COVID-19 Italian and Europe Epidemic Evolution: A SEIR Model with Lockdown-Dependent Transmission Rate Based on Chinese Data

2020 ◽  
Author(s):  
Nicola Picchiotti ◽  
Monica Salvioli ◽  
Elena Zanardini ◽  
Francesco Missale
Keyword(s):  
Transmission Rate ◽  
Seir Model

scholarly journals Impact of public health interventions to curb SARS-CoV-2 spread assessed by an evidence-educated Delphi panel and tailored SEIR model

2021 ◽  
Author(s):  
Bernd Brüggenjürgen ◽  
Hans-Peter Stricker ◽  
Lilian Krist ◽  
Miriam Ortiz ◽  
Thomas Reinhold ◽  
...  
Keyword(s):  
Public Health ◽  
Transmission Rate ◽  
Latency Period ◽  
Policy Decision ◽  
Sensitivity Analyses ◽  
Delphi Panel ◽  
Time Step ◽  
Seir Model ◽  
Health Policy Decision ◽  
The Impact

Abstract Aim To use a Delphi-panel-based assessment of the effectiveness of different non-pharmaceutical interventions (NPI) in order to retrospectively approximate and to prospectively predict the SARS-CoV-2 pandemic progression via a SEIR model (susceptible, exposed, infectious, removed). Methods We applied an evidence-educated Delphi-panel approach to elicit the impact of NPIs on the SARS-CoV-2 transmission rate R0 in Germany. Effectiveness was defined as the product of efficacy and compliance. A discrete, deterministic SEIR model with time step of 1 day, a latency period of 1.8 days, duration of infectiousness of 5 days, and a share of the total population of 15% assumed to be protected by immunity was developed in order to estimate the impact of selected NPI measures on the course of the pandemic. The model was populated with the Delphi-panel results and varied in sensitivity analyses. Results Efficacy and compliance estimates for the three most effective NPIs were as follows: test and isolate 49% (efficacy)/78% (compliance), keeping distance 42%/74%, personal protection masks (cloth masks or other face masks) 33%/79%. Applying all NPI effectiveness estimates to the SEIR model resulted in a valid replication of reported occurrence of the German SARS-CoV-2 pandemic. A combination of four NPIs at consented compliance rates might curb the CoViD-19 pandemic. Conclusion Employing an evidence-educated Delphi-panel approach can support SARS-CoV-2 modelling. Future curbing scenarios require a combination of NPIs. A Delphi-panel-based NPI assessment and modelling might support public health policy decision making by informing sequence and number of needed public health measures.

scholarly journals A modified SEIR model to predict the behavior of the early stage in coronavirus and coronavirus-like outbreaks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wilfredo Angulo ◽  
José M. Ramírez ◽  
Dany De Cecchis ◽  
Juan Primera ◽  
Henry Pacheco ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Risk Perceptions ◽  
Transmission Rate ◽  
Early Stage ◽  
Individual Risk ◽  
Seir Model ◽  
Proposed Model ◽  
Probable Site ◽  
Adjusted Model ◽  
The Impact

AbstractCOVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.

scholarly journals Modifying the network-based stochastic SEIR model to account for quarantine: an application to COVID-19

2021 ◽  
Vol 10 (s1) ◽  
Author(s):  
Chris Groendyke ◽  
Adam Combs
Keyword(s):  
Network Model ◽  
Transmission Rate ◽  
Disease Spread ◽  
Contact Network ◽  
Model Parameters ◽  
Seir Model ◽  
Disease States ◽  
Potential Contact ◽  
The Mean ◽  
Infectious State

Abstract Objectives: Diseases such as SARS-CoV-2 have novel features that require modifications to the standard network-based stochastic SEIR model. In particular, we introduce modifications to this model to account for the potential changes in behavior patterns of individuals upon becoming symptomatic, as well as the tendency of a substantial proportion of those infected to remain asymptomatic. Methods: Using a generic network model where every potential contact exists with the same common probability, we conduct a simulation study in which we vary four key model parameters (transmission rate, probability of remaining asymptomatic, and the mean lengths of time spent in the exposed and infectious disease states) and examine the resulting impacts on various metrics of epidemic severity, including the effective reproduction number. We then consider the effects of a more complex network model. Results: We find that the mean length of time spent in the infectious state and the transmission rate are the most important model parameters, while the mean length of time spent in the exposed state and the probability of remaining asymptomatic are less important. We also find that the network structure has a significant impact on the dynamics of the disease spread. Conclusions: In this article, we present a modification to the network-based stochastic SEIR epidemic model which allows for modifications to the underlying contact network to account for the effects of quarantine. We also discuss the changes needed to the model to incorporate situations where some proportion of the individuals who are infected remain asymptomatic throughout the course of the disease.

scholarly journals The impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak - evidence from China

2020 ◽  
Author(s):  
Peng Shi ◽  
Yinqiao Dong ◽  
Huanchang Yan ◽  
Xiaoyang Li ◽  
Chenkai Zhao ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Infectious Diseases ◽  
Transmission Rate ◽  
Mainland China ◽  
Weather Condition ◽  
Absolute Humidity ◽  
List Type ◽  
Seir Model ◽  
Provincial Level ◽  
The Impact

ABSTRACTOBJECTIVETo investigate the impact of temperature and absolute humidity on the coronavirus disease 2019 (COVID-19) outbreak.DESIGNEcological study.SETTING31 provincial-level regions in mainland China.MAIN OUTCOME MEASURESData on COVID-19 incidence and climate between Jan 20 and Feb 29, 2020.RESULTSThe number of new confirm COVID-19 cases in mainland China peaked on Feb 1, 2020. COVID-19 daily incidence were lowest at -10 °C and highest at 10 °C, while the maximum incidence was observed at the absolute humidity of approximately 7 g/m3. COVID-19 incidence changed with temperature as daily incidence decreased when the temperature rose. No significant association between COVID-19 incidence and absolute humidity was observed in distributed lag nonlinear models. Additionally, A modified susceptible-exposed-infectious-recovered (M-SEIR) model confirmed that transmission rate decreased with the increase of temperature, leading to further decrease of infection rate and outbreak scale.CONCLUSIONTemperature is an environmental driver of the COVID-19 outbreak in China. Lower and higher temperatures might be positive to decrease the COVID-19 incidence. M-SEIR models help to better evaluate environmental and social impacts on COVID-19.What is already known on this topicMany infectious diseases present an environmental pattern in their incidence.Environmental factors, such as climate and weather condition, could drive the space and time correlations of infectious diseases, including influenza.Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be transmitted through aerosols, large droplets, or direct contact with secretions (or fomites) as influenza virus can.Little is known about environmental pattern in COVID-19 incidence.What this study addsThe significant association between COVID-19 daily incidence and temperature was confirmed, using 3 methods, based on the data on COVID-19 and weather from 31 provincial-level regions in mainland China.Environmental factors were considered on the basis of SEIR model, and a modified susceptible-exposed-infectious-recovered (M-SEIR) model was developed.Simulations of the COVID-19 outbreak in Wuhan presented similar effects of temperature on incidence as the incidence decrease with the increase of temperature.

scholarly journals Analysis of the COVID-19 epidemic in french overseas department Mayotte based on a modified deterministic and stochastic SEIR model

2020 ◽  
Author(s):  
Solym Mawaki Manou-Abi ◽  
Julien Balicchi
Keyword(s):  
Transmission Rate ◽  
Control Measure ◽  
Exponential Growth Phase ◽  
The Novel ◽  
Rate Parameter ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Access To Water ◽  
Novel Coronavirus ◽  
Death Cases

AbstractIn order to anticipate a future trends in the development of the novel coronavirus COVID-19 epidemic started early at march 13, in the french overseas department Mayotte, we consider in this paper a modified deterministic and stochastic epidemic model. The model divides the total population into several possible states or compartment: susceptible (S), exposed (E) infected and being under an incubation period, infected (I) being infectious, simple or mild removed RM, severe removed (including hospitalized) RS and death cases (D). The adding of the two new compartment RM and RS are driven by data which together replace the original R compartment in the classical SEIR model.We first fit the constant transmission rate parameter to the epidemic data in Mayotte during an early exponential growth phase using an algorithm with a package of the software R and based on a Maximum Likewood estimator. This allows us to predict the epidemic without any control in order to understand how the control measure and public policies designed are having the desired impact of controlling the epidemic. To do this, we introduce a temporally varying decreasing transmission rate parameter with a control or quarantine parameter q. Then we pointed out some values of q to maintain control which is critical in Mayotte given the fragility of its health infrastructure and the significant fraction of the population without access to water.

scholarly journals COVID 19: An SEIR model predicting disease progression and healthcare outcomes for Pakistan

2020 ◽  
Author(s):  
Ejaz Ahmad Khan ◽  
Maida Umar ◽  
Maryam Khalid
Keyword(s):  
Transmission Rate ◽  
Asymptomatic Infection ◽  
Control Measures ◽  
System Response ◽  
Inadequate Response ◽  
Healthcare Outcomes ◽  
Susceptible Population ◽  
Seir Model ◽  
Healthcare Facilities ◽  
The Impact

AbstractBackgroundRecent pandemic of the Noval Coronal Virus (COVID 19) has claimed more than 200,000 lives and about 3.8 million infected worldwide. Countries are being gradually exposed to its devastating threat without being properly prepared and with inadequate response. COVID 19’s first two cases were reported in Pakistan on February 26, 2020. We present a model depicting progression of epidemiology curve for Pakistan with and without interventions in view of its health system’ response capacity in near future.MethodologyWe used a modified compartmental epidemiological SEIR model to describe the outbreak of COVID-19 in Pakistan including the possibility of asymptomatic infection and presymptomatic transmission. The behavior of the dynamic model is determined by a set of clinical parameters and transmission rate.ResultsWe estimated that in the absence of a set of proven interventions, the total susceptible population would be 43.24 million, exposed individuals would be almost 32 million, asymptomatic cases would be 13.13 million, mildly infected 30.64 million, severely infected slightly more than 6 million and critical cases would be around 967,000 in number. By that time, almost 760,000 fatalities of infected critical would have taken place. Comparing with the healthcare capacity of Pakistan, if we could “flatten the curve” to a level below the dashed grey line, the healthcare system will be capable of managing the cases with ideal healthcare facilities, where the grey line representing the healthcare capacity of Pakistan. With the intervention in place, the number of symptomatic infected individuals is expected to be almost 20 million.ConclusionWe consider the impact of intervention and control measures on the spread of COVID-19 with 30% reduction in transmission from mild cases in case a set of interventions are judiciously in place to mitigate its impact.

scholarly journals The fomite contribution to the transmission of COVID-19 in the UK: an evolutionary population estimate

2021 ◽  
Author(s):  
Avery Meiksin
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Population Estimate ◽  
Reproduction Rate ◽  
Social Contacts ◽  
Seir Model ◽  
Upper Limit ◽  
Study Results ◽  
The Uk

A SEIR model with an added fomite term is used to constrain the contribution of fomites to the spread of COVID-19 under the Spring 2020 lockdown in the UK. Assuming uniform priors on the reproduction number in lockdown and the fomite transmission rate, an upper limit is found on the fomite transmission rate of less than 1 contaminated object in 7 per day per infectious person (95% CL). Basing the prior on the reproduction rate during lockdown instead on the CoMix study results for the reduction in social contacts under lockdown, and assuming the reproduction number scales with the number of social contacts, provides a much more restrictive upper limit on the transmission rate by contaminated objects of fewer than 1 in 30 per day per infectious person (95% CL). Applied to postal deliveries and groceries, the upper limit on the fomite transmission rate corresponds to a probability below 1 in 70 (95% CL) that a contaminated object transmits the infection. Fewer than about half (95% CL) of the total number of deaths during the lockdown are found to arise from fomites, and most likely fewer than a quarter. These findings apply only to fomites with a transmission rate that is unaffected by a lockdown.

scholarly journals Covid-19 mortality rates in Northamptonshire UK: initial sub-regional comparisons and provisional SEIR model of disease spread

2020 ◽  
Author(s):  
Nick Petford ◽  
Jackie Campbell
Keyword(s):  
Mortality Rate ◽  
Transmission Rate ◽  
Local Population ◽  
Mortality Rates ◽  
Disease Spread ◽  
Parameter Estimates ◽  
Deterministic Models ◽  
Seir Model ◽  
East Midlands ◽  
Public Health Practitioners

We analysed mortality rates in a non-metropolitan UK subregion (Northamptonshire) to understand SARS-CoV-2 disease fatalities at sub 1000000 population levels. A numerical (SEIR) model was then developed to predict the spread of Covid-19 in Northamptonshire. A combined approach using statistically-weighted data to fit the start of the epidemic to the mortality record. Parameter estimates were then derived for the transmission rate and basic reproduction number. Age standardised mortality rates are highest in Northampton (urban) and lowest in semi-rural districts. Northamptonshire has a statistically higher Covid-19 mortality rate than for the East Midlands and England as a whole. Model outputs suggest the number of infected individuals exceed official estimates, meaning less than 40 percent of the population may require immunisation. Combining published (sub-regional) mortality rate data with deterministic models on disease spread has the potential to help public health practitioners develop bespoke mitigations, guided by local population demographics.

scholarly journals Efficient Prediction and Analysis of the possible evolution of the SARS-CoV-2 in COVID-19 applying the SEIR model in Santo Domingo de los Tsáchilas, Ecuador

Enfoque UTE ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 101-115
Author(s):  
Moisés Filiberto Mora Murillo ◽  
Walter Alfredo Mora Murillo ◽  
Digvijay Pandey
Keyword(s):  
Infectious Disease ◽  
Social Impact ◽  
Transmission Rate ◽  
Prediction Method ◽  
Santo Domingo ◽  
Initial Value ◽  
Seir Model ◽  
Special Operations ◽  
Containment Measures ◽  
Efficient Prediction

In Ecuador, in the Santo Domingo de los Tsáchilas province, a Special Operations Committee (SOC) was created to take containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). This research deals with an analysis of the possible spread of the SARS-COV-2 virus causing the infectious disease caused by new coronavirus (2019-nCoV) using the Susceptible, Exposed, Infected and Recovered (SEIR) model as a prediction method according to the rigor of the containment measures evaluated. with the acceptability of people through a survey (95 %, CI) in which three parameters (α) severity of containment measures, (k) social impact of the pandemic and (β) transmission rate, are determined, which we then used as β (t) with initial value of β = 1. All this considering the rapid proliferation of the virus in the province and having an average of α = 3.23 (95 % CI: 3 - 4) and for k = 4.10 (95 % CI: 4 - 5) that the authorities will use to mitigate the spread of the virus, as well as future outbreaks of the disease.

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