Building citizen science intelligence for outbreak preparedness and response: a mixed-method study in nine countries to assess knowledge, readiness and feasibility.

INTRODUCTION: Citizen science (CS) is an emerging approach in public health to harness the collective intelligence of individuals to augment traditional scientific efforts. However, citizens' viewpoint, especially the hard-to-reach population, is lacking in current outbreak-related literature. We aim to understand the awareness, readiness and feasibility of outbreak-related CS, including digitally enabled CS, in low-income and middle-income countries. METHODS: This mixed-method study was conducted in nine countries between October 2022 and June 2023. Recruitment through civil society targeted the general population, marginalised/indigenous groups, youth and community health workers. Participants (aged ≥18 years) completed a quantitative survey, and a subset participated in focus group discussions (FGDs). RESULTS: 2912 participants completed the survey and 4 FGDs were conducted in each country. Incorporating participants' perspectives, CS is defined as the practice of active public participation, collaboration and communication in all aspects of scientific research to increase public knowledge, create awareness, build trust and facilitate information flow between citizens, governments and scientists. In Bangladesh, Indonesia, the Philippines, Cameroon and Kenya, majority were unaware of outbreak-related CS. In India and Uganda, majority were aware but unengaged, while in Nepal and Zimbabwe, majority participated in CS before. Engagement approaches should consider different social and cultural contexts, while addressing incentivisation, attitudes and practicality factors. Overall, 76.0% expressed interest in digital CS but needed training to build skills and confidence. Digital CS was perceived as convenient, safer for outbreak-related activities and producing better quality and quantity of data. However, there were concerns over non-inclusion of certain groups, data security and unclear communication. CONCLUSION: CS interventions need to be relatable and address context-specific factors influencing CS participation. Digital CS has the potential to facilitate collaboration, but capacity and access issues must be considered to ensure inclusive and sustainable engagement.

Are physicians ready for precision antibiotic prescribing? A qualitative analysis of the acceptance of artificial intelligence-enabled clinical decision support systems in India and Singapore.

OBJECTIVES: Artificial intelligence (AI)-driven clinical decision support systems (CDSSs) can augment antibiotic decision-making capabilities, but physicians' hesitancy in adopting them may undermine their utility. We conducted a cross-country comparison of physician perceptions on the barriers and facilitators in accepting an AI-enabled CDSS for antibiotic prescribing. METHODS: We conducted in-depth interviews with physicians from the National Centre for Infectious Diseases (NCID), Singapore, and Christian Medical College Vellore (CMCV), India, between April and December 2022. Our semi-structured in-depth interview guides were anchored on Venkatesh's UTAUT model. We used clinical vignettes to illustrate the application of AI in clinical decision support for antibiotic prescribing and explore medico-legal concerns. RESULTS: Most NCID physicians felt that an AI-enabled CDSS could facilitate antibiotic prescribing, while most CMCV physicians were sceptical about the tool's utility. The hesitancy in adopting an AI-enabled CDSS stems from concerns about the lack of validated and successful examples, fear of losing autonomy and clinical skills, difficulty of use, and impediment in work efficiency. Physicians from both sites felt that a user-friendly interface, integration with workflow, transparency of output, a guiding medico-legal framework, and training and technical support would improve the uptake of an AI-enabled CDSS. CONCLUSION: In conclusion, the acceptance of AI-enabled CDSSs depends on the physician's confidence with the tool's recommendations, perceived ease of use, familiarity with AI, the organisation's digital culture and support, and the presence of medico-legal governance of AI. Progressive implementation and continuous feedback are essential to allay scepticism around the utility of AI-enabled CDSSs.

A call for citizen science in pandemic preparedness and response: beyond data collection.

The COVID-19 pandemic has underlined the need to partner with the community in pandemic preparedness and response in order to enable trust-building among stakeholders, which is key in pandemic management. Citizen science, defined here as a practice of public participation and collaboration in all aspects of scientific research to increase knowledge and build trust with governments and researchers, is a crucial approach to promoting community engagement. By harnessing the potential of digitally enabled citizen science, one could translate data into accessible, comprehensible and actionable outputs at the population level. The application of citizen science in health has grown over the years, but most of these approaches remain at the level of participatory data collection. This narrative review examines citizen science approaches in participatory data generation, modelling and visualisation, and calls for truly participatory and co-creation approaches across all domains of pandemic preparedness and response. Further research is needed to identify approaches that optimally generate short-term and long-term value for communities participating in population health. Feasible, sustainable and contextualised citizen science approaches that meaningfully engage affected communities for the long-term will need to be inclusive of all populations and their cultures, comprehensive of all domains, digitally enabled and viewed as a key component to allow trust-building among the stakeholders. The impact of COVID-19 on people's lives has created an opportune time to advance people's agency in science, particularly in pandemic preparedness and response.

One-Bed-One-Team-Does an Integrated General Hospital Inpatient Model Improve Care Outcomes and Productivity: An Observational Study.

Introduction: With the increasing complexity of healthcare problems worldwide, the demand for better-coordinated care delivery is on the rise. However, current hospital-based practices remain largely disease-centric and specialist-driven, resulting in fragmented care. This study aimed to evaluate the effectiveness and feasibility of an integrated general hospital (IGH) inpatient care model. Methods: Retrospective analysis of medical records between June 2018 and August 2019 compared patients admitted under the IGH model and patients receiving usual care in public hospitals. The IGH model managed patients from one location with a multidisciplinary team, performing needs-based care transition utilizing acuity tagging to match the intensity of care to illness acuity. Results: 5,000 episodes of IGH care entered analysis. In the absence of care transition in intervention and control, IGH average length of stay (ALOS) was 0.7 days shorter than control. In the group with care transition in intervention but not in control, IGH acute ALOS was 2 days shorter, whereas subacute ALOS was 4.8 days longer. In the presence of care transition in intervention and control, IGH acute ALOS was 6.4 and 10.2 days shorter and subacute ALOS was 15.8 and 26.9 days shorter compared with patients under usual care at acute hospitals with and without co-located community hospitals, respectively. The 30- and 60-days readmission rates of IGH patients were marginally higher than usual care, though not clinically significant. Discussions: The IGH care model maybe associated with shorter ALOS of inpatients and optimize resource allocation and service utilization. Patients with dynamic acuity transition benefited from a seamless care transition process.

Cross-sectional study of prevalence and risk factors, and a cost-effectiveness evaluation of screening and preventive treatment strategies for latent tuberculosis among migrants in Singapore.

OBJECTIVES: WHO recommends that low burden countries consider systematic screening and treatment of latent tuberculosis infection (LTBI) in migrants from high incidence countries. We aimed to determine LTBI prevalence and risk factors and evaluate cost-effectiveness of screening and treating LTBI in migrants to Singapore from a government payer perspective. DESIGN: Cross-sectional study and cost-effectiveness analysis. SETTING: Migrants in Singapore. PARTICIPANTS: 3618 migrants who were between 20 and 50 years old, have not worked in Singapore previously and stayed in Singapore for less than a year were recruited. PRIMARY AND SECONDARY OUTCOME MEASURES: Costs, quality-adjusted life-years (QALYs), threshold length of stay, incremental cost-effectiveness ratios (ICERs), cost per active TB case averted. RESULTS: Of 3584 migrants surveyed, 20.4% had positive interferon-gamma release assay (IGRA) results, with the highest positivity in Filipinos (33.2%). Higher LTBI prevalence was significantly associated with age, marital status and past TB exposure. The cost-effectiveness model projected an ICER of S$57 116 per QALY and S$12 422 per active TB case averted for screening and treating LTBI with 3 months once weekly isoniazid and rifapentine combination regimen treatment compared with no screening over a 50-year time horizon. ICER was most sensitive to the cohort's length of stay in Singapore, yearly disease progression rates from LTBI to active TB, followed by the cost of IGRA testing. CONCLUSIONS: For LTBI screening and treatment of migrants to be cost-effective, migrants from high burden countries would have to stay in Singapore for ~50 years. Risk-stratified approaches based on projected length of stay and country of origin and/or age group can be considered.

Identifying COVID-19 cases in outpatient settings.

Case identification is an ongoing issue for the COVID-19 epidemic, in particular for outpatient care where physicians must decide which patients to prioritise for further testing. This paper reports tools to classify patients based on symptom profiles based on 236 severe acute respiratory syndrome coronavirus 2 positive cases and 564 controls, accounting for the time course of illness using generalised multivariate logistic regression. Significant symptoms included abdominal pain, cough, diarrhoea, fever, headache, muscle ache, runny nose, sore throat, temperature between 37.5 and 37.9 °C and temperature above 38 °C, but their importance varied by day of illness at assessment. With a high percentile threshold for specificity at 0.95, the baseline model had reasonable sensitivity at 0.67. To further evaluate accuracy of model predictions, leave-one-out cross-validation confirmed high classification accuracy with an area under the receiver operating characteristic curve of 0.92. For the baseline model, sensitivity decreased to 0.56. External validation datasets reported similar result. Our study provides a tool to discern COVID-19 patients from controls using symptoms and day from illness onset with good predictive performance. It could be considered as a framework to complement laboratory testing in order to differentiate COVID-19 from other patients presenting with acute symptoms in outpatient care.

Government trust, perceptions of COVID-19 and behaviour change: cohort surveys, Singapore.

OBJECTIVE: To evaluate how public perceptions and trust in government communications affected the adoption of protective behaviour in Singapore during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We launched our community-based cohort to assess public perceptions of infectious disease outbreaks in mid-2019. After the first case of COVID-19 was reported in Singapore on 23 January, we launched a series of seven COVID-19 surveys to both existing and regularly enrolled new participants every 2 weeks. As well as sociodemographic properties of the participants, we recorded changing responses to judge awareness of the situation, trust in various information sources and perceived risk. We used multivariable logistic regression models to evaluate associations with perceptions of risk and self-reported adopted frequencies of protective behaviour. FINDINGS: Our cohort of 633 participants provided 2857 unique responses during the seven COVID-19 surveys. Most agreed or strongly agreed that information from official government sources (99.1%; 528/533) and Singapore-based news agencies (97.9%; 522/533) was trustworthy. Trust in government communication was significantly associated with higher perceived threat (odds ratio, OR: 2.2; 95% confidence interval, CI: 1.6-3.0), but inversely associated with perceived risk of infection (OR: 0.6; 95% CI: 0.4-0.8) or risk of death if infected (OR: 0.6; 95% CI: 0.4-0.9). Trust in government communication was also associated with a greater likelihood of adopting protective behaviour. CONCLUSION: Our findings show that trust is a vital commodity when managing an evolving outbreak. Our repeated surveys provided real-time feedback, allowing an improved understanding of the interplay between perceptions, trust and behaviour.

Perceptions of an HIV self-testing intervention and its potential role in addressing the barriers to HIV testing among at-risk heterosexual men: a qualitative analysis.

OBJECTIVES: Voluntary HIV testing rates are still low in several Asian countries including Singapore. HIV self-testing (HIVST) has the potential to increase testing, leading to earlier diagnosis and better prognosis. However, the views of at-risk individuals, especially heterosexual men (HSM), who are not coming forward for testing are still poorly understood. In this study, we examined the barriers and facilitators to and delivery preferences for HIVST in order to implement an effective intervention in Singapore. METHODS: From May 2017 to June 2018, 48 in-depth interviews were conducted with HSM aged 21-66 years and at risk of HIV infection. Participants were purposively sampled based on ethnicity, age and testing behaviour. Recruitment was done mainly at brothels and entertainment establishments in Singapore. Participants gave their views on HIV testing, factors affecting HIVST use and their preferred HIVST service delivery model. RESULTS: Most participants preferred HIVST over conventional testing for its convenience, privacy, anonymity and autonomy, but older men still preferred conventional testing. Low self-perceived risk, low awareness and self-efficacy for HIVST, and non-comprehensive test for other STIs were reported as barriers to HIVST. There were mixed opinions on kit preference. A blood-based kit was favoured for higher accuracy, while the oral-fluid-based kit was favoured for ease of use. Participants wanted a human touch for post-test counselling and linkage to care only if they self-tested positive. Traditional media, internet and social media, and venue-based outreach were potential advertising platforms mentioned. CONCLUSIONS: A locally acceptable and feasible HIVST intervention must address the barriers and facilitators of using HIVST in order to improve HIV testing rates among this at-risk population who might otherwise delay or fail to present for testing.

Effectiveness of a Mobile-Based Influenza-Like Illness Surveillance System (FluMob) Among Health Care Workers: Longitudinal Study.

BACKGROUND: Existing studies have suggested that internet-based participatory surveillance systems are a valid sentinel for influenza-like illness (ILI) surveillance. However, there is limited scientific knowledge on the effectiveness of mobile-based ILI surveillance systems. Previous studies also adopted a passive surveillance approach and have not fully investigated the effectiveness of the systems and their determinants. OBJECTIVE: The aim of this study was to assess the efficiency of a mobile-based surveillance system of ILI, termed FluMob, among health care workers using a targeted surveillance approach. Specifically, this study evaluated the effectiveness of the system for ILI surveillance pertaining to its participation engagement and surveillance power. In addition, we aimed to identify the factors that can moderate the effectiveness of the system. METHODS: The FluMob system was launched in two large hospitals in Singapore from April 2016 to March 2018. A total of 690 clinical and nonclinical hospital staff participated in the study for 18 months and were prompted via app notifications to submit a survey listing 18 acute respiratory symptoms (eg, fever, cough, sore throat) on a weekly basis. There was a period of study disruption due to maintenance of the system and the end of the participation incentive between May and July of 2017. RESULTS: On average, the individual submission rate was 41.4% (SD 24.3%), with a rate of 51.8% (SD 26.4%) before the study disruption and of 21.5% (SD 30.6%) after the disruption. Multivariable regression analysis showed that the adjusted individual submission rates were higher for participants who were older (<30 years, 31.4% vs 31-40 years, 40.2% [P<.001]; 41-50 years, 46.0% [P<.001]; >50 years, 39.9% [P=.01]), ethnic Chinese (Chinese, 44.4% vs non-Chinese, 34.7%; P<.001), and vaccinated against flu in the past year (vaccinated, 44.6% vs nonvaccinated, 34.4%; P<.001). In addition, the weekly ILI incidence was 1.07% on average. The Pearson correlation coefficient between ILI incidence estimated by FluMob and that reported by Singapore Ministry of Health was 0.04 (P=.75) with all data and was 0.38 (P=.006) including only data collected before the study disruption. Health care workers with higher risks of ILI and influenza such as women, non-Chinese, allied health staff, those who had children in their households, not vaccinated against influenza, and reported allergy demonstrated higher surveillance correlations. CONCLUSIONS: Mobile-based ILI surveillance systems among health care workers can be effective. However, proper operation of the mobile system without major disruptions is vital for the engagement of participants and the persistence of surveillance power. Moreover, the effectiveness of the mobile surveillance system can be moderated by participants' characteristics, which highlights the importance of targeted disease surveillance that can reduce the cost of recruitment and engagement.

Increasing Influenza and Pneumococcal Vaccination Uptake in Seniors Using Point-of-Care Informational Interventions in Primary Care in Singapore: A Pragmatic, Cluster-Randomized Crossover Trial.

Objectives. To evaluate the effectiveness of point-of-care informational interventions in general practitioner clinics to improve influenza and pneumococcal vaccination uptake among elderly patients.Methods. We conducted a pragmatic, cluster-randomized crossover trial in 22 private general practitioner clinics in Singapore, from November 2017 to July 2018. We included all patients aged 65 years or older. Clinics were assigned to a 3-month intervention (flyers and posters encouraging vaccination) plus 1-month washout period, and a 4-month control period (usual care). Primary outcomes were differences in vaccination uptake rates between periods. Secondary outcomes were identification of other factors associated with vaccination uptake.Results. A total of 4378 and 4459 patients were included in the intervention and control periods, respectively. Both influenza (5.9% vs 4.8%; P = .047) and pneumococcal (5.7% vs 3.7%; P = .001) vaccination uptake rates were higher during the intervention period compared with the control period. On multilevel logistic regression analysis, follow-up for hypertension, diabetes mellitus, hyperlipidemia, or any combination of the 3 was associated with uptake of both vaccines.Conclusions. Point-of-care informational interventions likely contributed to increased influenza and pneumococcal vaccination uptake. Patients on follow-up for hypertension, diabetes mellitus, hyperlipidemia, or any combination of the 3 were more likely to receive influenza and pneumococcal vaccination and should be actively engaged by physicians.Trial Registration. ClinicalTrials.gov Identifier: NCT03445117.

Adequacy of public health communications on H7N9 and MERS in Singapore: insights from a community based cross-sectional study.

BACKGROUND: Singapore remains vulnerable to worldwide epidemics due to high air traffic with other countries This study aims to measure the public's awareness of the Middle East Respiratory Syndrome (MERS) and Avian Influenza A (H7N9), identify population groups who are uninformed or misinformed about the diseases, understand their choice of outbreak information source, and assess the effectiveness of communication channels in Singapore. METHODS: A cross-sectional study, comprising of face-to-face interviews, was conducted between June and December 2013 to assess the public's awareness and knowledge of MERS and H7N9, including their choice of information source. Respondents were randomly selected and recruited from 3 existing cohort studies. An opportunistic sampling approach was also used to recruit new participants or members in the same household through referrals from existing participants. RESULTS: Out of 2969 participants, 53.2% and 79.4% were not aware of H7N9 and MERS respectively. Participants who were older and better educated were most likely to hear about the diseases. The mean total knowledge score was 9.2 (S.D ± 2.3) out of 20, and 5.9 (S.D ± 1.2) out of 10 for H7N9 and MERS respectively. Participants who were Chinese, more educated and older had better knowledge of the diseases. Television and radio were the primary sources of outbreak information regardless of socio-demographic factors. CONCLUSION: Heightening education of infectious outbreaks through appropriate media to the young and less educated could increase awareness.