The incubation period of COVID-19: A meta-analysis

ObjectivesThe aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation period of COVID-19.DesignRapid systematic review and meta-analysis of observational research.SettingInternational studies on incubation period of COVID-19.ParticipantsSearches were carried out in PubMed, Google Scholar, Embase, Cochrane Library as well as the preprint servers MedRxiv and BioRxiv. Studies were selected for meta-analysis if they reported either the parameters and CIs of the distributions fit to the data, or sufficient information to facilitate calculation of those values. After initial eligibility screening, 24 studies were selected for initial review, nine of these were shortlisted for meta-analysis. Final estimates are from meta-analysis of eight studies.Primary outcome measuresParameters of a lognormal distribution of incubation periods.ResultsThe incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters (95% CIs) of 1.63 (95% CI 1.51 to 1.75) and 0.50 (95% CI 0.46 to 0.55), respectively. The corresponding mean (95% CIs) was 5.8 (95% CI 5.0 to 6.7) days. It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates (95% CIs) resulted in a median incubation period of 5.1 (95% CI 4.5 to 5.8) days, whereas the 95th percentile was 11.7 (95% CI 9.7 to 14.2) days.ConclusionsThe choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Accordingly, we present an R Shiny app that facilitates updating these estimates as new data become available.

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The incubation period of COVID-19: A scoping review and meta-analysis to aid modelling and planning

10.1101/2020.10.20.20216143 ◽

2020 ◽

Author(s):

Prakashini Banka ◽

Catherine Comiskey

Keyword(s):

Incubation Period ◽

Scoping Review ◽

Meta Analysis ◽

Accurate Estimate ◽

Mitigation Strategies ◽

Global Index ◽

Distribution Modelling ◽

Period Distribution ◽

Incubation Periods ◽

The Mean

AbstractBackgroundAn accurate estimate of the distribution of the incubation period for COVID-19 is the foundational building block for modelling the spread of the SARS COV2 and the effectiveness of mitigation strategies on affected communities. Initial estimates were based on early infections, the aim of this study was to provide an updated estimate and meta-analysis of the incubation period distribution for COVID-19.MethodsThe review was conducted according to the PRISMA Scoping Review guidelines. Five databases were searched; CINAHL, MEDLINE, PUBMED, EMBASE, ASSIA, and Global Index Medicus for studies published between 1 January 2020 - 27 July 2020.ResultsA total of 1,084 articles were identified through the database searches and 1 article was identified through the reference screening of retrieved articles. After screening 64 articles were included. The studies combined had a sample of 45,151 people. The mean of the incubation periods was 6.71 days with 95% CIs ranging from 1 to 12.4 days. The median was 6 days and IQR ranging from 1.8 to 16.3. The resulting parameters for a Gamma Distribution modelling the incubation period were Γ(α, λ) = Γ(2.810,0.419) with mean, μ = α/λ.ConclusionGovernments are planning their strategies on a maximum incubation period of 14 days. While our results are limited to primarily Chinese research studies, the findings highlight the variability in the mean period and the potential for further incubation beyond 14 days. There is an ongoing need for detailed surveillance on the timing of self-isolation periods and related measures protecting communities as incubation periods may be longer.

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Meta-analysis of the SARS-CoV-2 serial interval and the impact of parameter uncertainty on the COVID-19 reproduction number

10.1101/2020.11.17.20231548 ◽

2020 ◽

Author(s):

Robert Challen ◽

Ellen Brooks-Pollock ◽

Krasimira Tsaneva-Atanasova ◽

Leon Danon

Keyword(s):

Incubation Period ◽

Time Delays ◽

Hospital Admissions ◽

Reproduction Number ◽

Meta Analysis ◽

Model Parameters ◽

Small Data ◽

Generation Interval ◽

Serial Interval ◽

The Impact

AbstractThe serial interval of an infectious disease, commonly interpreted as the time between onset of symptoms in sequentially infected individuals within a chain of transmission, is a key epidemiological quantity involved in estimating the reproduction number. The serial interval is closely related to other key quantities, including the incubation period, the generation interval (the time between sequential infections) and time delays between infection and the observations associated with monitoring an outbreak such as confirmed cases, hospital admissions and deaths. Estimates of these quantities are often based on small data sets from early contact tracing and are subject to considerable uncertainty, which is especially true for early COVID-19 data. In this paper we estimate these key quantities in the context of COVID-19 for the UK, including a meta-analysis of early estimates of the serial interval. We estimate distributions for the serial interval with a mean 5.6 (95% CrI 5.1–6.2) and SD 4.2 (95% CrI 3.9–4.6) days (empirical distribution), the generation interval with a mean 4.8 (95% CrI 4.3–5.41) and SD 1.7 (95% CrI 1.0–2.6) days (fitted gamma distribution), and the incubation period with a mean 5.5 (95% CrI 5.1–5.8) and SD 4.9 (95% CrI 4.5–5.3) days (fitted log normal distribution). We quantify the impact of the uncertainty surrounding the serial interval, generation interval, incubation period and time delays, on the subsequent estimation of the reproduction number, when pragmatic and more formal approaches are taken. These estimates place empirical bounds on the estimates of most relevant model parameters and are expected to contribute to modelling COVID-19 transmission.

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Incubation Period of Severe Acute Respiratory Syndrome Novel Coronavirus 2 that Causes Coronavirus Disease 2019: A Systematic Review and Meta-Analysis

Current Therapeutic Research ◽

10.1016/j.curtheres.2020.100607 ◽

2020 ◽

Vol 93 ◽

pp. 100607 ◽

Cited By ~ 1

Author(s):

Gizachew Tadesse Wassie ◽

Abebaw Gedef Azene ◽

Getasew Mulat Bantie ◽

Getenet Dessie ◽

Abiba Mihret Aragaw

Keyword(s):

Systematic Review ◽

Severe Acute Respiratory Syndrome ◽

Incubation Period ◽

Meta Analysis ◽

Novel Coronavirus

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A systematic review and meta-analysis on the incubation period of Campylobacteriosis

Epidemiology and Infection ◽

10.1017/s0950268817001303 ◽

2017 ◽

Vol 145 (11) ◽

pp. 2241-2253 ◽

Cited By ~ 7

Author(s):

A. AWOFISAYO-OKUYELU ◽

I. HALL ◽

G. ADAK ◽

J.I. HAWKER ◽

S. ABBOTT ◽

...

Keyword(s):

Systematic Review ◽

Incubation Period ◽

Meta Analysis ◽

Age Distribution ◽

Age Groups ◽

Experimental Studies ◽

Public Health Policies ◽

Explanatory Factors ◽

Kolmogorov Smirnov ◽

The Mean

AbstractAccurate knowledge of pathogen incubation period is essential to inform public health policies and implement interventions that contribute to the reduction of burden of disease. The incubation period distribution of campylobacteriosis is currently unknown with several sources reporting different times. Variation in the distribution could be expected due to host, transmission vehicle, and organism characteristics, however, the extent of this variation and influencing factors are unclear. The authors have undertaken a systematic review of published literature of outbreak studies with well-defined point source exposures and human experimental studies to estimate the distribution of incubation period and also identify and explain the variation in the distribution between studies. We tested for heterogeneity using I2 and Kolmogorov–Smirnov tests, regressed incubation period against possible explanatory factors, and used hierarchical clustering analysis to define subgroups of studies without evidence of heterogeneity. The mean incubation period of subgroups ranged from 2·5 to 4·3 days. We observed variation in the distribution of incubation period between studies that was not due to chance. A significant association between the mean incubation period and age distribution was observed with outbreaks involving only children reporting an incubation of 1·29 days longer when compared with outbreaks involving other age groups.

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Estimation of Incubation Period and Serial Interval for SARS-CoV-2 in Jiangxi, China, and an Updated Meta-Analysis

The Journal of Infection in Developing Countries ◽

10.3855/jidc.14025 ◽

2021 ◽

Vol 15 (03) ◽

pp. 326-332

Author(s):

Tianchen Zhang ◽

Sheng Ding ◽

Zhili Zeng ◽

Huijian Cheng ◽

Chengfeng Zhang ◽

...

Keyword(s):

Incubation Period ◽

Disease Transmission ◽

Meta Analysis ◽

Jiangxi Province ◽

Analysis Method ◽

R Software ◽

Serial Interval

Introduction: This paper aims to estimate the incubation period and serial intervals for SARS-CoV-2 based on confirmed cases in Jiangxi Province of China and meta-analysis method. Methodology: Distributions of incubation period and serial interval of Jiangxi epidemic data were fitted by “fitdistrplus” package of R software, and the meta-analysis was conducted by “meta” package of R software. Results: Based on the epidemic data of Jiangxi, we found the median days of incubation period and serial interval were 5.9 days [IQR: 3.8 – 8.6] and 5.7 days [IQR: 3.6 – 8.3], respectively. The median days of the infectivity period at pre-symptomatic was 1.7 days [IQR: 1.1 – 2.4]. The meta-analysis based on 64 papers showed the pooled means of the incubation period and serial interval were 6.25 days (95% CrI: 5.75 – 6.75) and 5.15 days (95% CrI: 4.73 – 5.57), respectively. Conclusions: Our results contribute to a better understanding of COVID-19 and provide useful parameters for modelling the dynamics of disease transmission. The serial interval is shorter than the incubation period, which indicates that the patients are infectious at pre-symptomatic period, and isolation of detected cases alone is likely to be difficult to halt the spread of SARS-CoV-2.

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The incubation period of COVID-19: a global meta-analysis of 53 studies and a Chinese observation study of 11 545 patients

Infectious Diseases of Poverty ◽

10.1186/s40249-021-00901-9 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Cheng Cheng ◽

DongDong Zhang ◽

Dejian Dang ◽

Juan Geng ◽

Peiyu Zhu ◽

...

Keyword(s):

Incubation Period ◽

Meta Analysis ◽

Random Effect ◽

Random Effect Model ◽

Observation Study ◽

Effect Model ◽

Time Of Infection ◽

The Mainland Of China ◽

The Mean ◽

Log Normal

Abstract Background The incubation period is a crucial index of epidemiology in understanding the spread of the emerging Coronavirus disease 2019 (COVID-19). In this study, we aimed to describe the incubation period of COVID-19 globally and in the mainland of China. Methods The searched studies were published from December 1, 2019 to May 26, 2021 in CNKI, Wanfang, PubMed, and Embase databases. A random-effect model was used to pool the mean incubation period. Meta-regression was used to explore the sources of heterogeneity. Meanwhile, we collected 11 545 patients in the mainland of China outside Hubei from January 19, 2020 to September 21, 2020. The incubation period fitted with the Log-normal model by the coarseDataTools package. Results A total of 3235 articles were searched, 53 of which were included in the meta-analysis. The pooled mean incubation period of COVID-19 was 6.0 days (95% confidence interval [CI] 5.6–6.5) globally, 6.5 days (95% CI 6.1–6.9) in the mainland of China, and 4.6 days (95% CI 4.1–5.1) outside the mainland of China (P = 0.006). The incubation period varied with age (P = 0.005). Meanwhile, in 11 545 patients, the mean incubation period was 7.1 days (95% CI 7.0–7.2), which was similar to the finding in our meta-analysis. Conclusions For COVID-19, the mean incubation period was 6.0 days globally but near 7.0 days in the mainland of China, which will help identify the time of infection and make disease control decisions. Furthermore, attention should also be paid to the region- or age-specific incubation period. Graphic Abstract

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The incubation period during the pandemic of COVID-19: a systematic review and meta-analysis

Systematic Reviews ◽

10.1186/s13643-021-01648-y ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Wafa Dhouib ◽

Jihen Maatoug ◽

Imen Ayouni ◽

Nawel Zammit ◽

Rim Ghammem ◽

...

Keyword(s):

Systematic Review ◽

Incubation Period ◽

Meta Analysis ◽

Population Based ◽

Parametric Models ◽

Moderator Variables ◽

Method Of Calculation ◽

Study Heterogeneity ◽

The Mean ◽

Meta Analyses

Abstract Background The aim of our study was to determine through a systematic review and meta-analysis the incubation period of COVID-19. It was conducted based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). Criteria for eligibility were all published population-based primary literature in PubMed interface and the Science Direct, dealing with incubation period of COVID-19, written in English, since December 2019 to December 2020. We estimated the mean of the incubation period using meta-analysis, taking into account between-study heterogeneity, and the analysis with moderator variables. Results This review included 42 studies done predominantly in China. The mean and median incubation period were of maximum 8 days and 12 days respectively. In various parametric models, the 95th percentiles were in the range 10.3–16 days. The highest 99th percentile would be as long as 20.4 days. Out of the 10 included studies in the meta-analysis, 8 were conducted in China, 1 in Singapore, and 1 in Argentina. The pooled mean incubation period was 6.2 (95% CI 5.4, 7.0) days. The heterogeneity (I2 77.1%; p < 0.001) was decreased when we included the study quality and the method of calculation used as moderator variables (I2 0%). The mean incubation period ranged from 5.2 (95% CI 4.4 to 5.9) to 6.65 days (95% CI 6.0 to 7.2). Conclusions This work provides additional evidence of incubation period for COVID-19 and showed that it is prudent not to dismiss the possibility of incubation periods up to 14 days at this stage of the epidemic.

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Epidemiological Characteristics of COVID-19; a Systemic Review and Meta-Analysis

10.1101/2020.04.01.20050138 ◽

2020 ◽

Cited By ~ 3

Author(s):

Malahat Khalili ◽

Mohammad Karamouzian ◽

Naser Nasiri ◽

Sara Javadi ◽

Ali Mirzazadeh ◽

...

Keyword(s):

Incubation Period ◽

Viral Infections ◽

Virus Disease ◽

Data Extraction ◽

Meta Analysis ◽

Senior Author ◽

Systemic Review ◽

Medical Visit ◽

Icu Admission ◽

Epidemiological Characteristics

AbstractBackgroundOur understanding of the corona virus disease 2019 (COVID-19) continues to evolve. However, there are many unknowns about its epidemiology.PurposeTo synthesize the number of deaths from confirmed COVID-19 cases, incubation period, as well as time from onset of COVID-19 symptoms to first medical visit, ICU admission, recovery and death of COVID-19.Data SourcesMEDLINE, Embase, and Google Scholar from December 01, 2019 through to March 11, 2020 without language restrictions as well as bibliographies of relevant articles.Study SelectionQuantitative studies that recruited people living with or died due to COVID-19.Data ExtractionTwo independent reviewers extracted the data. Conflicts were resolved through discussion with a senior author.Data SynthesisOut of 1675 non-duplicate studies identified, 57 were included. Pooled mean incubation period was 5.84 (99% CI: 4.83, 6.85) days. Pooled mean number of days from the onset of COVID-19 symptoms to first clinical visit was 4.82 (95% CI: 3.48, 6.15), ICU admission was 10.48 (95% CI: 9.80, 11.16), recovery was 17.76 (95% CI: 12.64, 22.87), and until death was 15.93 (95% CI: 13.07, 18.79). Pooled probability of COVID-19-related death was 0.02 (95% CI: 0.02, 0.03).LimitationsStudies are observational and findings are mainly based on studies that recruited patient from clinics and hospitals and so may be biased toward more severe cases.ConclusionWe found that the incubation period and lag between the onset of symptoms and diagnosis of COVID-19 is longer than other respiratory viral infections including MERS and SARS; however, the current policy of 14 days of mandatory quarantine for everyone might be too conservative. Longer quarantine periods might be more justified for extreme cases.FundingNone.Protocol registrationOpen Science Framework: https://osf.io/a3k94/

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