Outbreak detector: a web application to boost disease surveillance systems and timely detection of infectious disease epidemics.

OBJECTIVE: Digital technologies have improved the performance of surveillance systems through early detection of outbreaks and epidemic control. The aim of this study is to introduce an outbreak detection web application called OBDETECTOR (Outbreak Detector), which as a professional web application has the ability to process weekly or daily reported data from disease surveillance systems and facilitates the early detection of disease outbreaks. RESULTS: OBDETECTOR generates a histogram that exhibits the trend of infection within a time range selected by the user. The output comprises red triangles and plus signs, where the former denotes outbreak days determined by the algorithm applied to the data, and the latter represents days identified as outbreaks by the researcher. The graph also displays threshold values and its symbols enable researchers to compute evaluation criteria for outbreak detection algorithms, including sensitivity and specificity. OBDETECTOR allows users to modify algorithm parameters based on their research objectives immediately after loading data. The implementation of automatic web applications results in immediate reporting, precise analysis, and prompt alert notification. Moreover, Public Health authorities and other stakeholders of surveillance can benefit from the widespread accessibility and user-friendliness of these tools, enhancing their knowledge and skills for better engagement in surveillance programs.

Comparison of Different Reverse Transcriptase-Polymerase Chain Reaction-Based Methods for Wastewater Surveillance of SARS-CoV-2: Exploratory Study.

BACKGROUND: Many countries have applied the wastewater surveillance of the COVID-19 pandemic to their national public health monitoring measures. The most used methods for detecting SARS-CoV-2 in wastewater are quantitative reverse transcriptase-polymerase chain reaction (RT-qPCR) and reverse transcriptase-droplet digital polymerase chain reaction (RT-ddPCR). Previous comparison studies have produced conflicting results, thus more research on the subject is required. OBJECTIVE: This study aims to compare RT-qPCR and RT-ddPCR for detecting SARS-CoV-2 in wastewater. It also aimed to investigate the effect of changes in the analytical pipeline, including the RNA extraction kit, RT-PCR kit, and target gene assay, on the results. Another aim was to find a detection method for low-resource settings. METHODS: We compared 2 RT-qPCR kits, TaqMan RT-qPCR and QuantiTect RT-qPCR, and RT-ddPCR based on sensitivity, positivity rates, variability, and correlation of SARS-CoV-2 gene copy numbers in wastewater to the incidence of COVID-19. Furthermore, we compared 2 RNA extraction methods, column- and magnetic-bead-based. In addition, we assessed 2 target gene assays for RT-qPCR, N1 and N2, and 2 target gene assays for ddPCR N1 and E. Reverse transcription strand invasion-based amplification (RT-SIBA) was used to detect SARS-CoV-2 from wastewater qualitatively. RESULTS: Our results indicated that the most sensitive method to detect SARS-CoV-2 in wastewater was RT-ddPCR. It had the highest positivity rate (26/30), and its limit of detection was the lowest (0.06 gene copies/µL). However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using TaqMan RT-qPCR (correlation coefficient [CC]=0.697, P<.001). We found a significant difference in sensitivity between the TaqMan RT-qPCR kit and the QuantiTect RT-qPCR kit, the first having a significantly lower limit of detection and a higher positivity rate than the latter. Furthermore, the N1 target gene assay was the most sensitive for both RT-qPCR kits, while no significant difference was found between the gene targets using RT-ddPCR. In addition, the use of different RNA extraction kits affected the result when the TaqMan RT-qPCR kit was used. RT-SIBA was able to detect SARS-CoV-2 RNA in wastewater. CONCLUSIONS: As our study, as well as most of the previous studies, has shown RT-ddPCR to be more sensitive than RT-qPCR, its use in the wastewater surveillance of SARS-CoV-2 should be considered, especially if the amount of SARS-CoV-2 circulating in the population was low. All the analysis steps must be optimized for wastewater surveillance as our study showed that all the analysis steps including the compatibility of the RNA extraction, the RT-PCR kit, and the target gene assay influence the results. In addition, our study showed that RT-SIBA could be used to detect SARS-CoV-2 in wastewater if a qualitative result is sufficient.

Impact of Color Space and Color Resolution on Vehicle Recognition Models.

In this study, we analyze both linear and nonlinear color mappings by training on versions of a curated dataset collected in a controlled campus environment. We experiment with color space and color resolution to assess model performance in vehicle recognition tasks. Color encodings can be designed in principle to highlight certain vehicle characteristics or compensate for lighting differences when assessing potential matches to previously encountered objects. The dataset used in this work includes imagery gathered under diverse environmental conditions, including daytime and nighttime lighting. Experimental results inform expectations for possible improvements with automatic color space selection through feature learning. Moreover, we find there is only a gradual decrease in model performance with degraded color resolution, which suggests the need for simplified data collection and processing. By focusing on the most critical features, we could see improved model generalization and robustness, as the model becomes less prone to overfitting to noise or irrelevant details in the data. Such a reduction in resolution will lower computational complexity, leading to quicker training and inference times.

The importance of "one health approach" to the AMR study and surveillance in Angola and other African countries.

The dissemination of multidrug-resistant (MDR) bacterial isolates in low- and middle-income countries, including several African countries, is a major concern. The poor sanitary conditions of rural and urban families observed in certain regions may favor the transmission of bacterial infections between animals and humans, including those promoted by strains resistant to practically all available antibiotics. In Angola, in particular, the presence of these strains in human hospitals has already been described. Nevertheless, the information on antimicrobial resistance (AMR) prevalence in Angola is still scarce, especially regarding veterinary isolates. This review aimed to synthesize data on antimicrobial resistance in African countries, with a special focus on Angola, from a One Health perspective. The main goals were to identify research gaps that may require further analysis, and to draw attention to the importance of the conscious use of antimicrobials and the establishment of preventive strategies, aiming to guarantee the safeguarding of public health. To understand these issues, the available literature on AMR in Africa was reviewed. We searched PubMed for articles pertinent to AMR in relevant pathogens in Angola and other African countries. In this review, we focused on AMR rates and surveillance capacity. The principal findings were that, in Africa, especially in sub-Saharan countries, AMR incidence is high due to the lack of legislation on antibiotics, to the close interaction of humans with animals and the environment, and to poverty. The information about current resistance patterns of common pathogenic bacteria is sparse, and the number of quality studies is limited in Angola and in some other Sub-Saharan African countries. Also, studies on the "One Health Approach" focusing on the environment, animals, and humans, are scarce in Africa. The surveillance capacity is minimal, and only a low number of AMR surveillance programs and national health programs are implemented. Most international and cooperative surveillance programs, when implemented, are not properly followed, concluded, nor reported. In Angola, the national health plan does not include AMR control, and there is a consistent omission of data submitted to international surveillance programs. By identifying One Health strengths of each country, AMR can be controlled with a multisectoral approach and governmental commitment.

The impact of dengue viruses: Surveillance, response, and public health implications in Queensland, Australia.

This study examines dengue transmission, symptoms, vaccination efforts, treatment options, and global impact, focusing on Australia, especially Queensland. It evaluates current surveillance and response systems, identifies areas for improvement, and proposes strategies to enhance public health preparedness. Highlighting the socioeconomic impact of dengue outbreaks, the study underscores the need for integrated public health measures, effective vaccines, advanced surveillance methods, and sustainable mosquito control programs to mitigate the threat of dengue outbreaks and potential endemicity.

Using wastewater surveillance for mpox as a complement to traditional case-based reporting - Chicago, March-June 2023.

The Chicago Department of Public Health tested wastewater samples for the presence of Monkeypox Virus (MPXV) from March 13 through June 26, 2023. There were persistent detections prior to reported cases. This indicated the baseline levels of MPXV prevalence might warrant routine monitoring. Detections in areas without corresponding reported clinical cases might highlight areas where cases are being under-reported by traditional surveillance.

A call-to-action: integrate a learning health system framework into longitudinal population studies to improve health response in Africa.

Longitudinal population studies (LPSs) in Africa have the potential to become powerful engines of change by adopting a learning health system (LHS) framework. This is a call-to-action opinion and highlights the importance of integrating an LHS approach into LPSs, emphasizing their transformative potential to improve population health response, drive evidence-based decision making, and enhance community well-being. Operators of LPS platforms, community members, government officials, and funding agencies have a role to contribute to this transformative journey of driving evidence-based interventions, promoting health equity, and fostering long-term public health solutions for African communities.

Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty.

Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

Exploring COVID-19 Vaccination Willingness in Italy: A Focus on Resident Foreigners and Italians Using Data from PASSI and PASSI d'Argento Surveillance Systems.

(1) The COVID-19 pandemic exacerbated health disparities, both between foreign and autochthonous populations. Italy was one of the European countries that was the most affected by the COVID-19 pandemic; however, only limited data are available on vaccine willingness. This study aims to assess the propensity of foreign and autochthonous populations residing in Italy to be vaccinated and the relative associated factors. (2) Data were collected and analysed from the two Italian surveillance systems, PASSI and PASSI d'Argento, in the period of August 2020-December 2021. The data include those of the Italian resident adult population over 18 years old. A multinomial logistic regression model, stratified by citizenship, was used to assess the associations of sociodemographic, health, and COVID-19 experience variables with vaccination attitudes. (3) This study encompassed 19,681 eligible subjects. Considering the willingness to be vaccinated, foreign residents were significantly less certain to get vaccinated (49.4% vs. 60.7% among Italians). Sociodemographic characteristics, economic difficulties, and trust in local health units emerged as factors that were significantly associated with vaccine acceptance. Having received the seasonal flu vaccine was identified as a predictor of COVID-19 vaccine acceptance among foreign and Italian residents. (4) This study underscores the significance of tailoring interventions to address vaccine hesitancy based on the diverse characteristics of foreign and Italian residents. This research offers practical insights for public health strategies, highlighting the importance of tailored educational campaigns, improved communication, and nuanced interventions to enhance vaccine acceptance and uptake within both populations.

Rethinking the World Health Organization's leadership of global health governance and the global health surveillance systems.

Global health governance is a strategic priority for the World Health Organization (WHO), and the public health surveillance system (PHSS) is a fundamental element of the global health governance structure to timely identify emerging diseases and guide global public health decisions and actions. This analysis explores the overall landscape of global health governance, with a specific focus on the PHSS to understand whether the existing governance landscape facilitates or undermines the WHO's ability to formulate and implement global health policies and initiatives. To achieve this, the existing evidence was reviewed, and synthesized with the experts' perspectives. It is reported that fragmentation is the main drawback of the global health governance landscape, necessitating reorganization and restructuring. The disintegration of PHSS at the global, regional and local levels is associated with a lack of leadership, misalignment with global health priorities, imbalance in coverage of surveillance systems, inadequate innovative technology and digitalization, and fragmented data and information systems. The fragmentation and disintegration of global health governance undermine the effectiveness of the WHO's global health strategic directions and programmes and hinder its ability to govern and guide the global, regional and national public health emergency response. Strategic rethinking of the WHO's governance is essential because strong governance and leadership lead to a robust, aligned and effective PHSS.

How to improve the surveillance of the Taliban ban's impact on European drug markets.

In April 2023, the Taliban banned poppy cultivation and the trade of all narcotics. This caused a 95% reduction in opium production. Usually, that would be good news. But there is a substantial worry: synthetic opioids might fill the void left by heroin. This is concerning because these drugs have led to health emergencies in areas where they are prevalent. This paper highlights the limitations of the current drug surveillance system in Europe and proposes improvements. It argues that reliance on secondary data is insufficient. Instead, we need to interview a sentinel group of people who inject drugs and adjust city-level sentinel systems, such as wastewater analysis, to specifically track the spread of synthetic opioids. Without these proactive steps, we risk only noticing a transition from heroin to synthetic opioids after it has occurred, with its harmful impacts already in place.

Enhancing Water Safety: Exploring Recent Technological Approaches for Drowning Detection.

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection systems. However, the image-processing approach requires substantial resources and sophisticated MLAs, making it costly and complex to implement. Conversely, sensor-based approaches offer practical, cost-effective, and widely applicable solutions for drowning detection. These approaches involve data transmission from the swimmer's condition to the processing unit through sensing technology, utilising both wired and wireless communication channels. This paper explores the recent developments in drowning detection systems while considering costs, complexity, and practicality in selecting and implementing such systems. The assessment of various technological approaches contributes to ongoing efforts aimed at improving water safety and reducing the risks associated with drowning incidents.

Reducing fall injuries with better data.

BACKGROUND: Fall deaths in the USA almost tripled in the twenty-first century. While various interventions have been effective in reducing fall deaths, they have failed to make a substantial impact at a population level. MAIN BODY: An overarching factor that has been relatively neglected in fall injury prevention is the need for more and better data. We need better data on the causes and circumstances of older adult fall deaths. While there are excellent national surveillance systems on the circumstances of other injury deaths (e.g., motor vehicle crashes, suicides, and homicides), such a system is lacking for fall deaths. These other data systems have been instrumental in indicating and evaluating policies that will reduce injury. It is also important to provide consumers with better information concerning the many products that affect the likelihood of fall injury (e.g., flooring, hip protectors, footwear). Automotive buyers are provided with relevant up-to-date make-model safety information from crash tests and real-world performance. Such information not only helps protect buyers from purchasing dangerous products, but it provides producers with the incentive to make ever safer products over time. CONCLUSION: We believe that creation of a national surveillance system on the circumstances of fall deaths, and increased testing/certifying of fall-related products, are two steps that would help create the conditions for continuous reductions in fall fatalities. Fall prevention should apply some of the same basic strategies that have proved effective in addressing other injuries.

Development, implementation, and evaluation of a local community-based ophthalmology sentinel surveillance system in a remote rural area in Japan.

INTRODUCTION: Solid and sensitive infectious disease surveillance systems need to be developed and implemented to prevent and control epidemics. Although statutory national infectious disease surveillance systems have been developed in many countries, some challenges remain, such as their limited timeliness, representativeness, and sensitivity, as well as the fact that they cannot capture all local outbreaks that occur in small communities. To overcome these limitations, local community-based infectious disease surveillance systems that meet local needs and can operate with constrained resources need to be developed, especially in remote and rural low-resource areas. This study aimed to develop, implement, and evaluate a voluntary and unique local community-based ophthalmology sentinel surveillance system in Isa city (OSSS-Isa), a remote rural area in Japan. METHODS: For the development of OSSS-Isa, one hospital in Isa city assumed a leading role and developed a network with all medical institutions - 20 hospitals and clinics in the local community, including two ophthalmology clinics - as sentinel reporting sites. Surveillance was conducted on a weekly basis from Monday to Sunday. The collection, aggregation, and reporting of the surveillance data were implemented promptly on the same day, Monday, using a paper-based form and fax. For the evaluation of OSSS-Isa, the study followed the updated guidelines for evaluating public health surveillance systems proposed by the Centers for Disease Control and Prevention to select the evaluation criteria and develop a questionnaire. The questionnaires were then distributed to 20 hospitals and clinics, with the responses evaluated on a five-point Likert scale. RESULTS: For the implementation of OSSS-Isa, the system issued alerts twice to the networked hospitals and clinics when signs of an increase in the prevalence of a target infectious eye disease appeared in Isa city. After the alerts, the number of cases decreased in the community. Regarding the evaluation survey, physicians from 18 hospitals and clinics responded to the questionnaire (response rate 90%). In contrast to flexibility, more than 75% of the respondents gave high ratings to simplicity, data quality, acceptability, timeliness, and stability in evaluating OSSS-Isa, with the mean score for these evaluation criteria higher than 3.67. CONCLUSION: The present results indicate that OSSS-Isa has high simplicity, data quality, acceptability, timeliness, and stability, which is highly embedded with the local healthcare providers in Isa city. OSSS-Isa contributed to the early and accurate detection of signs of infectious eye disease outbreaks emerging in a small remote rural local community. The success factors seem to include its simple well-designed implementation methods, good external factors, and active human factors suited to the characteristics of the small remote rural community. The OSSS-Isa initiative appears to be a meaningful practical example of successful health advocacy by healthcare providers by developing a system at the local social level while going beyond the boundaries of routine medical practice. If voluntary small-scale surveillance systems can complement statutory large-scale ones and work together locally, nationally, and internationally, it might be possible to detect small, unusual happenings that occur in the community, such as emerging infectious diseases, and thereby help avert global outbreaks.

Connecting patients notified with hepatitis C to treatment (CONNECT Study): A randomized controlled trial of active case management by a health department to support primary care practitioners.

BACKGROUND: Despite subsidised access to direct-acting antivirals (DAAs), hepatitis C (HCV) treatment uptake in Australia is declining. Interventions are needed to link people living with HCV to care and treatment. We implemented and measured effectiveness of a state-wide, health department-led, enhanced case management through the primary care practitioner for all HCV notifications, aiming to encourage and support treatment commencement. METHODS: A randomised controlled trial compared enhanced case management, delivered by the health department to diagnosing clinicians, with standard of care using notifiable disease systems in Tasmania, Australia (2020-21). The intervention involved a nurse specialist contacting and providing support by telephone to primary care practitioners making an HCV notification. The primary outcome was the proportion of cases notified with chronic hepatitis C who commenced treatment within 12 weeks of notification. We allowed a 12-week extended follow-up period at the end of the study for participants with no outcomes. RESULTS: Eighty-five primary care practitioners randomised to the intervention and 86 to standard of care arms notified 111 and 115 HCV cases, respectively. The proportion of cases notified with chronic hepatitis (HCV RNA detected) commencing treatment within 12 weeks was similar between study arms (41% vs 33%; p=0·51) and after extended study follow-up (65% vs 48%; p=0·18). RNA test completion was higher in the intervention than in standard of care arm (89% vs. 78%; p=0·03), while completing pre-treatment workup for chronic patients (65% vs. 64%; p=0·93) was similar. CONCLUSION: This was the first prospective randomised study of the utility of immediate HCV notification follow-up of primary care practitioners to enhance treatment uptake using disease notification surveillance data. We demonstrated improvement in HCV RNA testing and trend toward better engagement in care, but no significant increase in treatment uptake.

One Health Surveillance System in Gujarat, India: A Health Policy and Systems Research Protocol for Exploring the Cross-Sectoral Collaborations to Detect Emerging Threats at the Human-Animal-Environment Interface.

The close interaction between humans, animals and the ecosystem has been a reason for the emergence and re-emergence of zoonotic diseases worldwide. Zoonoses are estimated to be responsible for 2.5 billion human illnesses and 2.7 million deaths worldwide. Gujarat is a western state in India with more than 65 million people and 26 million livestock, and includes surveillance systems for humans and animals; however, more evidence is needed on joint collaborative activities and their effect on the early warning response for zoonoses. Thus, this study aims to investigate sectoral collaborations for early warning and response systems for emerging and re-emerging zoonoses, aiming to develop a One Health surveillance (OHS) system in Gujarat, India. This case study uses policy content analysis followed by qualitative and quantitative data collection among state- and district-level surveillance actors to provide insight into the current cross-sectoral collaborations among surveillance actors. It helps identify triggers and documents factors helpful in strengthening cross-sectoral collaborations among these systems and facilitates the establishment of an OHS system in Gujarat, India.

Dynamic household structure and composition: a manual for longitudinal analysis of living arrangements.

OBJECTIVE: This research note introduces a set of tools to conduct analysis of household structure and composition with either limited or comprehensive longitudinal data. The data used here are from Health and Demographic Surveillance Systems in Africa, but the methods can be adapted and applied to other longitudinal micro-data such as register data. A training manual describing the procedures for creating time-varying household measures step-by-step is supplied as supplementary material to this note. Code is provided in STATA but can easily be translated for other statistical software, and the logic for each step remains the same. RESULTS: The analysis of household structure demonstrates how with limited data (such as a household identifier), it is possible to construct time-varying measures of household membership, including household size or the number of members in specific age and sex groups. The analysis of household composition demonstrates how with expanded data (including links to parents in addition to residence status in the same household), it is possible to construct time-varying measures of household membership of specific kin, i.e. mother, sibling or grandparent. The results illustrated in this research note are a taste of what can be achieved by following the training manual in the supplementary material.

Deployment of Rotavirus Vaccine in Western Kenya Coincides with a Reduction in All-Cause Child Mortality: A Retrospective Cohort Study.

Rotavirus is an important cause of fatal pediatric diarrhea worldwide. Many national immunization programs began adding rotavirus vaccine following a 2009 World Health Organization recommendation. Kenya added rotavirus vaccine to their immunization program at the end of 2014. From a cohort of 38,463 children in the Kisumu health and demographic surveillance site in western Kenya, we assessed how the implementation of the rotavirus vaccine affected mortality in children under 3 years of age. Following its introduction in late 2014, the span of rotavirus vaccine coverage for children increased to 75% by 2017. Receiving the rotavirus vaccine was associated with a 44% reduction in all-cause child mortality (95% confidence interval = 28-68%, p < 0.0001), but not diarrhea-specific mortality (p = 0.401). All-cause child mortality declined 2% per month following the implementation of the rotavirus vaccine (p = 0.002) among both vaccinated and unvaccinated children, but diarrhea-specific mortality was not associated with the implementation of the rotavirus vaccine independent of individual vaccine status (p = 0.125). The incidence of acute diarrhea decreased over the study period, and the introduction of the rotavirus vaccine was not associated with population-wide trends (p = 0.452). The receipt of the rotavirus vaccine was associated with a 34% reduction in the incidence of diarrhea (95% confidence interval = 24-43% reduction). These results suggest that rotavirus vaccine may have had an impact on all-cause child mortality. The analyses of diarrhea-specific mortality were limited by relatively few deaths (n = 57), as others have found a strong reduction in diarrhea-specific mortality. Selection bias may have played a part in these results-children receiving rotavirus vaccine were more likely to be fully immunized than children not receiving the rotavirus vaccine.

Delay analysis of pulmonary tuberculosis in the eastern coastal county of China from 2010 to 2021: evidence from two surveillance systems.

Background: Tuberculosis (TB) remains a major public health challenge. However, indicators of delays in assessing effective TB prevention and control and its influencing factors have not been investigated in the eastern coastal county of China. Methods: All notified pulmonary tuberculosis (PTB) cases in the Fenghua District, China were collected between 2010 and 2021 from the available TB information management system. Comparison of delays involving patient, health system, and total delays among local and migrant cases. Additionally, in correlation with available Basic Public Health Service Project system, we performed univariate and multivariate logistic regression analyses identified the influencing factors associated with patient and total delays in patients aged >60 years. Results: In total, 3,442 PTB cases were notified, including 1,725 local and 1,717 migrant patients, with a male-to-female ratio of 2.13:1. Median patient and total delays of local TB patients were longer than those for migrant patients; the median health system delay did not show any significant difference. For patient delay among the older adult, female (cOR: 1.93, 95% CI: 1.07-3.48), educational level of elementary school and middle school (cOR: 0.23, 95% CI: 0.06-0.84) had a statistical difference from univariable analysis; however, patients without diabetes showed a higher delay for multiple-factor analysis (aOR: 2.12, 95% CI: 1.02-4.41). Furthermore, only the education level of elementary school and middle school presented a low total delay for both univariate (cOR: 0.22, 95% CI: 0.06-0.82) and multivariate analysis (aOR: 0.21, 95% CI: 0.05-0.83) in the older patients. Conclusion: The delay of TB cases among migrants was lower than the local population in the Fenghua District, which may be related to the "healthy migrant effect". It highlights that women, illiterate people, and people without diabetes are key groups for reducing delays among older adults. Health awareness should focus on these target populations, providing accessible health services, and reducing the time from symptom onset to diagnosis.

Exploring Older Adults' Willingness to Install Home Surveil-Lance Systems in Taiwan: Factors and Privacy Concerns.

Taiwan has a rapidly increasing aging population with a considerably high life expectancy rate, which poses challenges for healthcare and medical systems. This study examines three key factors: safety concerns, family expectations, and privacy concerns, and their influence on surveillance system installation decisions. A cross-sectional study was conducted involving a group of physically active older adults in Taiwan, using a questionnaire to collect data on the reasons for in-stalling a surveillance system and preferences for three image privacy protection techniques: blurring the face and transformation to a 2D or 3D character. The study concluded that while safety concerns and family expectations facilitate the adoption of surveillance systems, privacy concerns serve as a significant barrier. Furthermore, older adults showed a clear preference for avatar-based privacy protection methods over simpler techniques, such as blurring. The outcomes of this research will be instrumental in shaping the development of privacy-conscious home surveillance technologies, adeptly balancing safety and privacy. This understanding can pave the way for technology design that skillfully balances privacy concerns with remote monitoring quality, thereby enhancing the well-being and safety of this demographic. These results could possibly be extended to other demographics as well.