health systems, health policy and systems research, health services, resilience, equity in health, non-communicable diseases
16
Scopus Publications
Scopus Publications
Representation, activism, health promotion, and communication: The role of art in advancing global health and social justice Mark Donald C. Reñosa, Kelly E. Perry, Siddharth Srivastava, Angeli Rawat, Zaida Orth, et al. Plos Global Public Health, 2025 This viewpoint advocates for the inclusion of art in global health discourse and practice. We explore four areas in which art can be leveraged to improve global health: (1) to amplify disenfranchised voices, (2) to advance social justice activism, (3) to strengthen communities and individuals, and (4) to improve global health communication. Drawing on community-driven art initiatives, we argue for an inclusive approach that respects diverse cultural perspectives and uplifts marginalized voices. Emphasizing interdisciplinary collaboration and ethical engagement, our framework invites global health discourse and practice to integrate art in order to foster empathy, challenge systemic inequities, and envision sustainable futures. By centering art, we seek to enrich the global health discipline with insights and transformative potential grounded in human experiences, cultural diversity, and shared humanity.
A Paradigm Shift in Health Surveillance: Preparing for the Future of Longevity Vivek Jason Jayaraj, Diane Woei-Quan Chong, Mohd Zulfadli Hafiz Bin Ismail, Nur Aisyah Abdul Rahim, Karthikeyanathan Ramoo International Journal of Public Health, 2025 As lifespans lengthen, societies face the challenge of ensuring people live these additional years in good health [1]. The World Health Organization's (WHO) Global Roadmap for Healthy Longevity envisions "years of good health approaching the biological life span, with physical, cognitive, and social functioning enabling well-being" [1,2]. But as people age, their health problems become more complex, so we need to transform public health surveillance.Traditional surveillance has depended on periodic surveys, hospital discharge data, and mortality statistics, which provide retrospective insights rather than data we can act on in real-time. In a digital era marked by personal computing, the internet, and mobile healthcare, surveillance must become proactive, continuous, and data-driven. We must proactively monitor and address the health concerns of our growing population of elderly citizens, harness technology to effectively address the complexities of ageing populations, and use big data analytics and artificial intelligence (AI) to enable predictive modelling, real-time insights, and personalised interventions. To future-proof our health systems we recommend leveraging technologies, big data analytics, and AI to create an adaptive surveillance ecosystem—one that evolves to integrate emerging technologies and novel data streams [1,3]. In this essay, we explore two interlocking paradigm shifts: the first is a shift in foundational infrastructure, to centralised lifetime health records, ubiquitous IoT devices, and AI-driven analytics; the second is a shift in how we use advanced human–machine interfaces and responsive AI solutions to harness these real-time data streams for immediate interventions. The first shift will transform surveillance systems within a decade to address the health challenges of an ageing population. This shift depends on three components: centralised health records, ubiquitous IoT sensing for real-time monitoring, and AI-driven analytics for targeted interventions. Centralised lifetime health records (LHR) will become the primary repository for health data from birth to death, integrating electronic health records, genomic profiles, and social determinants of health [1,4]. IoT sensing will collect and transmit health data in real-time to interconnected devices, such as smartwatches. Today, smartwatches can monitor heart rate, activity levels, sleep patterns, and even electrocardiograms; future iterations are likely to capture richer, more nuanced data about an individual's health. A network of these sensors will overlay the LHR, continuously capturing real-time health data at individual and population levels [1]. IoT-infused LHR, alongside other non-traditional data from our environments and social media, will stream information to AIs and machine learning tools that will analyse data in real-time, identify patterns, predict outcomes, and detect emerging issues that might escape human observation [1]. This triad will facilitate precise interventions at population, community, and individual levels so we can prevent chronic conditions and personalise health strategies [1,4,5] extending health and life.In alignment with the consequentialist paradigm of surveillance, the second shift will translate personalised surveillance data into immediate action via technologies like human-machine interfaces (HMIs) and AI [6]. An early example of an HMI is Neuralink, a chip that interfaces with the brain to assist individuals with neurological disorders. AIs of the future may be superintelligent agents that will constantly be available to us. In this scenario, advanced AIs will translate surveillance inputs from real-time IoT data and data developed in Phase 1 into real-time interventions implemented via HMIs, bypassing traditional intermediaries and improving the responsiveness of the public health system [7–9]. Imagine an older adult’s typical morning routine in this scenario. Upon waking, their AI companion reminds them to take their medication, having analysed their sleep patterns, vitals, and schedule for optimal timing and dosage. As they prepare for a bus ride, the AI detects subtle gait changes via sensors in their clothing and living space, advising them to slow down via a brain interface, and calculates an increased fall risk based on their current state. The AI guides them to a rest station to recuperate. Chemical and vitals sensors track their heart rate and blood sugar levels. As their vitals normalise and their gait improves, the system updates their status in real-time. Meanwhile, their AI/HMI assistant notifies emergency services to be on a yellow alert based on their location and health status. Anti-fall devices, like smart clothing, are primed for deployment if needed. While the first paradigm shift lays the groundwork, the second opens a new frontier in health surveillance and intervention, requiring health systems to be more modular and agile in adapting to evolving technologies and unforeseen challenges [1,9,10].As we venture into this new era of health surveillance, we must navigate complex ethical challenges. Safeguarding against a "Big Brother" scenario is paramount, so data management systems must be robust and decentralised to prevent misuse of sensitive information [1,5]. Participation in health surveillance should remain voluntary, based on informed consent. We must also ensure access to these technologies is equitable. We risk exacerbating health disparities if we fail to democratise access to devices and digital infrastructure [1,2]. The digital divide extends beyond affordability, encompassing issues of connectivity, user-friendly design, and digital literacy. We must answer questions about data ownership, consent, and the right to be forgotten in lifelong health tracking. Our path forward demands technological innovation, moral imagination, and a sound ethical grounding, so health surveillance advancements serve the greater good without compromising fundamental rights [1]. We must also acknowledge and address the limitations of AI, such as biases embedded in algorithms, opaque decision-making processes, and the challenge of ensuring model accuracy across diverse populations. Government agencies must lead healthcare providers, technology companies, and academic institutions in collaborating to develop standards, protocols, and ethical frameworks for data collection and analysis. Public health professionals will need skills in data science, AI, and digital health to use these advanced surveillance systems [1,5,7,10].The future of health surveillance lies in the convergence of big data, IoT, AI, and advanced human-machine interfaces. By embracing these technologies and shifting our approach from reactive to proactive monitoring, we can better assure healthy longevity in an ageing world. As we navigate this transformation, we must remain committed to ethical principles and ensure the benefits of advanced health surveillance are distributed equitably across all segments of society. Only then can we truly realise the vision of a future where people of all ages can thrive, enjoy ‘ageing in place,’ and reap the benefits of longer, healthier lives.
Estimating the impact of the COVID-19 pandemic on infectious disease notifications in Klang district, Malaysia, 2020-2022 V. J. Jayaraj, D. Chong, Faridah Jafri, Nur Adibah Binti Mat Saruan, Gurpreet Kaur Karpal Singh, Ravikanth Perumal, Shakirah Binti Jamaludin, Juvina Binti Mohd Janurudin, Siti Rohana Binti Saad Western Pacific Surveillance and Response Journal Wpsar, 2025 Objective The COVID-19 pandemic disrupted disease surveillance systems globally, leading to reduced notifications of other infectious diseases. This study aims to estimate the impact of the COVID-19 pandemic on the infectious disease surveillance system in Klang district, Selangor state, Malaysia. Methods Data on notifiable diseases from 2014 to 2022 were sourced from the Klang District Health Office. The 11 diseases with more than 100 notifications each were included in the study. For these 11 diseases, a negative binomial regression model was used to explore the effect of the pandemic on case notifications and registrations by year, and a quasi-Poisson regression model was used to explore the changes by week. Results The results showed a reduction in the number of notifications and registrations for all 11 diseases combined during the pandemic compared with previous years. Changes between expected and observed notifications by week were heterogeneous across the diseases. Discussion These findings suggest that restrictive public health and social measures in Klang district may have impacted the transmission of other infectious diseases during the COVID-19 pandemic. The differential impact of the pandemic on disease notifications and reporting highlights the large ancillary effects of restrictive public health and social measures and the importance of building resilience into infectious disease surveillance systems.
Study protocol for a mixed methods approach to optimize colorectal cancer screening in Malaysia: Integrating stakeholders insights and knowledge-to-action framework Diane Woei-Quan Chong, Vivek Jason Jayaraj, Fathullah Iqbal Ab Rahim, Sharifah Saffinas Syed Soffian, Muhammad Fikri Azmi, Mohd Yusaini Mohd Yusri, Ahmad Shanwani Mohamed Sidek, Norfarizan Azmi, Rosaida Md Said, Muhammad Firdaus Md Salleh, Norasiah Abu Bakar, Hamiza Shahar, Rima Marhayu Abdul Rashid, Shazimah Abdul Samad, Zanita Ahmad, Mohd Safiee Ismail, Adilah A. Bakar, Nor Mashitah Hj Jobli, Sondi Sararaks Plos One, 2024 Introduction Colorectal cancer is a growing global health concern and the number of reported cases has increased over the years. Early detection through screening is critical to improve outcomes for patients with colorectal cancer. In Malaysia, there is an urgent need to optimize the colorectal cancer screening program as uptake is limited by multiple challenges. This study aims to systematically identify and address gaps in screening service delivery to optimize the Malaysian colorectal cancer screening program. Methods This study uses a mixed methods design. It focuses primarily on qualitative data to understand processes and strategies and to identify specific areas that can be improved through stakeholder engagement in the screening program. Quantitative data play a dual role in supporting the selection of participants for the qualitative study based on program monitoring data and assessing inequalities in screening and program implementation in healthcare facilities in Malaysia. Meanwhile, literature review identifies existing strategies to improve colorectal cancer screening. Additionally, the knowledge-to-action framework is integrated to ensure that the research findings lead to practical improvements to the colorectal cancer screening program. Discussion Through this complex mix of qualitative and quantitative methods, this study will explore the complex interplay of population- and systems-level factors that influence screening rates. It involves identifying barriers to effective colorectal cancer screening in Malaysia, comparing current strategies with international best practices, and providing evidence-based recommendations to improve the local screening program.
Rapidly scalable and low-cost public health surveillance reporting system for COVID-19 V. J. Jayaraj, Chiu-Wan Ng, Victor Chee Wai Hoe, D. Chong, S. Rampal BMJ Health and Care Informatics, 2024 OBJECTIVE Data-driven innovations are essential in strengthening disease control. We developed a low-cost, open-source system for robust epidemiological intelligence in response to the COVID-19 crisis, prioritising scalability, reproducibility and dynamic reporting. METHODS A five-tiered workflow of data acquisition; processing; databasing, sharing, version control; visualisation; and monitoring was used. COVID-19 data were initially collated from press releases and then transitioned to official sources. RESULTS Key COVID-19 indicators were tabulated and visualised, deployed using open-source hosting in October 2022. The system demonstrated high performance, handling extensive data volumes, with a 92.5% user conversion rate, evidencing its value and adaptability. CONCLUSION This cost-effective, scalable solution aids health specialists and authorities in tracking disease burden, particularly in low-resource settings. Such innovations are critical in health crises like COVID-19 and adaptable to diverse health scenarios.
Evidence Synthesis for the Development of National Nursing-Sensitive Indicators in Malaysia: A Literature Review and Stakeholder Engagement Approach Devi Shantini Rata Mohan, Nurul Iman Jamalul-lail, Diane Woei-Quan Chong, Kalvina Chelladorai, Kartiekasari Syahidda Mohammad Zubairi, Inin Roslyza Rusli, Nur Azmiah Zainuddin, Roslina Supadi, Noor Hasidah Ab Rahman, Mariyah Mohamad, Devi K. Saravana Muthu, Gowry Narayanan, Cheah Jenny Sage Open Nursing, 2024 Introduction Nursing-sensitive indicators measure and evaluate nursing care quality and its contribution to patient care. The identification of indicators that demonstrate nursing care contribution and the quality of care delivered locally is of paramount importance, and national indicators that demonstrate this are essential. This paper aims to provide an evidence base of nursing-sensitive indicators that can facilitate the conceptualization of local nursing national indicators. Method A multifaceted and iterative approach incorporating literature review, and stakeholder engagements was utilized in evidence synthesis. A review of indicators present internationally complemented by the inclusion of context-specific local NSIs through stakeholder engagements was performed. Secondary data analysis of documents from an environmental scan was also included to highlight areas of concern for nursing-sensitive indicator prioritization from the viewpoint of nurses. Results A total of 64 articles were reviewed and indicators were coded according to the Nursing Care Performance Framework subsystems, dimensions, and variables. All papers reviewed had documented outcome indicators. From our secondary data analysis, nurses identified areas of concern such as nursing staff supply, staff maintenance, nursing processes and risk outcomes, and safety to be prioritized for developing quality indicators. Conclusion This paper provides a list of NSIs coded systematically with definitions to aid stakeholders in prioritizing indicators for national indicator development. The inclusion of areas of concern provides insight into NSIs that nurse practitioners find relevant to the local context. To our knowledge, this is the first paper that includes evidence available in the literature and incorporates stakeholders’ perspectives in synthesizing evidence needed to guide the development of national nursing indicators. This iterative approach is crucial because it enhances the likelihood of knowledge translation.
Estimating excess mortalities due to the COVID-19 pandemic in Malaysia between January 2020 and September 2021 Vivek Jason Jayaraj, Diane Woei-Quan Chong, Kim-Sui Wan, Noran Naqiah Hairi, Nirmala Bhoo-Pathy, Sanjay Rampal, Chiu-Wan Ng Scientific Reports, 2023 Excess mortalities are a more accurate indicator of true COVID-19 disease burden. This study aims to investigate levels of excess all-cause mortality and their geographic, age and sex distributions between January 2020-September 2021. National mortality data between January 2016 and September 2021 from the Department of Statistics Malaysia was utilised. Baseline mortality was estimated using the Farrington algorithm and data between 1 January 2016 and 31 December 2019. The occurrence of excess all-cause mortality by geographic-, age- and sex-stratum was examined from 1 January 2020 to 30 September 2021. A sub-analysis was also conducted for road-traffic accidents, ethnicity and nationality. Malaysia had a 5.5–23.7% reduction in all-cause mortality across 2020. A reversal is observed in 2021, with an excess of 13.0–24.0%. Excess mortality density is highest between July and September 2021. All states and sexes reported excess trends consistent with the national trends. There were reductions in all all-cause mortalities in individuals under the age of 15 (0.4–8.1%) and road traffic accident-related mortalities (36.6–80.5%). These reductions were higher during the first Movement Control Order in 2020. Overall, there appears to be a reduction in all-cause mortality for Malaysia in 2020. This trend is reversed in 2021, with excess mortalities being observed. Surveillance of excess mortalities can allow expedient detection of aberrant events allowing timely health system and public health responses.
Learning from the process evaluation of a complex, pre-conception randomised controlled trial in Malaysia: The Jom Mama project Shakirah Md. Sharif, Mark Hanson, Diane W. Chong, Ainul Nadziha M. Hanafiah, Mohamad Z. Zulkepli, Syatirah F. Zulbahari, Jutta Skau, Julius Cheah C. Ho, Priya Matzen, Regien Biesma, Shane A. Norris, Jens Aagaard-Hansen Journal of Global Health Reports, 2022 Background Seen from a life-course perspective, pre-conception interventions are essential to reduce transmission to the next generation of obesity as a risk factor for later non-communicable diseases. The Malaysian Jom Mama project investigated the effectiveness of a combined behaviour change communication and e-health intervention in young married couples prior to first pregnancy. This paper reports on the extensive process evaluation (PE) that accompanied the Jom Mama trial. Methods In accordance with the realistic evaluation approach, a programme theory was developed for the Jom Mama project, based on key functions selected for six PE sub-studies, namely: recruitment; attrition; behaviour change communication (BCC); e-health (the Jom app); peer-support for community health promoters (CHPs); and contextual factors. The results of the first four sub-studies are reported here. Three cycles of data collection were conducted based on triangulation and a mixed-methods approach. Results The findings permitted distinguishing between theory and implementation challenges in interpreting the outcome of the Jom Mama trial.1 Recruitment and attrition proved to be challenges, and although the PE allowed Jom Mama investigators to improve procedures in order to achieve a sufficient sample size, it also has implications for engaging this age group in future pre-conception interventions. PE sub-studies showed that there were challenges in applying the BCC, and that the uptake of the Jom app varied. In one way this can be seen as an indication of limited fidelity, but it also leads to questions about how best to change the communication culture within the Malaysian health care system. Conclusions The Jom Mama PE highlighted the challenges of recruiting newly-wed couples for a pre-conception intervention. Despite thorough intervention development preparations, the PE revealed the difficulty of lifestyle behaviour change through Malaysian community health wokers who were trained on new communication strategies combined with e-health solutions, and that six intervention sessions of eight months do not constitute a sufficient dose to affect change. <div style=“page-break-after: always;”></div>
The Epidemiology of COVID-19 in Malaysia Vivek Jason Jayaraj, Sanjay Rampal, Chiu-Wan Ng, Diane Woei Quan Chong Lancet Regional Health Western Pacific, 2021 BACKGROUND: COVID-19 has rapidly spread across the globe. Critical to the control of COVID-19 is the characterisation of its epidemiology. Despite this, there has been a paucity of evidence from many parts of the world, including Malaysia. We aim to describe the epidemiology of COVID-19 in Malaysia to inform prevention and control policies better. METHODS: Malaysian COVID-19 data was extracted from 16 March 2020 up to 31 May 2021. We estimated the following epidemiological indicators: 7-day incidence rates, 7-day mortality rates, case fatality rates, test positive ratios, testing rates and the time-varying reproduction number (Rt). FINDINGS: Between 16 March 2020 and 31 May 2021, Malaysia has reported 571,901 cases and 2,796 deaths. Malaysia's average 7-day incidence rate was 26•6 reported infections per 100,000 population (95% CI: 17•8, 38•1). The average test positive ratio and testing rate were 4•3% (95% CI: 1•6, 10•2) and 0•8 tests per 1,000 population (95% CI: <0•1, 3•7), respectively. The case fatality rates (CFR) was 0•6% (95% CI: <0•1, 3•7). Among the 2,796 cases who died, 87•3% were ≥ 50 years. INTERPRETATION: The public health response was successful in the suppression of COVID-19 transmission or the first half of 2020. However, a state election and outbreaks in institutionalised populations have been the catalyst for more significant community propagation. This rising community transmission has continued in 2021, leading to increased incidence and strained healthcare systems. Calibrating NPI based on epidemiological indicators remain critical for us to live with the virus. (243 words). FUNDING: This study is part of the COVID-19 Epidemiological Analysis and Strategies (CEASe) Project with funding from the Ministry of Science, Technology and Innovation (UM.0000245/HGA.GV).
Propagation of a hospital-associated cluster of COVID-19 in Malaysia Diane Woei-Quan Chong, Vivek Jason Jayaraj, Chiu-Wan Ng, I-Ching Sam, Mas Ayu Said, Rafdzah Ahmad Zaki, Noran Naqiah Hairi, Nik Daliana Nik Farid, Victor Chee-Wai Hoe, Marzuki Isahak, Sasheela Ponnampalavanar, Sharifah Faridah Syed Omar, Shahrul Bahyah Kamaruzzaman, Hang-Cheng Ong, Kejal Hasmukharay, Nazirah Hasnan, Adeeba Kamarulzaman, Yoke Fun Chan, Yoong Min Chong, Sanjay Rampal BMC Infectious Diseases, 2021
Implementation of a COVID-19 surveillance programme for healthcare workers in a teaching hospital in an upper-middle-income country Kim Sui Wan, Peter Seah Keng Tok, Kishwen Kanna Yoga Ratnam, Nuraini Aziz, Marzuki Isahak, Rafdzah Ahmad Zaki, Nik Daliana Nik Farid, Noran Naqiah Hairi, Sanjay Rampal, Chiu-Wan Ng, Mohd Fauzy Samsudin, Vinura Venugopal, Mohammad Asyraf, Narisa Hatun Damanhuri, Sanpagavalli Doraimuthu, Catherine Thamarai Arumugam, Thaneswaran Marthammuthu, Fathhullah Azmie Nawawi, Faiz Baharudin, Diane Woei Quan Chong, Vivek Jason Jayaraj, Venna Magarita, Sasheela Ponnampalavanar, Nazirah Hasnan, Adeeba Kamarulzaman, Mas Ayu Said Plos One, 2021
