Transmission of Acute Respiratory Infections in a City: Agent-Based Approach

Abstract

An incidence curve of acute respiratory infections in Moscow has three picks between September and April and reaches its maximum in January- February. The emergence of new strains of influenza A could account for only one pick a year. The most cases of common cold are caused by ubiquitous low pathogenic viruses. In order to simulate weekly fluctuation of incidence rate of acute respiratory illnesses we developed an agent-based model. It contains 10 millions agents with such attributes as sex, age, social status, levels of specific immune memory and lists of contacts. Each agent can contact with members of its household, colleagues or classmates. Through such contacts susceptible agent can be infected with one of seven circulating respiratory viruses. Viruses differ in their immunologic properties and assume to present influenza A virus, influenza B virus, parainfluenza, adenovirus, coronavirus, rhinovirus and respiratory syncytial virus. The rate of transmission depends on duration of contact, vulnerability of susceptible agent, infectivity of infected agent and air temperature. Proposed network of social interactions proved to be sufficiently detailed as it provided good fitting for observed incidence rate including periods of school holidays and winter public holidays. Additionally, the estimates of basic reproductive rate for the viruses confirm that all these viruses except new strains of influenza A are relatively harmless and unable to cause significant growth of acute respiratory infections morbidity.

Direct Statistical Modeling of Spread of Epidemic Based On a Stage-Dependent Stochastic Model

“…Обратимся к предположениям H4, H6, H8 без учета H1, H2, H3, H5, H7. Рассмотрим компоненты Ω(t j ), заданные соотношениями ( 5)- (10). Положим:…”

“…Исследование эпидемических процессов представляет собой хорошо развитое направление в использовании метода математического моделирования для изучения живых систем. Примеры разнообразных математических моделей, возникающих в задачах эпидемиологии, приведены в работах [1]- [10] и содержащихся в них ссылках на работы других авторов. Пандемия Ковид-19 инфекции привела к активной разработке математических моделей, отражающих динамику численности инфицированных, больных и умерших от Ковид-19 индивидуумов.…”

Simulation of COVID-19 Spread Scenarios in the Republic of Kazakhstan Based on Regularization of the Agent-Based Model

“…Here is a brief survey of the publications on agent-based modeling of COVID-19, which are largely based on earlier work on the modeling of infectious diseases in 2013 [ 4 ] and 2020 [ 5 ].…”