scholarly journals The Basic Reproductive Number for Disease Systems with Multiple Coupled Heterogeneities

2017 ◽  
Author(s):  
Alun L. Lloyd ◽  
Uriel Kitron ◽  
T. Alex Perkins ◽  
Gonzalo M. Vazquez-Prokopec ◽  
Lance A. Waller
Keyword(s):  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Surprising Result ◽  
Multiple Sources ◽  
Multivariate Distributions ◽  
Coefficients Of Variation ◽  
Pairwise Correlations ◽  
Sources Of Variation ◽  
Log Normal ◽  
The Impact

AbstractIn mathematical epidemiology, a well-known formula describes the impact of heterogeneity on the basic reproductive number, R0, for situations in which transmission is separable and for which there is one source of variation in susceptibility and one source of variation in infectiousness. This formula is written in terms of the magnitudes of the heterogeneities, as quantified by their coefficients of variation, and the correlation between them. A natural question to ask is whether analogous results apply when there are multiple sources of variation in susceptibility and/or infectiousness. In this paper we demonstrate that with three or more coupled heterogeneities, R0 under separable transmission depends on details of the distribution of the heterogeneities in a way that is not seen in the well-known simpler situation. We provide explicit formulae for the cases of multivariate normal and multivariate log-normal distributions, showing that R0 can again be expressed in terms of the magnitudes of the heterogeneities and the pairwise correlations between them. The formulae, however, differ between the two multivariate distributions, demonstrating that no formula of this type applies generally when there are three or more coupled heterogeneities. We see that the results of the formulae are approximately equal when heterogeneities are relatively small and show that an earlier result in the literature (Koella, 1991) should be viewed in this light. We provide numerical illustrations of our results and discuss a setting in which coupled heterogeneities are likely to have a major impact on the value of R0. We also describe a rather surprising result: in a system with three heterogeneities, R0 can exhibit non-monotonic behavior with increasing levels of heterogeneity, in marked contrast to the familiar two heterogeneity setting in which R0 either increases or decreases with increasing heterogeneity.

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.

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 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.

THE IMPACT OF HUMAN LOCATION-SPECIFIC CONTACT PATTERN ON THE SIR EPIDEMIC TRANSMISSION BETWEEN POPULATIONS

2013 ◽  
Vol 23 (05) ◽  
pp. 1350095 ◽  
Author(s):  
LIN WANG ◽  
YAN ZHANG ◽  
ZHEN WANG ◽  
XIANG LI
Keyword(s):  
Population Model ◽  
Disease Incidence ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Contact Pattern ◽  
Structured Population Model ◽  
Epidemic Dynamics ◽  
Sir Epidemic ◽  
Structured Population ◽  
The Impact

The structured-population model is extensively used to study the complexity of epidemic dynamics. In many seminal researches, the impact of human mobility on the outbreak threshold has been profoundly studied, with the general assumption that the human contact pattern is mixing homogeneously. As the individual contact is assumed uniform among different subpopulations, the basic reproductive number, R0, which relates to the stability at the disease-free equilibrium, is equal to the same constant on separate locations. However, recent studies have shown that there may exist location-related factors driving the variance of disease incidence between populations, in reality. Therefore, in this study, the location-specific heterogeneous contact pattern has been introduced into a famous phenomenological structured-population model, where bidirectional recurrent commuting flows couple two typical subpopulations, to study the complex dynamics behaviors of spatial transmission of epidemics. Besides the usual SIR epidemic dynamics with birth and death processes, we take into account the contact process by assigning each member from a given subpopulation with a characteristic contact rate. Through theoretical arguments and agent-based computer simulations, we unveil that the stressed element dramatically affects the epidemic threshold of the system.

scholarly journals Predicted impact of vaccination and active case finding measures to control epidemic of Coronavirus Disease 2019 (COVID-19) in a migrant-populated area in Thailand

2021 ◽  
Author(s):  
Rapeepong Suphanchaimat ◽  
Natthaprang Nittayasoot ◽  
Panithee Thammawijaya ◽  
Pard Teekasap ◽  
Kamnuan Ungchusak
Keyword(s):  
Vaccination Coverage ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Initial Population ◽  
Deterministic System ◽  
Single Measure ◽  
Vaccination Strategies ◽  
Epidemic Area ◽  
The Impact ◽  
Second Wave

Abstract Background: Thailand experienced the first wave of Coronavirus Disease 2019 (COVID-19) during March-May 2020 and was now facing the second wave of COVID-19 since December 2020. For the second wave, the intensity was more pronounced. The area faced the greatest hit was Samut Sakhon, a main migrant-receiving province in the country. Thus, the Thai Ministry of Public Health (MOPH) was now considering the initiation of vaccination strategies in combination with active face finding (ACF) in the epidemic area. The objective of this study was to assess the impact of various vaccination and ACF policy scenarios in terms of case reduction and deaths averted.Methods: The study obtained data mainly from the Division of Epidemiology, Department of Disease Control (DDC), MOPH. Deterministic system dynamics and compartmental models were exercised. Basic reproductive number (R0) was estimated at 3 from the beginning. Vaccine efficacy against disease transmission was assumed to be 50%. A total of 10,000 people were estimated as an initial population size.Results: The findings showed that the greater the vaccination coverage was, the smaller the size of incident and cumulative cases. Compared with no-vaccination and no-ACF scenario, the 90%-vaccination coverage combined with 90%-ACF coverage contributed a reduction of cumulative cases by 33%. The case reduction benefit would be greater when R0 was smaller (⁓53% and ⁓51% when R0 equated 2 and 1.5 respectively).Conclusion: This study reaffirmed the idea that a combination of vaccination and ACF measures contributed to favourable results in reducing the number of COVID-19 cases and deaths, relative to the implementation of only a single measure. The greater the vaccination and ACF coverage was, the greater the volume of cases could be saved. Though we demonstrated the benefit of vaccination strategies in this setting, the actual implementation needs to consider many more policy angles, such as social acceptability, cost-effectiveness and operational feasibility. Further studies that address these topics based on empirical evidence are of great value.

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