The review situates Omicron within the broader evolutionary history of the pandemic. The Alpha variant, B.1.1.7, detected in the United Kingdom in late 2020, was estimated to be 30 to 50 percent more contagious than circulating strains. Beta, B.1.351, emerged in South Africa in October 2020 with mutations that accelerated its spread. Gamma, P.1, was reported by Japanese officials in January 2021 after ravaging Manaus in Brazil, a city that had already achieved high levels of natural immunity. Delta, B.1.617.2, first identified in India in December 2020, drove catastrophic waves across the subcontinent and beyond, and was estimated to be roughly 50 percent more contagious than its predecessors. Against this backdrop, Omicron’s arrival in November 2021 marked a step change: the variant carried 35 spike protein mutations and roughly 50 mutations overall, more than any previously characterized variant of concern, and its transmission rate was classified as very high.

That mutational burden is not random noise, the authors emphasize. Structural analyses of the Omicron spike protein, including cryo-electron microscopy studies of the spike bound to human ACE2, reveal that approximately 30 mutations cluster in the spike protein, with about half of them concentrated in the receptor-binding domain, the region that neutralizing antibodies target most directly. Mutations such as N501Y, shared with Alpha, Beta, and Gamma, enhance binding affinity to the ACE2 receptor. P681H, near the furin cleavage site, is associated with increased pathogenicity. D614G, K417N, and E484A further improve ACE2 binding while eroding the effectiveness of monoclonal antibodies. Beyond the spike, the review catalogues mutations in ORF1a, ORF1b, the envelope protein, the membrane protein, and the nucleocapsid, painting a picture of a virus that has been reshaped across its entire genome. The result, the authors note, is a variant that spreads faster than any before it while typically causing less severe illness, a combination that makes it harder to contain through symptoms alone.

The epidemiological numbers cited in the review illustrate how quickly that combination overwhelmed national defenses. According to the Centers for Disease Control and Prevention, Omicron’s share of infections in the United States grew by 2.5 percent in less than two weeks. In New York, the infection rate climbed by 13 percent. In Britain, cases doubled every two to three days. In South Africa, the infection rate rose from 10.3 percent to 24.3 percent in December 2021, faster than anywhere else. By early 2022, Omicron had taken global dominance, and by August 2024, genomic surveillance data showed a steady shift toward later lineages such as XBB and EG.5.1, with national prevalence varying according to immunity levels, sequencing coverage, and transmission dynamics. The virus has now been detected in 220 nations and territories across six continents, infecting over 687 million people and killing approximately 6.87 million.

Omicron’s descendants have continued to evolve, and the review devotes considerable attention to their divergent properties. The BA.1 subvariant began spreading on 10 January 2022 and gradually replaced Delta in Maharashtra, India. BA.2, sometimes called stealth Omicron because it can evade detection in certain RT-PCR assays, was identified in Sweden, India, and Norway in January 2022 and spread to more than 40 countries; it proved more contagious than BA.1, and unvaccinated, double-vaccinated, and booster-vaccinated individuals were all more vulnerable to BA.2 infection than to BA.1, suggesting that its advantage stems from more than immune evasion alone. BA.2.12.1, descended from BA.2, was poised to become the dominant strain in the United States by June 2022. BA.4 and BA.5, still under investigation when the review was compiled, prompted researchers to warn that South Africa, where only 30 percent of the population was vaccinated, could face a fifth wave sooner than expected. The review also describes three hybrid recombinants—XD, a Delta-Omicron BA.1 combination detected in France, Denmark, and Belgium; XE, a BA.1-BA.2 hybrid first identified in the United Kingdom around 19 January 2022 that could spread roughly ten times faster than BA.2; and XF, a Delta-BA.2 recombinant that spread to parts of the United Kingdom.

Vaccination remains the most effective preventive measure, the authors stress, but its effectiveness against Omicron wanes measurably over time. Serum-neutralizing antibodies begin to decline six months after immunization, indicating the need for boosters. Data compiled from public datasets show that as of 12 August 2024, India had fully vaccinated 951.99 million people, with 72.5 percent having completed initial doses and 17 percent having received boosters. In Africa, only 6.9 percent of people had received booster doses by the same date. Estonia had fully vaccinated just 2.11 million people, substantially below the global average of 58 percent, a gap the authors warn could accelerate Omicron transmission. Vaccine effectiveness data against acute illness tell a similar story: two weeks after a second Pfizer-BioNTech dose, effectiveness against BA.1 was 67.1 percent and against BA.2 was 63.6 percent, but after 25 weeks these figures had fallen to 24.3 percent and 17.4 percent respectively. A booster dose restored effectiveness to 72.2 percent against BA.2 and 71.3 percent against BA.1 within one week, though it declined to 48.4 percent and 45.5 percent after a minimum of 15 weeks. People who received all three doses of the mRNA vaccine had better protection against both Omicron and Delta than those with two doses or none.

It is against this biological and epidemiological backdrop that the review makes its central argument: that IoT technology offers a scalable, real-time surveillance layer that conventional healthcare cannot match. The authors describe a proposed architecture in which temperature data from sensors deployed in crowded locations are collected and transferred through a cloud gateway to a big data warehouse, where meaningful information about infected individuals is extracted and isolation actions triggered. Digital telehealth portals allow patients to consult doctors remotely, minimizing direct contact and reducing transmission. IoT-enabled ambulances allow remote medical experts to advise on patient care during transit, ensuring that hospitals can prepare for incoming patients before arrival. Artificial intelligence models trained on IoT data can predict potential virus spread and issue warnings to unaffected individuals about areas susceptible to future outbreaks. Health monitoring devices that track temperature and blood oxygen saturation, or SpO2, transmit data to the cloud for processing, with critical situations viewable through customized applications.

The review also examines the COVICT framework, an IoT-based architecture for COVID-19 detection and contact tracing that encompasses data gathering and uploading, a symptom analysis data centre, a cloud database, a healthcare centre, an isolation and quarantine centre, a contact tracing centre for positive cases, a national command and control centre, and industry partners. Its sensor layer collects data from biosensors embedded in wearable devices and onboard smartphone sensors, including cameras, microphones, and inertial sensors, which can detect symptoms such as fever, shortness of breath, sore throat, and headache. An edge device controls the movement of patient data between networks and the cloud database, optimizing, buffering, and processing patient data in real time before storage and analysis. If a positive case is confirmed, healthcare officials use the patient’s travel history, transmitted to the data centre, to follow the patient’s location and take measures to mitigate spread. The authors also catalogue mainstream sensors used in COVID-19 monitoring, comparing infrared temperature sensors with response times of seconds, pulse oximeters accurate to within 1 to 2 percent, PPG-based heart rate sensors, antigen and antibody biosensors with very high accuracy and specificity, respiratory rate sensors, wearable multi-sensor platforms, and environmental sensors that measure CO2 and air quality as proxies for indoor transmission risk.

Consumer-centric IoT devices, the authors argue, extend this surveillance into everyday life. A smartwatch-type thermometer worn on the wrist continuously monitors temperature and pairs with a mobile phone to display data through a customized application, allowing governments to track potential Omicron patients through abnormal temperature readings. Smart glasses equipped with infrared and optical cameras capture the body temperature of individuals in a crowd and use face recognition to facilitate tracking, with recorded data managed on a smartphone and sent to health officers for analysis. Intelligent drones equipped with medical supplies can record temperature data from crowds, provide first aid quickly in emergencies, and help health officers identify infected persons for rapid isolation. Autonomous swab test robots enable testing without human interaction, reducing the stress and infection risk faced by health workers. The authors also review the deployment of biosensors, artificial intelligence, and the Internet of Medical Things for COVID-19 and Zika virus detection, and assess wearable sensor integration in pandemic healthcare for IoT-based detection and protection approaches.

The review is candid about the limitations of these technologies. IoT healthcare solutions struggle to protect sensitive data from privacy and security threats, and the expense of setting up devices and infrastructure remains a significant barrier. Their influence is reduced in rural or low-income areas due to restricted access and inadequate connectivity. Inaccurate sensor data can result in misdiagnosis or panic, and platform interoperability issues impede smooth operation. Symptom-driven sensors such as temperature and SpO2 monitors cannot detect pre-symptomatic or asymptomatic individuals, a critical gap for a variant as transmissible as Omicron. Telehealth systems mitigate physical contact but require reliable Internet access and digital literacy. High latency in real-time data collection is identified as one of the biggest issues, with the authors recommending Mobile Edge Computing, a form of cloud computing deployed near the consumer at one hop, as the most practical solution. Privacy concerns arise because low-end IoT devices are highly susceptible to denial-of-service attacks and exploitation by hackers, prompting calls for privacy-preserving protocols for video conversations and contact tracing. The authors recommend encryption technologies, including symmetric encryption for real-time sensor data and end-to-end encryption from device to medical professional, alongside multi-factor authentication, role-based access control, and blockchain-based data storage to secure records. Despite these challenges, the authors conclude that IoT integration remains a critical tool for safeguarding communities against emerging variants, offering multifaceted solutions for immediate and long-term pandemic control, from quick identification and isolation of affected individuals to remote healthcare delivery, predictive analytics, and advanced monitoring systems tailored to the high transmissibility of Omicron and its descendants.

Subject of Research: Global impact and surveillance strategies of omicron SARSCoV-2: exploring IoT applications and prevention approaches

Article Title: Global impact and surveillance strategies of omicron SARSCoV-2: exploring IoT applications and prevention approaches

Article References: Dhanasekar, S., Sagayam, K. M., Ansarullah, S. I., & Alshmrany, S. (2026). Global impact and surveillance strategies of omicron SARSCoV-2: exploring IoT applications and prevention approaches. Frontiers in Communications and Networks, 7, Article 1762548. https://doi.org/10.3389/frcmn.2026.1762548

Image Credits: AI Generated

DOI: 10.3389/frcmn.2026.1762548

Keywords: Global, impact, surveillance, strategies, omicron, SARSCoV-2, exploring, applications, prevention, approaches, scientific research