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Acceptance of COVID-19 vaccination at different hypothetical efficacy and safety levels in ten countries in Asia, Africa, and South America Rosiello, Dott F.; Anwar, Samsul; Yufika, Amanda; Adam, Rashed Y.; Ismaeil, Mohajer IH.; Ismail, Asma Y.; Dahman, Nesrine BH.; Hafsi, Montacer; Ferjani, Manel; Sami, Farah S.; Monib, Fatma A; R, Subramaniam; Anandu, Sunil; Haque, Md Ariful; Ferreto, Lirane ED.; Aburto, José TO.; Rojas, Jorge ET.; Enitan, Seyi S.; Yomi, Akele R.; Ezigbo, Eyiuche D.; Babadi, Elham; Kakemam, Edris; Malik, Najma I.; Ullah, Irfan; Sallam, Malik
Narra J Vol. 1 No. 3 (2021): December 2021
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v1i3.55

Abstract

Vaccine hesitancy, defined as the reluctance or rejection in receiving a vaccine despite its availability, represents a major challenge to global health efforts aiming to control the ongoing COVID-19 pandemic. Understanding the possible factors correlated with COVID-19 vaccine hesitancy using a refined well-informed approach can be helpful to address the phenomenon. The current study aimed to evaluate COVID-19 vaccine acceptance rates using four hypothetical scenarios of varying levels of vaccine efficacy and safety profiles in ten Asian, African and South American countries. These scenarios included: 95% efficacy and 20% side effects (Vaccine A), 75% efficacy and 5% side effects (Vaccine B); 75% efficacy and 20% side effects (Vaccine C) and 50% efficacy and 5% side effects (Vaccine D). This study used a self-administered online survey that was distributed during February–May 2021. The total number of study respondents was 1337 with countries of residence as follows: India (21.1%), Pakistan (12.9%), Sudan (11.2%), Nigeria (9.3%), Iran (8.2%), Bangladesh and Brazil (7.9%), Chile (7.7%), Tunisia (7.6%), and Egypt (6.2%). The overall acceptance rates for COVID-19 vaccination were variable based on varying degrees of safety and efficacy as follows: 55.6% for Vaccine C, 58.3% for Vaccine D, 74.0% for Vaccine A and 80.1% for Vaccine B. The highest levels of COVID-19 vaccine acceptance were observed in Brazil followed by Chile across the four different safety and efficacy scenarios. The lowest COVID-19 vaccine acceptance rates were reported in Egypt and Tunisia for the low safety scenarios (20% side effects), and the low efficacy scenario (50% efficacy). The study revealed the potential effect of vaccine safety and efficacy on the intention to get COVID-19 vaccination. At the same efficacy level, higher possibility of side effects caused a large drop in COVID-19 vaccine acceptance rate. This indicates the importance of accurate communication regarding vaccine safety and efficacy on attitude towards the vaccine and intentions to get vaccinated. Regional differences in COVID-19 vaccine acceptance were observed with the Middle East/North African countries showing the lowest rates and the South American countries displaying the highest vaccine acceptance rates.
Willingness-to-pay for COVID-19 vaccine in ten low-middle-income countries in Asia, Africa and South America: A cross-sectional study Sallam, Malik; Anwar, Samsul; Yufika, Amanda; Fahriani, Marhami; Husnah, Milda; Kusuma, Hendrix I.; Raad, Rawan; Khiri, Namareg ME.; Abdalla, Rashed YA.; Adam, Rashed Y.; Ismaeil, Mohajer IH.; Ismail, Asma Y.; Kacem, Wajdi; Teyeb, Zeineb; Aloui , Khaoula; Hafsi , Montacer; Dahman, Nesrine Ben Hadj; Ferjani, Manel; Deeb, Dalia; Emad , Dina; Sami, Farah S.; Abbas, Kirellos Said; Monib, Fatma A.; R , Subramaniam; Panchawagh, Suhrud; Sharun, Khan; Anandu, Sunil; Gachabayov, Mahir; Haque , Md A.; Emran, Talha B.; Wendt, Guilherme W.; Ferreto, Lirane ED.; Castillo-Briones, María F.; Inostroza-Morales, Rocío B.; Lazcano-Díaz, Sebastián A.; Ordóñez-Aburto, José T.; Troncoso-Rojas, Jorge E.; Balogun, Emmanuel O.; Yomi, Akele R.; Durosinmi, Abiodun; Adejumo, Esther N.; Ezigbo, Eyiuche D.; Arab-Zozani, Morteza; Babadi, Elham; Kakemam, Edris; Ullah, Irfan; Malik, Najma I.; Dababseh, Deema; Rosiello, Francesco; Enitan , Seyi S.
Narra J Vol. 2 No. 1 (2022): April 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i1.74

Abstract

Vaccine hesitancy is considered as one of the greatest challenges to control the ongoing coronavirus disease 2019 (COVID-19) pandemic. A related challenge is the unwillingness of the general public to pay for vaccination. The objective of this study was to determine willingness-to-pay (WTP) for COVID-19 vaccine among individuals from ten low-middle-income countries (LMICs) in Asia, Africa, and South America. Data were collected using an online questionnaire distributed during February - May 2021 in ten LMICs (Bangladesh, Brazil, Chile, Egypt, India, Iran, Nigeria, Pakistan, Sudan, and Tunisia). The major response variable of in this study was WTP for a COVID-19 vaccine. The assessment of COVID-19 vaccine hesitancy was based on items adopted from the World Health Organization (WHO) Strategic Advisory Group of Experts (SAGE) vaccine hesitancy scale constructs. In this study, 1337 respondents included in the final analysis where the highest number of respondents was from India, while the lowest number was from Egypt. A total of 88.9% (1188/1337) respondents were willing to pay for the COVID-19 vaccination, and 11.1% (149/1337) were not. The average WTP for COVID-19 vaccination was 87.9 US dollars ($), (range: $5-$200). The multivariate model analysis showed that the country, monthly household income, having a history of respiratory disease, the agreement that routine vaccines recommended by health workers are beneficial and having received the flu vaccination within the previous 12 months were strongly associated with the WTP. Based on the country of origin, the highest mean WTP for COVID-19 vaccine was reported in Chile, while the lowest mean WTP for the vaccine was seen among the respondents from Sudan. The availability of free COVID-19 vaccination services appears as a top priority in the LMICs for successful control of the ongoing pandemic. This is particularly important for individuals of a lower socio-economic status. The effects of complacency regarding COVID-19 extends beyond vaccine hesitancy to involve less willingness to pay for COVID-19 vaccine and a lower value of WTP for the vaccine.
Acute severe hepatitis of unknown etiology in children: A mini-review Frediansyah, Andri; Sallam, Malik; Yufika, Amanda; Sharun, Khan; Iqhrammullah, Muhammad; Chandran, Deepak; Mamada, Sukamto S.; Sallam, Dina E.; Khader, Yousef; Lemu, Yohannes K.; Yusuf, Fauzi; Kretchy, James-Paul; Abdeen, Ziad; Torres-Roman, J. Smith; Acharya, Yogesh; Bondarenko, Anastasia; Ikram, Aamer; Jamil, Kurnia F.; Kotfis, Katarzyna; Koyanagi, Ai; Smith, Lee; Megawati, Dewi; Rademaker, Marius; Emran, Talha B.; Memish, Ziad A.; Vento, Sandro; Nainu, Firzan; Harapan, Harapan
Narra J Vol. 2 No. 2 (2022): August 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i2.83

Abstract

The emergence of acute, severe non hepA–E hepatitis of unknown etiology (ASHUE) has attracted global concern owing to the very young age of the patients and its unknown etiology. Although this condition has been linked to several possible causes, including viral infection, drugs and/or toxin exposure, the exact cause remains unknown; this makes treatment recommendation very difficult. In this review, we summarize recent updates on the clinical manifestations, complemented with laboratory results, case numbers with the global distribution and other epidemiological characteristics, and the possible etiologies. We also provide the proposed actions that could be undertaken to control and prevent further spread of this hepatitis. Since many etiological and pathological aspects of the acute non hepA–E hepatitis remain unclear, further research is needed to minimize the severe impact of this disease.
Monkeypox: Immune response, vaccination and preventive efforts Ophinni, Youdiil; Frediansyah, Andri; Sirinam, Salin; Megawati, Dewi; Stoian, Ana M.; Enitan, Seyi S.; Akele, Richard Y.; Sah, Ranjit; Pongpirul, Krit; Abdeen, Ziad; Aghayeva, Sevda; Ikram, Aamer; Kebede, Yohannes; Wollina, Uwe; Subbaram, Kannan; Koyanagi, Ai; Al Serouri, Abdulwahed; Nguendo-Yongsi, H. Blaise; Edwards, Jeffrey; Sallam, Dina E.; Khader, Yousef; Viveiros-Rosa, Sandro G.; Memish, Ziad A.; Amir-Behghadami, Mehrdad; Vento, Sandro; Rademaker, Marius; Sallam, Malik
Narra J Vol. 2 No. 3 (2022): December 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i3.90

Abstract

Infectious threats to humans are continuously emerging. The 2022 worldwide monkeypox outbreak is the latest of these threats with the virus rapidly spreading to 106 countries by the end of September 2022. The burden of the ongoing monkeypox outbreak is manifested by 68,000 cumulative confirmed cases and 26 deaths. Although monkeypox is usually a self-limited disease, patients can suffer from extremely painful skin lesions and complications can occur with reported mortalities. The antigenic similarity between the smallpox virus (variola virus) and monkeypox virus can be utilized to prevent monkeypox using smallpox vaccines; treatment is also based on antivirals initially designed to treat smallpox. However, further studies are needed to fully decipher the immune response to monkeypox virus and the immune evasion mechanisms. In this review we provide an up-to-date discussion of the current state of knowledge regarding monkeypox virus with a special focus on innate immune response, immune evasion mechanisms and vaccination against the virus.
The outbreak of Ebola virus disease in 2022: A spotlight on a re-emerging global health menace Al-Tammemi, Ala'a B.; Sallam, Malik; Rebhi, Asem; Soliman, Laarni; Al Sarayrih, Lina; Tarhini, Zeinab; Abutaima, Rana; Aljaberi, Musheer A.; Barakat, Muna
Narra J Vol. 2 No. 3 (2022): December 2022
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v2i3.97

Abstract

Ebola virus disease (EVD) is a rare but highly contagious and lethal disease that occurs predominantly in African countries, with a case-fatality rate of 30–90%. The causative viral pathogens of EVD are within the genus Ebolavirus in the family Filoviridae. The primary route of human-to-human transmission is through direct contact with blood, bodily fluids and secretions from infected individuals. Direct contact with virally contaminated objects and sexual transmission have also been reported. Management of EVD is aggressive supportive care with possibly new therapeutic options. On 20 September 2022, an EVD outbreak was declared in Uganda, caused by Sudan ebolavirus. As of 7 November 2022, a total of 136 confirmed cases, 53 confirmed deaths have been reported, including 18 cases with seven deaths among healthcare workers. In the Democratic Republic of Congo (DRC), an EVD outbreak was also declared on 22 August 2022 (which ended on 27 September 2022); with only one case, a middle-aged woman. At the time when most countries in the world have been occupied with the coronavirus disease 2019 (COVID-19) pandemic and the recent human monkeypox outbreak, these two outbreaks of EVD have the potential to significantly add to the burden on global health. Authorities need to augment their multi-faceted response, including stringent contact tracing and border control, to avoid the catastrophe of the 2014–2016 EVD epidemic.
ChatGPT applications in medical, dental, pharmacy, and public health education: A descriptive study highlighting the advantages and limitations Sallam, Malik; Salim, Nesreen; Barakat, Muna; Al-Tammemi, Alaa
Narra J Vol. 3 No. 1 (2023): April 2023
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v3i1.103

Abstract

Since its public release in November 2022, ChatGPT has gained a widespread attention and  received mixed responses in the academia. Promising applications of ChatGPT in university education has been suggested; however, several concerns were raised. The aim of this descriptive study was to investigate the pros and cons of ChatGPT use in medical, dental, pharmacy, and public health education. Based on expert panel discussion and review of the existing literature, specific and concise ChatGPT prompts were constructed and the responses were generated on 25 February 2023. Out data suggested that in medical education, ChatGPT benefits included the possibility of improving personalized learning, clinical reasoning and understanding of complex medical concepts. The benefits listed in the context of dental education included improved skills through step-by-step instructions and interactive content, with instant feedback on student techniques. In pharmacy education, the advantages included possible explanations of complex subjects and the deployment of interactive tools aiding to develop skills for patient counselling. In public health education, the listed benefits included providing explanations and case scenarios, besides improved skills in data analysis and literature review. The limitations listed based on ChatGPT-generated content were common across all of the investigated healthcare disciplines and included data privacy issues, risk of generating biased and inaccurate content, and the risk of deterioration of critical thinking and communication skills among healthcare students. The ChatGPT-generated content in the context of healthcare education was deemed partially helpful by the expert panel. However, several important points regarding the pros and cons of ChatGPT use in medical, dental, pharmacy and public health education were missed by ChatGPT-generated content including: the risk of plagiarism, copyright issues, the risk of academic dishonesty, and the lack of personal and emotional interactions necessary for developing proper communication skills in healthcare education. In conclusion, despite the promising prospects of ChatGPT in healthcare education, several drawbacks should be addressed with implementation of guidelines for proper use to ensure exploiting the benefits of this innovative technology.
TikTok content on measles-rubella vaccine in Jordan: A cross-sectional study highlighting the spread of vaccine misinformation Abdaljaleel, Maram; Barakat, Muna; Mahafzah, Azmi; Hallit, Rabih; Hallit, Souheil; Sallam, Malik
Narra J Vol. 4 No. 2 (2024): August 2024
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v4i2.877

Abstract

Social media platforms, including TikTok, have become influential sources of health information. However, they also present as potential sources for the spread of vaccine misinformation. The aim of this study was to assess the quality of measles-rubella (MR) vaccine-related contents on TikTok in Jordan and to analyze factors associated with vaccine misinformation. A systematic search for MR vaccine-related TikTok contents in Jordan was conducted using pre-defined keywords and a specified time range. Content metrics (likes, comments, shares, and saves) were collected while the content quality of health information was evaluated using a modified version of the DISCERN, a validated instrument by two expert raters. The average modified DISCERN score ranged from 1, denoting poor content, to 5, indicating excellent content. A total of 50 videos from 34 unique content creators formed the final study sample. The majority of MR vaccine-related content was created by lay individuals (61.8%), followed by TV/news websites/journalists (23.5%), and healthcare professionals (HCPs) (14.7%). The Cohen κ per modified DISCERN item was in the range of 0.579–0.808, p<0.001), indicating good to excellent agreement. The overall average modified DISCERN score was 2±1.2, while it was only 1.3±0.52 for lay individuals’ content, which indicated poor content quality. For the normalized per number of followers for each source, content by lay individuals had a significantly higher number of likes, saves, and shares with p=0.009, 0.012, and 0.004, respectively. Vaccine misinformation was detected in 58.8% of the videos as follows: lay individuals (85.7%), TV/news websites/journalists (25.0%), and HCPs content had none (p<0.001). Normalized per the number of followers for each source, videos flagged as having MR vaccine misinformation reached a higher number of likes, saves, and shares (p=0.012, 0.016, and 0.003, respectively). In conclusion, substantial dissemination of TikTok MR vaccine-related misinformation in Jordan was detected. Rigorous fact-checking is warranted by the platform to address misinformation on TikTok, which is vital to improve trust in MR vaccination and ultimately protect public health.
Bibliometric top ten healthcare-related ChatGPT publications in the first ChatGPT anniversary Sallam, Malik
Narra J Vol. 4 No. 2 (2024): August 2024
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v4i2.917

Abstract

Since its public release on November 30, 2022, ChatGPT has shown promising potential in diverse healthcare applications despite ethical challenges, privacy issues, and possible biases. The aim of this study was to identify and assess the most influential publications in the field of ChatGPT utility in healthcare using bibliometric analysis. The study employed an advanced search on three databases, Scopus, Web of Science, and Google Scholar, to identify ChatGPT-related records in healthcare education, research, and practice between November 27 and 30, 2023. The ranking was based on the retrieved citation count in each database. The additional alternative metrics that were evaluated included (1) Semantic Scholar highly influential citations, (2) PlumX captures, (3) PlumX mentions, (4) PlumX social media and (5) Altmetric Attention Scores (AASs). A total of 22 unique records published in 17 different scientific journals from 14 different publishers were identified in the three databases. Only two publications were in the top 10 list across the three databases. Variable publication types were identified, with the most common being editorial/commentary publications (n=8/22, 36.4%). Nine of the 22 records had corresponding authors affiliated with institutions in the United States (40.9%). The range of citation count varied per database, with the highest range identified in Google Scholar (1019–121), followed by Scopus (242–88), and Web of Science (171–23). Google Scholar citations were correlated significantly with the following metrics: Semantic Scholar highly influential citations (Spearman’s correlation coefficient ρ=0.840, p<0.001), PlumX captures (ρ=0.831, p<0.001), PlumX mentions (ρ=0.609, p=0.004), and AASs (ρ=0.542, p=0.009). In conclusion, despite several acknowledged limitations, this study showed the evolving landscape of ChatGPT utility in healthcare. There is an urgent need for collaborative initiatives by all stakeholders involved to establish guidelines for ethical, transparent, and responsible use of ChatGPT in healthcare. The study revealed the correlation between citations and alternative metrics, highlighting its usefulness as a supplement to gauge the impact of publications, even in a rapidly growing research field.
Chinese generative AI models (DeepSeek and Qwen) rival ChatGPT-4 in ophthalmology queries with excellent performance in Arabic and English Sallam, Malik; Alasfoor, Israa M.; W. Khalid, Shahad; Al-Mulla, Rand I.; Al-Farajat, Amwaj; M. Mijwil, Maad; Zahrawi, Reem; Sallam, Mohammed; Egger, Jan; Al-Adwan, Ahmad S.
Narra J Vol. 5 No. 1 (2025): April 2025
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v5i1.2371

Abstract

The rapid evolution of generative artificial intelligence (genAI) has ushered in a new era of digital medical consultations, with patients turning to AI-driven tools for guidance. The emergence of Chinese-developed genAI models such as DeepSeek-R1 and Qwen-2.5 presented a challenge to the dominance of OpenAI’s ChatGPT. The aim of this study was to benchmark the performance of Chinese genAI models against ChatGPT-4o and to assess disparities in performance across English and Arabic. Following the METRICS checklist for genAI evaluation, Qwen-2.5, DeepSeek-R1, and ChatGPT-4o were assessed for completeness, accuracy, and relevance using the CLEAR tool in common patient ophthalmology queries. In English, Qwen-2.5 demonstrated the highest overall performance (CLEAR score: 4.43±0.28), outperforming both DeepSeek-R1 (4.31±0.43) and ChatGPT-4o (4.14±0.41), with p=0.002. A similar hierarchy emerged in Arabic, with Qwen-2.5 again leading (4.40±0.29), followed by DeepSeek-R1 (4.20±0.49) and ChatGPT-4o (4.14±0.41), with p=0.007. Each tested genAI model exhibited near-identical performance across the two languages, with ChatGPT-4o demonstrating the most balanced linguistic capabilities (p=0.957), while Qwen-2.5 and DeepSeek-R1 showed a marginal superiority for English. An in-depth examination of genAI performance across key CLEAR components revealed that Qwen-2.5 consistently excelled in content completeness, factual accuracy, and relevance in both English and Arabic, setting a new benchmark for genAI in medical inquiries. Despite minor linguistic disparities, all three models exhibited robust multilingual capabilities, challenging the long-held assumption that genAI is inherently biased toward English. These findings highlight the evolving nature of AI-driven medical assistance, with Chinese genAI models being able to rival or even surpass ChatGPT-4o in ophthalmology-related queries.
Co-Authors Abbas, Kirellos Said Abdaljaleel, Maram Abdalla, Rashed YA. Abdeen, Ziad Aburto, José TO. Abutaima, Rana Acharya, Yogesh Adam, Rashed Y. Adejumo, Esther N. Aghayeva, Sevda Akele, Richard Y. Al Sarayrih, Lina Al Serouri, Abdulwahed Al-Adwan, Ahmad S. Al-Farajat, Amwaj Al-Mulla, Rand I. Al-Tammemi, Ala'a B. Al-Tammemi, Alaa Alasfoor, Israa M. Aljaberi, Musheer A. Aloui , Khaoula Amir-Behghadami, Mehrdad Anak Agung Dewi Megawati, Anak Agung Dewi Anandu, Sunil Andri Frediansyah, Andri Arab-Zozani, Morteza Babadi, Elham Balogun, Emmanuel O. Barakat, Muna Bondarenko, Anastasia Castillo-Briones, María F. Chandran, Deepak Dababseh, Deema Dahman, Nesrine Ben Hadj Dahman, Nesrine BH. Deeb, Dalia Durosinmi, Abiodun Edwards, Jeffrey Egger, Jan Emad , Dina Emran, Talha B. Enitan , Seyi S. Enitan, Seyi S. Ezigbo, Eyiuche D. Fahriani, Marhami Fauzi Yusuf, Fauzi Ferjani, Manel Ferreto, Lirane ED. Firzan Nainu Gachabayov, Mahir Hafsi , Montacer Hafsi, Montacer Hallit, Rabih Hallit, Souheil Haque , Md A. Haque, Md Ariful Harapan Harapan Husnah, Milda Ikram, Aamer Inostroza-Morales, Rocío B. Iqhrammullah, Muhammad Ismaeil, Mohajer IH. Ismail, Asma Y. Kacem, Wajdi Kakemam, Edris Kebede, Yohannes Khader, Yousef Khiri, Namareg ME. Kotfis, Katarzyna Koyanagi, Ai Kretchy, James-Paul Kurnia F. Jamil Kusuma, Hendrix I. Lazcano-Díaz, Sebastián A. Lemu, Yohannes K. M. Mijwil, Maad Mahafzah, Azmi Malik, Najma I. Mamada, Sukamto S. Memish, Ziad A. Monib, Fatma A Monib, Fatma A. Nguendo-Yongsi, H. Blaise Ophinni, Youdiil Ordóñez-Aburto, José T. Panchawagh, Suhrud Pongpirul, Krit R , Subramaniam R, Subramaniam Raad, Rawan Rademaker, Marius Rebhi, Asem Rojas, Jorge ET. Rosiello, Dott F. Rosiello, Francesco Sah, Ranjit Salim, Nesreen Sallam, Dina E. Sallam, Mohammed Sami, Farah S. Samsul Anwar Sharun, Khan Sirinam, Salin Smith, Lee Soliman, Laarni Stoian, Ana M. Subbaram, Kannan Tarhini, Zeinab Teyeb, Zeineb Torres-Roman, J. Smith Troncoso-Rojas, Jorge E. Ullah, Irfan Vento, Sandro Viveiros-Rosa, Sandro G. W. Khalid, Shahad Wendt, Guilherme W. Wollina, Uwe Yomi, Akele R. Yufika, Amanda Zahrawi, Reem