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Open accessJournal ArticleDOI: 10.1073/PNAS.2019716118

Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity.

02 Mar 2021-Proceedings of the National Academy of Sciences of the United States of America (Proceedings of the National Academy of Sciences)-Vol. 118, Iss: 9
Abstract: The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered.

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Topics: Asymptomatic (53%), Force of infection (50%)
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Open accessJournal ArticleDOI: 10.1503/CMAJ.210100
Abstract: [See related article at [www.cmaj.ca/lookup/doi/10.1503/cmaj.202827][2]][2] KEY POINTS Jurisdictions across Canada have been trying to combat a second wave of the coronavirus disease 2019 (COVID-19) pandemic without using all the available tools. Accumulating evidence has shown that people who are

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Topics: Mass screening (56%)

10 Citations


Open accessJournal ArticleDOI: 10.1038/S41598-021-83697-W
22 Feb 2021-Scientific Reports
Abstract: COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that is amenable to implementation in Excel spreadsheets and sufficiently accurate to reproduce observed data on the evolution of the COVID-19 pandemics in different regions [i.e., New York City (NYC), South Korea, Mexico City]. We show that the model can be adapted to closely follow the evolution of COVID-19 in any large city by simply adjusting parameters related to demographic conditions and aggressiveness of the response from a society/government to epidemics. Moreover, we show that this simple epidemiological simulator can be used to assess the efficacy of the response of a government/society to an outbreak. The simplicity and accuracy of this model will greatly contribute to democratizing the availability of knowledge in societies regarding the extent of an epidemic event and the efficacy of a governmental response.

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9 Citations


Open accessJournal ArticleDOI: 10.3390/IDR13020033
Brett Snider1, Bhumi Patel1, Edward A. McBean1Institutions (1)
Abstract: The numbers of novel coronavirus cases continue to grow at an unprecedented rate across the world. Attempts to control the growth of the virus using masks and social-distancing, and, recently, double-masking as well, continue to be difficult to maintain, in part due to the extent of asymptomatic cases. Analyses of large datasets consisting of 219,075 individual cases in Ontario, indicated that asymptomatic and pre-symptomatic cases are substantial in number. Large numbers of cases in children aged 0-9 were asymptomatic or had only one symptom (35.0% and 31.4% of total cases, respectively) and resulted in fever as the most common symptom (30.6% of total cases). COVID-19 cases in children were more likely to be milder symptomatic with cough not seen as frequently as in adults aged over 40, and past research has shown children to be index cases in familial clusters. These findings highlight the importance of targeting asymptomatic and mild infections in the continuing effort to control the spread of COVID-19. The Pearson correlation coefficient between test positivity rates and asymptomatic rates of -0.729 indicates that estimates of the asymptomatic rates should be obtained when the test positivity rates are lowest as the best approach.

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Topics: Asymptomatic (58%)

6 Citations


Open accessPosted ContentDOI: 10.1101/2020.12.22.20248622
22 Dec 2020-medRxiv
Abstract: Social distancing is an effective population-level mitigation strategy to prevent COVID19 propagation but it does not reduce the number of susceptible individuals and bears severe economic and psychological consequences. A vaccine has recently been developed but its deployment will be limited and not immediate. Designing an optimal combination of these two intervention strategies is a priority, but a mechanistic understanding of the interplay between these strategies is missing. To tackle this challenge we developed an age-structured deterministic model in which vaccines are deployed during the pandemic to individuals who, in the eye of public health, are susceptible (do not show symptoms). The model allows for flexible and dynamic prioritization strategies with shifts between target groups. We find that social distancing applied uniformly to all ages and with vaccination targeted towards adults (20-59) or elderly (60+) work in synergism but up to a threshold beyond which vaccination is not efficient. The inefficiency threshold can be eliminated by targeting social distancing at the age groups that are not vaccinated and the optimal strategy is to prioritize vaccines to elderly. Nevertheless, while vaccination reduces hospitalizations, it does not affect the time it takes to eliminate the virus from the population, which is affected only by social distancing. Finally, the same reduction in hospitalization can be achieved via different combination of strategies, giving decision makers flexibility in choosing public health policies. Our study provides insights into the factors that affect vaccination success and provides methodology to test different intervention strategies in a way that will align with ethical guidelines.

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Topics: Population (52%)

5 Citations


Open accessJournal ArticleDOI: 10.3390/IJMS22073773
Abstract: On 11 March 2020, the World Health Organization announced the Corona Virus Disease-2019 (COVID-19) as a global pandemic, which originated in China. At the host level, COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), affects the respiratory system, with the clinical symptoms ranging from mild to severe or critical illness that often requires hospitalization and oxygen support. There is no specific therapy for COVID-19, as is the case for any common viral disease except drugs to reduce the viral load and alleviate the inflammatory symptoms. Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (Mtb), also primarily affects the lungs and has clinical signs similar to pulmonary SARS-CoV-2 infection. Active TB is a leading killer among infectious diseases and adds to the burden of the COVID-19 pandemic worldwide. In immunocompetent individuals, primary Mtb infection can also lead to a non-progressive, asymptomatic latency. However, latent Mtb infection (LTBI) can reactivate symptomatic TB disease upon host immune-suppressing conditions. Importantly, the diagnosis and treatment of TB are hampered and admixed with COVID-19 control measures. The US-Center for Disease Control (US-CDC) recommends using antiviral drugs, Remdesivir or corticosteroid (CST), such as dexamethasone either alone or in-combination with specific recommendations for COVID-19 patients requiring hospitalization or oxygen support. However, CSTs can cause immunosuppression, besides their anti-inflammatory properties. The altered host immunity during COVID-19, combined with CST therapy, poses a significant risk for new secondary infections and/or reactivation of existing quiescent infections, such as LTBI. This review highlights CST therapy recommendations for COVID-19, various types and mechanisms of action of CSTs, the deadly combination of two respiratory infectious diseases COVID-19 and TB. It also discusses the importance of screening for LTBI to prevent TB reactivation during corticosteroid therapy for COVID-19.

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Topics: Tuberculosis (59%), Secondary infection (54%), Disease (54%) ... show more

5 Citations


References
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69 results found


Open accessBook
11 Jul 1991-
Abstract: Part 1 Microparasites: biology of host-microparasite associations the basic model - statics static aspects of eradication and control the basic model - dynamics dynamic aspects of eradication and control beyond the basic model - empirical evidence of inhomogeneous mixing age-related transmission rates genetic heterogeneity social heterogeneity and sexually transmitted diseases spatial and other kinds of heterogeneity endemic infections in developing countries indirectly transmitted microparasites. Part 2 Macroparasites: biology of host-macroparasite associations the basic model - statics the basic model - dynamics acquired immunity heterogeneity within the human community indirectly transmitted helminths experimental epidemiology parasites, genetic variability, and drug resistance the ecology and genetics of host-parasite associations.

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7,668 Citations


Open accessJournal ArticleDOI: 10.1016/S1473-3099(20)30120-1
Ensheng Dong1, Hongru Du1, Lauren Gardner1Institutions (1)
Abstract: The outbreak of the 2019 novel coronavirus disease (COVID-19) has induced a considerable degree of fear, emotional stress and anxiety among individuals around t

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Topics: Dashboard (business) (62%), Web application (53%)

5,397 Citations


Open accessJournal ArticleDOI: 10.1001/JAMA.2020.6775
26 May 2020-JAMA
Abstract: Importance There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19). Objective To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system. Design, Setting, and Participants Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system. The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates. Exposures Confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission. Main Outcomes and Measures Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected. Results A total of 5700 patients were included (median age, 63 years [interquartile range {IQR}, 52-75; range, 0-107 years]; 39.7% female). The most common comorbidities were hypertension (3026; 56.6%), obesity (1737; 41.7%), and diabetes (1808; 33.8%). At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/min, and 27.8% received supplemental oxygen. The rate of respiratory virus co-infection was 2.1%. Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2%) (median age, 68 years [IQR, 56-78]; 33.5% female) were treated in the intensive care unit care, 320 (12.2%) received invasive mechanical ventilation, 81 (3.2%) were treated with kidney replacement therapy, and 553 (21%) died. As of April 4, 2020, for patients requiring mechanical ventilation (n = 1151, 20.2%), 38 (3.3%) were discharged alive, 282 (24.5%) died, and 831 (72.2%) remained in hospital. The median postdischarge follow-up time was 4.4 days (IQR, 2.2-9.3). A total of 45 patients (2.2%) were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0-4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow-up date (median age, 65 years [IQR, 54-75]), the median follow-up at time of censoring was 4.5 days (IQR, 2.4-8.1). Conclusions and Relevance This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID-19 in the New York City area.

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Topics: Interquartile range (55%), Respiratory virus (51%)

5,140 Citations


Open accessJournal ArticleDOI: 10.7326/M20-0504
Stephen A. Lauer1, Kyra H. Grantz1, Qifang Bi1, Forrest K. Jones1  +5 moreInstitutions (2)
Abstract: Using news reports and press releases from provinces, regions, and countries outside Wuhan, Hubei province, China, this analysis estimates the length of the incubation period of COVID-19 and its pu...

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3,940 Citations


Open accessJournal ArticleDOI: 10.1126/SCIENCE.ABB3221
Ruiyun Li1, Sen Pei2, Bin Chen3, Yimeng Song4  +3 moreInstitutions (5)
16 Mar 2020-Science
Abstract: Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82–90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46–62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.

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2,669 Citations


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