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Association Between Sociodemographic Factors and Vaccine Acceptance for Influenza and SARS-CoV-2 in South Korea: Nationwide Cross-Sectional Study

Association Between Sociodemographic Factors and Vaccine Acceptance for Influenza and SARS-CoV-2 in South Korea: Nationwide Cross-Sectional Study

Among a variety of vaccines available in South Korea, influenza and SARS-Co V-2 vaccines were crucial to public health strategies during the COVID-19 pandemic. Both had similar transmission mechanisms and targeted similar demographics. Furthermore, the long-established influenza vaccination program in Korea provides robust data that enhance the reliability of comparative analyses.

Seohyun Hong, Yejun Son, Myeongcheol Lee, Jun Hyuk Lee, Jaeyu Park, Hayeon Lee, Elena Dragioti, Guillaume Fond, Laurent Boyer, Guillermo Felipe López Sánchez, Lee Smith, Mark A Tully, Masoud Rahmati, Yong Sung Choi, Young Joo Lee, Seung Geun Yeo, Selin Woo, Dong Keon Yon

JMIR Public Health Surveill 2024;10:e56989

Changes in the Epidemiological Features of Influenza After the COVID-19 Pandemic in China, the United States, and Australia: Updated Surveillance Data for Influenza Activity

Changes in the Epidemiological Features of Influenza After the COVID-19 Pandemic in China, the United States, and Australia: Updated Surveillance Data for Influenza Activity

Seasonal influenza is an epidemic disease caused by the influenza virus with a high burden and severity. The World Health Organization (WHO) and the Centers for Disease Control and Prevention of most countries jointly coordinate influenza surveillance and report weekly data on human seasonal influenza viruses, including the activities of A (H1 N1), A (H3 N2), B/Victoria, and B/Yamagata.

Mingyue Jiang, Mengmeng Jia, Qing Wang, Yanxia Sun, Yunshao Xu, Peixi Dai, Weizhong Yang, Luzhao Feng

Interact J Med Res 2024;13:e47370

Evaluation of Machine Learning to Detect Influenza Using Wearable Sensor Data and Patient-Reported Symptoms: Cohort Study

Evaluation of Machine Learning to Detect Influenza Using Wearable Sensor Data and Patient-Reported Symptoms: Cohort Study

Participants also completed daily surveys of whether they experienced influenza symptoms in the past 24 hours, self-reported ILI symptom severity, health care–seeking behaviors, and quality of life. Biweekly and monthly surveys were used to capture influenza-related complication events and vaccination history. Participants reporting certain ILI symptoms were instructed to perform a self-administered influenza diagnostic test.

Kamran Farooq, Melody Lim, Lawrence Dennison-Hall, Finn Janson, Aspen Hazel Olszewska, Muhammad Mamduh Ahmad Zabidi, Anna Haratym-Rojek, Karol Narowski, Barry Clinch, Marco Prunotto, Devika Chawla, Victoria Hunter, Vincent Ukachukwu

J Med Internet Res 2024;26:e47879

Digital Gamification Tool (Let’s Control Flu) to Increase Vaccination Coverage Rates: Proposal for Algorithm Development

Digital Gamification Tool (Let’s Control Flu) to Increase Vaccination Coverage Rates: Proposal for Algorithm Development

Influenza is an infectious respiratory disease caused by an airborne virus. There are 4 identified types of influenza viruses, with types A and B being responsible for most of the seasonal influenza epidemics that occur annually [1,2]. The influenza virus can cause mild to severe disease, with risk groups (older people, pregnant women, young children, and individuals with chronic health conditions and autoimmune diseases) being more susceptible to severe forms of the disease [1].

Henrique Lopes, Ricardo Baptista-Leite, Catarina Hermenegildo, Rifat Atun

JMIR Res Protoc 2024;13:e55613

Impact of the COVID-19 Pandemic on Influenza Hospital Admissions and Deaths in Wales: Descriptive National Time Series Analysis

Impact of the COVID-19 Pandemic on Influenza Hospital Admissions and Deaths in Wales: Descriptive National Time Series Analysis

A death due to influenza was defined as a death record in the ADDE data set with an ICD-10 code of influenza (J09-J11) as the underlying cause of death and a positive result for influenza A or B virus using a PCR test, collected in the last 28 days before death. Multimedia Appendix 1 contains a list of ICD-10 codes used to define influenza and influenza-related illness.

Mohammad Alsallakh, Davies Adeloye, Eleftheria Vasileiou, Shanya Sivakumaran, Ashley Akbari, Ronan A Lyons, Chris Robertson, Igor Rudan, Gwyneth A Davies, Aziz Sheikh

JMIR Public Health Surveill 2024;10:e43173

Risk Index of Regional Infection Expansion of COVID-19: Moving Direction Entropy Study Using Mobility Data and Its Application to Tokyo

Risk Index of Regional Infection Expansion of COVID-19: Moving Direction Entropy Study Using Mobility Data and Its Application to Tokyo

A moderately infective species, such as influenza, whose infectivity based on the basic reproduction number is lower than that of COVID-19 [38-40] or COVID-19 in less populated areas, is positioned as an intercommunity bridge of intermediate strength between Figure 1 A/C and Figure 1 B/D. Based on the literature, we assumed that influenza was less infectious than COVID-19, and influenza, including H7 N9, H5 N1, H1 N1, etc, was compared with COVID-19 before February 2021.

Yukio Ohsawa, Yi Sun, Kaira Sekiguchi, Sae Kondo, Tomohide Maekawa, Morihito Takita, Tetsuya Tanimoto, Masahiro Kami

JMIR Public Health Surveill 2024;10:e57742

Increased Risk of Influenza Infection During Cold Spells in China: National Time Series Study

Increased Risk of Influenza Infection During Cold Spells in China: National Time Series Study

Seasonal influenza causes substantial morbidity and mortality worldwide each year, with an estimated 291,000 to 645,000 seasonal influenza-related deaths annually [1]. The disease and economic burdens of seasonal influenza are substantial in China. It is estimated that an average of 88,100 influenza-related excess respiratory deaths occur each year in mainland China [2]. The influence of ambient low temperature on influenza has been well documented.

Haitao Wang, Mengjie Geng, Tamara Schikowski, Ashtyn Tracey Areal, Kejia Hu, Wen Li, Micheline de Sousa Zanotti Stagliorio Coelho, Paulo Hilário Nascimento Saldiva, Wei Sun, Chengchao Zhou, Liang Lu, Qi Zhao, Wei Ma

JMIR Public Health Surveill 2024;10:e55822

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation

A Bayesian System to Detect and Track Outbreaks of Influenza-Like Illnesses Including Novel Diseases: Algorithm Development and Validation

For example, suppose there are 50 patients and 20 have a 0.1 probability of influenza, while 30 have a 0.2 probability. Then the expected number of patients with influenza is 20×0.1+30×0.2=8. Given the expected number with each disease, we can compute the expected proportion of each disease. In the example above, the expected proportion of patients with influenza would be 8/50=0.16. The ILI Tracker algorithm combines the above steps to compute the expected proportion of each disease each day.

John M Aronis, Ye Ye, Jessi Espino, Harry Hochheiser, Marian G Michaels, Gregory F Cooper

JMIR Public Health Surveill 2024;10:e57349

Ischemic Stroke After Bivalent COVID-19 Vaccination: Self-Controlled Case Series Study

Ischemic Stroke After Bivalent COVID-19 Vaccination: Self-Controlled Case Series Study

The RI was not significantly above 1 across all subgroup analyses by age, coadministration of influenza vaccine, and history of SARS-Co V-2 infection. In analyses extending the risk interval to 1-42 days following bivalent vaccination, the overall RI was 0.97 (95% CI 0.81-1.15; Table 2). However, in subgroup analyses using the 1-42–day risk interval, we observed an increased risk of ischemic stroke only among individuals younger than 65 years of age who also received an influenza vaccine on the same day.

Stanley Xu, Lina S Sy, Vennis Hong, Kimberly J Holmquist, Lei Qian, Paddy Farrington, Katia J Bruxvoort, Nicola P Klein, Bruce Fireman, Bing Han, Bruno J Lewin

JMIR Public Health Surveill 2024;10:e53807

A Novel Web-Based Application for Influenza and COVID-19 Outbreak Detection and Response in Residential Aged Care Facilities

A Novel Web-Based Application for Influenza and COVID-19 Outbreak Detection and Response in Residential Aged Care Facilities

In 2017, the Sydney Local Health District (SLHD) Public Health Unit (PHU), a district-level public health authority, embarked on a digital health innovation project to design, develop, and implement a web-based application—the Influenza Outbreak Communication, Advice and Reporting (Flu CARE) application—to assist staff in residential aged care facilities (RACFs) in the timely detection and response to influenza outbreaks.

Kai Hsun Hsiao, Emma Quinn, Travers Johnstone, Maria Gomez, Andrew Ingleton, Arun Parasuraman, Zeina Najjar, Leena Gupta

JMIR Public Health Surveill 2024;10:e37625