# Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Methods

#### 2.1. Time from Symptom Onset to Hospitalisation

#### 2.2. Time-Varying Reproduction Number

#### 2.3. Proportion of Transmissions from Individuals with Few Symptoms

## 3. Results

#### 3.1. Time from Symptom Onset to Hospitalisation

#### 3.2. Reproduction Number and Proportion of Transmissions from Individuals with Few Symptoms

## 4. Discussion

## Supplementary Materials

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

- Thompson, R.N. Novel coronavirus outbreak in Wuhan, China, 2020: Intense surveillance is vital for preventing sustained transmission in new locations. J. Clin. Med.
**2020**, 9, 498. [Google Scholar] [CrossRef] [PubMed][Green Version] - Stoecklin, S.; Rolland, P.; Silue, Y.; Mailles, A.; Campese, C.; Simondon, A.; Yamani, E. First cases of coronavirus disease 2019 (COVID-19) in France: Surveillance, investigations and control measures, January 2020. Eurosurveillance
**2020**, 25, 2000094. [Google Scholar] - Gostic, K.M.; Gomez, A.C.R.; Mummah, R.O.; Kucharski, A.J.; Lloyd-Smith, J.O. Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19. Elife
**2020**, 9, 55570. [Google Scholar] [CrossRef] [PubMed] - Hellewell, J.; Abbott, S.; Gimma, A.; Bosse, N.I.; Jarvis, C.I.; Russell, T.W.; Munday, J.D.; Kucharski, J.; Edmunds, J. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob. Health
**2020**, 8, E488–E496. [Google Scholar] [CrossRef][Green Version] - Spina, S.; Marrazzo, F.; Migliari, M.; Stucchi, R.; Sforza, A.; Fumagalli, R. The response of Milan’s Emergency Medical System to the COVID-19 outbreak in Italy. Lancet
**2020**, 395, E49–E50. [Google Scholar] [CrossRef][Green Version] - Clifford, S.J.; Pearson, C.A.B.; Klepac, P.; Van Zandvoort, K.; Quilty, B.J.; CMMID COVID-19 Working Group; Eggo, R.M.; Flasche, S. Effectiveness of interventions targeting air travellers for delaying local outbreaks of SARS-CoV-2. medRxiv
**2020**. [Google Scholar] [CrossRef][Green Version] - Fauci, A.S.; Lane, H.C.; Redfield, R.R. Covid-19—Navigating the uncharted. N. Engl. J. Med.
**2020**, 382, 1268–1269. [Google Scholar] [CrossRef] - Anzai, A.; Kobayashi, T.; Linton, N.M.; Kinoshita, R.; Hayashi, K.; Suzuki, A.; Yang, Y.; Jung, S.-M.; Miyama, T.; Akhmetzhanov, A.R.; et al. Assessing the Impact of Reduced Travel on Exportation Dynamics of Novel Coronavirus Infection (COVID-19). J. Clin. Med.
**2020**, 9, 601. [Google Scholar] [CrossRef][Green Version] - Chen, S.; Yang, J.; Yang, W.; Wang, C.; Bärnighausen, T. COVID-19 control in China during mass population movements at New Year. Lancet
**2020**, 395, 764–766. [Google Scholar] [CrossRef][Green Version] - Thompson, R.N. Pandemic potential of 2019-nCoV. Lancet Infect. Dis.
**2020**, 3099, 30068. [Google Scholar] [CrossRef][Green Version] - Wilder-Smith, A.; Freedman, D.O. Isolation, quarantine, social distancing and community containment: Pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. J Travel Med.
**2020**, 2, taaa020. [Google Scholar] [CrossRef] [PubMed] - Fraser, C.; Riley, S.; Anderson, R.M.; Ferguson, N.M. Factors that make an infectious disease outbreak controllable. Proc. Natl. Acad. Sci. USA
**2004**, 101, 6146–6151. [Google Scholar] [CrossRef] [PubMed][Green Version] - Lipsitch, M.; Swerdlow, D.L.; Finelli, L. Defining the epidemiology of Covid-19—Studies needed. N. Engl. J. Med.
**2020**, 382, 1194–1196. [Google Scholar] [CrossRef] [PubMed] - Ferretti, L.; Wymant, C.; Kendall, M.; Zhao, L.; Nurtay, A.; Abeler-Dörner, L.; Parker, M.; Bonsall, D.; Fraser, C. Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science
**2020**, eabb6936. [Google Scholar] [CrossRef] [PubMed][Green Version] - Guan, W.-J.; Ni, Z.-Y.; Hu, Y.; Liang, W.-H.; Ou, C.-Q.; He, J.-X.; Liu, L.; Shan, H.; Lei, C.-L.; Hui, D.S.; et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N. Engl. J. Med.
**2020**. [Google Scholar] [CrossRef] - Chen, N.; Zhou, M.; Dong, X.; Qu, J.; Gong, F.; Han, Y.; Qiu, Y.; Wang, J.; Liu, Y.; Wei, Y.; et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet
**2020**, 395, 507–513. [Google Scholar] [CrossRef][Green Version] - Yeo, C.; Kaushal, S.; Yeo, D. Enteric involvement of coronaviruses: Is faecal–oral transmission of SARS-CoV-2 possible? Lancet Gastroenterol. Hepatol.
**2020**, 5, 335–337. [Google Scholar] [CrossRef][Green Version] - Bai, Y.; Yao, L.; Wei, T.; Tian, F.; Jin, D.-Y.; Chen, L.; Wang, M. Presumed Asymptomatic Carrier Transmission of COVID-19. JAMA
**2020**, 323, 1406. [Google Scholar] [CrossRef][Green Version] - Rothe, C.; Schunk, M.; Sothmann, P.; Bretzel, G.; Froeschl, G.; Wallrauch, C.; Zimmer, T.; Thiel, V.; Janke, C.; Guggemos, W.; et al. Transmission of 2019-nCoV Infection from an Asymptomatic Contact in Germany. N. Engl. J. Med.
**2020**, 382, 970–971. [Google Scholar] [CrossRef][Green Version] - Pan, X.; Chen, D.; Xia, Y.; Wu, X.; Li, T.; Ou, X.; Zhou, L.; Liu, J. Asymptomatic cases in a family cluster with SARS-CoV-2 infection. Lancet Infect. Dis.
**2020**, 20, 410–411. [Google Scholar] [CrossRef] - Li, R.; Pei, S.; Chen, B.; Song, Y.; Zhang, T.; Yang, W.; Shaman, J. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2). Science
**2020**, eabb3221. [Google Scholar] [CrossRef] [PubMed][Green Version] - Nishiura, H.; Kobayashi, T.; Suzuki, A.; Jung, S.-M.; Hayashi, K.; Kinoshita, R.; Yang, Y.; Yuan, B.; Akhmetzhanov, A.R.; Linton, N.M.; et al. Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19). Int. J. Infect. Dis.
**2020**. [Google Scholar] [CrossRef] [PubMed] - Chen, Z.; Hu, J.; Zhang, Z.; Jiang, S.S.; Wang, T.; Daszak, P.; Zhang, Z. Caution: The clinical characteristics of COVID-19 patients at admission are changing. medRxiv
**2020**. [Google Scholar] [CrossRef] - Yang, P.; Ding, Y.; Xu, Z.; Pu, R.; Li, P.; Yan, J.; Liu, J.; Meng, F.; Huang, L.; Shi, L.; et al. Epidemiological and clinical features of COVID-19 patients with and without pneumonia in Beijing, China. medRxiv
**2020**. [Google Scholar] [CrossRef][Green Version] - Nishiura, H.; Kobayashi, T.; Yang, Y.; Hayashi, K.; Miyama, T.; Kinoshita, R.; Linton, N.M.; Jung, S.-M.; Yuan, B.; Suzuki, A.; et al. The Rate of Underascertainment of Novel Coronavirus (2019-nCoV) Infection: Estimation Using Japanese Passengers Data on Evacuation Flights. J. Clin. Med.
**2020**, 9, 419. [Google Scholar] [CrossRef][Green Version] - Wu, Z.; McGoogan, J.M. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA
**2020**, 323, 1239–1242. [Google Scholar] [CrossRef] - Tong, Z.-D.; Tang, A.; Li, K.-F.; Li, P.; Wang, H.-L.; Yi, J.-P. Potential presymptomatic transmission of SARS-CoV-2, Zhejiang Province, China, 2020. Emerg. Infect Dis.
**2020**, 26, 1052–1054. [Google Scholar] [CrossRef][Green Version] - Kraemer, M.; Pigott, D.; Xu, B.; Hill, S.; Gutierrez, B.; Pybus, O. Epidemiological Data from the nCoV-2019 Outbreak: Early Descriptions from Publicly Available Data. 2020. Available online: http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/ (accessed on 9 February 2020).
- Linton, N.M.; Kobayashi, T.; Yang, Y.; Hayashi, K.; Akhmetzhanov, A.R.; Jung, S.-M.; Yuan, B.; Kinoshita, R.; Nishiura, H. Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data. J. Clin. Med.
**2020**, 9, 538. [Google Scholar] [CrossRef][Green Version] - Cori, A.; A Donnelly, C.; Dorigatti, I.; Ferguson, N.M.; Fraser, C.; Garske, T.; Jombart, T.; Nedjati-Gilani, G.; Nouvellet, P.; Riley, S.; et al. Key data for outbreak evaluation: Building on the Ebola experience. Philos. Trans. R. Soc. B Boil. Sci.
**2017**, 372, 20160371. [Google Scholar] [CrossRef][Green Version] - Mizumoto, K.; Kagaya, K.; Zarebski, A.; Chowell, G. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveillance
**2020**, 25, 2000180. [Google Scholar] [CrossRef][Green Version] - Thompson, R.; Stockwin, J.; Van Gaalen, R.; Polonsky, J.; Kamvar, Z.; DeMarsh, P.; Dahlqwist, E.; Li, S.; Miguel, E.; Jombart, T.; et al. Improved inference of time-varying reproduction numbers during infectious disease outbreaks. Epidemics
**2019**, 29, 100356. [Google Scholar] [CrossRef] [PubMed] - Cori, A.; Ferguson, N.M.; Fraser, C.; Cauchemez, S. A new framework and software to estimate time-varying reproduction numbers during epidemics. Am. J. Epidemiol.
**2013**, 178, 1505–1512. [Google Scholar] [CrossRef] [PubMed][Green Version] - Nishiura, H.; Chowell, G. The Effective Reproduction Number as a Prelude to Statistical Estimation of Time-Dependent Epidemic Trends. In Mathematical and Statistical Estimation Approaches in Epidemiology; Springer: Berlin/Heidelberg, Germany, 2009; pp. 103–121. [Google Scholar]
- Fraser, C. Estimating individual and household reproduction numbers in an emerging epidemic. PLoS ONE
**2007**, 2, 758. [Google Scholar] [CrossRef] - Forsberg White, L.; Pagano, M. A likelihood-based method for real-time estimation of the serial interval and reproduction number of an epidemic. Stat. Med.
**2008**, 27, 2999–3016. [Google Scholar] [CrossRef] [PubMed][Green Version] - Heymann, D.L.; Shindo, N. WHO Scientific and Technical Advisory Group for Infectious Hazards. COVID-19: What is next for public health? Lancet
**2020**, 395, 542–545. [Google Scholar] [CrossRef][Green Version] - Kucharski, A.J.; Russell, T.W.; Diamond, C.; Liu, Y.; Edmunds, J.; Funk, S.; Eggo, R.M.; Sun, F.; Jit, M.; Munday, J.D.; et al. Early dynamics of transmission and control of COVID-19: A mathematical modelling study. Lancet Infect. Dis.
**2020**. [Google Scholar] [CrossRef][Green Version] - Flaxman, S.; Mishra, S.; Gandy, A.; Unwin, J.T.; Coupland, H.; Mellan, T.; Eaton, J.; Perez Guzman, P.; Cilloni, L.; Schmit, N.; et al. Estimating the Number of Infections and the Impact of Non-Pharmaceutical Interventions on COVID-19 in 11 European Countries. Available online: https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-Europe-estimates-and-NPI-impact-30-03-2020.pdf (accessed on 4 April 2020).
- Reich, N.G.; Lessler, J.; Cummings, D.A.T.; Brookmeyer, R. Estimating incubation period distributions with coarse data. Stat. Med.
**2009**, 28, 2769–2784. [Google Scholar] [CrossRef] - He, X.; Lau, E.H.Y.; Wu, P.; Deng, X.; Wang, J.; Hao, X.; Lau, Y.C.; Wong, J.Y.; Guan, Y.; Tan, X.; et al. Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat. Med.
**2020**, 1–4. [Google Scholar] [CrossRef][Green Version] - Ganyani, T.; Kremer, C.; Chen, D.; Torneri, A.; Faes, C.; Wallinga, J.; Hens, N. Estimating the generation interval for COVID-19 based on symptom onset data. medRxiv
**2020**. [Google Scholar] [CrossRef][Green Version]

**Figure 1.**Changes in the period between symptom onset and hospitalisation (the assumed symptomatic infectious period) from 2 January 2020 to 22 January 2020. (

**A**) Schematic showing the assumed epidemiology of infected hosts. Infected individuals initially have no or few symptoms. Later in infection, infected individuals develop clear symptoms. (

**B**) Estimated mean period between symptom onset and hospitalisation (blue), along with the corresponding 95% confidence interval for the mean value (grey shaded region). Circle areas are proportional to the numbers of individuals with symptom onset date t who were hospitalised $1/{\gamma}_{t}$ days later.

**Figure 2.**The reproduction number (${R}_{t}$ ) and the proportion of transmissions from hosts with few symptoms (${\alpha}_{t}$) vary in response to changes in the period between symptom onset and hospitalisation. (

**A**) Variation in ${R}_{t}$ and ${\alpha}_{t}$ between 2 January and 22 January 2020 due to changes in the mean time from symptom onset to hospitalisation ($1/{\gamma}_{t}$ days; see Figure 1B), under the assumption that ${R}_{0}=2$. Values of ${R}_{t}$ and ${\alpha}_{t}$ were calculated using Equations (1) and (2), respectively. Lines represent different values of the initial proportion of transmissions from hosts with few symptoms (${\alpha}_{0}$). Values of ${\alpha}_{0}$ between 0 and 0.4 were considered in steps of 0.05 (i.e., nine values in total). In the period from 2 January to 22 January 2020, transmissions from hosts with clear symptoms were typically prevented increasingly effectively, leading to a temporal trend from the tops to the bottoms of the lines shown. (

**B**) Equivalent figure to panel A, but with ${R}_{0}=3$. (

**C**) Equivalent figure to panel A, but with ${R}_{0}=4$. (

**D**) Required time within which symptomatic infectious hosts must be isolated on average ($1/{\gamma}_{t}$ days) so that ${R}_{t}$ is less than one (i.e., the outbreak is controlled), calculated using Equation (1) for different pairs of values of ${\alpha}_{0}$ and ${R}_{0}$. In panels A-C, the horizontal black line shows the threshold value of ${R}_{t}$ for outbreak control (${R}_{t}=1$). The value of $1/{\gamma}_{0}$ used in all panels is 6.7 days (as estimated in Figure 1B).

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Thompson, R.N.; Lovell-Read, F.A.; Obolski, U. Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms. *J. Clin. Med.* **2020**, *9*, 1297.
https://doi.org/10.3390/jcm9051297

**AMA Style**

Thompson RN, Lovell-Read FA, Obolski U. Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms. *Journal of Clinical Medicine*. 2020; 9(5):1297.
https://doi.org/10.3390/jcm9051297

**Chicago/Turabian Style**

Thompson, Robin N., Francesca A. Lovell-Read, and Uri Obolski. 2020. "Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms" *Journal of Clinical Medicine* 9, no. 5: 1297.
https://doi.org/10.3390/jcm9051297