Emerging Challenges and Opportunities in Infectious Disease Epidemiology.

Much of the intellectual tradition of modern epidemiology stems from efforts to understand and combat chronic diseases persisting through the 20th century epidemiologic transition of countries such as the United States and United Kingdom. After decades of relative obscurity, infectious disease epidemiology has undergone an intellectual rebirth in recent years amid increasing recognition of the threat posed by both new and familiar pathogens. Here, we review the emerging coalescence of infectious disease epidemiology around a core set of study designs and statistical methods bearing little resemblance to the chronic disease epidemiology toolkit. We offer our outlook on challenges and opportunities facing the field, including the integration of novel molecular and digital information sources into disease surveillance, the assimilation of such data into models of pathogen spread, and the increasing contribution of models to public health practice. We next consider emerging paradigms in causal inference for infectious diseases, ranging from approaches to evaluating vaccines and antimicrobial therapies to the task of ascribing clinical syndromes to etiologic microorganisms, an age-old problem transformed by our increasing ability to characterize human-associated microbiota. These areas represent an increasingly important component of epidemiology training programs for future generations of researchers and practitioners

THE DISINFODEMIC MITIGATION STRATEGY OF MAFINDO IN INDONESIA

Social media is usually utilized for literacy and education in articulating ideas and criticism. This study focused on the utilization of social media in the community during the COVID-19 outbreak, the implications for critical political awareness, and the wise use of social media. The data used was a compilation of hoax data circulating in Indonesia from independent fact-checking sites, government-run fact-checking sites, and fact-checking channels created by the mainstream media. The results revealed that the strong political polarization among the people was the cause of the massive spread of false news and hate speech during the COVID-19 outbreak. This study also described the mitigation strategy of MAFINDO to improve information security in facing an event that leads to an information crisis during the COVID-19 pandemic. Therefore, disinfodemic mitigation strategy was constructed as part of an early warning system in increasing public immunity against disinfodemic and controlling the spread of public suggestions and dangerous reactions. This study can be used an early warning system to prevent health misinformation by revitalizing the movement of the anti hoax community in online and offline education

BAND: Biomedical Alert News Dataset

Infectious disease outbreaks continue to pose a significant threat to human health and well-being. To improve disease surveillance and understanding of disease spread, several surveillance systems have been developed to monitor daily news alerts and social media. However, existing systems lack thorough epidemiological analysis in relation to corresponding alerts or news, largely due to the scarcity of well-annotated reports data. To address this gap, we introduce the Biomedical Alert News Dataset (BAND), which includes 1,508 samples from existing reported news articles, open emails, and alerts, as well as 30 epidemiology-related questions. These questions necessitate the model's expert reasoning abilities, thereby offering valuable insights into the outbreak of the disease. The BAND dataset brings new challenges to the NLP world, requiring better disguise capability of the content and the ability to infer important information. We provide several benchmark tasks, including Named Entity Recognition (NER), Question Answering (QA), and Event Extraction (EE), to show how existing models are capable of handling these tasks in the epidemiology domain. To the best of our knowledge, the BAND corpus is the largest corpus of well-annotated biomedical outbreak alert news with elaborately designed questions, making it a valuable resource for epidemiologists and NLP researchers alike

Biotechnologies Applied in Biomedical Vaccines

Vaccination, the administration of an antigenic material (vaccine), is considered to be the most effective method for disease prevention and control. A vaccine usually contains an agent that resembles a diseases‐causing pathogen and is often made from inactivated microbes, live attenuated microbes, its toxins, or part of surface antigens (subunit). However, the modern biotechnological tools and genomics have opened a new era to develop novel vaccines and many products are successfully marketing around the world. It is important to formulate and deliver these vaccines appropriately to maximize the potential advances in prevention, therapy, and vaccinology. New vaccines employing biotechnological innovations are helping us to change the way for illness prevention. The clinical application of vaccines will be diversified along with the development of biotechnologies. In modern society, the outbreak of many infectious diseases has decreased through vaccination, but the burden of noninfectious diseases is growing. The new biotechnologies may result in not only the appreciation of vaccines which are critical in inducing protection against an infectious disease but also the production of therapeutic vaccines which are effective for alldiseases including infectious and noninfectious diseases

The Frailty of the Invincible

The COVID-19 pandemic has unveiled the frailty of our societies from too many points of view to look away. We need to understand why we were all caught unprepared. On the one hand, we have all short memories. As we forget too quickly, we were unable to recognize key factors influencing response and preparedness to public health threats. For many years, economic evaluation pushed governments all over the world to cut resources for public health systems, with COVID-19 pandemic the question arises: do we spend too much or too little on health care? What is the right amount to spend on health? Moreover, in many countries, the privatisation, or semi-privatisation, of healthcare may give rise to inequitable access to health care for everyone. Although COVID-19 is very "democratic", its consequences aren't. According to OECD, income inequality in OECD countries is at its highest level for the past half century. Three main causes have been recognized, technological revolution, globalization, and "financialisation". In this scenario, lockdown measures adopted to save lives are showing dramatic economic consequences. To address post COVID-19 reconstruction we need to go beyond GDP. As an economic measure this has many shortcomings in describing the real well-being of a country, and since what we measure affects what we do, new paradigms will have to guide the post COVID-19 reconstruction strategies, as the fate of countries and their citizens is at stake