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

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.

scholarly journals The incubation period of COVID-19 – A rapid systematic review and meta-analysis of observational research

2020 ◽  
Author(s):  
Conor G. McAloon ◽  
Áine B. Collins ◽  
Kevin Hunt ◽  
Ann Barber ◽  
Andrew W. Byrne ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Incubation Period ◽  
Lognormal Distribution ◽  
Meta Analysis ◽  
Observational Research ◽  
List Type ◽  
Period Distribution ◽  
Incubation Periods ◽  
Inform Decision Making

ABSTRACTBackgroundReliable estimates of the incubation period are important for decision making around the control of infectious diseases. Knowledge of the incubation period distribution can be used directly to inform decision-making or as inputs into mathematical models.ObjectivesThe aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation periods of COVID-19.DesignRapid systematic review and meta-analysis of observational researchData sourcesPublications on the electronic databases PubMed, Google Scholar, MedRxiv and BioRxiv were searched. The search was not limited to peer-reviewed published data, but also included pre-print articles.Study appraisal and synthesis methodsStudies were selected for meta-analysis if they reported either the parameters and confidence intervals of the distributions fit to the data, or sufficient information to facilitate calculation of those values. The majority of studies suitable for inclusion in the final analysis modelled incubation period as a lognormal distribution. We conducted a random effects meta-analysis of the parameters of this distribution.ResultsThe incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters of 1.63 (1.51, 1.75) and 0.50 (0.45, 0.55) respectively. The corresponding mean was 5.8 (5.01, 6.69 days). It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates resulted in a median incubation period of 5.1 (4.5, 5.8) days, whereas the 95th percentile was 11.6 (9.5, 14.2) days.Conclusions and implicationsThe 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. Finally, we present an RShiny app that facilitates updating these estimates as new data become available.ARTICLE SUMMARYStrengths and limitations of this studyThis study provides a pooled estimate of the distribution of incubation periods which may be used in subsequent modelling studies or to inform decision-makingThis estimate will need to be revisited as subsequent data become available. We present an RShiny app to allow the meta-analysis to be updated with new estimates

The effects of corticosteroids on rabies in mice

1970 ◽  
Vol 16 (8) ◽  
pp. 667-675 ◽  
Author(s):  
J. B. Enright ◽  
C. E. Franti ◽  
F. L. Frye ◽  
D. E. Behymer
Keyword(s):  
Incubation Period ◽  
Rabies Virus ◽  
Day Treatment ◽  
Steroid Treatment ◽  
Time Of Death ◽  
Virus Inoculation ◽  
Mortality Pattern ◽  
Delayed Onset ◽  
Incubation Periods ◽  
The Mean

Corticosteroid (2–3 mg, 1 mg/day) treatment of mice started within 24 h after rabies virus inoculation increased mortality up to 20% above that in nontreated mice. In contrast, steroid treatment started 48, 72, or 96 h after rabies virus inoculation did not significantly increase mortality. Up to 50% higher mortality occurred in the corticosteroid-treated mice than in the controls after small dosages of rabies virus were injected.In addition to consistently higher mortality, corticosteroid used in conjunction with rabies virus resulted in two changes in the mortality pattern: shortening of the mean incubation period of rabies in mice receiving an LD50 dose, and an aggravation of sublethal infections, causing deaths with abnormally or comparatively long incubation periods in mice that otherwise might have survived. These two actions increased the variability in time of onset and time of death, with an increase in early as well as in late (delayed) onset times.

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

2017 ◽  
Vol 145 (11) ◽  
pp. 2241-2253 ◽  
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.

scholarly journals Transmission interval estimates suggest pre-symptomatic spread of COVID-19

2020 ◽  
Author(s):  
Lauren C. Tindale ◽  
Michelle Coombe ◽  
Jessica E. Stockdale ◽  
Emma S. Garlock ◽  
Wing Yin Venus Lau ◽  
...  
Keyword(s):  
Incubation Period ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Interval Estimates ◽  
Secondary Infections ◽  
Serial Interval ◽  
Incubation Periods ◽  
Key Variables ◽  
The Mean ◽  
Interval Distribution

AbstractBackgroundAs the COVID-19 epidemic is spreading, incoming data allows us to quantify values of key variables that determine the transmission and the effort required to control the epidemic. We determine the incubation period and serial interval distribution for transmission clusters in Singapore and in Tianjin. We infer the basic reproduction number and identify the extent of pre-symptomatic transmission.MethodsWe collected outbreak information from Singapore and Tianjin, China, reported from Jan.19-Feb.26 and Jan.21-Feb.27, respectively. We estimated incubation periods and serial intervals in both populations.ResultsThe mean incubation period was 7.1 (6.13, 8.25) days for Singapore and 9 (7.92, 10.2) days for Tianjin. Both datasets had shorter incubation periods for earlier-occurring cases. The mean serial interval was 4.56 (2.69, 6.42) days for Singapore and 4.22 (3.43, 5.01) for Tianjin. We inferred that early in the outbreaks, infection was transmitted on average 2.55 and 2.89 days before symptom onset (Singapore, Tianjin). The estimated basic reproduction number for Singapore was 1.97 (1.45, 2.48) secondary cases per infective; for Tianjin it was 1.87 (1.65, 2.09) secondary cases per infective.ConclusionsEstimated serial intervals are shorter than incubation periods in both Singapore and Tianjin, suggesting that pre-symptomatic transmission is occurring. Shorter serial intervals lead to lower estimates of R0, which suggest that half of all secondary infections should be prevented to control spread.

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

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

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

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.

scholarly journals The Epidemiology, Transmissions and Risk Factors of SARS-CoV-2

2020 ◽  
Vol 3 (1) ◽  
pp. 28-43
Author(s):  
Roberto Badaró ◽  
Bruna Aparecida Souza Machado ◽  
Milena Soares ◽  
Luciana Knop
Keyword(s):  
Risk Factors ◽  
Incubation Period ◽  
Clinical Investigation ◽  
Meta Analysis ◽  
Case Fatality ◽  
Epidemiological Data ◽  
Mitigation Strategies ◽  
World Health ◽  
Medical Subject Headings ◽  
Novel Coronavirus

The outbreak of a novel coronavirus (SARS-CoV-2) and associated COVID-19 disease in late December 2019 has led to a global pandemic, spreading very quickly and causing a more than 500,000 deaths in less than six monhs of the ourbreak. The incidence differs by country and depends on many agents, such as population density, demography, the amount of testing people and reporting, and actions of mitigation strategies, provisions of sanitary and education of the society. In this article, we presented the current studies about the epidemiology of COVID-19, including the transmission routes of the SARS-CoV-2, the incubation period, the reproduction number (R0), the case fatality risks (CFR), comorbidities and measures prevention against COVID-19. We searched the articles in the main database (PubMed/Medline, Elsevier Science Direct, Scopus, Isi Web of Science, Embase, Exerpta Medica, UptoDate, Lilacs, Novel Coronavirus Resource Directory from Elsevier), in the high-impact international scientific Journals (Scimago Journal and Country Rank - SJR - and Journal Citation Reports - JCR), such as The Lancet, Science, Nature, The New England Journal of Medicine, Physiological Reviews, Journal of the American Medical Association, Plos One, Journal of Clinical Investigation, and in the data from Center for Disease Control (CDC), National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID) and World Health Organization (WHO). We prior selected meta-analysis, systematic reviews, article reviews and original articles in this order. We reviewed 235 articles and used 131 from March to June 2020, using the terms coronavirus, SARS-CoV-2, novel coronavirus, Wuhan coronavirus, severe acute respiratory syndrome, 2019-nCoV, 2019 novel coronavirus, n-CoV-2, covid, n-Sars-2, COVID-19, corona virus, coronaviruses, epodemiology of COVID-19, risk factors, viral spreading, transmissions, routes, animals incubation, period, RO, CFR, comorbidities, prevention, with the tools MeSH (Medical Subject Headings), AND, OR, and characters [,“,; /., to ensure the best review topics. We concluded that the epidemiological data is very important to know the transmission risks rate, purpose public political policies of mitigating the disease, protect the vulnerable population. Also, it is important reconsider the legislation about wild animals, the potential intermediate host(s) of various viruses, as well as the conditions of live for animals for human comsuption to prevent future outbreaks.

scholarly journals Antibiotics resistance and mitigation strategies in healthcare settings: A scoping review

2020 ◽  
Author(s):  
Bernard Okeah ◽  
Jaci Huws ◽  
Valerie Morrison
Keyword(s):  
Klebsiella Pneumoniae ◽  
Scoping Review ◽  
Meta Analysis ◽  
Significant Proportion ◽  
Mitigation Strategies ◽  
Antibiotics Resistance ◽  
Drug Resistant ◽  
Feedback Systems ◽  
Healthcare Settings ◽  
Healthcare Associated

AbstractBackgroundAccording to the European Center for Disease Prevention and Control (ECDC), the EU records an estimated 3.2 million healthcare associated infections (HAIs) and an associated 37,000 deaths annually. A significant proportion of the HAIs burden is attributable to multi-drug resistant pathogens. Infectious diseases remain top on the list of the leading causes of death globally with multi-drug resistant microorganisms (MDROs) playing a significant role.AimsTo assess the breadth of studies on antibiotics stewardship C. diff and Klebsiella pneumoniae in healthcare settings. To identify existing literature on the interventions for reducing healthcare associated C. diff and Klebsiella pneumoniae transmission.MethodsThis scoping review was undertaken and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P) guidelines. The specific databases searched included MEDLINE, PubMed, Web of Science Core Collection, and CINAHL. The process for screening articles and data extraction was undertaken in duplicate by two reviewers. A narrative synthesis of the results is provided.ResultsThe review included 34 studies (16 studies on Clostridium difficile and 18 articles focussed on Klebsiella pneumoniae). These interventions include Education, Surveillance/Screening, Consultations, Audits, Policies/Protocols, Environmental disinfection, Bundles, Isolation, and Notifications or alerts (ESCAPE-BIN). A study involving screening, alerts, staff education, and antimicrobial protocols recorded a 75% reduction in the use of targeted antimicrobials. The largest absolute reduction in antimicrobial use of 310 DDs/1000PDs was reported from an intervention that involved audits and feedback systems. The highest improvement (95%) in adherence was reported by an intervention involving the use of an infection prevention bundle and an environmental cleaning protocol.ConclusionAntimicrobial resistance represents a global threat requiring urgent measures to protect lives. Reducing the burden of AMR entails a host of multi-level approaches aimed at curbing transmission of the resistant pathogens, and optimizing the use of antibiotics.

scholarly journals Serial interval and incubation period of COVID-19: a systematic review and meta-analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Muluneh Alene ◽  
Leltework Yismaw ◽  
Moges Agazhe Assemie ◽  
Daniel Bekele Ketema ◽  
Wodaje Gietaneh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Incubation Period ◽  
Meta Analysis ◽  
Random Effect ◽  
Public Health Intervention ◽  
Cochrane Library ◽  
Cross Sectional ◽  
Serial Interval ◽  
The Mean

Abstract Background Understanding 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. Methods We 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. Results We 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. Conclusions This 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.

scholarly journals Sex ratio of the green sea turtle Chelonia mydas (Testudines: Cheloniidae) hatchlings in the Guanahacabibes Peninsula, Cuba

2020 ◽  
Vol 68 (3) ◽  
Author(s):  
Randy Calderón-Peña ◽  
Ryan Betancourt-Avila ◽  
Elizabeth Rodríguez-Fajardo ◽  
Yoel Martínez-González ◽  
Julia Azanza Ricardo
Keyword(s):  
Sex Ratio ◽  
Incubation Period ◽  
Chelonia Mydas ◽  
Sea Turtle ◽  
Nest Temperature ◽  
Data Loggers ◽  
Incubation Periods ◽  
The Mean ◽  
Study Sites ◽  
Incubation Temperatures

Introduction: Sea turtles have temperature dependent sex determination. The increase in global temperature leads to higher nest temperatures that can cause a prevalence of females, threatening the future of these species. Objective: The present work aims to evaluate the trend of incubation temperatures and the incubation period, as well as to estimate the sex ratio in nests of Chelonia mydas at Antonio and La Barca beaches, Southwestern Cuba, during the seasons from 2012 to 2018. Methods: Temperature data loggers were placed in green turtle nests with a representativeness that varied between the years analyzed. To assess the temporal variation of temperatures and incubation periods, a Kruskal-Wallis test was performed in each case. Sex ratio was estimated from its relation with temperature and incubation duration. Results: At La Barca beach, there was a 1.5 °C increase in the mean nest temperature from 2012 to 2018, although no differences were found in the period from 2015 to 2018. At Antonio beach, there is no trend since no differences were found in the mean nest temperature except for the years 2013 and 2017, which had lower temperatures than the other seasons. In both beaches mean nest temperature exceeded 30 °C in most of the years. As a result, there was a predominance of nests with incubation periods shorter than 55 days. With these values, a female hatchling production over 90 % is expected in both study sites. Conclusions: In correspondence with the registered temperature and incubation period values, most of the years reflect a hatchling production biased towards females in both beaches.

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