Abstract
Eradicated infectious diseases like smallpox can re-emerge through accident or the designs of bioterrorists, and cause heavy casualties. Presently, the populace is largely susceptible as only a small percentage is vaccinated, and their immunity is likely to have waned. And when the disease re-emerges, the susceptible individuals may be manipulated by disinformation on Social Media to refuse vaccines. Thus, a combination of countermeasures consisting of antiviral drugs and vaccines and a range of policies for their application need to be investigated. Opinions regarding whether to receive vaccines evolve over time through social exchanges via networks that overlap with but are not identical to the disease propagation networks. These couple the spread of the biological and information contagion and necessitate a joint investigation of the two. We develop a computationally tractable metapopulation epidemiological model that captures the joint spatio-temporal evolution of an infectious disease (e.g., smallpox, COVID-19) and opinion dynamics. Considering smallpox, the computations based on the model show that opinion dynamics have a substantial impact on the fatality count. Towards understanding how perpetrators are likely to seed the infection, we identify a) the initial distribution of infected individuals that maximize the overall fatality count; and b) which habitation structures are more vulnerable to outbreaks. We assess the relative efficacy of different countermeasures and conclude that a combination of vaccines and drugs minimize the fatalities, and by itself, drugs reduce fatalities more than the vaccine. Accordingly, we assess the impact of increase in the supply of drugs and identify the most effective among a collection of policies for administering of drugs for various parameter combinations. Many of the observed patterns are stable to variations of a diverse set of parameters. Our findings provide a quantitative foundation for various important elements of public health discourse that have largely been conducted qualitatively.
Highlights
The devastating potential of a sudden outbreak of an infectious disease is self-evident in this time of a pandemic
We have been able to adapt the metapopulation model to capture these attributes, we describe the adaptations in Appendix A in S1 Appendix and refer to the resulting model as clustered epidemiological differential equations or the Clustered Epidemiological Differential Equation (CEDE), given that our target area is spatially decomposed in subregions referred to as clusters
Considering COVID-19 as an example, we show in Section 5 that our framework ports to any other infectious disease that spreads between individuals in proximity, through the consideration of a different set of disease states and parameters
Summary
The devastating potential of a sudden outbreak of an infectious disease is self-evident in this time of a pandemic. The havoc caused by the COVID-19 outbreak may be replicated but may be amplified should an eradicated infectious disease re-emerge. While naturally occurring smallpox was eradicated in the 1970s through decades of a global vaccination campaign, it could re-emerge under various scenarios [1,2,3,4]. Variola virus (smallpox virus) is a category A bioterrorism agent [6] and stocks of the virus are known to officially exist in two high-security biosafety level 4 laboratories in the United States (Centers for Disease Control and Prevention) and Russia (VECTOR Institute) and potentially elsewhere too [1,2,3,4]. A virus similar to Variola, horsepox, has recently been synthesized from genetic pieces ordered in the mail [9], and smallpox may be recreated using similar techniques
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