How the Field of Infectious Diseases Can Leverage Digital Strategy and Social Media Use During a Pandemic

Online spaces and the control of communicable diseases: implications for nursing practice

The digital revolution has significantly altered healthcare, including communicable disease control, with online spaces emerging as vital tools in preventing, identifying and controlling the spread of diseases. However, healthcare professionals, including nurses, need to find a balance between harnessing the benefits of mass communication and mitigating the potentially harmful effects of online misinformation. This article explores the benefits and challenges of using online spaces such as social media platforms in the control of communicable diseases and discusses the potential use of telehealth in reducing the risk of healthcare-associated infection and antimicrobial resistance. The author also describes a framework that nurses can use to explore potential roles and practice in the context of communicable disease control in online spaces.

Deep evolutionary fusion neural network: a new prediction standard for infectious disease incidence rates

BACKGROUND

Previously, many methods have been used to predict the incidence trends of infectious diseases. There are numerous methods for predicting the incidence trends of infectious diseases, and they have exhibited varying degrees of success. However, there are a lack of prediction benchmarks that integrate linear and nonlinear methods and effectively use internet data. The aim of this paper is to develop a prediction model of the incidence rate of infectious diseases that integrates multiple methods and multisource data, realizing ground-breaking research.

RESULTS

The infectious disease dataset is from an official release and includes four national and three regional datasets. The Baidu index platform provides internet data. We choose a single model (seasonal autoregressive integrated moving average (SARIMA), nonlinear autoregressive neural network (NAR), and long short-term memory (LSTM)) and a deep evolutionary fusion neural network (DEFNN). The DEFNN is built using the idea of neural evolution and fusion, and the DEFNN + is built using multisource data. We compare the model accuracy on reference group data and validate the model generalizability on external data. (1) The loss of SA-LSTM in the reference group dataset is 0.4919, which is significantly better than that of other single models. (2) The loss values of SA-LSTM on the national and regional external datasets are 0.9666, 1.2437, 0.2472, 0.7239, 1.4026, and 0.6868. (3) When multisource indices are added to the national dataset, the loss of the DEFNN + increases to 0.4212, 0.8218, 1.0331, and 0.8575.

CONCLUSIONS

We propose an SA-LSTM optimization model with good accuracy and generalizability based on the concept of multiple methods and multiple data fusion. DEFNN enriches and supplements infectious disease prediction methodologies, can serve as a new benchmark for future infectious disease predictions and provides a reference for the prediction of the incidence rates of various infectious diseases.

Pivoting Continuing Professional Development During the COVID-19 Pandemic: A Narrative Scoping Review of Adaptations and Innovations

INTRODUCTION

Most formal continuing professional development (CPD) opportunities were offered in person until March 2020 when the COVID-19 pandemic disrupted traditional structures of CPD offerings. The authors explored the adaptations and innovations in CPD that were strengthened or newly created during the first 16 months of the pandemic.

METHODS

The objectives of the narrative review were to answer the following questions: (1) what types of adaptations to CPD innovations are described? and (2) what may shape future innovations in CPD? The following databases were searched: Medline, Embase, CINAHL, and ERIC to identify the literature published between March 2020 to July 2021. The authors conducted a comprehensive search by including all study types that described adaptations and/or innovations in CPD during the stated pandemic period.

RESULTS

Of the 8295 citations retrieved from databases, 191 satisfied the inclusion criteria. The authors found three categories to describe adaptations to CPD innovations: (1) creation of new online resources, (2) increased use of the existing online platforms/software to deliver CPD, and (3) use of simulation for teaching and learning. Reported advantages and disadvantages associated with these adaptations included logistical, interactional, and capacity building elements. The review identified five potential future CPD innovations: (1) empirical research on the effectiveness of virtual learning; (2) novel roles and ways of thinking; (3) learning from other disciplines beyond medicine; (4) formation of a global perspective; and (5) emerging wellness initiatives.

DISCUSSION

This review provided an overview of the adaptations and innovations that may shape the future of CPD beyond the pandemic.

Preserving the Future of Infectious Diseases: Why We Must Address the Decline in Compensation for Clinicians and Researchers

Infectious diseases (ID) physicians play a pivotal role in patient care and public health, yet concerns are mounting about their under-compensation compared with other medical specialties. This trend sees ID physicians, including new graduates, receiving lower remuneration than their general and hospital medicine peers, despite their significant contributions. The persistent disparity in compensation has been identified as a key factor behind the declining interest in the ID specialty among medical students and residents, potentially threatening patient care quality, research advancement, and diversity within the ID workforce. This viewpoint underscores the urgent need for the ID community to rally behind the Infectious Diseases Society of America in advocating for fair compensation for ID physicians and researchers. While focusing on wellness and work-life balance is vital, it is critical to address compensation, a significant source of distress for physicians. Failure to confront the issue of under-compensation promptly may jeopardize the future growth and sustainability of the ID specialty.

Adoption and Utilization of Social Media Among Adult and Pediatric Infectious Diseases Divisions and Fellowship Programs in the United States

Background

Social media (SoMe) is ubiquitous, but its adoption and utilization by infectious diseases (ID) divisions are poorly characterized in the United States.

Methods

A systematic search of US ID fellowship/division Twitter, Facebook, and Instagram accounts occurred in November-December 2021. Social media account and program characteristics, post frequency and content, and other measures of SoMe adoption and utilization were recorded and compared between adult and pediatric programs. Posts were thematically categorized as social, promotional, educational, recruitment, or other.

Results

Of 222 ID programs identified, 158 (71.2%) were adult and 64 (28.8%) pediatric. Seventy (31.5%) Twitter, 14 (6.3%) Facebook, and 14 (6.3%) Instagram accounts were identified from US programs. Twitter accounts were associated with larger programs and higher match rates. More adult than pediatric programs had Twitter accounts (37.3% vs 17.2%, P = .004); utilization was similar between adult and pediatric programs. Most Twitter posts were educational (1653 of 2859, 57.8%); most Facebook posts were promotional (68 of 128, 53.1%); and most Instagram posts were social (34 of 79, 43%). Facebook was the earliest adopted SoMe platform, but Twitter and Instagram have more recent growth. Rate of Twitter account creation increased from 1.33 accounts/month in the year before March 2020 (coronavirus disease [COVID] pandemic declaration) to 2.58 accounts/month in the year after March 2020 (P = .18).

Conclusions

Social media remains underutilized across ID divisions, but COVID-19 and virtual recruiting may have influenced recent account creation. Twitter was the most frequently used ID program SoMe platform. Social media may benefit ID programs in recruitment and amplification of their trainees, faculty, and specialty.

Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission

With the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission. Hence, we collect Internet multisource big data (including retrieval, migration, and media data) and propose comprehensive and relative application strategies to eliminate the impact of national and media data. We use statistical classification and regression to construct an early warning model for occurrence and development. Under the guidance of the improved coronavirus herd immunity optimizer (ICHIO), we construct a "sampling-feature-hyperparameter-weight" synchronous optimization strategy. In occurrence warning, we propose an undersampling synchronous evolutionary ensemble (USEE); in development warning, we propose a bootstrap-sampling synchronous evolutionary ensemble (BSEE). Regarding the internal training data (Heilongjiang Province), the ROC-AUC of USEE3 incorporating multisource data is 0.9553, the PR-AUC is 0.8327, and the R² of BSEE2 fused by the "nonlinear + linear" method is 0.8698. Regarding the external validation data (Shaanxi Province), the ROC-AUC and PR-AUC values of USEE3 were 0.9680 and 0.9548, respectively, and the R² of BSEE2 was 0.8255. Our method has good accuracy and generalization and can be flexibly used in the prediction of cryptic transmission in various regions. We propose strategy research that integrates multiple early warning tasks based on multisource Internet big data and combines multiple ensemble models. It is an extension of the research in the field of traditional infectious disease monitoring and has important practical significance and innovative theoretical value.

#Curbsiding: potential value and patient confidentiality implications of infectious disease clinician peer consultations via social media

Infectious disease (ID) clinician’s social media use for peer consultation is unstudied. We reviewed ID peer consultation via Twitter over a 6-week period. We found this practice frequently solicited meaningful replies, but we identified potential for confidentiality breaches. We offer recommendations for responsible discussion of clinical scenarios via social media.

Digital Strategy and Social Media for Infectious Diseases

This supplement demonstrates the profound reach of social media across several domains: improved clinical care and advocacy, data analysis, broad reach to diverse patient populations, educational access, best practices in medical education, peer review, digital strategy for individuals and institutions, and combating misinformation.

How to Harness the Power of Social Media for Quality Drug Information in Infectious Diseases: Perspectives on Behalf of the Society of Infectious Diseases Pharmacists

Clinicians, researchers, and the public frequently turn to digital channels and social media for up-to-the-minute information on novel therapeutics and vaccines. The value of credible infectious diseases drug information is more apparent in the setting of the coronavirus disease 2019 (COVID-19) pandemic. This viewpoint by the Society of Infectious Diseases Pharmacists (SIDP) provides guidance on utilizing social media platforms to optimize infectious diseases pharmacotherapy. It includes tips for all levels of users but primarily serves a guide for the infectious diseases clinician who has not yet joined social media. It compares various social media platforms and suggests which to begin with based on user needs, recommends efficient curation of social media content, and outlines a stepwise approach (shown below) to increasing engagement over time. This summary will hopefully spur further quality content and engagement regarding drug information from the infectious diseases social media network.

Social Media: Flattening Hierarchies for Women and Black, Indigenous, People Of Color (BIPOC) to Enter the Room Where It Happens

Social media platforms are widely used to connect people across multiple settings, including country of origin, profession, race/ethnicity, sexual orientation, gender identity, seniority, and training. Groups that have been marginalized or historically excluded from decision-making encounters may lack formal mentors/sponsors because of a lack of representation of women and Black, Indigenous, People Of Color (BIPOC) in senior leadership positions. This can serve as a barrier to professional advancement at all stages of career development. Identifying and connecting with these potential mentors/sponsors outside of one's institutional space can be challenging. For this reason, leveraging social media to develop these professional relationships through flattened hierarchies can allow for professional networking beyond traditional mechanisms. Here we aim to describe how individuals can connect through social media to advance their careers and scientific and clinical expertise, advocate for communities, and provide high-quality communication to the public.

#SoMe the Money! Value, Strategy, and Implementation of Social Media Engagement for Infectious Diseases Trainees, Clinicians, and Divisions

Social media platforms have revolutionized how we consume information, along with how to effectively present communication, education, and advocacy efforts. There is profound value in leveraging social media within these aspects for the field of infectious diseases, for divisions and individual clinicians. Herein, we provide the rationale to incorporate social media as a key competency for infectious diseases training and specific guidance on aspects of education and strategic development of new accounts critical for success.

Vaccine Hesitancy towards COVID-19 Vaccination: Investigating the Role of Information Sources through a Mediation Analysis

Mass vaccination campaigns have been implemented worldwide to counteract the SARS-CoV-2/COVID-19 pandemic, however their effectiveness could be challenged by vaccine hesitancy. The tremendous rise in the use of social media have made them acquire a leading role as an information source, thus representing a crucial factor at play that could contribute to increase or mitigate vaccine hesitancy, as information sources play a pivotal role in shaping public opinion and perceptions. The aims of the study were to investigate if information sources could affect the attitude towards COVID-19 vaccination and if they could act as a mediator in the relationship between individual characteristics and vaccine hesitancy. A cross-sectional online survey was conducted by a professional panellist on a representative sample of 1011 citizens from the Emilia-Romagna region in Italy in January 2021. A mediation analysis using structural equation modelling was performed. Our results show how social media directly or indirectly increases vaccine hesitancy towards COVID-19 vaccination, while the opposite effect was observed for institutional websites. Given the global widespread use of social media, their use should be enhanced to disseminate scientifically sound information to a greater audience to counteract vaccine hesitancy, while at the same time continuing to promote and update institutional websites that have proven to be effective in reducing vaccine hesitancy.