scholarly journals Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms

2020 ◽  
Vol 9 (5) ◽  
pp. 1297 ◽  
Author(s):  
Robin N. Thompson ◽  
Francesca A. Lovell-Read ◽  
Uri Obolski
Keyword(s):  
Basic Reproduction Number ◽  
Symptom Onset ◽  
Reproduction Number ◽  
Wide Spectrum ◽  
Control Measures ◽  
Current Evidence ◽  
The Novel ◽  
Novel Coronavirus ◽  
The Basic Reproduction Number

Interventions targeting symptomatic hosts and their contacts were successful in bringing the 2003 SARS pandemic under control. In contrast, the COVID-19 pandemic has been harder to contain, partly because of its wide spectrum of symptoms in infectious hosts. Current evidence suggests that individuals can transmit the novel coronavirus while displaying few symptoms. Here, we show that the proportion of infections arising from hosts with few symptoms at the start of an outbreak can, in combination with the basic reproduction number, indicate whether or not interventions targeting symptomatic hosts are likely to be effective. However, as an outbreak continues, the proportion of infections arising from hosts with few symptoms changes in response to control measures. A high proportion of infections from hosts with few symptoms after the initial stages of an outbreak is only problematic if the rate of new infections remains high. Otherwise, it can simply indicate that symptomatic transmissions are being prevented successfully. This should be considered when interpreting estimates of the extent of transmission from hosts with few COVID-19 symptoms.

scholarly journals The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Khosravi ◽  
R. Chaman ◽  
M. Rohani-Rasaf ◽  
F. Zare ◽  
S. Mehravaran ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Early Stage ◽  
Screening Tests ◽  
The Novel ◽  
Epidemic Size ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Interval Distribution ◽  
The Basic Reproduction Number

Abstract The aim of this study was to estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud in Northeastern Iran. The R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The 30-day probable incidence and cumulative incidence were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using ‘earlyR’ and ‘projections’ packages in R software. The maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1−3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI 1.03–1.25) by the end of day 42. The expected average number of new cases in Shahroud was 9.0 ± 3.8 cases/day, which means an estimated total of 271 (95% CI: 178–383) new cases for the period between 02 April to 03 May 2020. By day 67 (27 April), the effective reproduction number (Rt), which had a descending trend and was around 1, reduced to 0.70. Based on the Rt for the last 21 days (days 46–67 of the epidemic), the prediction for 27 April to 26 May is a mean daily cases of 2.9 ± 2.0 with 87 (48–136) new cases. In order to maintain R below 1, we strongly recommend enforcing and continuing the current preventive measures, restricting travel and providing screening tests for a larger proportion of the population.

scholarly journals Mathematical modelling and optimal cost-effective control of COVID-19 transmission dynamics

2020 ◽  
Author(s):  
S. Olaniyi ◽  
O.S. Obabiyi ◽  
K.O. Okosun ◽  
A.T. Oladipo ◽  
S.O. Adewale
Keyword(s):  
Basic Reproduction Number ◽  
Least Squares Method ◽  
Reproduction Number ◽  
Cost Effective ◽  
Effective Control ◽  
Cumulative Number ◽  
The Novel ◽  
Novel Coronavirus ◽  
Disease Free ◽  
The Basic Reproduction Number

Abstract The novel coronavirus disease (COVID-19) caused by a new strain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains the current global health challenge. In this paper, an epidemic model based on system of ordinary differential equations is formulated by taking into account the transmission routes from symptomatic, asymptomatic and hospitalized individuals. The model is fitted to the corresponding cumulative number of hospitalized individuals (active cases) reported by the Nigeria Centre for Disease Control (NCDC), and parameterized using the least squares method. The basic reproduction number which measures the potential spread of COVID-19 in the population is computed using the next generation operator method. Further, Lyapunov function is constructed to investigate the stability of the model around a disease-free equilibrium point. It is shown that the model has a globally asymptotically stable disease-free equilibrium if the basic reproduction number of the novel coronavirus transmission is less than one. Sensitivities of the model to changes in parameters are explored. It is revealed further that the basic reproduction number can be brought to a value less than one in Nigeria, if the current effective transmission rate of the disease can be reduced by 50%. Otherwise, the number of active cases may get up to 2.5% of the total estimated population. In addition, two time-dependent control variables, namely preventive and management measures, are considered to mitigate the damaging effects of the disease using Pontryagin's maximum principle. The most cost-effective control measure is determined through cost-effectiveness analysis. Numerical simulations of the overall system are implemented in MatLab® for demonstration of the theoretical results.

scholarly journals The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran

2020 ◽  
Author(s):  
Ahmad Khosravi ◽  
Reza Chaman ◽  
Marzieh Rohani-Rasaf ◽  
Fariba Zare ◽  
Shiva Mehravaran ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Early Stage ◽  
Screening Tests ◽  
The Novel ◽  
Epidemic Size ◽  
Serial Interval ◽  
Novel Coronavirus ◽  
Interval Distribution ◽  
The Basic Reproduction Number

AbstractObjectivesTo estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud, Northeast of Iran.MethodsThe R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The serial interval was fit with a gamma distribution. The probable incidence and cumulative incidence in the next 30 days were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using “earlyR” and “projections” packages in R software.ResultsThe maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1 to 3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI: 1.03 to 1.25) by the end of the day 41. The expected average number of new cases in Shahroud is 9.0±3.8 case/day, which means an estimated total of 271 (95% CI: 178-383) new cases in the next 30 days.ConclusionsIt is essential to reduce the R0 to values below one. Therefore, we strongly recommend enforcing and continuing the current preventive measures, restricting travel, and providing screening tests for a larger proportion of the population.

scholarly journals A statistical analysis of the novel coronavirus (COVID-19) in Italy and Spain

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0249037
Author(s):  
Jeffrey Chu
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Basic Reproduction Number ◽  
Linear Regression Model ◽  
Reproduction Number ◽  
Early Stage ◽  
The Novel ◽  
Novel Coronavirus ◽  
Log Linear ◽  
The Basic Reproduction Number

The novel coronavirus (COVID-19) that was first reported at the end of 2019 has impacted almost every aspect of life as we know it. This paper focuses on the incidence of the disease in Italy and Spain—two of the first and most affected European countries. Using two simple mathematical epidemiological models—the Susceptible-Infectious-Recovered model and the log-linear regression model, we model the daily and cumulative incidence of COVID-19 in the two countries during the early stage of the outbreak, and compute estimates for basic measures of the infectiousness of the disease including the basic reproduction number, growth rate, and doubling time. Estimates of the basic reproduction number were found to be larger than 1 in both countries, with values being between 2 and 3 for Italy, and 2.5 and 4 for Spain. Estimates were also computed for the more dynamic effective reproduction number, which showed that since the first cases were confirmed in the respective countries the severity has generally been decreasing. The predictive ability of the log-linear regression model was found to give a better fit and simple estimates of the daily incidence for both countries were computed.

scholarly journals Estimating the reproduction number of COVID-19 in Iran using epidemic modeling

2020 ◽  
Author(s):  
Ebrahim Sahafizadeh ◽  
Samaneh Sartoli
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Transmission Model ◽  
The Novel ◽  
Epidemic Spreading ◽  
Social Distancing ◽  
Novel Coronavirus ◽  
And Control ◽  
Second Wave ◽  
The Basic Reproduction Number

AbstractBackgroundAs reported by Iranian governments, the first cases of coronavirus (COVID-19) infections confirmed in Qom, Iran on February 19, 2020 (30 Bahman 1398). The number of identified cases afterward increased rapidly and the novel coronavirus spread to all provinces of the country. This study aimed to fit an epidemic model to the reported cases data to estimate the basic reproduction number (R0) of COVID-19 in Iran.MethodsWe used data from February 21, 2020, to April 21, 2020, on the number of cases reported by Iranian governments and we employed the SIR (Susceptible-Infectious-Removed) epidemic spreading model to fit the transmission model to the reported cases data by tuning the parameters in order to estimate the basic reproduction number of COVID-19 in Iran.ResultsThe value of reproduction number was estimated 4.86 in the first week and 4.5 in the second week. it decreased from 4.29 to 2.37 in the next four weeks. At the seventh week of the outbreak the reproduction number was reduced below one.ConclusionsThe results indicate that the basic reproduction number of COVID-19 was significantly larger than one in the early stages of the outbreak. However, implementing social distancing and preventing travelling on Nowruz (Persian New Year) effectively reduced the reproduction number. Although the results indicate that reproduction number is below one, it is necessary to continue social distancing and control travelling to prevent causing a second wave of outbreak.

scholarly journals Preliminary estimating the reproduction number of the coronavirus disease (COVID-19) outbreak in Republic of Korea from 31 January to 1 March 2020

2020 ◽  
Author(s):  
Zian Zhuang ◽  
Shi Zhao ◽  
Qianying Lin ◽  
Peihua Cao ◽  
Yijun Lou ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Republic Of Korea ◽  
The Novel ◽  
Transmission Process ◽  
Novel Coronavirus ◽  
Dispersion Term ◽  
The Basic Reproduction Number

AbstractThe novel coronavirus disease 2019 (COVID-19) outbreak in Republic of Korea has caused 3736 cases and 18 deaths by 1 March 2020. We modeled the transmission process in Republic of Korea with a stochastic model and estimated the basic reproduction number R0 as 2.6 (95%CI: 2.3-2.9) and 3.2 (95%CI: 2.9-3.5), under the assumption that the exponential growth starting 31 January and 5 February, 2020, respectively. Estimates of dispersion term (k) were larger than 10 significantly, which implies few super-spreading events..

scholarly journals Effects of (Un)lockdown on COVID-19 transmission: A mathematical study of different phases in India

2020 ◽  
Author(s):  
Rohit Kumar ◽  
Md. Zubbair Malik ◽  
Sapna Ratan Shah
Keyword(s):  
Mathematical Modelling ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Real Data ◽  
The Novel ◽  
Mathematical Study ◽  
The Third ◽  
Novel Coronavirus ◽  
The Basic Reproduction Number ◽  
Modelling Approach

The novel coronavirus (SARS-CoV-2), identified in China at the end of the December 2019 is causing a potentially fatal respiratory syndrome (COVID-19), has meanwhile led to outbreak all over the globe. India has now become the third worst hit country globally with 16,38,870 confirmed cases and 35,747 confirmed deaths due to COVID-19 as of 31 July 2020. In this paper we have used mathematical modelling approach to study the effects of lockdowns and un-lockdowns on the pandemic evolution in India. This, study is based on SIDHARTHE model, which is an extension of classical SIR (Susceptible-Infected-Recovered) model. The SIDHARTHE model distinguish between the diagnosed and undiagnosed cases, which is very important because undiagnosed individuals are more likely to spread the virus than diagnosed individuals. We have stratified the lockdowns and un-lockdowns into seven phases and have computed the basic reproduction number R0 for each phase. We have calibrated our model results with real data from 20 March 2020 to 31 July 2020. Our results demonstrate that different strategies implemented by GoI, have delayed the peak of pandemic by approximately 100 days. But due to under-diagnosis of the infected asymptomatic subpopulation, a sudden outbreak of cases can be observed in India.

scholarly journals Early epidemiological assessment of the transmission potential and virulence of coronavirus disease 2019 (COVID-19) in Wuhan City: China, January-February, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Katsushi Kagaya ◽  
Gerardo Chowell
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Public Health Intervention ◽  
Ecological Modelling ◽  
The Novel ◽  
Wuhan City ◽  
Transmission Potential ◽  
The World ◽  
Novel Coronavirus ◽  
Epidemiological Parameters

AbstractBackgroundSince the first cluster of cases was identified in Wuhan City, China, in December, 2019, coronavirus disease 2019 (COVID-19) rapidly spread around the world. Despite the scarcity of publicly available data, scientists around the world have made strides in estimating the magnitude of the epidemic, the basic reproduction number, and transmission patterns. Accumulating evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which highlights the need to reassess the transmission potential of this emerging disease. In this study, we derive estimates of the transmissibility and virulence of COVID-19 in Wuhan City, China, by reconstructing the underlying transmission dynamics using multiple data sources.MethodsWe employ statistical methods and publicly available epidemiological datasets to jointly derive estimates of transmissibility and severity associated with the novel coronavirus. For this purpose, the daily series of laboratory–confirmed COVID-19 cases and deaths in Wuhan City together with epidemiological data of Japanese repatriated from Wuhan City on board government–chartered flights were integrated into our analysis.ResultsOur posterior estimates of basic reproduction number (R) in Wuhan City, China in 2019–2020 reached values at 3.49 (95%CrI: 3.39–3.62) with a mean serial interval of 6.0 days, and the enhanced public health intervention after January 23rd in 2020 was associated with a significantly reduced R at 0.84 (95%CrI: 0.81–0.88), with the total number of infections (i.e. cumulative infections) estimated at 1906634 (95%CrI: 1373500–2651124) in Wuhan City, elevating the overall proportion of infected individuals to 19.1% (95%CrI: 13.5–26.6%). We also estimated the most recent crude infection fatality ratio (IFR) and time–delay adjusted IFR at 0.04% (95% CrI: 0.03%–0.06%) and 0.12% (95%CrI: 0.08–0.17%), respectively, estimates that are several orders of magnitude smaller than the crude CFR estimated at 4.06%ConclusionsWe have estimated key epidemiological parameters of the transmissibility and virulence of COVID-19 in Wuhan, China during January-February, 2020 using an ecological modelling approach. The power of this approach lies in the ability to infer epidemiological parameters with quantified uncertainty from partial observations collected by surveillance systems.

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