scholarly journals Association of host, agent and environment characteristics and the duration of incubation and symptomatic periods of norovirus gastroenteritis

2014 ◽  
Vol 143 (11) ◽  
pp. 2308-2314 ◽  
Author(s):  
T. DEVASIA ◽  
B. LOPMAN ◽  
J. LEON ◽  
A. HANDEL
Keyword(s):  
Confidence Interval ◽  
Incubation Period ◽  
Environmental Characteristics ◽  
Norovirus Gastroenteritis ◽  
Incubation Periods ◽  
Host Pathogen ◽  
The Mean ◽  
Reported Data

SUMMARYWe analysed the reported duration of incubation and symptomatic periods of norovirus for a dataset of 1022 outbreaks, 64 of which reported data on the average incubation period and 87 on the average symptomatic period. We found the mean and median incubation periods for norovirus to be 32·8 [95% confidence interval (CI) 30·9–34·6] hours and 33·5 (95% CI 32·0–34·0) hours, respectively. For the symptomatic period we found the mean and median to be 44·2 (95% CI 38·9–50·7) hours and 43·0 (95% CI 36·0–48·0) hours, respectively. We further investigated how these average periods were associated with several reported host, agent and environmental characteristics. We did not find any strong, biologically meaningful associations between the duration of incubation or symptomatic periods and the reported host, pathogen and environmental characteristics. Overall, we found that the distributions of incubation and symptomatic periods for norovirus infections are fairly constant and showed little differences with regard to the host, pathogen and environmental characteristics we analysed.

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 Distribution of Incubation Period of COVID-19 in the Canadian Context: Modeling and Computational Study

2020 ◽  
Author(s):  
Subhendu Paul ◽  
Emmanuel Lorin
Keyword(s):  
Confidence Interval ◽  
Incubation Period ◽  
Delay Differential Equations ◽  
Computational Study ◽  
Context Modeling ◽  
Canadian Context ◽  
Incubation Periods ◽  
Delay Differential ◽  
Novel Model ◽  
Good Agreement

Abstract We propose a novel model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost approach to estimate the incubation period.

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 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 Distribution of incubation periods of COVID-19 in the Canadian context

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Subhendu Paul ◽  
Emmanuel Lorin
Keyword(s):  
Computational Complexity ◽  
Confidence Interval ◽  
Differential Equations ◽  
Incubation Period ◽  
Delay Differential Equations ◽  
Canadian Context ◽  
Incubation Periods ◽  
Delay Differential ◽  
Novel Model ◽  
Good Agreement

AbstractWe propose a novel model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost computational complexity to estimate the incubation period.

scholarly journals Distribution of Incubation Period of COVID-19 in the Canadian Context: Modeling and Computational Study

2020 ◽  
Author(s):  
Subhendu Paul ◽  
Emmanuel Lorin
Keyword(s):  
Confidence Interval ◽  
Incubation Period ◽  
Delay Differential Equations ◽  
Computational Study ◽  
Original Model ◽  
Context Modeling ◽  
Canadian Context ◽  
Incubation Periods ◽  
Delay Differential ◽  
Good Agreement

We propose an original model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost approach to estimate the incubation period.

scholarly journals Incubation Period of COVID-19 From 11545 Patients in Observation Study

2021 ◽  
Author(s):  
Cheng Cheng ◽  
Dongdong Zhang ◽  
Dejian Dang ◽  
Juan Geng ◽  
Peiyu Zhu ◽  
...  
Keyword(s):  
Decision Making ◽  
Confidence Interval ◽  
Incubation Period ◽  
Mainland China ◽  
Observation Study ◽  
Male And Female ◽  
Precise Data ◽  
Validation Population ◽  
Significant Difference ◽  
The Mean

Abstract Background The incubation period is a key index of epidemiology in understanding of the spread of infectious diseases and the decision-making of the disease control. However, the incubation period of the emerging COVID-19 is still unclear. Methods Between January 19, 2020 and September 21, 2020, we collected information on 11545 patients in Mainland China outside Hubei. The 218 patients with precise data was validation population. The incubation period was fitted with lognormal model by the coarseDataTools package in R. Results In 11545 patients, the mean incubation period of COVID-19 was 7.1 days (95% Confidence interval [CI], 7.0–7.2). About 5.4% of patients had precise incubation period less than 3 days, 10.2% longer than 14 days, and 2.1% longer than 21 days. There was no statistically significant difference in incubation period between male and female (P = 0.603). It was similar in the 218 patients. The mean accurate incubation period was 6.8 days (6.2–7.4). Of which, 14.7% (32/218) of patients had incubation period less than 3 days, 12.4% (27/218) longer than 14 days, and 0.9% (2/218) longer than 21 days. Conclusions For COVID-19, the mean incubation period is 7.1 days and 10.2% of patients developed disease 14 days after infection, which challenges the current 14-day quarantine strategy.

scholarly journals Estimating the latent period of coronavirus disease 2019 (COVID-19)

2021 ◽  
Author(s):  
Hualei Xin ◽  
Yu Li ◽  
Peng Wu ◽  
Zhili Li ◽  
Eric H Y Lau ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Latent Period ◽  
Incubation Period ◽  
Laboratory Testing ◽  
The Mean

Abstract Using detailed exposure information on COVID-19 cases, we estimated the mean latent period to be 5.5 days (95% confidence interval: 5.1-5.9 days), shorter than the mean incubation period (6.9 days). Laboratory testing may allow shorter quarantines since 95% of COVID-19 cases shed virus within 10.6 days (95%CI: 9.6-11.6) of infection.

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.

scholarly journals Onchocerciasis control in Ghana (1974–2016)

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Nana-Kwadwo Biritwum ◽  
Dziedzom K. de Souza ◽  
Odame Asiedu ◽  
Benjamin Marfo ◽  
Uche Veronica Amazigo ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Vector Control ◽  
Control Strategy ◽  
Financial Support ◽  
Control Programme ◽  
Ivermectin Treatment ◽  
Mobile Community ◽  
The Mean ◽  
The Impact ◽  
Onchocerciasis Control

Abstract Background The control of onchocerciasis in Ghana started in 1974 under the auspices of the Onchocerciasis Control Programme (OCP). Between 1974 and 2002, a combination of approaches including vector control, mobile community ivermectin treatment, and community-directed treatment with ivermectin (CDTI) were employed. From 1997, CDTI became the main control strategy employed by the Ghana OCP (GOCP). This review was undertaken to assess the impact of the control interventions on onchocerciasis in Ghana between 1974 and 2016, since which time the focus has changed from control to elimination. Methods In this paper, we review programme data from 1974 to 2016 to assess the impact of control activities on prevalence indicators of onchocerciasis. This review includes an evaluation of CDTI implementation, microfilaria (Mf) prevalence assessments and rapid epidemiological mapping of onchocerciasis results. Results This review indicates that the control of onchocerciasis in Ghana has been very successful, with a significant decrease in the prevalence of infection from 69.13% [95% confidence interval) CI 60.24–78.01] in 1975 to 0.72% (95% CI 0.19–1.26) in 2015. Similarly, the mean community Mf load decreased from 14.48 MF/skin snip in 1975 to 0.07 MF/skin snip (95% CI 0.00–0.19) in 2015. Between 1997 and 2016, the therapeutic coverage increased from 58.50 to 83.80%, with nearly 100 million ivermectin tablets distributed. Conclusions Despite the significant reduction in the prevalence of onchocerciasis in Ghana, there are still communities with MF prevalence above 1%. As the focus of the GOCP has changed from the control of onchocerciasis to its elimination, both guidance and financial support are required to ensure that the latter goal is met.

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