Background: The heterologous prime‐boost vaccination technique is not novel as it has a history of deployment in previous outbreaks.Aim: Hence, this narrative review aims to provide critical insight for reviving the heterologous prime‐boost immunization strategy for SARS‐CoV‐2 vaccination relative to a brief positive outlook on the mix‐dose approach deployed in previous and existing outbreaks (ie, Ebola virus disease (EVD), malaria, tuberculosis, hepatitis B, HIV and influenza virus).Methodology and Materials: A Boolean search was carried out to find the literature in MEDLINE‐PubMed, Clinicaltrials, and Cochrane Central Register of Controlled Trials databases up till December 22, 2021, using the specific keywords that include “SARS‐CoV2”, “COVID‐19”, “Ebola,” “Malaria,” “Tuberculosis,” “Human Immunodeficiency Virus,” “Hepatitis B,” “Influenza,” “Mix and match,” “Heterologous prime‐boost,” with interposition of “OR” and “AND.” Full text of all the related articles in English language with supplementary appendix was retrieved. In addition, the full text of relevant cross‐references was also retrieved.Results: Therefore, as generally evident by the primary outcomes, that is, safety, reactogenicity, and immunogenicity reported and updated by preclinical and clinical studies for addressing previous and existing outbreaks so far, including COVID‐19, it is understood that heterologous prime‐boost immunization has been proven successful for eliciting a more efficacious immune response as of yet in comparison to the traditional homologous prime‐boost immunization regimen.Discussion: Accordingly, with increasing cases of COVID‐19, many countries such as Germany, Pakistan, Canada, Thailand, and the United Kingdom have started administering the heterologous vaccination as the technique aids to rationalize the usage of the available vaccines to aid in the global race to vaccinate majority to curb the spread of COVID‐19 efficiently. However, the article emphasizes the need for more large controlled trials considering demographic details of vaccine recipients, which would play an essential role in clearing the mistrust about safety concerns to pace up the acceptance of the technique across the globe.Conclusion: Consequently, by combatting the back‐to‐back waves of COVID‐19 and other challenging variants of concerns, including Omicron, the discussed approach can also help in addressing the expected evolution of priority outbreaks as coined by WHO, that is, “Disease X” in 2018 with competency, which according to WHO can turn into the “next pandemic” or the “next public health emergency,” thus would eventually lead to eradicating the risk of “population crisis.”

Objective: “Zero-dose children” remain a crucial burden to global health, particularly in low- and middle-income countries (LMICs) where vulnerable children have limited access to immunizations. This review explores the transformative potential of artificial intelligence (AI) in addressing this challenge and examines how AI can enhance routine childhood immunization. Methodology: This narrative review synthesizes literature on AI, digital health innovations, vaccine delivery, and public health informatics. Literature was sourced from PubMed, Scopus, and Google Scholar, as well as institutional and authoritative reports such as the World Health Organization, the United Nations Children's Fund (UNICEF), and Gavi, the Vaccine Alliance. Results: AI applications have demonstrated utility in identifying zero-dose populations, optimizing vaccine delivery, and supporting data-driven decision-making. Tools such as digital health passports, predictive analytics, and real-time monitoring platforms (e.g. UNICEF's real-time vaccination monitoring and analysis) enhance immunization tracking and reduce inequities. AI-driven chatbots, mobile applications, and social listening tools address vaccine hesitancy by providing tailored communication and combating misinformation. Furthermore, geographic information systems (GISs) and AI-based behavioral analysis improve outreach to underserved populations. However, challenges remain, including data quality, scalability, and ethical considerations. Conclusion: AI solutions allow efficient identification of potential pockets of non-vaccinated populations, enhance decision-making processes based on data, and reduce vaccine skepticism due to AI-based interventions. Examples of successful implementation of AI include digital health passports, continuous monitoring mechanisms, and GISs for vaccine administration and coverage. This review also discusses the challenges and ethical considerations associated with AI implementation in LMICs, as well as the ethical implications. Using the insights derived from the review, this paper calls for the targeted utilization of AI toward the realization of a healthier future for children in need to achieve the target of reducing the number of zero-dose children by 50% by the year 2030, not only in areas afflicted by immunization disparities but across the globe.

Despite the vaccine against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) being reported to be safe and effective, the unwillingness to vaccinate and doubts are still common. The aim of this international study was to assess the major reasons for the unwillingness to vaccinate in a group of students from Poland (n = 1202), Bangladesh (n = 1586), India (n = 484), Mexico (n = 234), Egypt (n = 566), Philippines (n = 2076), Pakistan (n = 506), Vietnam (n = 98) and China (n = 503). We conducted an online cross-sectional study that aimed to assess (1) the percentage of vaccinated and unvaccinated students and (2) the reasons associated with willingness/unwillingness to the vaccine. The study included 7255 respondents from 9 countries with a mean age of 21.85 ± 3.66 years. Only 22.11% (n = 1604) of students were vaccinated. However, the majority (69.25%, n = 5025) expressed a willingness to be vaccinated. More willing to vaccinate were students in informal relationships who worked mentally, used psychological/psychiatric services before the pandemic, and studied medicine. There are cultural differences regarding the reasons associated with the unwillingness to vaccinate, but some ‘universal’ might be distinguished that apply to the whole group.

Background: Double burden of malnutrition (DBM) is a complex nutritional phenomenon, where an individual or a household simultaneously face two contradictory forms of nutritional adversities. Studies on assessing the prevalence, trends, and determinants of DBM at household in Pakistan are scarce, so this study measured the prevalence, trends, and determinants of DBM at household level using nationally representative datasets. Methods: Data of last two waves of Demographic and Health Surveys (DHS) of Pakistan conducted in 2012–2013 and 2017–2018 were used to assess the DBM prevalence, trends, and determinants at the household level. Data of mother–child dyads aged between 15 and 49 years and 0 and 59 months was included, while data with incomplete anthropometry or anthropometric outliers was excluded. Results: Across two survey periods, there has been a significant decrease in pediatrics stunting from 45% to 37.3%, while a rapid proliferation of maternal obesity from 45% to 52.3% was reported. Similarly, the prevalence of DBM at household level was 17.3% in 2012‐2013, which increased to 18.9% in 2017–2018. Among different provinces of Pakistan, Baluchistan, Khyber Pakhtunkhwa (KPK) and Federally Administered Tribal Areas (FATA) have significantly higher prevalence of DBM at household than Islamabad Capital Territory (ICT). Factors such as child age, birth order, and socioeconomic status were significantly associated with DBM in Pakistani households. Conclusion: DBM in Pakistan is a complex and chronic challenge, which affects almost one‐fifth of households. There is need to urgently address the issues of DBM and to improvise nutrition specific and nutrition sensitive interventions to curtail the issues pertaining to DBM at household.