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Influenza and COVID-19 are infectious diseases with significant burdens. Information and awareness on preventative techniques can be spread through the use of social media, which has become an increasingly utilized tool in recent years. This study developed a dynamic transmission model to investigate the impact of social media, particularly tweets via the social networking platform, Twitter on the number of influenza and COVID-19 cases of infection and deaths. We modified the traditional Susceptible-Exposed-Infectious-Recovered (SEIR-V) model with an additional social media component, in order to increase the accuracy of transmission dynamics and gain insight on whether social media is a beneficial behavioral intervention for these infectious diseases. The analysis found that social media has a positive effect in mitigating the spread of contagious disease in terms of peak time, peak magnitude, total infected, and total death; and the results also showed that social media's effect has a non-linear relationship with the reproduction number R 0 and it will be amplified when a vaccine is available. The findings indicate that social media is an integral part in the humanitarian logistics of pandemic and emergency preparedness, and contributes to the literature by informing best practices in the response to similar disasters.

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Purpose Hepatitis A is a prevalent disease that is largely preventable by vaccine usage. The vaccine for this illness is highly underused in most regions. In an attempt to find the strategies that are most beneficial in regard to quality-adjusted life years (QALYs) and cost in current environments, the purpose of this paper is to conduct cost-effectiveness analyses to investigate vaccination strategies in a more economically developed country (MEDC), generally known as a “developed” area: the USA, and a less economically developed country (LEDC), generally known as a “developing” area: the state of Rio de Janeiro, Brazil. Design/methodology/approach This study used a dynamic transmission model for comparative effectiveness analyses. The model ran two different scenarios. The two regions studied have different policies and strategies for Hepatitis A vaccination currently, and also used different strategies in 2009. In the USA, a universal vaccination policy was modeled, along with a scenario in which it was removed. In Rio de Janeiro, a no vaccination policy was modeled, along with a scenario in which a universal vaccination policy was effected. Findings The comparison of resulting incremental cost-effectiveness ratio values to accepted threshold values showed universal vaccination to be cost-effective in both the USA and Rio de Janeiro as compared to no vaccination. When episode and vaccination costs and vaccination efficacy were varied, this still remained true. Universal vaccination was found to result in lower incidence of Hepatitis A in both the USA and Rio de Janeiro. Over the twenty-year time horizon, universal vaccination is projected to prevent 506,945 cases of symptomatic Hepatitis A in the USA and 42,318 cases of Hepatitis A in Rio de Janeiro. Other benefits include a projected increase in cumulative QALYs through the use of universal vaccination. Originality/value This analysis showed universal vaccination to be cost-effective as compared to no vaccination, and portions of the study’s approach had not previously been applied in tandem to investigate Hepatitis A interventions. The results may help foster higher compliance rates for Hepatitis A vaccination and even greater per-person economic benefits of universal vaccination, particularly in the USA. The purpose of this study is also to encourage elevated levels of surveillance on age of infection in developing regions and consistent reevaluation utilizing dynamic transmission models in both the USA and Brazil, as well as other rapidly developing regions, in order to prevent future epidemics and costs associated with the disease.