Incubation period of COVID-19: A systematic review and meta-analysis.
Ontology highlight
ABSTRACT: Background and objective
The incubation period of COVID-19 helps to determine the optimal duration of the quarantine and inform predictive models of incidence curves. Several emerging studies have produced varying results; this systematic review aims to provide a more accurate estimate of the incubation period of COVID-19.Methods
For this systematic review, a literature search was conducted using Pubmed, Scopus/EMBASE, and the Cochrane Library databases, covering all observational and experimental studies reporting the incubation period and published from 1 January 2020 to 21 March 2020.We estimated the mean and 95th percentile of the incubation period using meta-analysis, taking into account between-study heterogeneity, and the analysis with moderator variables.Results
We included seven studies (n=792) in the meta-analysis. The heterogeneity (I2 83.0%, p<0.001) was significantly decreased when we included the study quality and the statistical model used as moderator variables (I2 15%). The mean incubation period ranged from 5.6 (95% CI: 5.2-6.0) to 6.7 days (95% CI: 6.0-7.4) according to the statistical model. The 95th percentile was 12.5 days when the mean age of patients was 60 years, increasing 1 day for every 10 years.Conclusion
Based on the published data reporting the incubation period of COVID-19, the mean time between exposure and onset of clinical symptoms depended on the statistical model used, and the 95th percentile depended on the mean age of the patients. It is advisable to record sex and age when collecting data in order to analyze possible differential patterns.
SUBMITTER: Quesada JA
PROVIDER: S-EPMC7698828 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background and objectiveThe incubation period of COVID-19 helps to determine the optimal duration of the quarantine and inform predictive models of incidence curves. Several emerging studies have produced varying results; this systematic review aims to provide a more accurate estimate of the incubation period of COVID-19.MethodsFor this systematic review, a literature search was conducted using Pubmed, Scopus/EMBASE, and the Cochrane Library databases, covering all observational and experimental studies reporting the incubation period and published from 1 January 2020 to 21 March 2020.We estimated the mean and 95th percentile of the incubation period using meta-analysis, taking into account between-study heterogeneity, and the analysis with moderator variables.ResultsWe included seven studies (n = 792) in the meta-analysis. The heterogeneity (I2 83.0%, p < 0.001) was significantly decreased when we included the study quality and the statistical model used as moderator variables (I2 15%). The mean incubation period ranged from 5.6 (95% CI: 5.2 to 6.0) to 6.7 days (95% CI: 6.0 to 7.4) according to the statistical model. The 95th percentile was 12.5 days when the mean age of patients was 60 years, increasing 1 day for every 10 years.ConclusionBased on the published data reporting the incubation period of COVID-19, the mean time between exposure and onset of clinical symptoms depended on the statistical model used, and the 95th percentile depended on the mean age of the patients. It is advisable to record sex and age when collecting data in order to analyze possible differential patterns.
| S-EPMC7528969 | biostudies-literature
Project description:BackgroundUnderstanding the epidemiological parameters that determine the transmission dynamics of COVID-19 is essential for public health intervention. Globally, a number of studies were conducted to estimate the average serial interval and incubation period of COVID-19. Combining findings of existing studies that estimate the average serial interval and incubation period of COVID-19 significantly improves the quality of evidence. Hence, this study aimed to determine the overall average serial interval and incubation period of COVID-19.MethodsWe followed the PRISMA checklist to present this study. A comprehensive search strategy was carried out from international electronic databases (Google Scholar, PubMed, Science Direct, Web of Science, CINAHL, and Cochrane Library) by two experienced reviewers (MAA and DBK) authors between the 1st of June and the 31st of July 2020. All observational studies either reporting the serial interval or incubation period in persons diagnosed with COVID-19 were included in this study. Heterogeneity across studies was assessed using the I2 and Higgins test. The NOS adapted for cross-sectional studies was used to evaluate the quality of studies. A random effect Meta-analysis was employed to determine the pooled estimate with 95% (CI). Microsoft Excel was used for data extraction and R software was used for analysis.ResultsWe combined a total of 23 studies to estimate the overall mean serial interval of COVID-19. The mean serial interval of COVID-19 ranged from 4. 2 to 7.5 days. Our meta-analysis showed that the weighted pooled mean serial interval of COVID-19 was 5.2 (95%CI: 4.9-5.5) days. Additionally, to pool the mean incubation period of COVID-19, we included 14 articles. The mean incubation period of COVID-19 also ranged from 4.8 to 9 days. Accordingly, the weighted pooled mean incubation period of COVID-19 was 6.5 (95%CI: 5.9-7.1) days.ConclusionsThis systematic review and meta-analysis showed that the weighted pooled mean serial interval and incubation period of COVID-19 were 5.2, and 6.5 days, respectively. In this study, the average serial interval of COVID-19 is shorter than the average incubation period, which suggests that substantial numbers of COVID-19 cases will be attributed to presymptomatic transmission.
| S-EPMC7948654 | biostudies-literature
Project description: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.
| S-EPMC7430485 | biostudies-literature
Project description:BackgroundThe 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.ResultsThis 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).ConclusionsThis 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.
| S-EPMC8031340 | biostudies-literature
Project description:PurposeTo estimate the central tendency and dispersion for incubation period of COVID-19 and, in turn, assess the effect of a certain length of quarantine for close contacts in active monitoring.MethodsLiterature related to SARS-CoV-2 and COVID-19 was searched through April 26, 2020. Quality was assessed according to Agency for Healthcare Research and Quality guidelines. Log-normal distribution for the incubation period was assumed to estimate the parameters for each study. Incubation period median and dispersion were estimated, and distribution was simulated.ResultsFifty-six studies encompassing 4095 cases were included in this meta-analysis. The estimated median incubation period for general transmissions was 5.8 days [95% confidence interval (95% CI): 5.3, 6.2]. Incubation period was significantly longer for asymptomatic transmissions (median: 7.7 days; 95% CI 6.3, 9.4) than for general transmissions (P = 0.0408). Median and dispersion were higher for SARS-CoV-2 incubation compared to other viral respiratory infections. Furthermore, about 12 in 10,000 contacts in active monitoring would develop symptoms after 14 days, or below 1 in 10,000 for asymptomatic transmissions. Meta-regression suggested that each 10-year increase in age resulted in an average 16% increment in length of median incubation (incubation period ratio, 1.16, 95% CI 1.01, 1.32; P = 0.0250).ConclusionThis study estimated the median and dispersion of the SARS-CoV-2 incubation period more precisely. A 14-day quarantine period is sufficient to trace and identify symptomatic infections.
| S-EPMC8372687 | biostudies-literature
Project description:Accurate 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 I 2 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.
| S-EPMC9148824 | biostudies-literature
Project description:Recent large cholera outbreaks highlight the need for improved understanding of the pathogenesis and epidemiology of cholera. The incubation period of cholera has important implications for clinical and public health decision-making, yet statements of the incubation period of cholera are often imprecise. Here we characterize the distribution of cholera's incubation period.We conducted a systematic review of the literature for statements of the incubation period of cholera and data that might aid in its estimation. We extracted individual-level data, parametrically estimated the distribution of toxigenic cholera's incubation period, and evaluated evidence for differences between strains.The incubation period did not differ by a clinically significant margin between strains (except O1 El Tor Ogawa). We estimate the median incubation period of toxigenic cholera to be 1.4 days (95% CI, 1.3-1.6). Five percent of cholera cases will develop symptoms by 0.5 days (95% CI 0.4-0.5), and 95% by 4.4 days (95% CI 3.9-5.0) after infection.We recommend that cholera investigations use a recall period of at least five days to capture relevant exposures; significantly longer than recent risk factor studies from the Haitian epidemic. This characterization of cholera's incubation period can help improve clinical and public health practice and advance epidemiologic research.
| S-EPMC3677557 | biostudies-literature
Project description:ObjectiveTo estimate the incubation period of Vietnamese confirmed COVID-19 cases.MethodsOnly confirmed COVID-19 cases who are Vietnamese and locally infected with available data on date of symptom onset and clearly defined window of possible SARS-CoV-2 exposure were included. We used three parametric forms with Hamiltonian Monte Carlo method for Bayesian Inference to estimate incubation period for Vietnamese COVID-19 cases. Leave-one-out Information Criterion was used to assess the performance of three models.ResultsA total of 19 cases identified from 23 Jan 2020 to 13 April 2020 was included in our analysis. Average incubation periods estimated using different distribution model ranged from 6.0 days to 6.4 days with the Weibull distribution demonstrated the best fit to the data. The estimated mean of incubation period using Weibull distribution model was 6.4 days (95% credible interval (CrI): 4.89-8.5), standard deviation (SD) was 3.05 (95%CrI 3.05-5.30), median was 5.6, ranges from 1.35 to 13.04 days (2.5th to 97.5th percentiles). Extreme estimation of incubation periods is within 14 days from possible infection.ConclusionThis analysis provides evidence for an average incubation period for COVID-19 of approximately 6.4 days. Our findings support existing guidelines for 14 days of quarantine of persons potentially exposed to SARS-CoV-2. Although for extreme cases, the quarantine period should be extended up to three weeks.
| S-EPMC7757798 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) has become a global pandemic, affecting millions of people. However, the relationship between COVID-19 and acute cerebrovascular diseases is unclear.AimsWe aimed to characterize the incidence, risk factors, clinical-radiological manifestations, and outcome of COVID-19-associated stroke.MethodsThree medical databases were systematically reviewed for published articles on acute cerebrovascular diseases in COVID-19 (December 2019-September 2020). The review protocol was previously registered (PROSPERO ID?=?CRD42020185476). Data were extracted from articles reporting ?5 stroke cases in COVID-19. We complied with the PRISMA guidelines and used the Newcastle-Ottawa Scale to assess data quality. Data were pooled using a random-effect model.Summary of reviewOf 2277 initially identified articles, 61 (2.7%) were entered in the meta-analysis. Out of 108,571 patients with COVID-19, acute CVD occurred in 1.4% (95%CI: 1.0-1.9). The most common manifestation was acute ischemic stroke (87.4%); intracerebral hemorrhage was less common (11.6%). Patients with COVID-19 developing acute cerebrovascular diseases, compared to those who did not, were older (pooled median difference?=?4.8 years; 95%CI: 1.7-22.4), more likely to have hypertension (OR?=?7.35; 95%CI: 1.94-27.87), diabetes mellitus (OR?=?5.56; 95%CI: 3.34-9.24), coronary artery disease (OR?=?3.12; 95%CI: 1.61-6.02), and severe infection (OR?=?5.10; 95%CI: 2.72-9.54). Compared to individuals who experienced a stroke without the infection, patients with COVID-19 and stroke were younger (pooled median difference?=?-6.0 years; 95%CI: -12.3 to -1.4), had higher NIHSS (pooled median difference?=?5; 95%CI: 3-9), higher frequency of large vessel occlusion (OR?=?2.73; 95%CI: 1.63-4.57), and higher in-hospital mortality rate (OR?=?5.21; 95%CI: 3.43-7.90).ConclusionsAcute cerebrovascular diseases are not uncommon in patients with COVID-19, especially in those whom are severely infected and have pre-existing vascular risk factors. The pattern of large vessel occlusion and multi-territory infarcts suggests that cerebral thrombosis and/or thromboembolism could be possible causative pathways for the disease.
| S-EPMC7859578 | biostudies-literature
Project description:Background: Due to lack of preparedness of health systems, fast spread of the new virus, high mortality rates, and lack of a definite treatment, the outbreak of Coronavirus disease (COVID-19) led to high levels of fear and anxiety in different populations. In addition, isolation, mental disorders, and limitations in social interactions as a result of lockdown and travel ban increased the fear of the new coronavirus. Methods: International databases, including Scopus, PubMed, Web of Science, and Google scholar, were searched without any time limitation, and all observational studies published in English reporting the mean of fear of COVID-19 based on the Fear of COVID-19 scale (FCV-19S) were included in the analysis. Methodological quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Random effects model, subgroup analysis, and meta-regression analysis were used to analyze the data. Heterogeneity across studies was examined using Cochran's Q test and I 2 statistic. All the statistical analyses were conducted using R software v4.0.3. Results: A total of 44 articles with a sample size of 52,462 were reviewed. A pooled mean of 18.57 was found for fear of COVID-19. The mean of fear of COVID-19 was higher in women than in men (20.67 vs. 18.21). The highest and lowest means of fear of COVID-19 had been found in Asia (18.36) and Australia (17.43) based on continent, and in hospital staff (19.51) and college students (17.95) based on target population, respectively. In addition, the highest and lowest means of fear of COVID-19 were related to items #1 and #3 of the scale, respectively. According to the results of meta-regression analysis, there was no significant association between the mean of fear of COVID-19 and sample size and participants' age. In addition, publication error was not significant (P = 0.721). Conclusion: The mean of fear of COVID-19 was high around the world; therefore, it seems necessary to pay more attention to the negative effects of the COVID-19 pandemic on mental health.
| S-EPMC8231929 | biostudies-literature