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      Transmission heterogeneities, kinetics, and controllability of SARS-CoV-2

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          Time and intimacy drive transmission

          A minority of people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmit most infections. How does this happen? Sun et al. reconstructed transmission in Hunan, China, up to April 2020. Such detailed data can be used to separate out the relative contribution of transmission control measures aimed at isolating individuals relative to population-level distancing measures. The authors found that most of the secondary transmissions could be traced back to a minority of infected individuals, and well over half of transmission occurred in the presymptomatic phase. Furthermore, the duration of exposure to an infected person combined with closeness and number of household contacts constituted the greatest risks for transmission, particularly when lockdown conditions prevailed. These findings could help in the design of infection control policies that have the potential to minimize both virus transmission and economic strain.

          Science, this issue p. eabe2424

          Abstract

          Modeling results indicate that SARS-CoV-2 control requires case isolation, contact quarantine, and population-level interventions.

          Abstract

          INTRODUCTION

          The role of transmission heterogeneities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dynamics remains unclear, particularly those heterogeneities driven by demography, behavior, and interventions. To understand individual heterogeneities and their effect on disease control, we analyze detailed contact-tracing data from Hunan, a province in China adjacent to Hubei and one of the first regions to experience a SARS-CoV-2 outbreak in January to March 2020. The Hunan outbreak was swiftly brought under control by March 2020 through a combination of nonpharmaceutical interventions including population-level mobility restriction (i.e., lockdown), traveler screening, case isolation, contact tracing, and quarantine. In parallel, highly detailed epidemiological information on SARS-CoV-2–infected individuals and their close contacts was collected by the Hunan Provincial Center for Disease Control and Prevention.

          RATIONALE

          Contact-tracing data provide information to reconstruct transmission chains and understand outbreak dynamics. These data can in turn generate valuable intelligence on key epidemiological parameters and risk factors for transmission, which paves the way for more-targeted and cost-effective interventions.

          RESULTS

          On the basis of epidemiological information and exposure diaries on 1178 SARS-CoV-2–infected individuals and their 15,648 close contacts, we developed a series of statistical and computational models to stochastically reconstruct transmission chains, identify risk factors for transmission, and infer the infectiousness profile over the course of a typical infection. We observe overdispersion in the distribution of secondary infections, with 80% of secondary cases traced back to 15% of infections, which indicates substantial transmission heterogeneities. We find that SARS-CoV-2 transmission risk scales positively with the duration of exposure and the closeness of social interactions, with the highest per-contact risk estimated in the household. Lockdown interventions increase transmission risk in families and households, whereas the timely isolation of infected individuals reduces risk across all types of contacts. There is a gradient of increasing susceptibility with age but no significant difference in infectivity by age or clinical severity. Early isolation of SARS-CoV-2–infected individuals drastically alters transmission kinetics, leading to shorter generation and serial intervals and a higher fraction of presymptomatic transmission. After adjusting for the censoring effects of isolation, we find that the infectiousness profile of a typical SARS-CoV-2 patient peaks just before symptom onset, with 53% of transmission occurring in the presymptomatic phase in an uncontrolled setting. We then use these results to evaluate the effectiveness of individual-based strategies (case isolation and contact quarantine) both alone and in combination with population-level contact reductions. We find that a plausible parameter space for SARS-CoV-2 control is restricted to scenarios where interventions are synergistically combined, owing to the particular transmission kinetics of this virus.

          CONCLUSION

          There is considerable heterogeneity in SARS-CoV-2 transmission owing to individual differences in biology and contacts that is modulated by the effects of interventions. We estimate that about half of secondary transmission events occur in the presymptomatic phase of a primary case in uncontrolled outbreaks. Achieving epidemic control requires that isolation and contact-tracing interventions are layered with population-level approaches, such as mask wearing, increased teleworking, and restrictions on large gatherings. Our study also demonstrates the value of conducting high-quality contact-tracing investigations to advance our understanding of the transmission dynamics of an emerging pathogen.

          Transmission chains, contact patterns, and transmission kinetics of SARS-CoV-2 in Hunan, China, based on case and contact-tracing data from Hunan, China.

          (Top left) One realization of the reconstructed transmission chains, with a histogram representing overdispersion in the distribution of secondary infections. (Top right) Contact matrices of community, social, extended family, and household contacts reveal distinct age profiles. (Bottom) Earlier isolation of primary infections shortens the generation and serial intervals while increasing the relative contribution of transmission in the presymptomatic phase.

          Abstract

          A long-standing question in infectious disease dynamics concerns the role of transmission heterogeneities, which are driven by demography, behavior, and interventions. On the basis of detailed patient and contact-tracing data in Hunan, China, we find that 80% of secondary infections traced back to 15% of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) primary infections, which indicates substantial transmission heterogeneities. Transmission risk scales positively with the duration of exposure and the closeness of social interactions and is modulated by demographic and clinical factors. The lockdown period increases transmission risk in the family and households, whereas isolation and quarantine reduce risks across all types of contacts. The reconstructed infectiousness profile of a typical SARS-CoV-2 patient peaks just before symptom presentation. Modeling indicates that SARS-CoV-2 control requires the synergistic efforts of case isolation, contact quarantine, and population-level interventions because of the specific transmission kinetics of this virus.

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          Most cited references53

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          Clinical Characteristics of Coronavirus Disease 2019 in China

          Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)
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            Fitting Linear Mixed-Effects Models Usinglme4

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              Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

              Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
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                Author and article information

                Journal
                Science
                Science
                SCIENCE
                science
                Science (New York, N.y.)
                American Association for the Advancement of Science
                0036-8075
                1095-9203
                15 January 2021
                24 November 2020
                : 371
                : 6526
                : eabe2424
                Affiliations
                [1 ]Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
                [2 ]School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
                [3 ]Hunan Provincial Center for Disease Control and Prevention, Changsha, China.
                [4 ]Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
                [5 ]ISI Foundation, Turin, Italy.
                [6 ]Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA, USA.
                Author notes
                [* ]Corresponding author. Email: kaiyuan.sun@ 123456nih.gov (K.S.); yhj@ 123456fudan.edu.cn (H.Y.)
                [†]

                These authors contributed equally to this work.

                [‡]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-1753-9884
                https://orcid.org/0000-0003-4056-3732
                https://orcid.org/0000-0003-0387-4451
                https://orcid.org/0000-0002-5620-2328
                https://orcid.org/0000-0001-6393-1943
                https://orcid.org/0000-0003-3419-4205
                https://orcid.org/0000-0003-1753-4749
                https://orcid.org/0000-0003-3243-4711
                https://orcid.org/0000-0002-6335-5648
                Article
                abe2424
                10.1126/science.abe2424
                7857413
                33234698
                c0b8b63c-a177-408e-9570-0639984c4503
                Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 09 August 2020
                : 19 November 2020
                Funding
                Funded by: doi http://dx.doi.org/10.13039/501100014219, National Science Fund for Distinguished Young Scholars;
                Award ID: 81525023
                Funded by: National Science and Technology Major Project of China;
                Award ID: 2018ZX10201001–010
                Funded by: National Science and Technology Major Project of China;
                Award ID: 2018ZX10713001–007
                Funded by: National Science and Technology Major Project of China;
                Award ID: 2017ZX10103009–005
                Funded by: Hunan Provincial Innovative Construction Special Fund: Emergency response to COVID-19 outbreak;
                Award ID: 2020SK3012
                Categories
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                Epidemiology
                Medicine
                Online
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