Epidemics on Networks: Reducing Disease Transmission Using Health Emergency Declarations and Peer Communication
| Autor: | Yun Kang, Cesar Montalvo, Baltazar Espinoza, Carlos Castillo-Chavez, Asma Azizi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_specialty
Physics - Physics and Society media_common.quotation_subject 030231 tropical medicine FOS: Physical sciences Physics and Society (physics.soc-ph) Computer security computer.software_genre lcsh:Infectious and parasitic diseases 03 medical and health sciences 0302 clinical medicine Behavior change medicine lcsh:RC109-216 Original Research Article 030212 general & internal medicine Function (engineering) Quantitative Biology - Populations and Evolution media_common Small-world network Social network Outbreak and epidemic threats business.industry Applied Mathematics Health Policy Public health Scale-free network Populations and Evolution (q-bio.PE) Infectious Diseases Erdős-rényi network FOS: Biological sciences Awareness spread The Internet Business Basic reproduction number computer |
| Zdroj: | Infectious Disease Modelling, Vol 5, Iss, Pp 12-22 (2020) Infectious Disease Modelling |
| Popis: | Understanding individual decisions in a world where communications and information move instantly via cell phones and the internet, contributes to the development and implementation of policies aimed at stopping or ameliorating the spread of diseases. In this manuscript, the role of official social network perturbations generated by public health officials to slow down or stop a disease outbreak are studied over distinct classes of static social networks. The dynamics are stochastic in nature with individuals (nodes) being assigned fixed levels of education or wealth. Nodes may change their epidemiological status from susceptible, to infected and to recovered. Most importantly, it is assumed that when the prevalence reaches a pre-determined threshold level, P * , information, called awareness in our framework, starts to spread, a process triggered by public health authorities. Information is assumed to spread over the same static network and whether or not one becomes a temporary informer, is a function of his/her level of education or wealth and epidemiological status. Stochastic simulations show that threshold selection P * and the value of the average basic reproduction number impact the final epidemic size differentially. For the Erdős-Renyi and Small-world networks, an optimal choice for P * that minimize the final epidemic size can be identified under some conditions while for Scale-free networks this is not case. |
| Databáze: | OpenAIRE |
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