Age-related model for estimating the symptomatic and asymptomatic transmissibility of COVID-19 patients.

Estimation of age-dependent transmissibility of COVID-19 patients is critical for effective policymaking. Although the transmissibility of symptomatic cases has been extensively studied, asymptomatic infection is understudied due to limited data. Using a dataset with reliably distinguished symptomatic and asymptomatic statuses of COVID-19 cases, we propose an ordinary differential equation model that considers age-dependent transmissibility in transmission dynamics. Under a Bayesian framework, multi-source information is synthesized in our model for identifying transmissibility. A shrinkage prior among age groups is also adopted to improve the estimation behavior of transmissibility from age-structured data. The added values of accounting for age-dependent transmissibility are further evaluated through simulation studies. In real-data analysis, we compare our approach with two basic models using the deviance information criterion (DIC) and its extension. We find that the proposed model is more flexible for our epidemic data. Our results also suggest that the transmissibility of asymptomatic infections is significantly lower (on average, 76.45% with a credible interval (27.38%, 88.65%)) than that of symptomatic cases. In both symptomatic and asymptomatic patients, the transmissibility mainly increases with age. Patients older than 30 years are more likely to develop symptoms with higher transmissibility. We also find that the transmission burden of asymptomatic cases is lower than that of symptomatic patients.

Transmission roles of symptomatic and asymptomatic COVID-19 cases: a modelling study.

Coronavirus disease 2019 (COVID-19) asymptomatic cases are hard to identify, impeding transmissibility estimation. The value of COVID-19 transmissibility is worth further elucidation for key assumptions in further modelling studies. Through a population-based surveillance network, we collected data on 1342 confirmed cases with a 90-days follow-up for all asymptomatic cases. An age-stratified compartmental model containing contact information was built to estimate the transmissibility of symptomatic and asymptomatic COVID-19 cases. The difference in transmissibility of a symptomatic and asymptomatic case depended on age and was most distinct for the middle-age groups. The asymptomatic cases had a 66.7% lower transmissibility rate than symptomatic cases, and 74.1% (95% CI 65.9-80.7) of all asymptomatic cases were missed in detection. The average proportion of asymptomatic cases was 28.2% (95% CI 23.0-34.6). Simulation demonstrated that the burden of asymptomatic transmission increased as the epidemic continued and could potentially dominate total transmission. The transmissibility of asymptomatic COVID-19 cases is high and asymptomatic COVID-19 cases play a significant role in outbreaks.

Mycobacterium tuberculosis Transmission in High-Incidence Settings-New Paradigms and Insights.

Tuberculosis has affected humankind for thousands of years, but a deeper understanding of its cause and transmission only arose after Robert Koch discovered Mycobacterium tuberculosis in 1882. Valuable insight has been gained since, but the accumulation of knowledge has been frustratingly slow and incomplete for a pathogen that remains the number one infectious disease killer on the planet. Contrast that to the rapid progress that has been made in our understanding SARS-CoV-2 (the cause of COVID-19) aerobiology and transmission. In this Review, we discuss important historical and contemporary insights into M. tuberculosis transmission. Historical insights describing the principles of aerosol transmission, as well as relevant pathogen, host and environment factors are described. Furthermore, novel insights into asymptomatic and subclinical tuberculosis, and the potential role this may play in population-level transmission is discussed. Progress towards understanding the full spectrum of M. tuberculosis transmission in high-burden settings has been hampered by sub-optimal diagnostic tools, limited basic science exploration and inadequate study designs. We propose that, as a tuberculosis field, we must learn from and capitalize on the novel insights and methods that have been developed to investigate SARS-CoV-2 transmission to limit ongoing tuberculosis transmission, which sustains the global pandemic.

A university-clustered tuberculosis outbreak during the COVID-19 pandemic in eastern China.

During the COVID-19 pandemic in 2020, a tuberculosis outbreak occurred in a university in eastern China, with 4,488 students and 421 staff on the campus. A 19-year-old student was diagnosed in August 2019. Later, the first round of screening was initiated among close contacts, but no active cases were found. Till September 2020, four rounds of screening were performed. Four rounds of screening were conducted on September 9, November 8, November 22-25 in 2019 and September 2020, with 0, 5, 0 and 43 cases identified, respectively. A total of 66 active tuberculosis were found in the same university, including 4 sputum culture-positive and 7 sputum smear-positive. The total attack rate of active tuberculosis was 1.34% (66/4909). The whole-genome sequencing showed that the isolates belonged to the same L2 sub-specie and were sensitive to all tested antituberculosis drugs. Delay detection, diagnosis and report of cases were the major cause of this university tuberculosis epidemic. More attention should be paid to the asymptomatic students in the index class. After the occurrence of tuberculosis cases in schools, multiple rounds of screening should be carried out, and preventive therapy should be applied in a timely manner.

Development and Validation of a Two-Step Predictive Risk Stratification Model for Coronavirus Disease 2019 In-hospital Mortality: A Multicenter Retrospective Cohort Study.

Objectives: An accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information. Design: Multicenter retrospective observational cohort study. Setting: Four health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles. Patients: Coronavirus Disease 2019-confirmed and hospitalized adult patients. Measurements and Main Results: We included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate ≥30 breaths/min, and SpO2 <93% into the predictive model. Besides age and SpO2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79-0.88) and external validation at the other three health systems (range, 0.79-0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score. Conclusions: The two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice.

Sovereign Debt Standstills

As a response to economic crises triggered by COVID-19, sovereign debt standstill proposals emphasize debt payment suspensions without haircuts on the face value of debt obligations. We quantify the effects of standstills using a standard default model. We find that a one-year standstill generates welfare gains for the sovereign equivalent to a permanent consumption increase of between 0.1% and 0.3%, depending on the initial shock. However, except when it avoids a default, the standstill also implies capital losses for creditors of between 9% and 27%, which is consistent with their reluctance to participate in these operations and indicates that this reluctance would persist even without a free-riding or holdout problem. Standstills also generate a form of "debt overhang" and thus the opportunity for a "voluntary debt exchange": complementing the standstill with haircuts could reduce creditors' losses and simultaneously increase welfare gains. Our results cast doubts on the emphasis on standstills without haircuts.

The Household Secondary Attack Rate of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Rapid Review.

BACKGROUND: Although much of the public health effort to combat coronavirus disease 2019 (COVID-19) has focused on disease control strategies in public settings, transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within households remains an important problem. The nature and determinants of household transmission are poorly understood. METHODS: To address this gap, we gathered and analyzed data from 22 published and prepublished studies from 10 countries (20 291 household contacts) that were available through 2 September 2020. Our goal was to combine estimates of the SARS-CoV-2 household secondary attack rate (SAR) and to explore variation in estimates of the household SAR. RESULTS: The overall pooled random-effects estimate of the household SAR was 17.1% (95% confidence interval [CI], 13.7-21.2%). In study-level, random-effects meta-regressions stratified by testing frequency (1 test, 2 tests, >2 tests), SAR estimates were 9.2% (95% CI, 6.7-12.3%), 17.5% (95% CI, 13.9-21.8%), and 21.3% (95% CI, 13.8-31.3%), respectively. Household SARs tended to be higher among older adult contacts and among contacts of symptomatic cases. CONCLUSIONS: These findings suggest that SARs reported using a single follow-up test may be underestimated, and that testing household contacts of COVID-19 cases on multiple occasions may increase the yield for identifying secondary cases.

COVID-19 Transmission Dynamics Among Close Contacts of Index Patients With COVID-19: A Population-Based Cohort Study in Zhejiang Province, China.

Importance: Much remains unknown about the transmission dynamics of COVID-19. How the severity of the index case and timing of exposure is associated with disease in close contacts of index patients with COVID-19 and clinical presentation in those developing disease is not well elucidated. Objectives: To investigate the association between the timing of exposure and development of disease among close contacts of index patients with COVID-19 and to evaluate whether the severity of the index case is associated with clinical presentation in close contacts who develop COVID-19. Design, Setting, and Participants: This study used a large, population-based cohort of 730 individuals (index patients) who received a diagnosis of COVID-19 in Zhejiang Province, China, from January 8 to July 30, 2020, along with a contact tracing surveillance program. Field workers visited 8852 close contacts of the index patients and evaluated them for COVID-19 through August 2020. A timeline was constructed to characterize different exposure periods between index patients and their contacts. Main Outcomes and Measures: The primary outcome was the attack rate of COVID-19, defined as the total number of new COVID-19 cases diagnosed among contacts of index patients divided by the total number of exposed contacts. A secondary outcome was asymptomatic clinical presentation among infected contacts. Relative risks were calculated to investigate risk factors for COVID-19 among contacts and asymptomatic clinical presentation among infected contacts. Results: Among 8852 close contacts (4679 male contacts [52.9%]; median age, 41 years [interquartile range, 28-54 years]) of 730 index patients (374 male patients [51.2%]; median age, 46 years [interquartile range, 36-56 years]), contacts were at highest risk of COVID-19 if they were exposed between 2 days before and 3 days after the index patient's symptom onset, peaking at day 0 (adjusted relative risk [ARR], 1.3; 95% CI, 1.2-1.5). Compared with being exposed to an asymptomatic index patient, the risk of COVID-19 among contacts was higher when they were exposed to index patients with mild (ARR, 4.0; 95% CI, 1.8-9.1) and moderate (ARR, 4.3; 95% CI, 1.9-9.7) cases of COVID-19. As index case severity increased, infected contacts were less likely to be asymptomatic (exposed to patient with mild COVID-19: ARR, 0.3; 95% CI, 0.1-0.9; exposed to patient with moderate COVID-19: ARR, 0.3; 95% CI, 0.1-0.8). Conclusions and Relevance: This cohort study found that individuals with COVID-19 were most infectious a few days before and after symptom onset. Infected contacts of asymptomatic index patients were less likely to present with COVID-19 symptoms, suggesting that quantity of exposure may be associated with clinical presentation in close contacts.

Collateral Impact of the Coronavirus Disease 2019 (COVID-19) Pandemic on Tuberculosis Control in Jiangsu Province, China.

The coronavirus disease 2019 (COVID-19) pandemic may impede global tuberculosis elimination goals. In Jiangsu Province, China, tuberculosis notifications dropped 52% in 2020 compared to 2015-2019. Treatment completion and screening for drug resistance decreased continuously in 2020. Urgent attention must be paid to tuberculosis control efforts during and after the COVID-19 pandemic.

The impact of social distancing, contact tracing, and case isolation interventions to suppress the COVID-19 epidemic: A modeling study.

INTRODUCTION: Most countries are dependent on nonpharmaceutical public health interventions such as social distancing, contact tracing, and case isolation to mitigate COVID-19 spread until medicines or vaccines widely available. Minimal research has been performed on the independent and combined impact of each of these interventions based on empirical case data. METHODS: We obtained data from all confirmed COVID-19 cases from January 7th to February 22nd 2020 in Zhejiang Province, China, to fit an age-stratified compartmental model using human contact information before and during the outbreak. The effectiveness of social distancing, contact tracing, and case isolation was studied and compared in simulation. We also simulated a two-phase reopening scenario to assess whether various strategies combining nonpharmaceutical interventions are likely to achieve population-level control of a second-wave epidemic. RESULTS: Our study sample included 1,218 symptomatic cases with COVID-19, of which 664 had no inter-province travel history. Results suggest that 36.5 % (95 % CI, 12.8-57.1) of contacts were quarantined, and approximately five days (95 % CI, 2.2-11.0) were needed to detect and isolate a case. As contact networks would increase after societal and economic reopening, avoiding a second wave without strengthening nonpharmaceutical interventions compared to the first wave it would be exceedingly difficult. CONCLUSIONS: Continuous attention and further improvement of nonpharmaceutical interventions are needed in second-wave prevention. Specifically, contact tracing merits further attention.

SARS-CoV-2: how safe is it to fly and what can be done to enhance protection?

With lockdown restrictions over coronavirus disease 2019 being relaxed, airlines are returning to the skies. Published evidence of severe acute respiratory syndrome (SARS) coronavirus 2 transmission on aircraft is limited, but in-flight transmission of respiratory infections such as tuberculosis, influenza and SARS has been well described. Risk factors include proximity to index patients and sitting in aisle seats. Personal protection on aircraft could be enhanced by always wearing a well-fitting face mask and face shield or sunglasses, wiping surfaces and hands with alcohol-based sanitizers, not touching the face, not queuing for washrooms, changing seats if nearby passengers are coughing and choosing a window rather than an aisle seat.

Community Outbreak Investigation of SARS-CoV-2 Transmission Among Bus Riders in Eastern China.

Importance: Evidence of whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), can be transmitted as an aerosol (ie, airborne) has substantial public health implications. Objective: To investigate potential transmission routes of SARS-CoV-2 infection with epidemiologic evidence from a COVID-19 outbreak. Design, Setting, and Participants: This cohort study examined a community COVID-19 outbreak in Zhejiang province. On January 19, 2020, 128 individuals took 2 buses (60 [46.9%] from bus 1 and 68 [53.1%] from bus 2) on a 100-minute round trip to attend a 150-minute worship event. The source patient was a passenger on bus 2. We compared risks of SARS-CoV-2 infection among at-risk individuals taking bus 1 (n = 60) and bus 2 (n = 67 [source patient excluded]) and among all other individuals (n = 172) attending the worship event. We also divided seats on the exposed bus into high-risk and low-risk zones according to the distance from the source patient and compared COVID-19 risks in each zone. In both buses, central air conditioners were in indoor recirculation mode. Main Outcomes and Measures: SARS-CoV-2 infection was confirmed by reverse transcription polymerase chain reaction or by viral genome sequencing results. Attack rates for SARS-CoV-2 infection were calculated for different groups, and the spatial distribution of individuals who developed infection on bus 2 was obtained. Results: Of the 128 participants, 15 (11.7%) were men, 113 (88.3%) were women, and the mean age was 58.6 years. On bus 2, 24 of the 68 individuals (35.3% [including the index patient]) received a diagnosis of COVID-19 after the event. Meanwhile, none of the 60 individuals in bus 1 were infected. Among the other 172 individuals at the worship event, 7 (4.1%) subsequently received a COVID-19 diagnosis. Individuals in bus 2 had a 34.3% (95% CI, 24.1%-46.3%) higher risk of getting COVID-19 compared with those in bus 1 and were 11.4 (95% CI, 5.1-25.4) times more likely to have COVID-19 compared with all other individuals attending the worship event. Within bus 2, individuals in high-risk zones had moderately, but nonsignificantly, higher risk for COVID-19 compared with those in the low-risk zones. The absence of a significantly increased risk in the part of the bus closer to the index case suggested that airborne spread of the virus may at least partially explain the markedly high attack rate observed. Conclusions and Relevance: In this cohort study and case investigation of a community outbreak of COVID-19 in Zhejiang province, individuals who rode a bus to a worship event with a patient with COVID-19 had a higher risk of SARS-CoV-2 infection than individuals who rode another bus to the same event. Airborne spread of SARS-CoV-2 seems likely to have contributed to the high attack rate in the exposed bus. Future efforts at prevention and control must consider the potential for airborne spread of the virus.

A Cluster of Novel Coronavirus Disease 2019 Infections Indicating Person-to-Person Transmission Among Casual Contacts From Social Gatherings: An Outbreak Case-Contact Investigation.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2, the pathogen causing novel coronavirus disease of 2019 (COVID-19), efficiently spreads from person to person in close contact settings. Transmission among casual contacts in settings such as during social gatherings is not well understood. METHODS: We report several transmission events to both close and casual contacts from a cluster of 7 COVID-19 cases occurring from mid-January to early February 2020. A total of 539 social and family contacts of the index patient's, including members of a 2-day wedding and a family party, were contacted and screened through epidemiologic surveys. The clinical progression of all cases is described. RESULTS: We estimate the secondary attack rate among close contacts to be 29% (2 of 7) and for the casual contacts to be 0.6% (3 of 473). The incubation period of our case cluster was 4-12 days (median, 7 days). CONCLUSIONS: Transmission efficiency among close contacts was higher than among casual contacts; however, transmission from second-generation cases may help spread the virus during the incubation period.