FLUed: A Novel Four-Layer Model for Simulating Epidemic Dynamics and Assessing Intervention Policies

From the 2003 severe acute respiratory syndrome (SARS) epidemic, to the 2009 swine-origin influenza A (H1N1) pandemic, to the projected highly pathogenic avian influenza A event, emerging infectious diseases highlight the importance of computational epidemiology to assess potential intervention policies. Hence, an important and timely research goal is a general-purpose and extendable simulation model that integrates two major epidemiological factors—age group and population movement—and substantial amounts of demographic, geographic, and epidemiologic data. In this paper, we describe a model that we have named FLUed for Four-layer Universal Epidemic Dynamics that integrates complex daily commuting network data into multiple age-structured compartmental models. FLUed has four contact structures for simulating the epidemic dynamics of emerging infectious diseases, assessing the potential efficacies of various intervention policies, and identifying the potential impacts of spatial-temporal epidemic trends on specific populations. We used data from the seasonal influenza A and 2009 swine-origin influenza A (H1N1) epidemics to validate model reliability and suitability and to assess the potential impacts of intervention policies and variation in initial outbreak areas for novel/seasonal influenza A in Taiwan. We believe that the FLUed model represents an effective tool for public health agencies responsible for initiating early responses to potential pandemics.

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Ocular manifestations of emerging viral diseases

Eye ◽

10.1038/s41433-020-01376-y ◽

2021 ◽

Author(s):

Ashwin Venkatesh ◽

Ravi Patel ◽

Simran Goyal ◽

Timothy Rajaratnam ◽

Anant Sharma ◽

...

Keyword(s):

Public Health ◽

Infectious Diseases ◽

Influenza A ◽

Emerging Infectious Diseases ◽

Global Scale ◽

Viral Diseases ◽

Valley Fever ◽

Ocular Manifestations ◽

Influenza A H1n1 ◽

Emerging Viral Diseases

AbstractEmerging infectious diseases (EIDs) are an increasing threat to public health on a global scale. In recent times, the most prominent outbreaks have constituted RNA viruses, spreading via droplets (COVID-19 and Influenza A H1N1), directly between humans (Ebola and Marburg), via arthropod vectors (Dengue, Zika, West Nile, Chikungunya, Crimean Congo) and zoonotically (Lassa fever, Nipah, Rift Valley fever, Hantaviruses). However, specific approved antiviral therapies and vaccine availability are scarce, and public health measures remain critical. Patients can present with a spectrum of ocular manifestations. Emerging infectious diseases should therefore be considered in the differential diagnosis of ocular inflammatory conditions in patients inhabiting or returning from endemic territories, and more general vigilance is advisable in the context of a global pandemic. Eye specialists are in a position to facilitate swift diagnosis, improve clinical outcomes, and contribute to wider public health efforts during outbreaks. This article reviews those emerging viral diseases associated with reports of ocular manifestations and summarizes details pertinent to practicing eye specialists.

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Assessing the Use of Antiviral Treatment to Control Influenza

10.1101/001537 ◽

2013 ◽

Author(s):

Sarah C Kramer ◽

Shweta Bansal

Keyword(s):

Antiviral Therapy ◽

Influenza A ◽

Seasonal Influenza ◽

Antiviral Treatment ◽

Control Policy ◽

Population Level ◽

Contact Network ◽

Therapy Strategy ◽

Influenza A H1n1 ◽

Age Structured

Vaccines are the cornerstone of influenza control policy, but can suffer from several drawbacks. Seasonal influenza vaccines are prone to production problems and low efficacies, while pandemic vaccines are unlikely to be available in time to slow a rapidly spreading global outbreak. Antiviral therapy was found to be beneficial during the influenza A(H1N1)pdm09 pandemic even with limited use; however, antiviral use has decreased further since then. We seek to determine the role antiviral therapy can play in pandemic and seasonal influenza control on the population level, and to find optimized strategies for more efficient use of treatment. Using an age-structured contact network model for an urban population, we find that while a conservative antiviral therapy strategy cannot replace a robust influenza vaccine, it can play a role in reducing attack rates and eliminating outbreaks.

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Active surveillance of acute paediatric hospitalisations demonstrates the impact of vaccination programmes and informs vaccine policy in Canada and Australia

Eurosurveillance ◽

10.2807/1560-7917.es.2020.25.25.1900562 ◽

2020 ◽

Vol 25 (25) ◽

Author(s):

Karina A Top ◽

Kristine Macartney ◽

Julie A Bettinger ◽

Ben Tan ◽

Christopher C Blyth ◽

...

Keyword(s):

Public Health ◽

Infectious Diseases ◽

Active Surveillance ◽

Influenza A ◽

Monitoring Program ◽

Emerging Infectious Diseases ◽

Emerging Infections ◽

Public Health Response ◽

Influenza A H1n1 ◽

The Impact

Sentinel surveillance of acute hospitalisations in response to infectious disease emergencies such as the 2009 influenza A(H1N1)pdm09 pandemic is well described, but recognition of its potential to supplement routine public health surveillance and provide scalability for emergency responses has been limited. We summarise the achievements of two national paediatric hospital surveillance networks relevant to vaccine programmes and emerging infectious diseases in Canada (Canadian Immunization Monitoring Program Active; IMPACT from 1991) and Australia (Paediatric Active Enhanced Disease Surveillance; PAEDS from 2007) and discuss opportunities and challenges in applying their model to other contexts. Both networks were established to enhance capacity to measure vaccine preventable disease burden, vaccine programme impact, and safety, with their scope occasionally being increased with emerging infectious diseases’ surveillance. Their active surveillance has increased data accuracy and utility for syndromic conditions (e.g. encephalitis), pathogen-specific diseases (e.g. pertussis, rotavirus, influenza), and adverse events following immunisation (e.g. febrile seizure), enabled correlation of biological specimens with clinical context and supported responses to emerging infections (e.g. pandemic influenza, parechovirus, COVID-19). The demonstrated long-term value of continuous, rather than incident-related, operation of these networks in strengthening routine surveillance, bridging research gaps, and providing scalable public health response, supports their applicability to other countries.

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Influenza: An Emerging and Re-emerging Public Health Threat in Nepal

Annals of Clinical Chemistry and Laboratory Medicine ◽

10.3126/acclm.v3i2.20737 ◽

2018 ◽

Vol 3 (2) ◽

pp. 1-2

Author(s):

Bishnu Prasad Upadhyay

Keyword(s):

Influenza Virus ◽

Influenza A ◽

Winter Season ◽

Emerging Infectious Diseases ◽

Influenza Viruses ◽

Influenza B ◽

Influenza A Viruses ◽

Influenza A H1n1 ◽

New Variant ◽

Seasonal Epidemics

Influenza virus type A and B are responsible for seasonal epidemics as well as pandemics in human. Influenza A viruses are further divided into two major groups namely, low pathogenic seasonal influenza (A/H1N1, A/H1N1 pdm09, A/H3N2) and highly pathogenic influenza virus (H5N1, H5N6, H7N9) on the basis of two surface antigens: hemagglutinin (HA) and neuraminidase (NA). Mutations, including substitutions, deletions, and insertions, are one of the most important mechanisms for producing new variant of influenza viruses. During the last 30 years; more than 50 viral threat has been evolved in South-East Asian countriesof them influenza is one of the major emerging and re-emerging infectious diseases of global concern. Similar to tropical and sub-tropical countries of Southeast Asia; circulation of A/H1N1 pdm09, A/H3N2 and influenza B has been circulating throughout the year with the peak during July-November in Nepal. However; the rate of infection transmission reach peak during the post-rain and winter season of Nepal.

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Comparisons of Clinical Features among Influenza A (H1N1) and Seasonal Influenza A and B during 2009 to 2010 at a Single Institution

Pediatric Allergy and Respiratory Disease ◽

10.7581/pard.2011.21.4.269 ◽

2011 ◽

Vol 21 (4) ◽

pp. 269 ◽

Cited By ~ 6

Author(s):

Tae-Gon Kang ◽

Mi-Jin Kim ◽

Byoung-Gwon Kim ◽

Hye-Sung An ◽

Hyun-Jin Yun ◽

...

Keyword(s):

Clinical Features ◽

Influenza A ◽

Seasonal Influenza ◽

Single Institution ◽

Influenza A H1n1

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Seasonal influenza vaccines induced high levels of neutralizing cross-reactive antibody responses against different genetic group influenza A(H1N1)pdm09 viruses

Vaccine ◽

10.1016/j.vaccine.2019.03.078 ◽

2019 ◽

Vol 37 (20) ◽

pp. 2731-2740 ◽

Cited By ~ 1

Author(s):

Anu Haveri ◽

Niina Ikonen ◽

Anu Kantele ◽

Veli-Jukka Anttila ◽

Eeva Ruotsalainen ◽

...

Keyword(s):

Influenza A ◽

Seasonal Influenza ◽

Antibody Responses ◽

Genetic Group ◽

Influenza Vaccines ◽

Influenza A H1n1 ◽

Reactive Antibody

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Hospitalized Children with 2009 Pandemic Influenza A (H1N1): Comparison to Seasonal Influenza and Risk Factors for Admission to the ICU

PLoS ONE ◽

10.1371/journal.pone.0015173 ◽

2010 ◽

Vol 5 (12) ◽

pp. e15173 ◽

Cited By ~ 50

Author(s):

Dayanand Bagdure ◽

Donna J. Curtis ◽

Emily Dobyns ◽

Mary P. Glodé ◽

Samuel R. Dominguez

Keyword(s):

Risk Factors ◽

Pandemic Influenza ◽

Influenza A ◽

Seasonal Influenza ◽

Hospitalized Children ◽

Influenza A H1n1

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Spread of Infectious Disease Modeling and Analysis of Different Factors on Spread of Infectious Disease Based on Cellular Automata

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16234683 ◽

2019 ◽

Vol 16 (23) ◽

pp. 4683 ◽

Cited By ~ 7

Author(s):

Sheng Bin ◽

Gengxin Sun ◽

Chih-Cheng Chen

Keyword(s):

Infectious Disease ◽

Cellular Automata ◽

Infectious Diseases ◽

Pandemic Influenza ◽

Influenza A ◽

Disease Modeling ◽

Real Life ◽

Automata Theory ◽

Future Research ◽

Influenza A H1n1

Infectious diseases are an important cause of human death. The study of the pathogenesis, spread regularity, and development trend of infectious diseases not only provides a theoretical basis for future research on infectious diseases, but also has practical guiding significance for the prevention and control of their spread. In this paper, a controlled differential equation and an objective function of infectious diseases were established by mathematical modeling. Based on cellular automata theory and a compartmental model, the SLIRDS (Susceptible-Latent-Infected-Recovered-Dead-Susceptible) model was constructed, a model which can better reflect the actual infectious process of infectious diseases. Considering the spread of disease in different populations, the model combines population density, sex ratio, and age structure to set the evolution rules of the model. Finally, on the basis of the SLIRDS model, the complex spread process of pandemic influenza A (H1N1) was simulated. The simulation results are similar to the macroscopic characteristics of pandemic influenza A (H1N1) in real life, thus the accuracy and rationality of the SLIRDS model are confirmed.

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