scholarly journals Assessing the Impact of (Self)-Quarantine through a Basic Model of Infectious Disease Dynamics

2021 ◽  
Vol 13 (4) ◽  
pp. 978-992
Author(s):  
József Z. Farkas ◽  
Roxane Chatzopoulos
Keyword(s):  
Population Size ◽  
Infection Process ◽  
Mass Action ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Disease Dynamics ◽  
Susceptible Population ◽  
Model Simulations ◽  
The Uk ◽  
The Impact

We introduce a system of differential equations to assess the impact of (self-)quarantine of symptomatic infectious individuals on disease dynamics. To this end we depart from using the classic bilinear infection process, but remain within the framework of the mass-action assumption. From the mathematical point of view, the model we propose is interesting due to the lack of continuous differentiability at disease-free steady states, which implies that the basic reproductive number cannot be computed following established mathematical approaches for certain parameter values. However, we parametrise our mathematical model using published values from the COVID-19 literature, and analyse the model simulations. We also contrast model simulations against publicly available COVID-19 test data, focusing on the first wave of the pandemic during March–July 2020 in the UK. Our simulations indicate that actual peak case numbers might have been as much as 200 times higher than the reported positive test cases during the first wave in the UK. We find that very strong adherence to self-quarantine rules yields (only) a reduction of 22% of peak numbers and delays the onset of the peak by approximately 30–35 days. However, during the early phase of the outbreak, the impact of (self)-quarantine is much more significant. We also take into account the effect of a national lockdown in a simplistic way by reducing the effective susceptible population size. We find that, in case of a 90% reduction of the effective susceptible population size, strong adherence to self-quarantine still only yields a 25% reduction of peak infectious numbers when compared to low adherence. This is due to the significant number of asymptomatic infectious individuals in the population.

SE2IR Invest Market Rumor Spreading Model Considering Hesitating Mechanism

2019 ◽  
Vol 7 (1) ◽  
pp. 54-69 ◽  
Author(s):  
Hongxing Yao ◽  
Xiangyang Gao
Keyword(s):  
Mean Field ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Field Equations ◽  
Rumor Spreading ◽  
Immunization Strategy ◽  
Scale Free ◽  
Spreading Model ◽  
Mean Field Equations ◽  
The Impact

Abstract According to the actual situation of investor network, a SE2IR rumor spreading model with hesitating mechanism is proposed, and the corresponding mean-field equations is obtained on scale-free network. In this paper, we first combine the theory of spreading dynamics and find out the basic reproductive number R0. And then analyzes the stability of the rumor-free equilibrium and the final rumor size. Finally, we discuss random immune strategies and target immune strategies for the rumor spreading, respectively. Through numerical simulation, we can draw the following conclusions: Reducing the fuzziness and attractiveness of invest market rumor can effectively reduce the impact of rumor. And the target immunization strategy is more effective than the random immunization strategy for the communicators in the invest investor network.

scholarly journals Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yongmei Su ◽  
Sinuo Liu ◽  
Shurui Song ◽  
Xiaoke Li ◽  
Yongan Ye
Keyword(s):  
Fractional Order ◽  
Equilibrium Points ◽  
Mass Action ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Infection Model ◽  
Order Model ◽  
Infected Cells ◽  
Set Up ◽  
Hbv Model

In this paper, a fractional-order HBV model was set up based on standard mass action incidences and quasisteady assumption. The basic reproductive number R0 and the cytotoxic T lymphocytes’ immune-response reproductive number R1 were derived. There were three equilibrium points of the model, and stable analysis of each equilibrium point was given with corresponding hypothesis about R0 or R1. Some numerical simulations were also given based on HBeAg clinical data, and the simulation showed that there existed positive logarithmic correlation between the number of infected cells and HBeAg, which was consistent with the clinical facts. The simulation also showed that the clinical individual differences should be reflected by the fractional-order model.

HEPATITIS C VIRUS AND INTRAVENOUS DRUG MISUSE: A MODELING APPROACH

2014 ◽  
Vol 07 (01) ◽  
pp. 1450006 ◽  
Author(s):  
STEADY MUSHAYABASA ◽  
CLAVER P. BHUNU
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Steady States ◽  
Transmission Dynamics ◽  
Intravenous Drug ◽  
Basic Reproductive Number ◽  
Drug Misuse ◽  
Dynamical Analysis ◽  
Reproductive Number ◽  
The Impact

Hepatitis C virus (HCV) is a blood-borne infection that can lead to progressive liver failure, cirrhosis, hepatocellular carcinoma and death. A deterministic mathematical model for assessing the impact of daily intravenous drug misuse on the transmission dynamics of HCV is presented and analyzed. A threshold quantity known as the reproductive number has been computed. Stability of the steady states has been investigated. The dynamical analysis reveals that the model has globally asymptotically stable steady states. The impact of daily intravenous drug misuse on the transmission dynamics of HCV has been discussed through the basic reproductive number and numerical simulations.

scholarly journals A Simulation on Potential Secondary Spread of Novel Coronavirus in an Exported Country Using a Stochastic Epidemic SEIR Model

2020 ◽  
Vol 9 (4) ◽  
pp. 944 ◽  
Author(s):  
Kentaro Iwata ◽  
Chisato Miyakoshi
Keyword(s):  
Healthcare Professionals ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Asian Countries ◽  
Hospital Visit ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Novel Coronavirus ◽  
The Impact ◽  
Multiple Scenarios

Ongoing outbreak of pneumonia caused by novel coronavirus (2019-nCoV) began in December 2019 in Wuhan, China, and the number of new patients continues to increase. Even though it began to spread to many other parts of the world, such as other Asian countries, the Americas, Europe, and the Middle East, the impact of secondary outbreaks caused by exported cases outside China remains unclear. We conducted simulations to estimate the impact of potential secondary outbreaks in a community outside China. Simulations using stochastic SEIR model were conducted, assuming one patient was imported to a community. Among 45 possible scenarios we prepared, the worst scenario resulted in the total number of persons recovered or removed to be 997 (95% CrI 990–1000) at day 100 and a maximum number of symptomatic infectious patients per day of 335 (95% CrI 232–478). Calculated mean basic reproductive number (R0) was 6.5 (Interquartile range, IQR 5.6–7.2). However, better case scenarios with different parameters led to no secondary cases. Altering parameters, especially time to hospital visit. could change the impact of a secondary outbreak. With these multiple scenarios with different parameters, healthcare professionals might be able to better prepare for this viral infection.

scholarly journals The heterogeneous severity of COVID-19 in African countries: A modeling approach

2021 ◽  
Author(s):  
Salihu Sabiu Musa ◽  
Xueying Wang ◽  
Shi Zhao ◽  
Shudong Li ◽  
Nafiu Hussaini ◽  
...  
Keyword(s):  
Case Fatality ◽  
Well Being ◽  
Mitigation Strategies ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Time Varying ◽  
African Countries ◽  
Awareness Campaigns ◽  
Considerable Impact ◽  
The Impact

Abstract Background: The COVID-19 pandemic has had a considerable impact on global health and economics. The impact in African countries has not been investigated through fitting epidemic models to the reported COVID-19 deaths.Method: We downloaded data for the twelve most affected countries with the highest cumulative COVID-19 deaths to estimate the time-varying basic reproductive number (R0(t)) and infection attack rate (IAR). We developed a simple epidemic model and fitted the model to reported COVID-19 deaths in twelve African countries using iterated filtering and allowing a flexible transmission rate.Results: We observed high heterogeneity in the case-fatality rate across countries, which may be due to different reporting or testing efforts. South Africa, Tunisia, and Libya were affected most strongly, exhibiting a relatively higher(R0(t)) and infection attack rate.Conclusion: To effectively control the spread of COVID-19 epidemics in Africa, there is a need to consider other mitigation strategies (such as improvements in socioeconomic well-being, healthcare systems, the water supply, and awareness campaigns).

scholarly journals Modeling influenza seasonality in the tropics and subtropics

2021 ◽  
Vol 17 (6) ◽  
pp. e1009050
Author(s):  
Haokun Yuan ◽  
Sarah C. Kramer ◽  
Eric H. Y. Lau ◽  
Benjamin J. Cowling ◽  
Wan Yang
Keyword(s):  
Hong Kong ◽  
Mechanistic Model ◽  
Seasonal Pattern ◽  
Influenza Viruses ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Influenza Surveillance ◽  
Influenza Epidemic ◽  
Influenza Transmission ◽  
The Impact

Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R0 estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future.

scholarly journals Variation in SARS-CoV-2 free-living survival and environmental transmission can modulate the intensity of COVID-19 outbreaks

2020 ◽  
Author(s):  
C. Brandon Ogbunugafor ◽  
Miles Miller-Dickson ◽  
Victor A. Meszaros ◽  
Lourdes M. Gomez ◽  
Anarina L. Murillo ◽  
...  
Keyword(s):  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Disease Dynamics ◽  
Free Living ◽  
Environmental Transmission ◽  
Country Level ◽  
History Of ◽  
Virus Survival ◽  
Case Data

ABSTRACTCOVID-19 has circled the globe, rapidly expanding into a pandemic within a matter of weeks. While early studies revealed important features of SARS-CoV-2 transmission, the role of variation in free-living virus survival in modulating the dynamics of outbreaks remains unclear and controversial. Using an empirically determined understanding of the natural history of SARS-CoV-2 infection and detailed, country-level case data, we elucidate how variation in free-living virus survival influences key features of COVID-19 epidemics. Our findings suggest that environmental transmission can have a subtle, yet significant influence on COVID-19’s basic reproductive number () and other key signatures of outbreak intensity. Summarizing, we propose that variation in environmental transmission may explain some observed differences in disease dynamics from setting to setting, and can inform public health interventions.

scholarly journals Transmission dynamics of SARS-COV-2 in China: impact of public health interventions

2020 ◽  
Author(s):  
Wenbao Wang ◽  
Yiqin Chen ◽  
Qi Wang ◽  
Ping Cai ◽  
Ye He ◽  
...  
Keyword(s):  
Public Health ◽  
Health Interventions ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Public Health Interventions ◽  
The Public ◽  
Global Pandemic ◽  
Actual Growth ◽  
Global Threat ◽  
The Impact

AbstractCOVID-19 has become a global pandemic. However, the impact of the public health interventions in China needs to be evaluated. We established a SEIRD model to simulate the transmission trend of China. In addition, the reduction of the reproductive number was estimated under the current forty public health interventions policies. Furthermore, the infection curve, daily transmission replication curve, and the trend of cumulative confirmed cases were used to evaluate the effects of the public health interventions. Our results showed that the SEIRD curve model we established had a good fit and the basic reproductive number is 3.38 (95% CI, 3.25–3.48). The SEIRD curve show a small difference between the simulated number of cases and the actual number; the correlation index (H2) is 0.934, and the reproductive number (R) has been reduced from 3.38 to 0.5 under the current forty public health interventions policies of China. The actual growth curve of new cases, the virus infection curve, and the daily transmission replication curve were significantly going down under the current public health interventions. Our results suggest that the current public health interventions of China are effective and should be maintained until COVID-19 is no longer considered a global threat.

scholarly journals The impact of the COVID-19 pandemic on rabies reemergence in Latin America: the case of Arequipa, Peru

2020 ◽  
Author(s):  
Brinkley Raynor ◽  
Elvis W. Díaz ◽  
Julianna Shinnick ◽  
Edith Zegarra ◽  
Ynes Monroy ◽  
...  
Keyword(s):  
Latin America ◽  
Compartment Model ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Human Rabies ◽  
Innovative Strategies ◽  
Public Health Departments ◽  
Canine Rabies ◽  
Vaccination Campaigns ◽  
The Impact

Over the past decades, there has been tremendous progress towards eliminating canine rabies in Latin America. Major components of rabies prevention programs in Latin America leading to these successes have been constant and intense surveillance for rabid dogs and uninterrupted yearly mass dog vaccination campaigns. However, vital measures to control COVID-19 in Latin America have had the negative trade-off of jeopardizing these rabies elimination and prevention activities. In this paper, we aimed to assess the effect of interrupting canine rabies surveillance and mass dog vaccination campaigns on rabies trends. We built a deterministic compartment model of dog rabies dynamics parameterized for conditions found in Arequipa, Peru, where there is an ongoing dog rabies epidemic. Our model suggests that a decrease in canine vaccination coverage as well as decreased surveillance leading to an increased length of survival of infected dogs could lead to a sharp rise in canine rabies and, subsequently, human rabies risk. We examined our results over the best estimate of the basic reproductive number in Arequipa (R0 = 1.44) and a range of plausible values for R0 (1.36 - 2). The rising trend was consistent. It is very possible that COVID-19 will continue to challenge our public health departments in the short- and medium-term. Innovative strategies to conduct dog vaccination and rabies surveillance during these trying times should be considered to safeguard the achievements made in Latin America towards the elimination of dog-mediated human rabies.

scholarly journals Rubella vaccination in India: identifying broad consequences of vaccine introduction and key knowledge gaps

2017 ◽  
Vol 146 (1) ◽  
pp. 65-77 ◽  
Author(s):  
A. K. WINTER ◽  
S. PRAMANIK ◽  
J. LESSLER ◽  
M. FERRARI ◽  
B. T. GRENFELL ◽  
...  
Keyword(s):  
Public Sector ◽  
Vaccination Programme ◽  
Population Based ◽  
Childhood Vaccination ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Indian States ◽  
The Public ◽  
Low Level ◽  
The Impact

SUMMARYRubella virus infection typically presents as a mild illness in children; however, infection during pregnancy may cause the birth of an infant with congenital rubella syndrome (CRS). As of February 2017, India began introducing rubella-containing vaccine (RCV) into the public-sector childhood vaccination programme. Low-level RCV coverage among children over several years can result in an increase in CRS incidence by increasing the average age of infection without sufficiently reducing rubella incidence. We evaluated the impact of RCV introduction on CRS incidence across India's heterogeneous demographic and epidemiological contexts. We used a deterministic age-structured model that reflects Indian states’ rural and urban area-specific demography and vaccination coverage levels to simulate rubella dynamics and estimate CRS incidence with and without RCV introduction to the public sector. Our analysis suggests that current low-level private-sector vaccination has already slightly increased the burden of CRS in India. We additionally found that the effect of public-sector RCV introduction depends on the basic reproductive number, R0, of rubella. If R0 is five, a value empirically estimated from an array of settings, CRS incidence post-RCV introduction will likely decrease. However, if R0 is seven or nine, some states may experience short-term or annual increases in CRS, even if a long-term total reduction in cases (30 years) is expected. Investment in population-based serological surveys and India's fever/rash surveillance system will be key to monitoring the success of the vaccination programme.

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