The incubation period during the pandemic of COVID-19: a systematic review and meta-analysis.
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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.
SUBMITTER: Dhouib W
PROVIDER: S-EPMC8031340 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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: 5.2-6.0) 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.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.
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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.
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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: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.
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Project description:The purpose of this study was to assess the impact of measures designed to mitigate the spread of coronavirus disease 2019 (COVID-19) on worldwide cancer screening. We systematically searched PubMed, Ovid MEDLINE, the Cochrane COVID-19 Study Register, ClinicalTrials.gov, and EMBASE without language restrictions for studies published between January 1, 2021, and February 10, 2021. Studies selected for full-text review contained data on patients screened for any type of cancer during the COVID-19 pandemic and comparison data from a time interval just prior to the pandemic. Data were obtained through dual extraction. All the included studies were assessed for quality and risk of bias. A meta-analysis was performed on 13 studies: 7 on screening mammography, 5 on colon cancer screening, and 3 on cervical cancer screening. Two of our studies reported on more than one type of cancer screening. The screening outcomes were reported as pooled incidence rate ratios using the inverse variance method and random effects models. All studies included in our meta-analysis reported the number of patients screened for cancer in defined time intervals before and during the COVID-19 pandemic. We found that the pooled incidence rate ratios were significantly lower for screening during the COVID-19 pandemic for breast cancer (0.63; 95% CI, 0.53 to 0.77; P<.001), colon cancer (0.11; 95% CI, 0.05 to 0.24; P<.001), and cervical cancer (0.10; 95% CI, 0.04 to 0.24; P<.001). These findings may add further morbidity and mortality to this public health crisis.
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Project description:This systematic review and meta-analysis evaluated the extent of sleep disturbances during the COVID-19 pandemic. Eleven databases and six preprint repositories were searched for the period from November 1, 2019, to July 15, 2021. The DerSimonian and Laird method was used to develop random-effect meta-analyses. Two hundred and fifty studies comprising 493,475 participants from 49 countries were included. During COVID-19, the estimated global prevalence of sleep disturbances was 40.49% [37.56; 43.48%]. Bayesian meta-analysis revealed an odds of 0.68 [0.59; 0.77] which translates to a rate of approximately 41%. This provides reassurance that the estimated rate using classical meta-analysis is robust. Six major populations were identified; the estimated prevalence of sleep problem was 52.39% [41.69; 62.88%] among patients infected with COVID-19, 45.96% [36.90; 55.30%] among children and adolescents, 42.47% [37.95; 47.12%] among healthcare workers, 41.50% [32.98; 50.56%] among special populations with healthcare needs, 41.16% [28.76; 54.79%] among university students, and 36.73% [32.32; 41.38%] among the general population. Sleep disturbances were higher during lockdown compared to no lockdown, 42.49% versus 37.97%. Four in every ten individuals reported a sleep problem during the COVID-19 pandemic. Patients infected with the disease, children, and adolescents appeared to be the most affected groups.
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Project description:Study objectivesNo systematic review or meta-analysis has yet been conducted to examine the impact of the pandemic on the prevalence of sleep problems among the general population, health care workers, or patients with COVID-19. Therefore, this systematic review was conducted to assess the impact and prevalence of sleep problems among those categories.MethodsAmerican Psychological Association PsycINFO, Cochrane, Cumulative Index to Nursing and Allied Health Literature (CINAHL), EBSCOhost, EMBASE, Google Scholar, MEDLINE, ProQuest Medical, ScienceDirect, Scopus, and Web of Science from November 1, 2019 to July 5, 2020 were used. Additionally, 5 preprints servers (medRxiv.org; preprints.org; psyarxiv.com; arXiv.org; biorxiv.org) were also searched for papers accepted after peer review but not yet published and indexed. There was no language restriction. The random-effect models meta-analysis model was used with the DerSimonian and Laird methodology.ResultsForty-four papers, involving a total of 54,231 participants from 13 countries, were judged relevant and contributed to the systematic review and meta-analysis of sleep problems during COVID-19. The global pooled prevalence rate of sleep problems among all populations was 35.7% (95% confidence interval, 29.4-42.4%). Patients with COVID-19 appeared to be the most affected group, with a pooled rate of 74.8% (95% confidence interval, 28.7-95.6%). Health care workers and the general population had comparative rates of sleep problems, with rates of 36.0% (95% confidence interval, 21.1-54.2%) and 32.3% (95% confidence interval, 25.3-40.2%), respectively.ConclusionsThe prevalence of sleep problems during the COVID-19 pandemic is high and affects approximately 40% of people from the general and health care populations. Patients with active COVID-19 appeared to have a higher prevalence rates of sleep problems.
| S-EPMC7853219 | biostudies-literature
Project description:BackgroundDuring the COVID-19 pandemic in 2020 a decrease of emergency consultations and modification in treatment of numerous medical conditions were observed. Aim of this paper was to evaluate the effect of the COVID-19 pandemic on incidence, treatment strategies, severity, length of hospital stay and time of presentation in adults and children with acute appendicitis.MethodsA systematic literature search of Pubmed, Embase and Cochrane databases was performed, and eligible studies used to perform a meta-analysis.Results46 suitable studies were identified with an overall reduction of appendicitis cases by 20.9% in adults and an increase of 13.4% in children. The rate of open appendectomies increased without statistical significance in both groups (adults: 8.5% vs. 7.1%, P = 0.32; children: 7.1% vs. 5.3%, P = 0.13), whereas the rate of antibiotic treatment increased significantly (P = 0.007; P = 0.03). Higher rates of complicated appendicitis were observed in adults (adults: OR 2.00, P < 0.0001; children: OR 1.64, P = 0.12). Time to first consultation did not change significantly (adults: 52.3 vs. 38.5 h - P = 0.057; children: 51.5 vs. 32.0 h - P = 0.062) and length of stay was also not lengthened during the pandemic (adults: 2.9 vs. 2.7 days, P = 0.057; children: 4.2 vs. 3.7 days, P = 0.062).ConclusionThe COVID-19 pandemic of 2020 had major impact on incidence and treatment strategies of acute appendicitis. Results of this meta-analysis might be another hint to support the theory that appendicitis is not a progressive disease and surgeons can safely consider antibiotic therapy for acute uncomplicated appendicitis.
| S-EPMC8539829 | biostudies-literature
Project description:BackgroundThe global COVID-19 pandemic has generated major mental and psychological health problems worldwide. We conducted a meta-analysis to assess the prevalence of depression, anxiety, distress, and insomnia during the COVID-19 pandemic.MethodsWe searched online biomedical databases (PubMed, Embase, Web of Science, Ovid, CNKI, and Wanfang Data) and preprint databases (SSRN, bioRxiv, and MedRxiv) for observational studies from January 1, 2020 to March 16, 2020 investigating the prevalence of mental health problems during the COVID-19 pandemic.ResultsWe retrieved 821 citations from the biomedical databases and 53 citations from the preprint databases: 66 studies with 221,970 participants were included in our meta-analysis. The overall pooled prevalence of depression, anxiety, distress, and insomnia was 31.4%, 31.9%, 41.1% and 37.9%, respectively. Noninfectious chronic disease patients, quarantined persons, and COVID-19 patients had a higher risk of depression (Q=26.73, p<0.01) and anxiety (Q=21.86, p<0.01) than other populations. The general population and non-medical staff had a lower risk of distress than other populations (Q=461.21, p< 0.01). Physicians, nurses, and non-medical staff showed a higher prevalence of insomnia (Q=196.64, p<0.01) than other populations.LimitationsAll included studies were from the early phase of the global pandemic. Additional meta-analyses are needed to obtain more data in all phases of the pandemic.ConclusionsThe COVID-19 pandemic increases the mental health problems of the global population, particularly health care workers, noninfectious chronic disease patients, COVID-19 patients, and quarantined persons. Interventions for mental health are urgently needed for preventing mental health problems.
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