The role of digital tools and emerging devices in COVID-19 contact tracing during the first 18 months of the pandemic: a systematic review.

BACKGROUND: Contact tracing is a public health intervention implemented in synergy with other preventive measures to curb epidemics, like the coronavirus pandemic. The development and use of digital devices have increased worldwide to enhance the contact tracing process. The aim of the study was to evaluate the effectiveness and impact of tracking coronavirus disease 2019 (COVID-19) patients using digital solutions. METHODS: Observational studies on digital contact tracing (DCT), published 2020-21, in English were identified through a systematic literature review performed on nine online databases. An ad hoc form was used for data extraction of relevant information. Quality assessment of the included studies was performed with validated tools. A qualitative synthesis of the findings is reported. RESULTS: Over 8000 records were identified and 37 were included in the study: 24 modelling and 13 population-based studies. DCT improved the identification of close contacts of COVID-19 cases and reduced the effective reproduction number of COVID-19-related infections and deaths by over 60%. It impacted positively on societal and economic costs, in terms of lockdowns and use of resources, including staffing. Privacy and security issues were reported in 27 studies. CONCLUSIONS: DCT contributed to curbing the COVID-19 pandemic, especially with the high uptake rate of the devices and in combination with other public health measures, especially conventional contact tracing. The main barriers to the implementation of the devices are uptake rate, security and privacy issues. Public health digitalization and contact tracing are the keys to countries' emergency preparedness for future health crises.

Identifying the interplay between protective measures and settings on the SARS-CoV-2 transmission using a Bayesian network.

Contact tracing played a crucial role in minimizing the onward dissemination of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the recent pandemic. Previous studies had also shown the effectiveness of preventive measures such as mask-wearing, physical distancing, and exposure duration in reducing SARS-CoV-2 transmission. However, there is still a lack of understanding regarding the impact of various exposure settings on the spread of SARS-CoV-2 within the community, as well as the most effective preventive measures, considering the preventive measures adherence in different daily scenarios. We aimed to evaluate the effect of individual protective measures and exposure settings on the community transmission of SARS-CoV-2. Additionally, we aimed to investigate the interaction between different exposure settings and preventive measures in relation to such SARS-CoV-2 transmission. Routine SARS-CoV-2 contact tracing information was supplemented with additional data on individual measures and exposure settings collected from index patients and their close contacts. We used a case-control study design, where close contacts with a positive test for SARS-CoV-2 were classified as cases, and those with negative results classified as controls. We used the data collected from the case-control study to construct a Bayesian network (BN). BNs enable predictions for new scenarios when hypothetical information is introduced, making them particularly valuable in epidemiological studies. Our results showed that ventilation and time of exposure were the main factors for SARS-CoV-2 transmission. In long time exposure, ventilation was the most effective factor in reducing SARS-CoV-2, while masks and physical distance had on the other hand a minimal effect in this ventilation spaces. However, face masks and physical distance did reduce the risk in enclosed and unventilated spaces. Distance did not reduce the risk of infection when close contacts wore a mask. Home exposure presented a higher risk of SARS-CoV-2 transmission, and any preventive measures posed a similar risk across all exposure settings analyzed. Bayesian network analysis can assist decision-makers in refining public health campaigns, prioritizing resources for individuals at higher risk, and offering personalized guidance on specific protective measures tailored to different settings or environments.

Providing HIV-assisted partner services to partners of partners in western Kenya: an implementation science study.

INTRODUCTION: Assisted partner services (APS), or exposure notification and HIV testing for sexual partners of persons diagnosed HIV positive (index clients), is recommended by the World Health Organization. Most APS literature focuses on outcomes among index clients and their partners. There is little data on the benefits of providing APS to partners of partners diagnosed with HIV. METHODS: We utilized data from a large-scale APS implementation project across 31 facilities in western Kenya from 2018 to 2022. Females testing HIV positive at facilities were offered APS; those who consented provided contact information for all male sexual partners in the last 3 years. Male partners were notified of their potential HIV exposure and offered HIV testing services (HTS). Males newly testing positive were also offered APS and asked to provide contact information for their female partners in the last 3 years. Female partners of male partners (FPPs) were provided exposure notification and HTS. All participants with HIV were followed up at 12 months post-enrolment to assess linkage-to antiretroviral treatment (ART) and viral suppression. We compared HIV positivity, demographics and linkage outcomes among female index clients and FPPs. RESULTS: Overall, 5708 FPPs were elicited from male partners, of whom 4951 received HTS through APS (87% coverage); 291 FPPs newly tested HIV positive (6% yield), an additional 1743 (35.2%) reported a prior HIV diagnosis, of whom 99% were on ART at baseline. At 12 months follow-up, most FPPs were taking ART (92%) with very few adverse events: <1% reported intimate partner violence or reported relationship dissolution. FPPs were more likely than female index clients to report HIV risk behaviours including no condom use at last sex (45% vs. 30%) and multiple partners (38% vs. 19%). CONCLUSIONS: Providing HIV testing via APS to FPP is a safe and effective strategy to identify newly diagnosed females and achieve high linkage and retention to ART and can be an efficient means of identifying HIV cases in the era of declining HIV incidence. The high proportion of FPPs reporting HIV risk behaviours suggests APS may help interrupt community HIV transmission via increased knowledge of HIV status and linkage to treatment.

A pilot project harnessing surveillance systems to support clinicians providing clinical care for people diagnosed with hepatitis C in Victoria, Australia, September 2021 to 31 March 2022.

BackgroundActive follow-up of chronic hepatitis C notifications to promote linkage to care is a promising strategy to support elimination.AimThis pilot study in Victoria, Australia, explored if the Department of Health could follow-up on hepatitis C cases through their diagnosing clinicians, to assess and support linkage to care and complete data missing from the notification.MethodsFor notifications received between 1 September 2021 and 31 March 2022 of unspecified hepatitis C cases (i.e. acquired > 24 months ago or of unknown duration), contact with diagnosing clinicians was attempted. Data were collected on risk exposures, clinical and demographic characteristics and follow-up care (i.e. HCV RNA test; referral or ascertainment of previous negative testing or treatment history). Reasons for unsuccessful doctor contact and gaps in care provision were investigated. Advice to clinicians on care and resources for clinical support were given on demand.ResultsOf 513 cases where information was sought, this was able to be obtained for 356 (69.4%). Reasons for unsuccessful contact included incomplete contact details or difficulties getting in touch across three attempts, particularly for hospital diagnoses. Among the 356 cases, 307 (86.2%) had received follow-up care. Patient-management resources were requested by 100 of 286 contacted diagnosing clinicians.ConclusionsMost doctors successfully contacted had provided follow-up care. Missing contact information and the time taken to reach clinicians significantly impeded the feasibility of the intervention. Enhancing system automation, such as integration of laboratory results, could improve completeness of notifications and support further linkage to care where needed.

Utilizing rapid qualitative assessment and thematic analysis methods to identify and share promising case investigation and contact tracing practices with people in refugee, immigrant, and migrant communities during COVID-19.

In the early months of the COVID-19 pandemic The National Resource Center for Refugees, Immigrants and Migrants (NRC-RIM) was established. NRC-RIM initially sought to rapidly identify promising case investigation and contact tracing (CICT) practices within refugee, immigrant, and migrant communities. Between September 2020 and April 2021, the team conducted 60 interviews with individuals from cross-sector organizations (i.e., public health, health systems, community experts/organizations) working with refugee, immigrant and migrant communities in health and public health capacities related to COVID-19. The overarching aim was to identify and amplify innovative promising and best practices for CICT with refugee, immigrant, and migrant communities, including an exploration of barriers and facilitators. We utilized layered methods to rapidly assess, summarize and disseminate promising practices while simultaneously completing four thematic analyses including: (1) public health organizations; (2) health system organizations; (3) community leaders and organizations; and (4) vaccine planning and access across the three sectors. The primary objective of this article is to describe the project design, applied methods, and team science approach we utilized. We found that rapid identification and dissemination of promising practices, and barriers and facilitators for CICT with refugee, immigrant and migrant communities was feasible during a public health emergency. This approach was essential for identifying and widely sharing culturally and linguistically concordant public health practices.

Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data.

While many countries employed digital contact tracing to contain the spread of SARS-CoV-2, the contribution of cospace-time interaction (i.e., individuals who shared the same space and time) to transmission and to super-spreading in the real world has seldom been systematically studied due to the lack of systematic sampling and testing of contacts. To address this issue, we utilized data from 2230 cases and 220,878 contacts with detailed epidemiological information during the Omicron outbreak in Beijing in 2022. We observed that contact number per day of tracing for individuals in dwelling, workplace, cospace-time interactions, and community settings could be described by gamma distribution with distinct parameters. Our findings revealed that 38% of traced transmissions occurred through cospace-time interactions whilst control measures were in place. However, using a mathematical model to incorporate contacts in different locations, we found that without control measures, cospace-time interactions contributed to only 11% (95%CI: 10%-12%) of transmissions and the super-spreading risk for this setting was 4% (95%CI: 3%-5%), both the lowest among all settings studied. These results suggest that public health measures should be optimized to achieve a balance between the benefits of digital contact tracing for cospace-time interactions and the challenges posed by contact tracing within the same setting.

An algorithm to build synthetic temporal contact networks based on close-proximity interactions data.

Small populations (e.g., hospitals, schools or workplaces) are characterised by high contact heterogeneity and stochasticity affecting pathogen transmission dynamics. Empirical individual contact data provide unprecedented information to characterize such heterogeneity and are increasingly available, but are usually collected over a limited period, and can suffer from observation bias. We propose an algorithm to stochastically reconstruct realistic temporal networks from individual contact data in healthcare settings (HCS) and test this approach using real data previously collected in a long-term care facility (LTCF). Our algorithm generates full networks from recorded close-proximity interactions, using hourly inter-individual contact rates and information on individuals' wards, the categories of staff involved in contacts, and the frequency of recurring contacts. It also provides data augmentation by reconstructing contacts for days when some individuals are present in the HCS without having contacts recorded in the empirical data. Recording bias is formalized through an observation model, to allow direct comparison between the augmented and observed networks. We validate our algorithm using data collected during the i-Bird study, and compare the empirical and reconstructed networks. The algorithm was substantially more accurate to reproduce network characteristics than random graphs. The reconstructed networks reproduced well the assortativity by ward (first-third quartiles observed: 0.54-0.64; synthetic: 0.52-0.64) and the hourly staff and patient contact patterns. Importantly, the observed temporal correlation was also well reproduced (0.39-0.50 vs 0.37-0.44), indicating that our algorithm could recreate a realistic temporal structure. The algorithm consistently recreated unobserved contacts to generate full reconstructed networks for the LTCF. To conclude, we propose an approach to generate realistic temporal contact networks and reconstruct unobserved contacts from summary statistics computed using individual-level interaction networks. This could be applied and extended to generate contact networks to other HCS using limited empirical data, to subsequently inform individual-based epidemic models.

An SEIR network epidemic model with manual and digital contact tracing allowing delays.

We consider an SEIR epidemic model on a network also allowing random contacts, where recovered individuals could either recover naturally or be diagnosed. Upon diagnosis, manual contact tracing is triggered such that each infected network contact is reported, tested and isolated with some probability and after a random delay. Additionally, digital tracing (based on a tracing app) is triggered if the diagnosed individual is an app-user, and then all of its app-using infectees are immediately notified and isolated. The early phase of the epidemic with manual and/or digital tracing is approximated by different multi-type branching processes, and three respective reproduction numbers are derived. The effectiveness of both contact tracing mechanisms is numerically quantified through the reduction of the reproduction number. This shows that app-using fraction plays an essential role in the overall effectiveness of contact tracing. The relative effectiveness of manual tracing compared to digital tracing increases if: more of the transmission occurs on the network, when the tracing delay is shortened, and when the network degree distribution is heavy-tailed. For realistic values, the combined tracing case can reduce R0 by 20%-30%, so other preventive measures are needed to reduce the reproduction number down to 1.2-1.4 for contact tracing to make it successful in avoiding big outbreaks.

FaceTouch: Detecting hand-to-face touch with supervised contrastive learning to assist in tracing infectious diseases.

Through our respiratory system, many viruses and diseases frequently spread and pass from one person to another. Covid-19 served as an example of how crucial it is to track down and cut back on contacts to stop its spread. There is a clear gap in finding automatic methods that can detect hand-to-face contact in complex urban scenes or indoors. In this paper, we introduce a computer vision framework, called FaceTouch, based on deep learning. It comprises deep sub-models to detect humans and analyse their actions. FaceTouch seeks to detect hand-to-face touches in the wild, such as through video chats, bus footage, or CCTV feeds. Despite partial occlusion of faces, the introduced system learns to detect face touches from the RGB representation of a given scene by utilising the representation of the body gestures such as arm movement. This has been demonstrated to be useful in complex urban scenarios beyond simply identifying hand movement and its closeness to faces. Relying on Supervised Contrastive Learning, the introduced model is trained on our collected dataset, given the absence of other benchmark datasets. The framework shows a strong validation in unseen datasets which opens the door for potential deployment.

The effectiveness of intervention measures on MERS-CoV transmission by using the contact networks reconstructed from link prediction data.

Introduction: Mitigating the spread of infectious diseases is of paramount concern for societal safety, necessitating the development of effective intervention measures. Epidemic simulation is widely used to evaluate the efficacy of such measures, but realistic simulation environments are crucial for meaningful insights. Despite the common use of contact-tracing data to construct realistic networks, they have inherent limitations. This study explores reconstructing simulation networks using link prediction methods as an alternative approach. Methods: The primary objective of this study is to assess the effectiveness of intervention measures on the reconstructed network, focusing on the 2015 MERS-CoV outbreak in South Korea. Contact-tracing data were acquired, and simulation networks were reconstructed using the graph autoencoder (GAE)-based link prediction method. A scale-free (SF) network was employed for comparison purposes. Epidemic simulations were conducted to evaluate three intervention strategies: Mass Quarantine (MQ), Isolation, and Isolation combined with Acquaintance Quarantine (AQ + Isolation). Results: Simulation results showed that AQ + Isolation was the most effective intervention on the GAE network, resulting in consistent epidemic curves due to high clustering coefficients. Conversely, MQ and AQ + Isolation were highly effective on the SF network, attributed to its low clustering coefficient and intervention sensitivity. Isolation alone exhibited reduced effectiveness. These findings emphasize the significant impact of network structure on intervention outcomes and suggest a potential overestimation of effectiveness in SF networks. Additionally, they highlight the complementary use of link prediction methods. Discussion: This innovative methodology provides inspiration for enhancing simulation environments in future endeavors. It also offers valuable insights for informing public health decision-making processes, emphasizing the importance of realistic simulation environments and the potential of link prediction methods.

Effects of User Experience in Automated Information Processing on Perceived Usefulness of Digital Contact-Tracing Apps: Cross-Sectional Survey Study.

BACKGROUND: In pandemic situations, digital contact tracing (DCT) can be an effective way to assess one's risk of infection and inform others in case of infection. DCT apps can support the information gathering and analysis processes of users aiming to trace contacts. However, users' use intention and use of DCT information may depend on the perceived benefits of contact tracing. While existing research has examined acceptance in DCT, automation-related user experience factors have been overlooked. OBJECTIVE: We pursued three goals: (1) to analyze how automation-related user experience (ie, perceived trustworthiness, traceability, and usefulness) relates to user behavior toward a DCT app, (2) to contextualize these effects with health behavior factors (ie, threat appraisal and moral obligation), and (3) to collect qualitative data on user demands for improved DCT communication. METHODS: Survey data were collected from 317 users of a nationwide-distributed DCT app during the COVID-19 pandemic after it had been in app stores for >1 year using a web-based convenience sample. We assessed automation-related user experience. In addition, we assessed threat appraisal and moral obligation regarding DCT use to estimate a partial least squares structural equation model predicting use intention. To provide practical steps to improve the user experience, we surveyed users' needs for improved communication of information via the app and analyzed their responses using thematic analysis. RESULTS: Data validity and perceived usefulness showed a significant correlation of r=0.38 (P<.001), goal congruity and perceived usefulness correlated at r=0.47 (P<.001), and result diagnosticity and perceived usefulness had a strong correlation of r=0.56 (P<.001). In addition, a correlation of r=0.35 (P<.001) was observed between Subjective Information Processing Awareness and perceived usefulness, suggesting that automation-related changes might influence the perceived utility of DCT. Finally, a moderate positive correlation of r=0.47 (P<.001) was found between perceived usefulness and use intention, highlighting the connection between user experience variables and use intention. Partial least squares structural equation modeling explained 55.6% of the variance in use intention, with the strongest direct predictor being perceived trustworthiness (ß=.54; P<.001) followed by moral obligation (ß=.22; P<.001). Based on the qualitative data, users mainly demanded more detailed information about contacts (eg, place and time of contact). They also wanted to share information (eg, whether they wore a mask) to improve the accuracy and diagnosticity of risk calculation. CONCLUSIONS: The perceived result diagnosticity of DCT apps is crucial for perceived trustworthiness and use intention. By designing for high diagnosticity for the user, DCT apps could improve their support in the action regulation of users, resulting in higher perceived trustworthiness and use in pandemic situations. In general, automation-related user experience has greater importance for use intention than general health behavior or experience.

Are we heroes or couriers? A phenomenological study on reappropriation of professional subjectivity and agency among health professionals during COVID-19 contact tracing in Türkiye.

During the COVID-19 pandemic, Türkiye implemented a distinctive contact tracing approach involving in-person home visits by medical professionals to individuals who tested positive for the virus. This study examines the experiences of health professionals involved in contact tracing, exploring how they reappropriated their professional subjectivity and agency during their deployment in this role. It is an interpretive phenomenological qualitative study. We conducted 21 semi-structured in-depth interviews, subsequently carried out two separate focus group interviews with an additional 31 participants from various districts in Istanbul. Participants were selected from different medical professions (i.e. doctors, nurses, midwives), career stages, gender and age groups, and hierarchical levels (i.e. officers and directors). Data analysis was conducted collaboratively by the research team from sociology and public health disciplines. Our main finding is that for the majority of health professionals, contact tracing was a novel experience with challenges and ambivalances. Yet, regardless of their perceptions (positive, negative, or mixed), the experience promoted a reaffirmation of professional identity and reappropriation of professional subjectivity and agency, which discloses that professional subjectivity is not firm but dynamic, carrying stability as well as flexibility and adjustment. Four main themes are identified in their reappropriation of professional subjectivity and agency: uncovering professional fulfillment, feeling restrained in professional dissatisfaction, assessing the job, and engaging in professional and bureaucratic negotiations.The profound exploration into the dynamics of contact tracing amidst the pandemic illuminates a multidimensional narrative that transcends the conventional discourse on physical and psychological stress experienced by medical professionals. Contact tracing experience had a transformative impact on meaning and purpose of professional identity. Our findings highlight a need for a balanced approach between centralized decision-making, mobilization of professionals, quantitative evaluation, and professional autonomy and discretion, qualitative assessments, and meaningful engagement.

Between Technological Utopia and Dystopia: Online Expression of Compulsory Use of Surveillance Technology.

This study investigated people's ethical concerns of surveillance technology. By adopting the spectrum of technological utopian and dystopian narratives, how people perceive a society constructed through the compulsory use of surveillance technology was explored. This study empirically examined the anonymous online expression of attitudes toward the society-wide, compulsory adoption of a contact tracing app that affected almost every aspect of all people's everyday lives at a societal level. By applying the structural topic modeling approach to analyze comments on four Hong Kong anonymous discussion forums, topics concerning the technological utopian, dystopian, and pragmatic views on the surveillance app were discovered. The findings showed that people with a technological utopian view on this app believed that the implementation of compulsory app use can facilitate social good and maintain social order. In contrast, individuals who had a technological dystopian view expressed privacy concerns and distrust of this surveillance technology. Techno-pragmatists took a balanced approach and evaluated its implementation practically.

Community tuberculosis screening, testing and care, Uganda.

Objective: To assess the effectiveness of a community-based tuberculosis and leprosy intervention in which village health teams and health workers conduct door-to-door tuberculosis screening, targeted screenings and contact tracing. Methods: We conducted a before-and-after implementation study in Uganda to assess the effectiveness of the community tuberculosis intervention by looking at reach, outputs, adoption and effectiveness of the intervention. Campaign 1 was conducted in March 2022 and campaign 2 in September 2022. We calculated percentages of targets achieved and compared case notification rates during the intervention with corresponding quarters in the previous year. We also assessed the leprosy screening. Findings: Over 5 days, campaign 1 screened 1 289 213 people (2.9% of the general population), of whom 179 144 (13.9%) fulfilled the presumptive tuberculosis criteria, and 4043 (2.3%) were diagnosed with bacteriologically-confirmed tuberculosis; 3710 (91.8%) individuals were linked to care. In campaign 2, 5 134 056 people (11.6% of the general population) were screened, detecting 428 444 (8.3%) presumptive tuberculosis patients and 8121 (1.9%) bacteriologically-confirmed tuberculosis patients; 5942 individuals (87.1%) were linked to care. The case notification rate increased from 48.1 to 59.5 per 100 000 population in campaign 1, with a case notification rate ratio of 1.24 (95% confidence interval, CI: 1.22-1.26). In campaign 2, the case notification rate increased from 45.0 to 71.6 per 100 000 population, with a case notification rate ratio of 1.59 (95% CI: 1.56-1.62). Of the 176 patients identified with leprosy, 137 (77.8%) initiated treatment. Conclusion: This community tuberculosis screening initiative is effective. However, continuous monitoring and adaptations are needed to overcome context-specific implementation challenges.

Digital interventions for STI and HIV partner notification: a scoping review.

BACKGROUND: Partner notification (PN) is key to the control of sexually transmitted infections (STIs) and human immunodeficiency virus (HIV). Digital interventions have been used to facilitate PN. A scoping review was conducted to describe the interventions used, user preferences and acceptability of digital PN interventions from patient and partner perspectives. METHODS: A systematic literature search was conducted of eight databases for articles published in English, available online with digital PN outcome data. Articles were assessed using the Mixed Methods Appraisal Tool. Quantitative and qualitative data were synthesised and analysed using thematic analysis. RESULTS: Twenty-six articles met the eligibility criteria. Articles were heterogeneous in quality and design, with the majority using quantitative methods. Nine articles focused solely on bacterial STIs (five on syphilis; four on chlamydia), one on HIV, two on syphilis and HIV, and 14 included multiple STIs, of which 13 included HIV. There has been a shift over time from digital PN interventions solely focusing on notifying partners, to interventions including elements of partner management, such as facilitation of partner testing and treatment, or sharing of STI test results (between index patients and tested sex partners). Main outcomes measured were number of partners notified (13 articles), partner testing/consultation (eight articles) and treatment (five articles). Relationship type and STI type appeared to affect digital PN preferences for index patients with digital methods preferred for casual rather than established partner types. Generally, partners preferred face-to-face PN. CONCLUSION: Digital PN to date mainly focuses on notifying partners rather than comprehensive partner management. Despite an overall preference for face-to-face PN with partners, digital PN could play a useful role in improving outcomes for certain partner types and infections. Further research needs to understand the impact of digital PN interventions on specific PN outcomes, their effectiveness for different infections and include health economic evaluations.

Tracing the Untraceables: A Joint Outbreak Investigation With Law Enforcement Using a Geographic Information System.

The application of geospatial data often allows the tracing of people who are involved in activities of an illegal nature. In June 2021, we estimated the true magnitude of the spread of COVID-19 within the networks of escort-karaoke bars in Seoul, Republic of Korea, using geographic information system (GIS)-based contact tracing that was applied to our epidemiological investigation. Our joint rapid response team, composed of epidemic investigation officers and police personnel, identified 19 paper-traced cases and 158 GIS-traced cases from 5,692 confirmed cases in Seoul during the study period (June to July 2021). Our findings suggest that collaboration with law enforcement agencies and the use of overlaid satellite imagery in outbreak investigations enhances high vigilance and reduces the risk of potential breaches of human rights in the process.

New framework to assess tracing and testing based on South Korea's response to COVID-19.

South Korea's remarkable success in controlling the spread of COVID-19 during the pre-Omicron period was based on extensive contact tracing and large-scale testing. Here we suggest a general criterion for tracing and testing based on South Korea's experience, and propose a new framework to assess tracing and testing. We reviewed papers on South Korea's response to COVID-19 to capture its concept of tracing and testing. South Korea expanded its testing capabilities to enable group tracing combined with preemptive testing, and to conduct open testing. According to our proposed model, COVID-19 cases are classified into 4 types: confirmed in quarantine, source known, source unknown, and unidentified. The proportion of the first two case types among confirmed cases is defined as "traced proportion", and used as the indicator of tracing and testing effectiveness. In conclusion, South Korea successfully suppressed COVID-19 transmission by maintaining a high traced proportion (> 60%) using group tracing in conjunction with preemptive testing as a complementary strategy to traditional contact tracing.

Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic.

BACKGROUND: The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19. METHODS: We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established. RESULTS: The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28. CONCLUSIONS: We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.

A qualitative study exploring approaches, barriers, and facilitators of the HIV partner notification program in Kerman, Iran.

BACKGROUND: HIV partner notification services can help people living with HIV (PLHIV) to identify, locate, and inform their sexual and injecting partners who are exposed to HIV and refer them for proper and timely counseling and testing. To what extent these services were used by PLHIV and what are the related barriers and facilitators in southeast Iran are not known. So, this study aimed to explore HIV notification and its barriers and facilitators among PLHIV in Iran. METHODS: In this qualitative study, the number of 23 participants were recruited from November 2022 to February 2023 including PLHIV (N = 12), sexual partners of PLHIV (N = 5), and staff members (N = 6) of a Voluntary Counseling and Testing (VCT) center in Kerman located in the southeast of Iran. Our data collection included purposive sampling to increase variation. The content analysis was conducted using the Graneheim and Lundman approach. The analysis yielded 221 (out of 322) related codes related to HIV notification, its barriers, and its facilitators. These codes were further categorized into one main category with three categories and nine sub-categories. RESULTS: The main category was HIV notification approaches, HIV notification barriers, and facilitators. HIV notification approaches were notification through clear, and direct conversation, notification through gradual preparation and reassurance, notification due to being with PLHIV, notification through suspicious talking of the physician, and notification due to the behavior of others. Also, the barriers were classified into individual, social, and environmental, and healthcare system barriers and the facilitators were at PLHIV, healthcare staff, and community levels. Stigma was a barrier mentioned by most participants. Also, the main facilitator of HIV notification was social support, especially from the family side. CONCLUSIONS: The findings highlighted the multidimensionality of HIV notification emphasizing the importance of tailored support and education to enhance the notification process for PLHIV and their networks. Also, our results show that despite all the efforts to reduce stigma and discrimination in recent years, stigma still exists as a main obstacle to disclosing HIV status and other barriers are the product of stigma. It seems that all programs should be directed towards destigmatization.

Examining the feasibility of assisted index case testing for HIV case-finding: a qualitative analysis of barriers and facilitators to implementation in Malawi.

BACKGROUND: Assisted index case testing (ICT), in which health care workers take an active role in referring at-risk contacts of people living with HIV for HIV testing services, has been widely recognized as an evidence-based intervention with high potential to increase status awareness in people living with HIV. While the available evidence from eastern and southern Africa suggests that assisted ICT can be an effective, efficient, cost-effective, acceptable, and low-risk strategy to implement in the region, it reveals that feasibility barriers to implementation exist. This study aims to inform the design of implementation strategies to mitigate these feasibility barriers by examining "assisting" health care workers' experiences of how barriers manifest throughout the assisted ICT process, as well as their perceptions of potential opportunities to facilitate feasibility. METHODS: In-depth interviews were conducted with 26 lay health care workers delivering assisted ICT in Malawian health facilities. Interviews explored health care workers' experiences counseling index clients and tracing these clients' contacts, aiming to inform development of a blended learning implementation package. Transcripts were inductively analyzed using Dedoose coding software to identify and describe key factors influencing feasibility of assisted ICT. Analysis included multiple rounds of coding and iteration with the data collection team. RESULTS: Participants reported a variety of barriers to feasibility of assisted index case testing implementation, including sensitivities around discussing ICT with clients, privacy concerns, limited time for assisted index case testing amid high workloads, poor quality contact information, and logistical obstacles to tracing. Participants also reported several health care worker characteristics that facilitate feasibility (knowledge, interpersonal skills, non-stigmatizing attitudes and behaviors, and a sense of purpose), as well as identified process improvements with the potential to mitigate barriers. CONCLUSIONS: Maximizing assisted ICT's potential to increase status awareness in people living with HIV requires equipping health care workers with effective training and support to address and overcome the many feasibility barriers that they face in implementation. Findings demonstrate the need for, as well as inform the development of, implementation strategies to mitigate barriers and promote facilitators to feasibility of assisted ICT. TRIAL REGISTRATION: NCT05343390. Date of registration: April 25, 2022.