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.

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 How quarantine and social distancing policy can suppress the outbreak of novel coronavirus in developing or under poverty level countries : a mathematical and statistical analysis.

2020 ◽  
Author(s):  
Atiqur Chowdhury ◽  
K M Ariful Kabir ◽  
Jun Tanimoto
Keyword(s):  
Basic Reproduction Number ◽  
Reproduction Number ◽  
Viral Disease ◽  
Poverty Level ◽  
Accurate Predictor ◽  
Social Distancing ◽  
The World Bank ◽  
Polynomial Fit ◽  
The World ◽  
Novel Coronavirus

Abstract Background: COVID-19 is a transmissible viral disease that has spread around the world rapidly and is currently a significant thread to developing and impoverished country by the World Bank and WHO’s prediction. Without inventing vaccination or the proper treatment, how we control the transmission of the COVID-19 is one of the most important questions with which peoples are facing right now . By the WHO’s guidelines, some policies termed as isolation, quarantine, lockdown, and social distancing would give a stunning direction to control the epidemic outbreak. Methods: In this paper, we developed a mathematical model named “Social distancing SEIQR model” to reduce the basic reproduction number R0 by combining both quarantine and social distancing parameters based on the real cases where medical equipment and other resources are limited. Results: Our modeling basic reproduction number R 0 is an almost accurate predictor threshold to assess the transmissibility of the COVID-19 in Bangladesh. Our modeling basic reproduction number R0 is an almost accurate predictor threshold to assess the transmissibility of the COVID-19 in Bangladesh. Our study result showed, our model fitted well with the numerically simulated results to the reported COVID-19 cases data for Bangladesh by a linear regression polynomial fit analysis. Conclusion: Our model will help to find strategies to reduce the human-to-human transmission of the virus and protect the nation when a country has limited medical resources.

scholarly journals Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020

2020 ◽  
Author(s):  
Kenji Mizumoto ◽  
Gerardo Chowell
Keyword(s):  
Mathematical Modeling ◽  
Time Series ◽  
Reproduction Number ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Threshold ◽  
Transmission Potential ◽  
Incidence Data ◽  
The Mean ◽  
Novel Coronavirus

AbstractAn outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ∼11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.

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 long-term dynamics of tuberculosis and other diseases with long serial intervals: implications of and for changing reproduction numbers

1998 ◽  
Vol 121 (2) ◽  
pp. 309-324 ◽  
Author(s):  
E. VYNNYCKY ◽  
P. E. M. FINE
Keyword(s):  
Infectious Disease ◽  
Basic Reproduction Number ◽  
Reproduction Number ◽  
England And Wales ◽  
Transmission Potential ◽  
Reproduction Numbers ◽  
Serial Interval ◽  
Net Reproduction ◽  
Epidemiological Parameters ◽  
The Basic Reproduction Number

The net and basic reproduction numbers are among the most widely-applied concepts in infectious disease epidemiology. A net reproduction number (the average number of secondary infectious cases resulting from each case in a given population) of above 1 is conventionally associated with an increase in incidence; the basic reproduction number (defined analogously for a ‘totally susceptible’ population) provides a standard measure of the ‘transmission potential’ of an infection. Using a model of the epidemiology of tuberculosis in England and Wales since 1900, we demonstrate that these measures are difficult to apply if disease can follow reinfection, and that they lose their conventional interpretations if important epidemiological parameters, such as the rate of contact between individuals, change over the time interval between successive cases in a chain of transmission (the serial interval).The net reproduction number for tuberculosis in England and Wales appears to have been approximately 1 from 1900 until 1950, despite concurrent declines in morbidity and mortality rates, and it declined rapidly in the second half of this century. The basic reproduction number declined from about 3 in 1900, reached 2 by 1950, and first fell below 1 in about 1960. Reductions in effective contact between individuals over this period, measured in terms of the average number of individuals to whom each case could transmit the infection, meant that the conventional basic reproduction number measure (which does not consider subsequent changes in epidemiological parameters) for a given year failed to reflect the ‘actual transmission potential’ of the infection. This latter property is better described by a variant of the conventional measure which takes secular trends in contact into account. These results are relevant for the interpretation of trends in any infectious disease for which epidemiological parameters change over time periods comparable to the infectious period, incubation period or serial interval.

scholarly journals Analysis of the stochastic model for predicting the novel coronavirus disease

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Ndolane Sene
Keyword(s):  
Stochastic Model ◽  
Deterministic Model ◽  
Reproduction Number ◽  
Equilibrium Points ◽  
The Novel ◽  
Stochastic Perturbations ◽  
Numerical Investigations ◽  
Rapid Spread ◽  
The World ◽  
Novel Coronavirus

Abstract In this paper, we propose a mathematical model to predict the novel coronavirus. Due to the rapid spread of the novel coronavirus disease in the world, we add to the deterministic model of the coronavirus the terms of the stochastic perturbations. In other words, we consider in this paper a stochastic model to predict the novel coronavirus. The equilibrium points of the deterministic model have been determined, and the reproduction number of our deterministic model has been implemented. The asymptotic behaviors of the solutions of the stochastic model around the equilibrium points have been studied. The numerical investigations and the graphical representations obtained with the novel stochastic model are made using the classical stochastic numerical scheme.

scholarly journals Early dynamics of transmission and control of COVID-19: a mathematical modelling study

2020 ◽  
Author(s):  
Adam J Kucharski ◽  
Timothy W Russell ◽  
Charlie Diamond ◽  
Yang Liu ◽  
John Edmunds ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Transmission Model ◽  
The Novel ◽  
Transmission Potential ◽  
Travel Restrictions ◽  
Gates Foundation ◽  
Novel Coronavirus ◽  
And Control ◽  
Over Time

AbstractBackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.MethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas.FindingsWe estimated that the median daily reproduction number, Rt, declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.InterpretationOur results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.FundingWellcome Trust (206250/Z/17/Z, 210758/Z/18/Z), HDR UK (MR/S003975/1), Gates Foundation (INV-003174), NIHR (16/137/109)

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.

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