An SEIR model of influenza A virus infection and reinfection within a farrow-to-finish swine farm

Etbaigha, Fatima; Willms, Allan R.; Poljak, Zvonimir

doi:10.1371/journal.pone.0202493

Cited by 42 publications

(36 citation statements)

References 28 publications

(54 reference statements)

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“…For pigs reared in groups of relatively small sizes, stochastic frameworks have been privileged [43,[46][47][48][49], although deterministic approaches based on ordinary differential equations were also developed. The latter were either theoretical models with in depth mathematical analysis, providing insight into the model behaviour according to epidemiological assumptions or parameter values [50][51][52][53], or applied models with an accurate representation of the farm systems [54][55][56]. For illustrative purpose, the issue of on-farm persistence of SIV represent a quarter of the selected articles.…”

Section: Mat 1)mentioning

confidence: 99%

“…For illustrative purpose, the issue of on-farm persistence of SIV represent a quarter of the selected articles. The set of companion papers by Reynolds et al [56] and Etbaigha et al [54] dealt with the spread of influenza virus in breeding and farrow-to-finish pig herds using deterministic modelling frameworks. The herd structure was described in details accounting for animal movements between different barns.…”

Section: Mat 1)mentioning

confidence: 99%

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Modelling infectious viral diseases in swine populations: a state of the art

Andraud

Rose

2020

Porc Health Manag

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Mathematical modelling is nowadays a pivotal tool for infectious diseases studies, completing regular biological investigations. The rapid growth of computer technology allowed for development of computational tools to address biological issues that could not be unravelled in the past. The global understanding of viral disease dynamics requires to account for all interactions at all levels, from within-host to between-herd, to have all the keys for development of control measures. A literature review was performed to disentangle modelling frameworks according to their major objectives and methodologies. One hundred and seventeen articles published between 1994 and 2020 were found to meet our inclusion criteria, which were defined to target papers representative of studies dealing with models of viral infection dynamics in pigs. A first descriptive analysis, using bibliometric indexes, permitted to identify keywords strongly related to the study scopes. Modelling studies were focused on particular infectious agents, with a shared objective: to better understand the viral dynamics for appropriate control measure adaptation. In a second step, selected papers were analysed to disentangle the modelling structures according to the objectives of the studies. The system representation was highly dependent on the nature of the pathogens. Enzootic viruses, such as swine influenza or porcine reproductive and respiratory syndrome, were generally investigated at the herd scale to analyse the impact of husbandry practices and prophylactic measures on infection dynamics. Epizootic agents (classical swine fever, foot-and-mouth disease or African swine fever viruses) were mostly studied using spatio-temporal simulation tools, to investigate the efficiency of surveillance and control protocols, which are predetermined for regulated diseases. A huge effort was made on model parameterization through the development of specific studies and methodologies insuring the robustness of parameter values to feed simulation tools. Integrative modelling frameworks, from within-host to spatio-temporal models, is clearly on the way. This would allow to capture the complexity of individual biological variabilities and to assess their consequences on the whole system at the population level. This would offer the opportunity to test and evaluate in silico the efficiency of possible control measures targeting specific epidemiological units, from hosts to herds, either individually or through their contact networks. Such decision support tools represent a strength for stakeholders to help mitigating infectious diseases dynamics and limiting economic consequences.

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Section: Mat 1)mentioning

confidence: 99%

Section: Mat 1)mentioning

confidence: 99%

Modelling infectious viral diseases in swine populations: a state of the art

Andraud

Rose

2020

Porc Health Manag

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“…Model SEIR adalah pengembangan dari SIS dan SIR. Beberapa penyebaran penyakit dimodelkan dalam bentuk SEIR, misalnya model penularan virus HIV ( [11,12]), model penularan virus rabies ( [13,14]), model penularan virus influenza [15]…”

Section: Model Matematikaunclassified

VSEIR Mathematical Model on Anthrax Disease Dissemination in Animal Population with Vaccination and Treatment Effect

Asikin

2020

JMSK

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This research aimed to determine the equilibrium point and analyze the stability of VSEIR model on Anthrax Disease with vaccination and treatment effects. It also aimed at measuring the level sensitivity of Anthrax disease deployment to proportion vaccination effect and proportion treatment effect by using . The writer used qualitative method to achieve the above objectives. The steps were: Reproduction Base Numbers, The R0, was analyzed using stability of disease-free equilibrium points, where the equilibrium point of both is said to asymptotically stable if and unstable if that originally based on the next generation method. Next, the writer also analyze the stability of equilibrium point that was obtained by using the Routh-Hurwitz Criteria and Numeric Simulation. After analyze the sensitivity, the writer finds the proportion of vaccination effects on new-born animal and the treatment of infected animal can reduce the spread of Anthrax Virus and also to terminate the endemic conditions. The numeric simulation is involved to describe the level of vaccination effect new-born animal, and the treatment of infected animal at Anthrax disease deployment.

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“…Human contact affects the epidemics of infectious diseases [11]. Generally, infectious, exposed, and recovered individuals are the core factors affecting the epidemic efficiency of infectious diseases [12]. Effective policies can reduce the transmission efficiency of infectious diseases by blocking infectious areas, collecting medical resources to cure patients, and suggesting the public to take personal protective measures (such as wearing masks and washing hands) [13].…”

Section: Introductionmentioning

confidence: 99%

Linking key intervention timings to rapid declining effective reproduction number to quantify lessons against COVID-19

et al. 2020

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Coronavirus disease 2019 (COVID-19) is currently under a global pandemic trend. The efficiency of containment measures and epidemic tendency of typical countries should be assessed. In this study, the efficiency of prevention and control measures in China, Italy, Iran, South Korea, and Japan was assessed, and the COVID-19 epidemic tendency among these countries was compared. Results showed that the effective reproduction number(Re) in Wuhan, China increased almost exponentially, reaching a maximum of 3.98 before a lockdown and rapidly decreased to below 1 due to containment and mitigation strategies of the Chinese government. The Re in Italy declined at a slower pace than that in China after the implementation of prevention and control measures. The Re in Iran showed a certain decline after the establishment of a national epidemic control command, and an evident stationary phase occurred because the best window period for the prevention and control of the epidemic was missed. The epidemic in Japan and South Korea reoccurred several times with the Re fluctuating greatly. The epidemic has hardly rebounded in China due to the implementation of prevention and control strategies and the effective enforcement of policies. Other countries suffering from the epidemic could learn from the Chinese experience in containing COVID-19.

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An SEIR model of influenza A virus infection and reinfection within a farrow-to-finish swine farm

Cited by 42 publications

References 28 publications

Modelling infectious viral diseases in swine populations: a state of the art

Modelling infectious viral diseases in swine populations: a state of the art

VSEIR Mathematical Model on Anthrax Disease Dissemination in Animal Population with Vaccination and Treatment Effect

Linking key intervention timings to rapid declining effective reproduction number to quantify lessons against COVID-19

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