the Delta variant (B.1.617.2) occurred in India from March to July 2021, resulting in 19 million documented cases. Given the limited healthcare and testing capacities, the actual number of infections is likely to have been greater than reported, and several modelling studies and excess mortality research indicate that this epidemic involved substantial morbidity and mortality. METHODS: To estimate the incidence during this epidemic, we used border entry screening data in Japan to estimate the daily incidence and cumulative incidence of COVID-19 infection in India. Analysing the results of mandatory testing among non-Japanese passengers entering Japan from India, we calculated the prevalence and then backcalculated the incidence in India from February 28 to July 3, 2021. RESULTS: The estimated number of infections ranged from 448 to 576 million people, indicating that 31.8% (95% confidence interval (CI): 26.1, 37.7) - 40.9% (95% CI: 33.5, 48.4) of the population in India had experienced COVID-19 infection from February 28 to July 3, 2021. In addition to obtaining cumulative incidence that was consistent with published estimates, we showed that the actual incidence of COVID-19 infection during the 2021 epidemic in India was approximately 30 times greater than that based on documented cases, giving a crude infection fatality risk of 0.47%. Adjusting for test-negative certificate before departure, the quality control of which was partly questionable, the cumulative incidence can potentially be up to 2.3-2.6 times greater than abovementioned estimates. CONCLUSIONS: Our estimate of approximately 32-41% cumulative infection risk from February 28 to July 3, 2021 is roughly consistent with other published estimates, and they can potentially be greater, given an exit screening before departure. The present study results suggest the potential utility of border entry screening data to backcalculate the incidence in countries with limited surveillance capacity owing to a major surge in infections.

Evaluation of the exit screening policy among travelers arriving from Asian and pacific nations.

BACKGROUND: The Japanese government has instituted border control measures against COVID-19, including entry and exit screening of people arriving from overseas. We sought to evaluate the effectiveness of the exit screening policy in Japan in reducing the risk of importing COVID-19 cases among travelers from Asian and Pacific countries. METHODS: The study period was stratified based on the timing of exit screening: (i) the control period (the pre-exit screening period from 25 October 2020 to 16 January 2021), (ii) the time period with the Alpha variant from 17 January to 10 April 2021, and (iii) the time period with the Delta variant from 2 May to 2 October 2021. Incidence data in the countries of origin were used to adjust for the risk of infection among travelers. The positivity rate of entry screening in Japan was compared among the three different study periods, adjusting for the risk of infection in the country of origin. RESULTS: The adjusted relative risk of positivity was greatly reduced and substantially below the value of 1 during the Alpha variant period compared with the control period. Although the relative risks increased when comparing the Delta variant period against control, the estimate remained below 1, except for among travelers from India and Myanmar. The relative risk reduction was greatest in high-income countries, with estimates of 100% and 96% risk reduction during the Alpha and Delta variant periods, respectively, followed by upper-middle-income countries with estimates of 90% and 76%, respectively. CONCLUSIONS: Even in the presence of the Alpha and Delta variants, exit screening clearly reduced the risk of infection among travelers arriving from Asian and Pacific nations. As the testing relies on the country of origin, the effectiveness varied greatly by the socioeconomic income status and epidemiological situation of those countries. Test standardization and quality assurance may be required in low- and middle-income countries.

Reconstruction and analysis of the transmission network of African swine fever in People's Republic of China, August 2018-September 2019.

Introduction of African swine fever (ASF) to China in mid-2018 and the subsequent transboundary spread across Asia devastated regional swine production, affecting live pig and pork product-related markets worldwide. To explore the spatiotemporal spread of ASF in China, we reconstructed possible ASF transmission networks using nearest neighbour, exponential function, equal probability, and spatiotemporal case-distribution algorithms. From these networks, we estimated the reproduction numbers, serial intervals, and transmission distances of the outbreak. The mean serial interval between paired units was around 29 days for all algorithms, while the mean transmission distance ranged 332 -456 km. The reproduction numbers for each algorithm peaked during the first two weeks and steadily declined through the end of 2018 before hovering around the epidemic threshold value of 1 with sporadic increases during 2019. These results suggest that 1) swine husbandry practices and production systems that lend themselves to long-range transmission drove ASF spread; 2) outbreaks went undetected by the surveillance system. Efforts by China and other affected countries to control ASF within their jurisdictions may be aided by the reconstructed spatiotemporal model. Continued support for strict implementation of biosecurity standards and improvements to ASF surveillance is essential for halting transmission in China and spread across Asia.

Projecting the COVID-19 immune landscape in Japan in the presence of waning immunity and booster vaccination.

Coronavirus disease 2019 (COVID-19) booster vaccination has been implemented globally in the midst of surges in infection due to the Delta and Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of the present study was to present a framework to estimate the proportion of the population that is immune to symptomatic SARS-CoV-2 infection with the Omicron variant (immune proportion) in Japan, considering the waning of immunity resulting from vaccination and naturally acquired infection. We quantified the decay rate of immunity against symptomatic infection with Omicron conferred by the second and third doses of COVID-19 vaccine. We estimated the current and future vaccination coverage for the second and third vaccine doses from February 17, 2021 to August 1, 2022 and used data on the confirmed COVID-19 incidence from February 17, 2021 to April 10, 2022. From this information, we estimated the age-specific immune proportion over the period from February 17, 2021 to August 1, 2022. Vaccine-induced immunity, conferred by the second vaccine dose in particular, was estimated to rapidly wane. There were substantial variations in the estimated immune proportion by age group because each age cohort experienced different vaccination rollout timing and speed as well as a different infection risk. Such variations collectively contributed to heterogeneous immune landscape trajectories over time and age. The resulting prediction of the proportion of the population that is immune to symptomatic SARS-CoV-2 infection could aid decision-making on when and for whom another round of booster vaccination should be considered. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Assessing the COVID-19 vaccination program during the Omicron variant (B.1.1.529) epidemic in early 2022, Tokyo.

BACKGROUND: Many countries, including high-income nations, struggled to control epidemic waves caused by the Omicron variant (B.1.1.529), which had an antigenically distinct evolution. Evaluating the direct and indirect effects of vaccination during the Omicron waves is essential to assess virus control policies. The present study assessed the population impacts of a vaccination program during the sixth wave caused by BA.1 and BA.2 from January to May 2022, in Tokyo. METHODS: We analyzed the primary series and booster vaccination coverages and the confirmed cases stratified by vaccination history. We estimated the number of COVID-19 cases that were directly and indirectly prevented by vaccination. To estimate the direct impact, we used a statistical model that compared risks between unvaccinated and vaccinated individuals. A transmission model employing the renewal process was devised to quantify the total effect, given as the sum of the direct and indirect effects. RESULTS: Assuming that the reporting coverage of cases was 25%, mass vaccination programs, including primary and booster immunizations, directly averted 640,000 COVID-19 cases (95% confidence interval: 624-655). Furthermore, these programs directly and indirectly prevented 8.5 million infections (95% confidence interval: 8.4-8.6). Hypothetical scenarios indicated that we could have expected a 19% or 7% relative reduction in the number of infections, respectively, compared with the observed number of infections, if the booster coverage had been equivalent to that of the second dose or if coverage among people aged 10-49 years had been 10% higher. If the third dose coverage was smaller and comparable to that of the fourth dose, the total number of infections would have increased by 52% compared with the observed number of infections. CONCLUSIONS: The population benefit of vaccination via direct and indirect effects was substantial, with an estimated 65% reduction in the number of SARS-CoV-2 infections compared with counterfactual (without vaccination) in Tokyo during the sixth wave caused by BA.1 and BA.2.

Age-Dependent Effects of COVID-19 Vaccine and of Healthcare Burden on COVID-19 Deaths, Tokyo, Japan.

COVID-19 vaccine effectiveness against death in Japan remains unknown. Furthermore, although evidence indicates that healthcare capacity influences case-fatality risk (CFR), it remains unknown whether this relationship is mediated by age. With a modeling study, we analyzed daily COVID-19 cases and deaths during January-August 2021 by using Tokyo surveillance data to jointly estimate COVID-19 vaccine effectiveness against death and age-specific CFR. We also examined daily healthcare operations to determine the association between healthcare burden and age-specific CFR. Among fully vaccinated patients, vaccine effectiveness against death was 88.6% among patients 60-69 years of age, 83.9% among patients 70-79 years of age, 83.5% among patients 80-89 years of age, and 77.7% among patients >90 years of age. A positive association of several indicators of healthcare burden with CFR among patients >70 years of age suggested an age-dependent effect of healthcare burden on CFR in Japan.

Relative instantaneous reproduction number of Omicron SARS-CoV-2 variant with respect to the Delta variant in Denmark.

The Omicron variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become widespread across the world in a flashing manner. As of December 7, 2021, a total of 758 Omicron cases were confirmed in Denmark. Using the nucleotide sequences of the Delta and Omicron variants registered from Denmark in the GISAID database, we found that the effective (instantaneous) reproduction number of Omicron is 3.19 (95% confidence interval [CI]: 2.82-3.61) times greater than that of Delta under the same epidemiological conditions. The proportion of Omicron infections among all SARS-CoV-2 infections in Denmark was expected to exceed 95% on December 28, 2021, with a 95% CI from December 25 to December 31, 2021. Given that the Delta variant or variants less transmissible than Delta are dominant in most countries, the rapid increase in Omicron in the virus population may be observed as soon as the Omicron is introduced. Preparing proactive control measures is vital, assuming the substantial advantage of the transmission by Omicron.

Double deficiency of cathepsin B and L in the mouse pancreas alters trypsin activity without affecting acute pancreatitis severity.

BACKGROUND: Premature intracellular trypsinogen activation has long been considered a key initiator of acute pancreatitis (AP). Cathepsin B (CTSB) activates trypsinogen, while cathepsin L (CTSL) inactivates trypsin(ogen), and both proteins play a role in the onset of AP. METHODS: AP was induced by 7 hourly intraperitoneal injections of cerulein (50 µg/kg) in wild-type and pancreas-specific conditional Ctsb knockout (CtsbΔpan), Ctsl knockout (CtslΔpan), and Ctsb;Ctsl double-knockout (CtsbΔpan;CtslΔpan) mice. Pancreatic samples were collected and analyzed by histology, immunohistochemistry, real-time PCR, and immunoblots. Trypsin activity was measured in pancreatic homogenates. Peripheral blood was collected, and serum amylase activity was measured. RESULTS: Double deletion of Ctsb and Cstl did not affect pancreatic development or mouse growth. After 7 times cerulein injections, double Ctsb and Ctsl deficiency in mouse pancreases increased trypsin activity to the same extent as that in Ctsl-deficient mice, while Ctsb deficiency decreased trypsin activity but did not affect the severity of AP. CtsbΔpan;CtslΔpan mice had comparable serum amylase activity and histopathological changes and displayed similar levels of proinflammatory cytokines, apoptosis, and autophagy activity compared with wild-type, CtsbΔpan, and CtslΔpan mice. CONCLUSION: Double deletion of Ctsb and Ctsl in the mouse pancreas altered intrapancreatic trypsin activity but did not affect disease severity and inflammatory response after cerulein-induced AP.

Doubling time of infectious diseases.

The concept of doubling time has been increasingly used since the onset of the coronavirus disease 2019 (COVID-19) pandemic, but its characteristics are not well understood, especially as applied to infectious disease epidemiology. The present study aims to be a practical guide to monitoring the doubling time of infectious diseases. Via simulation exercise, we clarify the epidemiological characteristics of doubling time, allowing possible interpretations. We show that the commonly believed relationship between the doubling time and intrinsic growth rate in population ecology does not strictly apply to infectious diseases, and derive the correct relationship between the two. We examined the impact of varying (i) the growth rate, (ii) the starting point of counting cumulative number of cases, and (iii) the length of observation on statistical estimation of doubling time. It was difficult to recover values of growth rate from doubling time, especially when the growth rate was small. Starting time period is critical when the statistical estimation of doubling time occurs during the course of an epidemic. The length of observation was critical in determining the overall magnitude of doubling time, and when only the latest 1-2 weeks' data were used, the resulting doubling time was very short, regardless of the intrinsic growth rate r. We suggest that doubling time estimates of infectious disease epidemics should at a minimum be accompanied by descriptions of (i) the starting time at which the cumulative count is initiated and (ii) the length of observation.

Time-dependent risk of COVID-19 death with overwhelmed health-care capacity in Japan, 2020-2022.

BACKGROUND: It has been descriptively argued that the case fatality risk (CFR) of coronavirus disease (COVID-19) is elevated when medical services are overwhelmed. The relationship between CFR and pressure on health-care services should thus be epidemiologically explored to account for potential epidemiological biases. The purpose of the present study was to estimate the age-dependent CFR in Tokyo and Osaka over time, investigating the impact of caseload demand on the risk of death. METHODS: We estimated the time-dependent CFR, accounting for time delay from diagnosis to death. To this end, we first determined the time distribution from diagnosis to death, allowing variations in the delay over time. We then assessed the age-dependent CFR in Tokyo and Osaka. In Osaka, the risk of intensive care unit (ICU) admission was also estimated. RESULTS: The CFR was highest among individuals aged 80 years and older and during the first epidemic wave from February to June 2020, estimated as 25.4% (95% confidence interval [CI] 21.1 to 29.6) and 27.9% (95% CI 20.6 to 36.1) in Tokyo and Osaka, respectively. During the fourth wave of infection (caused by the Alpha variant) in Osaka the CFR among the 70s and ≥ 80s age groups was, respectively, 2.3 and 1.5 times greater than in Tokyo. Conversely, despite the surge in hospitalizations, the risk of ICU admission among those aged 80 and older in Osaka decreased. Such time-dependent variation in the CFR was not seen among younger patients < 70 years old. With the Omicron variant, the CFR among the 80s and older in Tokyo and Osaka was 3.2% (95% CI 3.0 to 3.5) and 2.9% (95% CI 2.7 to 3.1), respectively. CONCLUSION: We found that without substantial control, the CFR can increase when a surge in cases occurs with an identifiable elevation in risk-especially among older people. Because active treatment options including admission to ICU cannot be offered to the elderly with an overwhelmed medical service, the CFR value can potentially double compared with that in other areas of health care under less pressure.

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.

Go To Travel campaign and the geographic spread of COVID-19 in Japan.

BACKGROUND: In 2020, the Japanese government implemented first of two Go To Travel campaigns to promote the tourism sector as well as eating and drinking establishments, especially in remote areas. The present study aimed to explore the relationship between enhanced travel and geographic propagation of COVID-19 across Japan, focusing on the second campaign with nationwide large-scale economic boost in 2020. METHODS: We carried out an interrupted time-series analysis to identify the possible cause-outcome relationship between the Go To Travel campaign and the spread of infection to nonurban areas in Japan. Specifically, we counted the number of prefectures that experienced a weekly incidence of three, five, and seven COVID-19 cases or more per 100,000 population, and we compared the rate of change before and after the campaign. RESULTS: Three threshold values and three different models identified an increasing number of prefectures above the threshold, indicating that the inter-prefectural spread intensified following the launch of the second Go To Travel campaign from October 1st, 2020. The simplest model that accounted for an increase in the rate of change only provided the best fit. We estimated that 0.24 (95% confidence interval 0.15 to 0.34) additional prefectures newly exceeded five COVID-19 cases per 100,000 population per week during the second campaign. CONCLUSIONS: The enhanced movement resulting from the Go To Travel campaign facilitated spatial spread of COVID-19 from urban to nonurban locations, where health-care capacity may have been limited.

Transmission Network of Measles During the Yamagata Outbreak in Japan, 2017.

BACKGROUND: A measles outbreak involving 60 cases occurred in Yamagata, Japan in 2017. Using two different mathematical models for different datasets, we aimed to estimate measles transmissibility over time and explore any heterogeneous transmission patterns. METHODS: The first model relied on the temporal distribution for date of illness onset for cases, and a generation-dependent model was applied to the data. Another model focused on the transmission network. Using the illness-onset date along with the serial interval and geographical location of exposure, we reconstructed a transmission network with 19 unknown links. We then compared the number of secondary transmissions with and without clinical symptoms or laboratory findings. RESULTS: Using a generation-dependent model (assuming three generations other than the index case), the reproduction number (R) over generations 0, 1, and 2 were 25.3, 1.3, and <0.1, respectively, explicitly yielding the transmissibility over each generation. The network data enabled us to demonstrate that both the mean and the variance for the number of secondary transmissions per primary case declined over time. Comparing primary cases with and without secondary transmission, high viral shedding was the only significant determinant (P < 0.01). CONCLUSIONS: The R declined abruptly over subsequent generations. Use of network data revealed the distribution of the number of secondary transmissions per primary case and also allowed us to identify possible secondary transmission risk factors. High viral shedding from the throat mucosa was identified as a potential predictor of secondary transmission.

[Grasping COVID-19 immune landscape in Japan].

COVID-19 vaccination commenced globally in December 2020. Japan launched its vaccination rollout on February 17, 2021 and commenced booster vaccination campaign on December 1, 2021. It has been crucial to grasp the immune landscape in the country in order to aid in decision-making and evaluation of vaccination campaigns as well as understating the transmission dynamics of various variants of SARS-CoV-2. The present article shows a framework that enables us to predict the immune landscape, specifically, the proportion of immune population, using a mathematical modeling approach. This involved: prediction of vaccine coverage; estimation of vaccine effectiveness against the dominant SARS-CoV-2 variant in circulation; the quantification of increasing vaccine effectiveness (immune-build up) since receiving the first dose; the estimation of waning rate of vaccine effectiveness since receiving the second and third doses; and the consideration on the infection-induced immunity.

Familial Clusters of Coronavirus Disease in 10 Prefectures, Japan, February-May 2020.

The overall coronavirus disease secondary attack rate (SAR) in family members was 19.0% in 10 prefectures of Japan during February 22-May 31, 2020. The SAR was lower for primary cases diagnosed early, within 2 days after symptom onset. The SAR of asymptomatic primary cases was 11.8%.

Proactive Engagement of the Expert Meeting in Managing the Early Phase of the COVID-19 Epidemic, Japan, February-June 2020.

To deal with the risk of emerging diseases with many unknowns, close and timely collaboration and communication between science experts and policymakers are crucial to developing and implementing an effective science-based intervention strategy. The Expert Meeting, an ad hoc medical advisory body, was established in February 2020 to advise Japan's COVID-19 Response Headquarters. The group played an important role in the policymaking process, promoting timely situation awareness and developing science-based proposals on interventions that were promptly reflected in government actions. However, this expert group may have been overly proactive in taking on the government's role in crisis management. For the next stage of managing the coronavirus disease pandemic and future pandemics, the respective roles of the government and its advisory bodies need to be clearly defined. Leadership and strategic risk communication by the government are key.

A method for estimating the transmissibility of influenza using serial cross-sectional seroepidemiological data.

BACKGROUND: Seroepidemiological surveillance data has been demonstrated to be useful for estimating the cumulative incidence of influenza, and measures the difference between pre- and post-epidemic seropositive fractions. Despite this, such studies relied on a chosen cut-off value for seropositivity. The aim of the present study is to develop a method to analyze distributions of serial cross-sectional seroepidemiological surveillance datasets using an epidemiological model so that the transmission potential can be estimated without imposing a cut-off value. METHODS: A mathematical model of influenza transmission with a discrete antibody titer level was constructed. The final size equation for pre- and post-epidemic titer levels was derived. Subsequently, using the estimated distribution of the dilution increase caused by infection and the measurement error distribution, the model parameters were optimized using the maximum likelihood method. A bootstrap-based confidence interval calculation and sensitivity analysis were also performed. RESULTS: Without imposing a cut-off value, the cumulative incidence was quantified, thereby yielding an estimate of the basic reproduction number. For the purpose of exposition, the proposed method was applied to influenza A/Victoria/3/75(H3N2) data, and serological data between 1975 and 1976 were compared. The estimated reproduction number was greater than that using the cut-off value of the hemagglutination inhibition level with titer level 20 (dilution 1:20) or above to define positives. CONCLUSION: The proposed method without a cut-off value offers an unbiased approach to estimating the cumulative incidence along with the reproduction number. If a cut-off value is required, the results imply that titer level 20 or above may better represent a reasonable cut-off value for calculating the incidence, but it could underestimate the basic reproduction number.

Exploring secondary SARS-CoV-2 transmission from asymptomatic cases using contact tracing data.

BACKGROUND: Individuals with asymptomatic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection can propagate the virus unknowingly and thus have been a focus of public health attentions since the early stages of the pandemic. Understanding viral transmissibility among asymptomatic individuals is critical for successful control of coronavirus disease 2019 (COVID-19). The present study aimed to understand SARS-CoV-2 transmissibility among young asymptomatic individuals and to assess whether symptomatology was associated with transmission of symptomatic vs. asymptomatic infections. METHODS: We analyzed one of the first-identified clusters of SARS-CoV-2 infections with multiple chains of transmission that occurred among university students in March 2020 in Kyoto prefecture, Japan, using discrete and two-type branching process models. Assuming that the number of secondary cases resulting from either primary symptomatic or asymptomatic cases independently followed negative binomial distributions, we estimated the relative reproduction numbers of an asymptomatic case compared with a symptomatic case. To explore the potential association between symptomatology and transmission of symptomatic vs. asymptomatic incident infections, we also estimated the proportion of secondary symptomatic cases produced by primary symptomatic and asymptomatic cases. RESULTS: The reproduction number for a symptomatic primary case was estimated at 1.14 (95% confidence interval [CI]: 0.61-2.09). The relative reproduction number for asymptomatic cases was estimated at 0.19 (95% CI: 0.03-0.66), indicating that asymptomatic primary cases did not result in sufficient numbers of secondary infections to maintain chains of transmission. There was no apparent tendency for symptomatic primary cases to preferentially produce symptomatic secondary cases. CONCLUSIONS: Using data from a transmission network during the early epidemic in Japan, we successfully estimated the relative transmissibility of asymptomatic cases of SARS-CoV-2 infection at 0.22. These results suggest that contract tracing focusing on symptomatic index cases may be justified given limited testing capacity.