Epidemics on networks: Reducing disease transmission using health emergency declarations and peer communication

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 Pand the value of the average basic reproduction number impact the final epidemic size differentially.For the ErdÖos-Rényi and Small-world networks,an optimal choice for Pthat minimize the final epidemic size can be identified under some conditions while for Scalefree networks this is not case.

Role of short-term dispersal on the dynamics of Zika virus in an extreme idealized environment

In November 2015,El Salvador reported their first case of Zika virus(ZIKV)infection,an event followed by an explosive outbreak that generated over 6000 suspected cases in a period of two months.National agencies began implementing control measures that included vector control and recommending an increased use of repellents.Further,in response to the alarming and growing number of microcephaly cases in Brazil,the importance of avoiding pregnancies for two years was stressed.In this paper,we explore the role of mobility within communities characterized by extreme poverty,crime and violence.Specifically,the role of short term mobility between two idealized interconnected highly distinct communities is explored in the context of ZIKV outbreaks.We make use of a Lagrangian modeling approach within a two-patch setting in order to highlight the possible effects that short-term mobility,within highly distinct environments,may have on the dynamics of ZIKV outbreak when the overall goal is to reduce the number of cases not just in the most affluent areas but everywhere.Outcomes depend on existing mobility patterns,levels of disease risk,and the ability of federal or state public health services to invest in resource limited areas,particularly in those where violence is systemic.The results of simulations in highly polarized and simplified scenarios are used to assess the role of mobility.It quickly became evident that matching observed patterns of ZIKV outbreaks could not be captured without incorporating increasing levels of heterogeneity.The number of distinct patches and variations on patch connectivity structure required to match ZIKV patterns could not be met within the highly aggregated model that is used in the simulations.