Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 18, 2026.

Incubation Period of COVID-19 Caused by Unique SARS-CoV-2 Strains

Yu Wu, Liangyu Kang, Zirui Guo and 3 more

JAMA Network Open · 2022 · Meta-analysis

doi:10.1001/jamanetworkopen.2022.28008

Abstract

Question. What are the incubation periods of COVID-19 caused by different SARS-CoV-2 strains?

Findings. In this systematic review and meta-analysis of 141 articles, the pooled incubation period was 6.57 days. The incubation periods of COVID-19 caused by the Alpha, Beta, Delta, and Omicron variants were 5.00, 4.50, 4.41, and 3.42 days, respectively.

Meaning. These results suggest that with the evolution of mutant strains, the incubation period of COVID-19 decreased gradually from Alpha variant to Omicron variant.

Importance. Several studies were conducted to estimate the average incubation period of COVID-19; however, the incubation period of COVID-19 caused by different SARS-CoV-2 variants is not well described.

Objective. To systematically assess the incubation period of COVID-19 and the incubation periods of COVID-19 caused by different SARS-CoV-2 variants in published studies.

Data Sources. PubMed, EMBASE, and ScienceDirect were searched between December 1, 2019, and February 10, 2022.

Study Selection. Original studies of the incubation period of COVID-19, defined as the time from infection to the onset of signs and symptoms.

Data Extraction and Synthesis. Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline, 3 reviewers independently extracted the data from the eligible studies in March 2022. The parameters, or sufficient information to facilitate calculation of those values, were derived from random-effects meta-analysis.

Main Outcomes and Measures. The mean estimate of the incubation period and different SARS-CoV-2 strains.

Results. A total of 142 studies with 8112 patients were included. The pooled incubation period was 6.57 days (95% CI, 6.26-6.88) and ranged from 1.80 to 18.87 days. The incubation period of COVID-19 caused by the Alpha, Beta, Delta, and Omicron variants were reported in 1 study (with 6374 patients), 1 study (10 patients), 6 studies (2368 patients) and 5 studies (829 patients), respectively. The mean incubation period of COVID-19 was 5.00 days (95% CI, 4.94-5.06 days) for cases caused by the Alpha variant, 4.50 days (95% CI, 1.83-7.17 days) for the Beta variant, 4.41 days (95% CI, 3.76-5.05 days) for the Delta variant, and 3.42 days (95% CI, 2.88-3.96 days) for the Omicron variant. The mean incubation was 7.43 days (95% CI, 5.75-9.11 days) among older patients (ie, aged over 60 years old), 8.82 days (95% CI, 8.19-9.45 days) among infected children (ages 18 years or younger), 6.99 days (95% CI, 6.07-7.92 days) among patients with nonsevere illness, and 6.69 days (95% CI, 4.53-8.85 days) among patients with severe illness.

Conclusions and Relevance. The findings of this study suggest that SARS-CoV-2 has evolved and mutated continuously throughout the COVID-19 pandemic, producing variants with different enhanced transmission and virulence. Identifying the incubation period of different variants is a key factor in determining the isolation period.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 18, 2026. Paragraph numbers are ours, so an answer can point at one.

Introduction

In December 2019, multiple cases of novel coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were reported in Wuhan, China. On March 11, 2020, the World Health Organization (WHO) declared that COVID-19 can be characterized as a pandemic. To date, the transmission of COVID-19 is still difficult to contain, as confirmed and death cases are still increasing. Up to March 16, 2022, 460 280 168 confirmed cases and 6 050 018 confirmed deaths have been reported to the WHO. Rapid spread of COVID-19 has had enormous social, economic, and health care system effects around the world. Effective treatment to block the spread of COVID-19 is not developed yet, so countries have implemented a series of nontreatment interventions such as social distancing, isolation, face mask mandates, and quarantining to reduce its rapid transmission. Existing evidence has shown that most of COVID-19 cases are missed by screening because infected persons are unaware they were exposed and have not developed symptoms yet.,,

Incubation period is one of the most important epidemiological parameters of infectious diseases. Knowledge of the disease’s incubation period is of great significance for case definition, management of emerging threats, estimation of the duration of follow-up for contact tracing and secondary case detection, and the establishment of public health programs aimed at reducing local transmission. Previous studies have reported that the average serial interval of COVID-19 is shorter than the average incubation period, which suggests a substantial proportion of presymptomatic transmission. For diseases caused by different pathogens, the length of incubation period is the key factor to determine the isolation period of infected persons.

Since the beginning of the COVID-19 epidemic, SARS-CoV-2 has evolved and mutated continuously, producing variants with different transmissibility and virulence. SARS-CoV-2 variants are classified by the WHO into 2 types: variants of concern (VOC) and variants of interest (VOI). According to the US Center for Disease Control and Prevention (CDC), a VOC is a variant that has increased transmissibility, increased virulence, a resistance to vaccine or acquired immunity from previous infection, and has the ability to elude diagnostic detection. Several VOC have emerged from the original wild-type strain isolated in Wuhan since the outbreak first began in December 2019, such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (B.1.1.529). The Alpha variant was first detected in the UK in September 2020; the Beta variant in South Africa in May 2020; and the Gamma variant in Brazil in September 2020. All 3 quickly became the main virus strains worldwide.

Globally, many studies were conducted to estimate the average incubation period of COVID-19. However, the reported estimates of incubation period in these fragmented studies vary depending on the number of study participants recruited, the type of design employed, the data collection period, and the country in which the study was conducted. In addition, with the spread of the Delta and Omicron variants, the current incubation period of COVID-19 is different from that in the outbreak of Wuhan. This meta-analysis was aimed to determine the overall pooled incubation period of COVID-19 and the incubation period of COVID-19 caused by different SARS-CoV-2 variants using available evidence, so as to adjust prevention and control strategies and better block the transmission of COVID-19.

Search Strategy

We conducted this meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. This review was not registered. This study was exempted from ethics review board at Peking University because it used previously published literature in its analysis. A survey of the literature was implemented between December 1, 2019, and February 10, 2022. Publications on the electronic databases PubMed, Embase and ScienceDirect were searched using the keywords novel coronavirus, SARS-CoV-2, 2019-nCoV, or COVID-19 and either incubation period or incubation (eTable 1 in the Supplement). No restrictions on language or publication status were imposed so long as an English abstract was available. The initial searches were carried out by 3 of the investigators (Y.W., L.K., R.G.).

Inclusion and Exclusion Criteria

Inclusion criteria for selecting the studies were that the incubation period was one of the primary outcomes of the study and that, when the incubation periods of multiple groups were reported in the same study, only the group with the largest study population was included. Criteria for exclusion included articles not conducted as studies (ie, editorials, perspective articles, letters to the editor, reviews, article information, or comments), duplicate studies, and articles with overlapping study populations (ie, enrolling the same population in the same region around the same period).

Outcome Measures and Study Selection

The outcome variable was the mean estimate of the incubation period. Incubation period was defined as the time from when the infection occurred to the onset of signs and symptoms or the first positive test. It was measured with cases of a well-defined period of exposure and symptom onset.

Results of searches were screened in 2 stages. First, titles and abstracts were screened and only relevant articles retained. Next, articles were read in detail—studies were selected for meta-analysis if they reported either results fitting our primary parameters (with CIs) or sufficient information to facilitate calculation of those values.

After screening for inclusion and exclusion criteria, data extraction was carried out from the included studies. The name of the first author, area of study, time period for data collection, characteristics of the study population, strain type, and estimates for the incubation period with 95% CI were extracted from the selected studies. Ninety-five percent CIs were estimated for the studies reporting mean with standard deviation by using the following formula, which is generally used to calculate the 95% CI for any parameter:

where μ indicates the mean incubation period, s the standard deviation, and n the sample size of the study. Some studies reported only median with interquartile range or range. Mean and the standard deviation were calculated for such studies by using an appropriate approximation for the consistency in synthesizing the results for meta-analysis.,

Quality Assessment

Once studies were shortlisted, 2 authors (Y.W., L.K.) independently conducted appraisals of study quality. We used a scale modified from the Newcastle-Ottawa scale by McAloon et al to assess the quality of observational studies in meta-analyses (eTable 2 in the Supplement). This scale consists of 2 parts with a full score of 5 stars. The first part is external validity, with a maximum of 1 star; the second part is internal validity, which includes exposure window (a maximum of 2 stars) and outcomes with (a maximum of 2 stars). Based on the combined score of these 2 parts, each paper was categorized as either weak (1 star or less), moderate (2 to 3 stars), or strong (4 stars or more). After the studies were evaluated by the 2 authors, the results were compared and differences in ratings were resolved by discussion until a consensus rating was agreed upon.

Statistical Analysis

A meta-analysis of continuous outcomes was employed for this study. We analyzed the data sets for the incubation period. After extracting all essential data using Excel 2021 (Microsoft Corporation), data were exported to Stata version 14.1 (StataCorp) statistical software for meta-analysis. A random-effect meta-analysis with an estimation of DerSimonian and Laird method was performed. Pooled mean estimates with 95% CIs were presented using forest plots. To determine the extent of variation between the studies, we conducted a heterogeneity test using the Higgins method, that was quantified by I2 value. Publication bias was also assessed using a funnel plot. A 2-sided P <.05 was considered statistically significant.

Search Results

We identified 5012 records through PubMed, EMBASE, and Science Direct database searches, and documented the study selection process in a flowchart and showed the total numbers of retrieved references and the numbers of included and excluded studies (Figure 1). Based on the inclusion and exclusion criteria, 142 articles (8112 patients) were selected for analysis.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,

Study Characteristics

Over the 142 studies, the quality assessment gave 45 strong, 82 moderate, and 15 weak studies (eTable 3 in the Supplement). Most of the studies (93 [65.5%]) were conducted between January and March 2020 and most were conducted in China (108 [76.1%]). One study used case data from multiple countries around the world, 6 studies were conducted in South Korea,,,,,, 4 in France,,,, 3 in Japan,, 2 in Singapore,, 2 in India,,,, 2 in Vietnam,, and 2 in Australia., One hundred nineteen studies (83.8%) included patients infected with the wild-type strain, 5 (3.5%) with the multiple strains,,,,, and 11 (7.7%) with an unknown strain,,,,,,,,,, (eTable 4 in the Supplement).

Pooled Average Estimate of Incubation Period

The mean incubation period of COVID-19 was 6.57 days (95% CI, 6.26-6.88 days), ranging from 1.80 to 18.87 days (Table). There was substantial heterogeneity between the studies (I2 = 98.8%; P <.001). Our results suggested no potential publication bias in the included studies (eFigure 1 in the Supplement). The standard error for all the included studies in the meta-analysis was very low except for a 2020 study conducted by Xie where the highest standard error was observed.

Mean Incubation Periods of COVID-19 Infected by Different Strains

Across a total of 119 studies with data on the wild-type strain, the mean incubation period was 6.65 days (95% CI, 6.31-6.99) (eFigure 2 in the Supplement). For infections caused by the Alpha variant, an incubation period of 5.00 days (95% CI, 4.94-5.06) was reported in a single study. One study from France reported the incubation period of 4.50 days (95% CI, 1.83-7.17 days) for COVID-19 caused by the Beta variant. Another study reported the incubation period of COVID-19 caused by the Beta/Gamma variant was 5.10 days (95% CI, 4.87-5.33 days).

A total of 6 studies reported the incubation period of COVID-19 caused by the Delta variant, including 2 from China,, 2 from Japan,, 1 from France, and 1 from Spain, with a pooled incubation period of 4.41 days (95% CI, 3.76-5.05 days) (Figure 2). Five studies reported the incubation period of COVID-19 caused by the Omicron variant—1 each from Norway, Spain, Japan, the Netherlands, and South Korea—with a pooled incubation period of 3.42 days (95% CI, 2.88-3.96 days) (Figure 2). With the evolution of the mutant strains, the incubation period of COVID-19 appeared to decrease gradually from the Alpha variant to Omicron variant, but there was no significant difference between the groups.

Subgroup Analysis

A total of 8 studies reported the incubation period of COVID-19 among older patients (ie, aged 60 years or more).,,,,,,, The pooled mean incubation period for these studies was 7.43 days (95% CI, 5.75-9.11 days), which was slightly higher than the pooled incubation period of the general population (6.65 days; 95% CI, 6.34-6.96 days), but the difference was not significant (Figure 3).

The mean incubation period of COVID-19 among infected children (under ages 18 years) was 8.82 days (95% CI, 8.19-9.45 days) across 8 studies,,,,,,,, which was higher than the pooled incubation period of the general population (6.65 days; 95% CI, 6.34-6.96 days), and the difference was significant (P <.001) (Figure 3).

Five studies reported the incubation period in patients with nonsevere illness,,,,, with a pooled value of 6.99 days (95% CI, 6.07-7.92 days). Five studies analyzed the incubation period of patients with severe disease,,,,, with a pooled value of 6.69 days (95% CI, 4.53-8.85 days), which was slightly shorter than that of patients with nonsevere illness, but the difference was not significant (Figure 4).

Discussion

Our findings suggested that COVID-19 had a mean incubation period of 6.57 days (95% CI, 6.26-6.88 days), which was similar to the results of Elias et al (6.38 days; 95% CI, 5.79-6.97 days) and McAloon et al (6.5 days, 95% CI, 5.9-7.1 days). COVID-19 seemed to have a longer incubation period than that of other acute respiratory viral infections such as human coronavirus (3.2 days), influenza A (1.43-1.64 days), parainfluenza (2.6 days), respiratory syncytial virus (4.4 days), and rhinovirus (1.4 days). Furthermore, the median incubation period for SARS in 2009 had been estimated as 4.0 days, which was lower than COVID-19. In this study, the shortest mean incubation reported was 1.8 days and the longest incubation was 18.87 days. At present, based on the assumption that the incubation period of COVID-19 is 1 to 14 days, the WHO still recommends that COVID-19 close contacts be isolated for 14 days.

Our study found that the incubation period of COVID-19 caused by Alpha variant was 5.00 days (95% CI, 4.94-5.06 days), and the incubation period of COVID-19 caused by Beta variant was 4.50 days (95% CI, 1.83-7.17 days), which were similar to that of the wild-type strain in Wuhan, China (5.2 days).,

The Delta variant, which was first reported in India in October 2020, was dominant in the second wave of COVID-19 outbreak in India in May 2021. Our study revealed that the incubation period of COVID-19 caused by Delta variant was 4.41 days (95% CI, 3.76-5.05), which was shorter than the pooled incubation period of COVID-19 (6.26 days), and also shorter than that caused by Alpha variant and Beta variants.

On November 24, 2021, South Africa first discovered and reported a case of Omicron variant infection to the WHO. Since then, this variant has quickly become the main virus strain in South Africa and spread to many countries and regions around the world. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, which have been predicted to influence antibody neutralization and spike function. Our study revealed that the incubation period of COVID-19 caused by Omicron variant was 3.42 days (95% CI, 2.88-3.96 days), which was shorter than the Alpha, Beta, and Delta variants. The CDC released new quarantine and isolation policy on March 30, 2022, which stated that people exposed to COVID-19 should stay home and away from other people for at least 5 days. At present, some countries around the world require close contacts to be isolated for 14 days. However, with the shortening of the incubation period of new variants, the isolation period can be adjusted appropriately to reduce the pressure on the health system.

Eight studies reported the incubation period among older patients (ages 60 years and older), and the mean incubation period of older patients was about 7.43 days (95% CI, 5.75-9.11), which was slightly higher than the pooled incubation period among the general population. Although the difference between the incubation periods of older patients and the overall incubation period was not significant, there was still a lot of evidence to support the hypothesis of a longer incubation period in older populations due to a slower immune response among older patients. Cowling et al hypothesized about this in their report on SARS in 2007, where they demonstrated that older patients had longer incubation periods, suggesting that this might have resulted from a delayed immune response. A study by Chen et al revealed that several SARS-CoV nonstructural proteins that were shared by SARS-CoV-2 suppress the type 1 interferon response, and such suppression was shown to lead to poor CD8+ T-cell response to viral infection. Therefore, age-associated weaker type 1 interferon responses coupled with direct viral suppression could serve as a critical innate immune mechanism that leads to poor cell-mediated immunity and increased vulnerability of older adults to SARS-CoV-2 infection with therapeutic implication. Additionally, older patients were more likely to experience symptom minimization and be more likely to ignore early symptoms and only report later when symptoms become more severe or intolerable. The lack of a fever response in older patients, the nonspecific geriatric presentations in an infectious illness (such as falls and delirium), and multi-comorbidities might result in a delayed awareness of disease onset and its detection by a clinician.

Additionally, our study also revealed that the mean incubation period for infected children (8.82 days; 95% CI, 8.19-9.45) was also shorter than the pooled incubation period among the general population (6.65 days). Infected children tend to present with mild clinical symptoms without the classic phenotype of lung pneumonia, and COVID-19 symptoms are easily confused with other influenza-like illnesses, which renders infected children difficult to identify. Second, previous studies found that children can be a source of transmission during the viral incubation period. Some infected children may have an incubation period of more than 14 days. Indeed, it is difficult for investigators to collect information about the symptoms of very young children because they cannot accurately express their symptoms.

Previous studies on SARS indicated that the incubation period of patients was related to the severity of the disease, and the incubation period of fatal cases was shorter. Virlogeux et al also found that Middle East Respiratory Syndrome patients with a shorter incubation period proceeded to have more severe disease. However, there are few studies on the association between the length of COVID-19 incubation period and the severity of infection. Our study found that the incubation period of COVID-19 in patients with severe illness was shorter (6.69 days) than patients with nonsevere illness. Studies have indicated that shorter incubation periods are associated with more serious disease, and this is related to the number of cells initially infected by the virus.

This study was the first meta-analysis of the incubation period of COVID-19 caused by SARS-CoV-2 variants. We compared the incubation period of COVID-19 caused by different variants and the wild-type strain, and the results may be helpful in changing public health guidance on duration of quarantine, outbreak investigation, and contact tracing.

Limitations

This study had several limitations. First, by definition, the required case data for the determination of individual incubation periods need to include both exposure (window) and onset of symptoms. In most studies, the data were collected retrospectively, resulting in a recall bias (uncertain exact dates of exposure) that would inevitably influence our assessment. Second, the estimate of the incubation period was computed with data with considerable heterogeneity. Possible sources of heterogeneity included difference in study population, data collection period, and method of analysis. Wild-type strain studies were mostly from Chinese patients; while variants studies were not. Population factors, especially those related to public policy and social behavior, may be confounding variables. In this study, we assumed that the incubation period was consistent across populations. Third, there were few studies on the incubation period of COVID-19 caused by SARS-CoV-2 variants. Because of the urgent timeline for data extraction and analysis, these studies have estimated the incubation period in a limited case number in a short period of time, which necessitates the cautious interpretation of the generalizability of our findings. The numbers were too small to detect systematic differences in incubation time in regards to age or sex.

Conclusions

Although variants such as Alpha, Beta, and Gamma are currently only prevalent in a few countries in Southeast Asia, South America, and Africa, the Delta and Omicron variants have become the dominant strains in many countries around the world. Identifying the incubation period of different variants is a key factor in determining the isolation period. The pooled incubation period of COVID-19 in this study was 6.57 days. The incubation period for COVID-19 caused by the Alpha and Beta variants was approximately 5 days. The incubation period of COVID-19 caused by the Delta and Omicron variants was significantly shorter than that of the other variants.

References 167

  1. 1.

    Guan W-J, Ni Z-Y, Hu Y,; China Medical Treatment Expert Group for Covid-19. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708-1720

    Not in our library10.1056/nejmoa2002032

  2. 2.

    World Health Organization. Coronavirus (COVID-19) Dashboard. 2022; https://covid19.who.int/.

    Not in our library

  3. 3.

    Sanders JM, Monogue ML, Jodlowski TZ, Cutrell JB. Pharmacologic treatments for coronavirus disease 2019 (COVID-19): a review. JAMA. 2020;323(18):1824-1836

    Not in our library10.1001/jama.2020.6019

  4. 4.
  5. 5.

    Tawe Ngi AM, Johnston S, Albayat SS,. Pre-symptomatic and asymptomatic transmission of COVID-19: Implications for control measures in Qatar. Qatar Med J. 2021;2021(3):59-59.

    Not in our library10.5339/qmj.2021.59

  6. 6.
  7. 7.

    Nishiura H, Mizumoto K, Ejima K, Zhong Y, Cowling B, Omori R. Incubation period as part of the case definition of severe respiratory illness caused by a novel coronavirus. Euro Surveill. 2012;17(42):20296.

    Not in our library

  8. 8.
  9. 9.

    World Health Organization. Tracking SARS-CoV-2 variants. Updated July 19, 2022. Accessed April 17, 2022. https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/

    Not in our library

  10. 10.

    US Centers for Disease Control and Prevention. SARS-CoV-2 Variant Classifications and Definitions. Updated April 26, 2021. Accessed April 17, 2022. https://www.cdc.gov/coronavirus/2019-ncov/variants/variant-classifications.html#anchor_1632158885160

    Not in our library

  11. 11.
  12. 12.
  13. 13.

    Wells G, Shea B, O’Connell D,. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Published 2021. Accessed April 17, 2022. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp

    Not in our library

  14. 14.

    McAloon C, Collins Á, Hunt K,. Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research. BMJ Open. 2020;10(8):e039652-e039652

    Not in our library10.1136/bmjopen-2020-039652

  15. 15.

    Melsen WG, Bootsma MC, Rovers MM, Bonten MJ. The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses. Clin Microbiol Infect. 2014;20(2):123-129

    Not in our library10.1111/1469-0691.12494

  16. 16.

    Areekal B, Vijayan SM, Suseela MS. Risk factors, epidemiological and clinical outcome of close contacts of COVID-19 cases in a tertiary hospital in southern India. J Clin Diagn Res. 2021;15(3):LC34-LC37.

    Not in our library

  17. 17.
  18. 18.
  19. 19.

    Bao C, Pan E, Ai J,. COVID-19 outbreak following a single patient exposure at an entertainment site: an epidemiological study. Transbound Emerg Dis. 2021;68(2):773-781

    Not in our library10.1111/tbed.13742

  20. 20.
  21. 21.
  22. 22.

    Chen G, Wu MZ, Qin CJ,. Epidemiological analysis of 18 patients with COVID-19. Eur Rev Med Pharmacol Sci. 2020;24(23):12522-12526.

    Not in our library10.26355/eurrev_202012_24049

  23. 23.

    Zhang W; Covid-Epidemiology Investigation Team; Laboratory Testing Team. Local outbreak of COVID-19 in Shunyi District attributed to an asymptomatic carrier with a history of stay in Indonesia—Beijing municipality, China, December 23, 2020. China CDC Wkly. 2021;3(10):214-217

    Not in our library10.46234/ccdcw2020.062

  24. 24.

    Dai J, Yang L, Zhao J. Probable longer incubation period for elderly COVID-19 cases: analysis of 180 contact tracing data in Hubei Province, China. Risk Manag Healthc Policy. 2020;13:1111-1117

    Not in our library10.2147/rmhp.s257907

  25. 25.

    de Laval F, Grosset-Janin A, Delon F,. Lessons learned from the investigation of a COVID-19 cluster in Creil, France: effectiveness of targeting symptomatic cases and conducting contact tracing around them. BMC Infect Dis. 2021;21(1):457-457

    Not in our library10.1186/s12879-021-06166-9

  26. 26.

    Del Águila-Mejía J, Wallmann R, Calvo-Montes J, Rodríguez-Lozano J, Valle-Madrazo T, Aginagalde-Llorente A. Secondary attack rate, transmission and incubation periods, and serial interval of SARS-CoV-2 Omicron variant, Spain. Emerg Infect Dis. 2022;28(6):1224-1228

    Not in our library10.3201/eid2806.220158

  27. 27.

    Deng L, Li Z, Liu Y,. Epidemiological and clinical findings of discharge patients infected with the 2019 novel coronavirus (SARS-CoV-2) in Changchun, Northeast China: a retrospective cohort study. Acta Med Mediter. 2021;37(2):1147-1153.

    Not in our library

  28. 28.

    Deng Y, You C, Liu Y, Qin J, Zhou X-H. Estimation of incubation period and generation time based on observed length-biased epidemic cohort with censoring for COVID-19 outbreak in China. Biometrics. 2021;77(3):929-941

    Not in our library10.1111/biom.13325

  29. 29.

    Denis F, Septans AL, Le Goff F, Jeanneau S, Lescure FX. Analysis of COVID-19 transmission sources in France by self-assessment before and after the partial lockdown: observational study. J Med Internet Res. 2021;23(5):e26932

    Not in our library10.2196/26932

  30. 30.

    Ding K, Yi B, Chen Y,. Epidemic cluster of novel coronavirus disease 2019 in Ningbo city of Zhejiang province. Article in Chinese. Chin J Publ Health. 2020;36(04):498-502.

    Not in our library

  31. 31.

    Dong XC, Li JM, Bai JY,. [Epidemiological characteristics of confirmed COVID-19 cases in Tianjin]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(5):638-641.

    Not in our library10.3760/cma.j.cn112338-20200221-00146

  32. 32.

    Du ZC, Gu J, Li JH,. [Estimating the distribution of COVID-19 incubation period by interval-censored data estimation method]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(7):1000-1003.

    Not in our library10.3760/cma.j.cn112338-20200313-00331

  33. 33.

    Gao Y, Hou L, Li Y,. Epidemiological investigation and analysis of 137 confirmed cases of COVID-19. Article in Chinese. Chinese Journal of Critical Care Medicine. 2020;40(03):232-236.

    Not in our library

  34. 34.

    Gao Y, Ma X, Bi J,. Epidemiological and clinical differences of coronavirus disease 2019 patients with distinct viral exposure history. Virulence. 2020;11(1):1015-1023

    Not in our library10.1080/21505594.2020.1802870

  35. 35.
  36. 36.
  37. 37.
  38. 38.

    Han T, Hua L, He S,. The epidemiological characteristics of cluster transmission of coronavirus disease 2019 (COVID-19): a multi-center study in Jiangsu Province. Am J Transl Res. 2020;12(10):6434-6444.

    Not in our library

  39. 39.

    Han YN, Feng ZW, Sun LN,. A comparative-descriptive analysis of clinical characteristics in 2019-coronavirus-infected children and adults. J Med Virol. 2020;92(9):1596-1602

    Not in our library10.1002/jmv.25835

  40. 40.

    Hong H, Shi HB, Jiang HB,. [Epidemic dynamic model based evaluation of effectiveness of prevention and control strategies for COVID-19 in Ningbo]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(10):1606-1610.

    Not in our library10.3760/cma.j.cn112338-20200311-00313

  41. 41.

    Hua C-Z, Miao Z-P, Zheng J-S,. Epidemiological features and viral shedding in children with SARS-CoV-2 infection. J Med Virol. 2020;92(11):2804-2812

    Not in our library10.1002/jmv.26180

  42. 42.

    Huang J, Zhao Q, Xu K,. Analysis of COVID-19 epidemic characteristics based on network data. Article in Chinese. Chinese Journal of Disease Control & Prevention. 2020;24(11):1338.

    Not in our library

  43. 43.

    Huang L, Zhang X, Xu A. Effectiveness of interventions as part of the One Health approach to control coronavirus disease 2019 and stratified case features in Anhui Province, China: a real-world population-based cohort study. One Health. 2021;12:100224-100224

    Not in our library10.1016/j.onehlt.2021.100224

  44. 44.

    Huang S, Li J, Dai C,. Incubation period of coronavirus disease 2019: new implications for intervention and control. Int J Environ Health Res. 2021;32(8):1707-1715.

    Not in our library10.1080/09603123.2021.1905781

  45. 45.

    Je D, O’Brolchain A, Ulett KB,. Demographics, clinical characteristics and outcomes among 197 patients with COVID-19 in the Gold Coast area. Intern Med J. 2021;51(5):666-672

    Not in our library10.1111/imj.15260

  46. 46.

    Jeong TH, Pak C, Ock M, Lee SH, Son JS, Jeon YJ. Real asymptomatic SARS-CoV-2 infection might be rare: importance of careful interviews and follow-up. J Korean Med Sci. 2020;35(37):e333-e333

    Not in our library10.3346/jkms.2020.35.e333

  47. 47.

    Jiang G, Wang C, Song L,. Aerosol transmission, an indispensable route of COVID-19 spread: case study of a department-store cluster. Front Environ Sci Eng. 2021;15(3):46

    Not in our library10.1007/s11783-021-1386-6

  48. 48.

    Jiang Z, Yang B, Qin J, Zhou Y. Enhanced empirical likelihood estimation of incubation period of COVID-19 by integrating published information. Stat Med. 2021;40(19):4252-4268

    Not in our library10.1002/sim.9026

  49. 49.

    Jin X, Lian J-S, Hu J-H,. Epidemiological, clinical and virological characteristics of 74 cases of coronavirus-infected disease 2019 (COVID-19) with gastrointestinal symptoms. Gut. 2020;69(6):1002-1009

    Not in our library10.1136/gutjnl-2020-320926

  50. 50.

    Khonyongwa K, Taori SK, Soares A,. Incidence and outcomes of healthcare-associated COVID-19 infections: significance of delayed diagnosis and correlation with staff absence. J Hosp Infect. 2020;106(4):663-672

    Not in our library10.1016/j.jhin.2020.10.006

  51. 51.

    Ki HJ, Kim J, Kim S, Park J, Lee J, Kim Y-J. Statistical analysis of estimating incubation period distribution and case fatality rate of COVID-19. Korean Journal of Applied Statistics. 2020;33(6):777-789.

    Not in our library

  52. 52.

    Kim SE, Jeong HS, Yu Y,. Viral kinetics of SARS-CoV-2 in asymptomatic carriers and presymptomatic patients. Int J Infect Dis. 2020;95:441-443

    Not in our library10.1016/j.ijid.2020.04.083

  53. 53.

    Kong D, Zheng Y, Wu H,. Pre-symptomatic transmission of novel coronavirus in community settings. Influenza Other Respir Viruses. 2020;14(6):610-614

    Not in our library10.1111/irv.12773

  54. 54.

    Kong T-K. Longer incubation period of coronavirus disease 2019 (COVID-19) in older adults. Aging Med (Milton). 2020;3(2):102-109

    Not in our library10.1002/agm2.12114

  55. 55.

    Kong W, Wang Y, Hu J, Chughtai A, Pu H; Clinical Research Collaborative Group of Sichuan Provincial People’s Hospital. Comparison of clinical and epidemiological characteristics of asymptomatic and symptomatic SARS-CoV-2 infection: a multi-center study in Sichuan Province, China. Travel Med Infect Dis. 2020;37:101754-101754

    Not in our library10.1016/j.tmaid.2020.101754

  56. 56.
  57. 57.

    Lau YC, Tsang TK, Kennedy-Shaffer L,. Joint estimation of generation time and incubation period for coronavirus disease (Covid-19). J Infect Dis. 2021;224(10):1664-1671

    Not in our library10.1093/infdis/jiab424

  58. 58.

    Le TQM, Takemura T, Moi ML,. Severe acute respiratory syndrome coronavirus 2 shedding by travelers, Vietnam, 2020. Emerg Infect Dis. 2020;26(7):1624-1626

    Not in our library10.3201/eid2607.200591

  59. 59.

    Lee JJ, Choe YJ, Jeong H,. Importation and transmission of SARS-CoV-2 B.1.1.529 (Omicron) variant of concern in Korea, November 2021. J Korean Med Sci. 2021;36(50):e346-e346

    Not in our library10.3346/jkms.2021.36.e346

  60. 60.

    Lei D, Wang C, Li C,. Clinical characteristics of COVID-19 in pregnancy: analysis of nine cases. Article in Chinese. Chinese Journal of Perinatal Medicine. 2020;12:222-228.

    Not in our library

  61. 61.

    Leung C. The difference in the incubation period of 2019 novel coronavirus (SARS-CoV-2) infection between travelers to Hubei and nontravelers: the need for a longer quarantine period. Infect Control Hosp Epidemiol. 2020;41(5):594-596

    Not in our library10.1017/ice.2020.81

  62. 62.

    Li J, Ding J, Chen L,. Epidemiological and clinical characteristics of three family clusters of COVID-19 transmitted by latent patients in China. Epidemiol Infect. 2020;148:e137-e137

    Not in our library10.1017/s0950268820001491

  63. 63.

    Li L, Han Z-G, Qin P-Z,. Transmission and containment of the SARS-CoV-2 Delta variant of concern in Guangzhou, China: a population-based study. PLoS Negl Trop Dis. 2022;16(1):e0010048-e0010048

    Not in our library10.1371/journal.pntd.0010048

  64. 64.

    Li Q, Guan X, Wu P,. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med. 2020;382(13):1199-1207

    Not in our library10.1056/nejmoa2001316

  65. 65.
  66. 66.

    Liu C-X, Liu Z-H, Sun L-Y, Zhang K-Y, Sun Y-Z. A familial cluster of COVID-19 infection in a northern Chinese region. J Infect Public Health. 2021;14(9):1127-1132

    Not in our library10.1016/j.jiph.2021.07.011

  67. 67.

    Liu F, Ji C, Luo J,. Clinical characteristics and corticosteroids application of different clinical types in patients with corona virus disease 2019. Sci Rep. 2020;10(1):13689-13689

    Not in our library10.1038/s41598-020-70387-2

  68. 68.
  69. 69.

    Liu JY, Chen TJ, Hwang SJ. Analysis of community-acquired COVID-19 cases in Taiwan. J Chin Med Assoc. 2020;83(12):1087-1092

    Not in our library10.1097/jcma.0000000000000411

  70. 70.

    Liu L, Du Y, Bai J,. Analysis of early characteristics of patients with novel coronavirus infection in Kunming City, Yunnan Province, China. Article in Chinese. Chinese Journal of Zoonoses. 2020;36(5):424-428.

    Not in our library

  71. 71.

    Liu L, Jing L, Li Y,. Clustering of 2019 novel coronavirus disease cases in Liaoning province: reported data-base analysis. Article in Chinese. Chin J Publ Health. 2020;36(04):473-476

    Not in our library10.11847/zgggws1128823

  72. 72.

    Liu P, Niu R, Chen J,. Epidemiological and clinical features in patients with coronavirus disease 2019 outside of Wuhan, China: special focus in asymptomatic patients. PLoS Negl Trop Dis. 2021;15(3):e0009248-e0009248

    Not in our library10.1371/journal.pntd.0009248

  73. 73.

    Liu W, Zhou M, Yang S,. Epidemiological characteristics of cluster cases of coronavirus disease 2019 (COVID-19) in China. Acta Medicinae Universitatis Scientiae et Technologiae Huazhong. 2020;49(02):161-168.

    Not in our library

  74. 74.

    Liu Y, Ding N, Zhou S,. Comparison of clinical characteristics between patients with coronavirus disease 2019 (COVID-19) who retested RT-PCR positive versus negative: a retrospective study of data from Nanjing. J Thorac Dis. 2020;12(11):6435-6445

    Not in our library10.21037/jtd.2020.04.17

  75. 75.

    Llaque-Quiroz P, Prudencio-Gamio R, Echevarría-Lopez S, Ccorahua-Paz M, Ugas-Charcape C. Clinical and epidemiological characteristics of children with COVID-19 in a pediatric hospital in Peru. Rev Peru Med Exp Salud Publica. 2020;37(4):689-693

    Not in our library10.17843/rpmesp.2020.374.6198

  76. 76.

    Mao S, Huang T, Yuan H,. Epidemiological analysis of 67 local COVID-19 clusters in Sichuan Province, China. BMC Public Health. 2020;20(1):1525-1525

    Not in our library10.1186/s12889-020-09606-4

  77. 77.

    Moazzami B, Moezedin Javad R, Samie S,. Is Computed tomography necessary for the diagnosis of coronavirus disease (COVID-19) in all suspected patients? a case series. J Kerman Univ Med Sci. 2021;2:187-193.

    Not in our library

  78. 78.

    Ng T-C, Cheng H-Y, Chang H-H,. Comparison of estimated effectiveness of case-based and population-based interventions on COVID-19 containment in Taiwan. JAMA Intern Med. 2021;181(7):913-921

    Not in our library10.1001/jamainternmed.2021.1644

  79. 79.

    Nie X, Fan L, Mu G,. Epidemiological characteristics and incubation period of 7015 confirmed cases with coronavirus disease 2019 outside Hubei Province in China. J Infect Dis. 2020;222(1):26-33

    Not in our library10.1093/infdis/jiaa211

  80. 80.

    Ogata T, Tanaka H, Irie F, Hirayama A, Takahashi Y. Shorter incubation period among unvaccinated delta variant coronavirus disease 2019 patients in Japan. Int J Environ Res Public Health. 2022;19(3):1127

    Not in our library10.3390/ijerph19031127

  81. 81.

    Pak D, Langohr K, Ning J, Cortés Martínez J, Gómez Melis G, Shen Y. Modeling the coronavirus disease 2019 incubation period: impact on quarantine policy. Mathematics. 2020;8(9):1631

    Not in our library10.3390/math8091631

  82. 82.

    Pan XX, Chen Y, Wang AH,. [Study on transmission dynamic of 15 clusters of COVID-2019 cases in Ningbo]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(12):2010-2014.

    Not in our library10.3760/cma.j.cn112338-20200330-00466

  83. 83.

    Patrikar SR, Kotwal A, Bhatti VK,. Incubation period and reproduction number for novel coronavirus 2019 (COVID-19) infections in India. Asia Pac J Public Health. 2020;32(8):458-460

    Not in our library10.1177/1010539520956427

  84. 84.
  85. 85.

    Ping K, Lei M, Gou Y,. Epidemiologic characteristics of COVID-19 in Guizhou Province, China. J Infect Dev Ctries. 2021;15(3):389-397

    Not in our library10.3855/jidc.12818

  86. 86.

    Pongpirul WA, Wiboonchutikul S, Charoenpong L,. Clinical course and potential predictive factors for pneumonia of adult patients with Coronavirus Disease 2019 (COVID-19): a retrospective observational analysis of 193 confirmed cases in Thailand. PLoS Negl Trop Dis. 2020;14(10):e0008806-e0008806

    Not in our library10.1371/journal.pntd.0008806

  87. 87.

    Pung R, Chiew CJ, Young BE,; Singapore 2019 Novel Coronavirus Outbreak Research Team. Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures. Lancet. 2020;395(10229):1039-1046

    Not in our library10.1016/s0140-6736(20)30528-6

  88. 88.

    Qi B, Peng H, Shou K,. Protecting healthcare professionals during the COVID-19 pandemic. Biomed Res Int. 2020;2020:8469560-8469560

    Not in our library10.1155/2020/8469560

  89. 89.

    Qian GQ, Yang NB, Ding F,. Epidemiologic and clinical characteristics of 91 hospitalized patients with COVID-19 in Zhejiang, China: a retrospective, multi-centre case series. QJM. 2020;113(7):474-481

    Not in our library10.1093/qjmed/hcaa089

  90. 90.

    Qiu C, Deng Z, Xiao Q,. Transmission and clinical characteristics of coronavirus disease 2019 in 104 outside-Wuhan patients, China. J Med Virol. 2020;92(10):2027-2035

    Not in our library10.1002/jmv.25975

  91. 91.

    Ratovoson R, Razafimahatratra R, Randriamanantsoa L,. Household transmission of COVID-19 among the earliest cases in Antananarivo, Madagascar. Influenza Other Respir Viruses. 2022;16(1):48-55

    Not in our library10.1111/irv.12896

  92. 92.

    Ren X, Li Y, Yang X,. Evidence for pre-symptomatic transmission of coronavirus disease 2019 (COVID-19) in China. Influenza Other Respir Viruses. 2021;15(1):19-26

    Not in our library10.1111/irv.12787

  93. 93.

    Samrah SM, Al-Mistarehi A-H, Kewan T,. Viral clearance course of COVID-19 outbreaks. J Multidiscip Healthc. 2021;14:555-565

    Not in our library10.2147/jmdh.s302891

  94. 94.
  95. 95.

    Shen Q, Guo W, Guo T,. Novel coronavirus infection in children outside of Wuhan, China. Pediatr Pulmonol. 2020;55(6):1424-1429

    Not in our library10.1002/ppul.24762

  96. 96.

    Shen Y, Xu W, Li C,. A cluster of novel coronavirus disease 2019 infections indicating person-to-person transmission among casual contacts from social gatherings: an outbreak case-contact investigation. Open Forum Infect Dis. 2020;7(6):ofaa231

    Not in our library10.1093/ofid/ofaa231

  97. 97.

    Shi J-C, Yu Z-J, He G-Q,. Epidemiological features of 105 patients infected with the COVID-19. J Natl Med Assoc. 2021;113(2):212-217

    Not in our library10.1016/j.jnma.2020.09.151

  98. 98.

    Shi P, Gao Y, Shen Y,. Characteristics and evaluation of the effectiveness of monitoring and control measures for the first 69 patients with COVID-19 from 18 January 2020 to 2 March in Wuxi, China. Sustain Cities Soc. 2021;64:102559-102559

    Not in our library10.1016/j.scs.2020.102559

  99. 99.

    Shiel E, Miyakis S, Tennant E,. Clinical characteristics and outcomes of COVID-19 in a low-prevalence, well resourced setting, Sydney, Australia. Intern Med J. 2021;51(10):1605-1613

    Not in our library10.1111/imj.15445

  100. 100.

    Shu Y, Deng Z, Wang H,. Epidemiological and clinical characteristics of 32 patients with COVID-19. Can J Infect Control. 2020;19(08):679-686.

    Not in our library

  101. 101.

    Song Q, Zhao H, Fang L, Liu W, Zheng C, Zhang Y. Study on assessing early epidemiological parameters of coronavirus disease epidemic in China. Article in Chinese. Chinese Journal of Epidemiology. 2020;41(4):461-465

    Not in our library10.3760/cma.j.cn112338-20200205-00069

  102. 102.

    Song R, Han B, Song M,. Clinical and epidemiological features of COVID-19 family clusters in Beijing, China. J Infect. 2020;81(2):e26-e30

    Not in our library10.1016/j.jinf.2020.04.018

  103. 103.

    Song YS, Hao YB, Liu WW, Zhang SS, Wang P, Fan TL. Clinical features of 17 patients with 2019-nCoV. Eur Rev Med Pharmacol Sci. 2020;24(20):10896-10901.

    Not in our library10.26355/eurrev_202010_23454

  104. 104.
  105. 105.

    Sugano N, Ando W, Fukushima W. Cluster of severe acute respiratory syndrome coronavirus 2 infections linked to music clubs in Osaka, Japan. J Infect Dis. 2020;222(10):1635-1640

    Not in our library10.1093/infdis/jiaa542

  106. 106.

    Sun B, Qi Y, Chen H,. Epidemiological profile of a cluster of COVID-19 caused by an imported case. Article in Chinese. Chin J Prev Med. 2021;22(04):246-249.

    Not in our library

  107. 107.

    Sun C, Zhang XB, Dai Y, Xu XZ, Zhao J. [Clinical analysis of 150 cases of 2019 novel coronavirus infection in Nanyang City, Henan Province]. Article in Chinese. Zhonghua Jie He He Hu Xi Za Zhi. 2020;43(6):503-508.

    Not in our library10.3760/cma.j.cn112147-20200224-00168

  108. 108.

    Sun L, Shen L, Fan J,. Clinical features of patients with coronavirus disease 2019 from a designated hospital in Beijing, China. J Med Virol. 2020;92(10):2055-2066

    Not in our library10.1002/jmv.25966

  109. 109.

    Sun YM, Liu F, Cai W,. [Transmission chains of clusters of COVID-19 associated with a market in Beijing]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2021;42(3):427-432.

    Not in our library10.3760/cma.j.cn112338-20201027-01285

  110. 110.

    Sun Y, Tian L, Du X, Wang H, Li Y, Wu R. Epidemiological and clinical characteristics of a familial cluster of COVID-19. Epidemiol Infect. 2020;148:e145-e145

    Not in our library10.1017/s0950268820001521

  111. 111.

    Tan WYT, Wong LY, Leo YS, Toh MPHS. Does incubation period of COVID-19 vary with age? a study of epidemiologically linked cases in Singapore. Epidemiol Infect. 2020;148:e197-e197

    Not in our library10.1017/s0950268820001995

  112. 112.

    Tanaka H, Ogata T, Shibata T,. Shorter incubation period among COVID-19 cases with the BA.1 Omicron variant. Int J Environ Res Public Health. 2022;19(10):6330

    Not in our library10.3390/ijerph19106330

  113. 113.

    SARS-CoV-2 variant with lineage B.1.351 clusters investigation team. Linked transmission chains of imported SARS-CoV-2 variant B.1.351 across mainland France, January 2021. Euro Surveill. 2021;26(13):2100333

    Not in our library10.2807/1560-7917.es.2021.26.13.2100333

  114. 114.

    Tian S, Hu N, Lou J,. Characteristics of COVID-19 infection in Beijing. J Infect. 2020;80(4):401-406

    Not in our library10.1016/j.jinf.2020.02.018

  115. 115.
  116. 116.

    Viego V, Geri M, Castiglia J, Jouglard E. Incubation period and serial interval of Covid-19 in a chain of infections in Bahia Blanca (Argentina). Cien Saude Colet. 2020;25(9):3503-3510

    Not in our library10.1590/1413-81232020259.20852020

  117. 117.

    Wang J, Wang S, Yang S,. Epidemiological characteristics of 17 coronavirus disease 2019 in Puyang, Henan. Article in Chinese. Chinese Journal of Disease Control & Prevention. 2021;25(04):416-420.

    Not in our library

  118. 118.

    Wang X, Gao J, Wang X, Hu W, Liu H. Clinical and epidemiological characteristics of patients with COVID. Can J Infect Control. 2020;19(03):223-226

    Not in our library10.3389/fpubh.2020.00244

  119. 119.
  120. 120.

    Wang X, Zhou Q, He Y,. Nosocomial outbreak of COVID-19 pneumonia in Wuhan, China. Eur Respir J. 2020;55(6):2000544

    Not in our library10.1183/13993003.00544-2020

  121. 121.

    Wang Y, Liao B, Guo Y,. Clinical characteristics of patients infected with the novel 2019 coronavirus (SARS-Cov-2) in Guangzhou, China. Open Forum Infect Dis. 2020;7(6):ofaa187

    Not in our library10.1093/ofid/ofaa187

  122. 122.

    Wei X. Analysis of clinical characteristics of 28 cases of COVID-19. Article in Chinese. Chinese Journal of Integrated Traditional and Western Medicine. 2021;28(3).

    Not in our library

  123. 123.

    Wei Y, Zeng W, Huang X,. Clinical characteristics of 276 hospitalized patients with coronavirus disease 2019 in Zengdu District, Hubei Province: a single-center descriptive study. BMC Infect Dis. 2020;20(1):549-549

    Not in our library10.1186/s12879-020-05252-8

  124. 124.

    Won YS, Kim J-H, Ahn CY, Lee H. Subcritical transmission in the early stage of COVID-19 in Korea. Int J Environ Res Public Health. 2021;18(3):1265

    Not in our library10.3390/ijerph18031265

  125. 125.

    Wong J, Chaw L, Koh WC,. Epidemiological investigation of the first 135 COVID-19 cases in Brunei: implications for surveillance, control, and travel restrictions. Am J Trop Med Hyg. 2020;103(4):1608-1613

    Not in our library10.4269/ajtmh.20-0771

  126. 126.

    Wu J, Chen X, Gong L,. Epidemiological and clinical features of SARS-CoV-2 cluster infection in Anhui Province, Eastern China. Int J Infect Dis. 2021;117:372-377

    Not in our library10.1016/j.ijid.2021.04.064

  127. 127.

    Wu J, Xia J, Yang Q,. Clinical characteristics of SARS-CoV-2 infection at early stage. Article in Chinese. Chinese Journal of Infection and Chemotherapy. 2020;20(05):521-524.

    Not in our library

  128. 128.

    Wu W, Liu Y, Wei Z,. Investigation and analysis on characteristics of a cluster of COVID-19 associated with exposure in a department store in Tianjin. Article in Chinese. Chin J Epidemiol. 2020;41(4):489-493

    Not in our library10.3760/cma.j.cn112338-20200221-00139

  129. 129.

    Wu Y. Epidemiological and clinical characteristics of 41 patients with COVID-19. Article in Chinese. Chinese Journal of Integrated Traditional and Western Medicine. 2020;27(4).

    Not in our library

  130. 130.

    Xiao F, Chen B, Xiao T, Lee SK, Yan K, Hu L. Children with SARS-CoV-2 infection during an epidemic in China (outside of Hubei province). Ann Transl Med. 2020;8(14):849-849

    Not in our library10.21037/atm-20-2908

  131. 131.

    Xiao M, Hou M, Liu X, Li Z, Zhao Q. Clinical characteristics of 71 patients with coronavirus disease 2019. Article in Chinese. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2020;45(7):790-796

    Not in our library10.11817/j.issn.1672-7347.2020.200187

  132. 132.

    Xiao Z, Guo W, Luo Z, Liao J, Wen F, Lin Y. Examining geographical disparities in the incubation period of the COVID-19 infected cases in Shenzhen and Hefei, China. Environ Health Prev Med. 2021;26(1):10-10

    Not in our library10.1186/s12199-021-00935-3

  133. 133.

    Xiao Z, Xie X, Guo W,. Examining the incubation period distributions of COVID-19 on Chinese patients with different travel histories. J Infect Dev Ctries. 2020;14(4):323-327

    Not in our library10.3855/jidc.12718

  134. 134.

    Xie S, Zhang G, Yu H,. The epidemiologic and clinical features of suspected and confirmed cases of imported 2019 novel coronavirus pneumonia in north Shanghai, China. Ann Transl Med. 2020;8(10):637-637

    Not in our library10.21037/atm-20-2119

  135. 135.

    Xin H, Li Y, Wu P,. Estimating the latent period of coronavirus disease 2019 (COVID-19). Clin Infect Dis. 2022;74(9):1678-1681

    Not in our library10.1093/cid/ciab746

  136. 136.

    Xu T, Chen C, Zhu Z,. Clinical features and dynamics of viral load in imported and non-imported patients with COVID-19. Int J Infect Dis. 2020;94:68-71

    Not in our library10.1016/j.ijid.2020.03.022

  137. 137.

    Xu X-W, Wu X-X, Jiang X-G,. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. BMJ. 2020;368:m606-m606

    Not in our library10.1136/bmj.m606

  138. 138.

    Yang HY, Xu J, Li Y,. [The preliminary analysis on the characteristics of the cluster for the COVID-19]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(5):623-628.

    Not in our library10.3760/cma.j.cn112338-20200223-00153

  139. 139.

    Yang J, Wu K, Ding A,. Clinical characteristics, treatment, and prognosis of 74 2019 novel coronavirus disease patients in Hefei: a single-center retrospective study. Medicine (Baltimore). 2021;100(21):e25645-e25645

    Not in our library10.1097/md.0000000000025645

  140. 140.

    Yang N, Shen Y, Shi C,. In-flight transmission cluster of COVID-19: a retrospective case series. Infect Dis (Lond). 2020;52(12):891-901

    Not in our library10.1080/23744235.2020.1800814

  141. 141.

    You C, Deng Y, Hu W,. Estimation of the time-varying reproduction number of COVID-19 outbreak in China. Int J Hyg Environ Health. 2020;228:113555-113555

    Not in our library10.1016/j.ijheh.2020.113555

  142. 142.
  143. 143.

    Yu X, Sun X, Cui P,. Epidemiological and clinical characteristics of 333 confirmed cases with coronavirus disease 2019 in Shanghai, China. Transbound Emerg Dis. 2020;67(4):1697-1707

    Not in our library10.1111/tbed.13604

  144. 144.

    Zhang H, Song S, Chen Z,. A Cluster transmission of coronavirus disease 2019 and the prevention and control measures in the early stage of the epidemic in Xi’an, China, 2020. Med Sci Monit. 2021;27:e929701-e929701

    Not in our library10.12659/msm.929701

  145. 145.

    Zhang J, Litvinova M, Wang W,. Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study. Lancet Infect Dis. 2020;20(7):793-802

    Not in our library10.1016/s1473-3099(20)30230-9

  146. 146.

    Zhang K, Zhang Y, Li M, Yu M, Cha L, Ruan L. Comparative analysis of clinical characteristics of imported and local family clusters of novel coronavirus pneumonia. Article in Chinese. Chinese Journal of Integrated Traditional and Western Medicine. 2020;27(4):385-389.

    Not in our library

  147. 147.
  148. 148.

    Zhang T, Ding S, Zeng Z,. Estimation of incubation period and serial interval for SARS-CoV-2 in Jiangxi, China, and an updated meta-analysis. J Infect Dev Ctries. 2021;15(3):326-332

    Not in our library10.3855/jidc.14025

  149. 149.

    Zhao C, Xu Y, Zhang X,. Public health initiatives from hospitalized patients with COVID-19, China. J Infect Public Health. 2020;13(9):1229-1236

    Not in our library10.1016/j.jiph.2020.06.013

  150. 150.

    Zhao H, Zhang Z, Lun W,. Transmission dynamics and successful control measures of SARS-CoV-2 in the mega-size city of Guangzhou, China. Medicine (Baltimore). 2021;100(48):e27846

    Not in our library10.1097/md.0000000000027846

  151. 151.

    Zhao S, Tang B, Musa SS,. Estimating the generation interval and inferring the latent period of COVID-19 from the contact tracing data. Epidemics. 2021;36:100482-100482

    Not in our library10.1016/j.epidem.2021.100482

  152. 152.

    Zhao WH, Ma Y, Wang H,. [Epidemiological characteristics of three local epidemics of COVID-19 in Guangzhou]. Article in Chinese. Zhonghua Liu Xing Bing Xue Za Zhi. 2021;42(12):2088-2095.

    Not in our library10.3760/cma.j.cn112338-20210728-00592

  153. 153.

    Zhao Z, Yin M, Yin S,. Analysis of clinical characteristics of 26 cases of COVID-19. Article in Chinese. Chinese Journal of Disease Control & Prevention. 2020;24(05):539-542.

    Not in our library

  154. 154.

    Zhong S, Lin F, Shi L. Clinical characteristics and outcomes of the patients with COVID-19: a report of 62 cases. Article in Chinese. Medical Journal of Chinese People’s Liberation Army. 2020;45(04):370-374.

    Not in our library

  155. 155.

    Zhu J, Zhang Q, Jia C,. Challenges caused by imported cases abroad for the prevention and control of COVID-19 in China. Front Med (Lausanne). 2021;8:573726-573726

    Not in our library10.3389/fmed.2021.573726

  156. 156.

    Zhu N, Chen S, Yang G,. Analysis of the path from discovery of novel coronavirus disease 2019 cases to its diagnosis in Shaanxi Province. Article in Chinese. Xi’an Jiaotong Daxue Xuebao Yixue Ban. 2020;41(06):923-926.

    Not in our library

  157. 157.

    Zhu W, Zhang M, Pan J, Yao Y, Wang W. Effects of prolonged incubation period and centralized quarantine on the COVID-19 outbreak in Shijiazhuang, China: a modeling study. BMC Med. 2021;19(1):308-308

    Not in our library10.1186/s12916-021-02178-z

  158. 158.

    Wang Y, Liao B, Guo Y,. Clinical characteristics of patients infected with the novel 2019 coronavirus (SARS-Cov-2) in Guangzhou, China. Open Forum Infect Dis. 2020;7(6):ofaa187

    Not in our library10.1093/ofid/ofaa187

  159. 159.

    Elias C, Sekri A, Leblanc P, Cucherat M, Vanhems P. The incubation period of COVID-19: a meta-analysis. Int J Infect Dis. 2021;104:708-710

    Not in our library10.1016/j.ijid.2021.01.069

  160. 160.

    Lessler J, Reich NG, Brookmeyer R, Perl TM, Nelson KE, Cummings DA. Incubation periods of acute respiratory viral infections: a systematic review. Lancet Infect Dis. 2009;9(5):291-300

    Not in our library10.1016/s1473-3099(09)70069-6

  161. 161.

    World Health Organization. Coronavirus disease (COVID-19). Updated May 13, 2021. Accessed April 17, 2022. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/question-and-answers-hub/q-a-detail/coronavirus-disease-covid-19

    Not in our library

  162. 162.
  163. 163.

    US Centers for Disease Control and Prevention. Quarantine and Isolation. Updated March 30, 2022. Accessed April 17, 2022. https://www.cdc.gov/coronavirus/2019-ncov/your-health/quarantine-isolation.html

    Not in our library

  164. 164.

    Cowling BJ, Muller MP, Wong IO,. Alternative methods of estimating an incubation distribution: examples from severe acute respiratory syndrome. Epidemiology. 2007;18(2):253-259

    Not in our library10.1097/01.ede.0000254660.07942.fb

  165. 165.

    Chen Y, Klein SL, Garibaldi BT,. Aging in COVID-19: vulnerability, immunity and intervention. Ageing Res Rev. 2021;65:101205-101205

    Not in our library10.1016/j.arr.2020.101205

  166. 166.

    Virlogeux V, Fang VJ, Wu JT,. Brief report: incubation period duration and severity of clinical disease following severe acute respiratory syndrome coronavirus infection. Epidemiology. 2015;26(5):666-669

    Not in our library10.1097/ede.0000000000000339

  167. 167.

    Virlogeux V, Park M, Wu JT, Cowling BJ. Association between severity of MERS-CoV infection and incubation period. Emerg Infect Dis. 2016;22(3):526-528

    Not in our library10.3201/eid2203.151437

Cited by papers we hold 2

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.