Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 871
Filter
1.
J Virol Methods ; : 114648, 2022 Nov 08.
Article in English | MEDLINE | ID: covidwho-2105515

ABSTRACT

In 2020, the novel coronavirus, SARS-CoV-2, caused a pandemic, which is still raging at the time of writing this. Here, we present results from SpikeSeq, the first published Sanger sequencing-based method for the detection of Variants of Concern (VOC) and key mutations, using a 1kb amplicon from the recognized ARTIC Network primers. The proposed setup relies entirely on materials and methods already in use in diagnostic RT-qPCR labs and on existing commercial infrastructure offering sequencing services. For data analysis, we provide an automated, open source, and browser-based mutation calling software (https://github.com/kblin/covid-spike-classification, https://ssi.biolib.com/covid-spike-classification). We validated the setup on 195 SARS-CoV-2 positive samples, and we were able to profile 85% of RT-qPCR positive samples, where the last 15% largely stemmed from samples with low viral count. We compared the SpikeSeq results to WGS results. SpikeSeq has been used as the primary variant identification tool on >10.000 SARS-CoV-2 positive clinical samples during 2021. At approximately 4€ per sample in material cost, minimal hands-on time, little data handling, and a short turnaround time, the setup is simple enough to be implemented in any SARS-CoV-2 RT-qPCR diagnostic lab. Our protocol provides results that can be used to choose antibodies in a clinical setting and for the tracking and surveillance of all positive samples for new variants and known ones such as Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) Delta (B.1.617.2), Omicron BA.1(B.1.1.529), BA.2, BA.4/5, BA.2.75.x, and many more, as of October 2022.

2.
Behaviour & Information Technology ; JOUR: 1-16,
Article in English | Academic Search Complete | ID: covidwho-2106756

ABSTRACT

This study aims to identify the critical factors influencing the user experience of contact tracing apps and the sentiments around them. For this purpose, we used Google play reviews of Aarogya Setu, a contact tracing app developed in India. First, we establish the relationship between review sentiment and review rating using regression between sentiment polarity and review rating. Then, we used a hybrid aspect-based sentiment analysis approach that uses unsupervised linguistic techniques to determine statistically significant concepts present in the review texts and cluster them into representative aspects that were then tagged under human supervision. Finally, supervised deep learning methods were applied for exhaustive extraction of the aspects and associated sentiments from the reviews. The final exercise of determining the key influencing factors was done by grouping these aspects under factors identified by marketing experts. A total of nine factors were identified, with the usefulness of the app being the most important factor. The findings of this study are essential for the development team and government to improve the application and increase adoption. [ FROM AUTHOR]

3.
eClinicalMedicine ; JOUR:101726, 55.
Article in English | ScienceDirect | ID: covidwho-2104825

ABSTRACT

Summary Background Case investigation and contact tracing (CICT) is an important tool for communicable disease control, both to proactively interrupt chains of transmission and to collect information for situational awareness. We run the first randomized trial of COVID-19 CICT to investigate the utility of manual (i.e., call-based) vs. automated (i.e., survey-based) CICT for pandemic surveillance. Methods Between December 15, 2021 and February 5, 2022, a stepped wedge cluster randomized trial was run in which Santa Clara County ZIP Codes progressively transitioned from manual to automated CICT. Eleven individual-level data fields on demographics and disease dynamics were observed for non-response. The data contains 106,522 positive cases across 29 ZIP Codes. Findings Automated CICT reduced overall collected information by 29 percentage points (SE = 0.08, p < 0.01), as well as the response rate for individual fields. However, we find no evidence of differences in information loss by race or ethnicity. Interpretations Automated CICT can serve as a useful alternative to manual CICT, with no substantial evidence of skewing data along racial or ethnic lines, but manual CICT improves completeness of key data for monitoring epidemiologic patterns. Funding This research was supported in part by the Stanford Office of Community Engagement and the Stanford Institute for Human-Centered Artificial Intelligence.

4.
Euro Surveill ; 27(43)2022 Oct.
Article in English | MEDLINE | ID: covidwho-2099047

ABSTRACT

BackgroundTracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective.AimWe demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters.MethodsGenomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021.ResultsCluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, sampled mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June; 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf.ConclusionIGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.


Subject(s)
COVID-19 , Communicable Diseases, Imported , Humans , SARS-CoV-2/genetics , Travel , Communicable Diseases, Imported/epidemiology , COVID-19/epidemiology , Phylogeny , Contact Tracing , Germany/epidemiology , Genomics
5.
J Med Internet Res ; 24(10): e40558, 2022 10 14.
Article in English | MEDLINE | ID: covidwho-2099001

ABSTRACT

BACKGROUND: Digital contact tracing (DCT) apps have been implemented as a response to the COVID-19 pandemic. Research has focused on understanding acceptance and adoption of these apps, but more work is needed to understand the factors that may contribute to their sustained use. This is key to public health because DCT apps require a high uptake rate to decrease the transmission of the virus within the general population. OBJECTIVE: This study aimed to understand changes in the use of the National Health Service Test & Trace (T&T) COVID-19 DCT app and explore how public trust in the app evolved over a 1-year period. METHODS: We conducted a longitudinal mixed methods study consisting of a digital survey in December 2020 followed by another digital survey and interview in November 2021, in which responses from 9 participants were explored in detail. Thematic analysis was used to analyze the interview transcripts. This paper focuses on the thematic analysis to unpack the reasoning behind participants' answers. RESULTS: In this paper, 5 themes generated through thematic analysis are discussed: flaws in the T&T app, usefulness and functionality affecting trust in the app, low trust in the UK government, varying degrees of trust in other stakeholders, and public consciousness and compliance dropping over time. Mistrust evolved from participants experiencing sociotechnical flaws in the app and led to concerns about the app's usefulness. Similarly, mistrust in the government was linked to perceived poor pandemic handling and the creation and procurement of the app. However, more variability in trust in other stakeholders was highlighted depending on perceived competence and intentions. For example, Big Tech companies (ie, Apple and Google), large hospitality venues, and private contractors were seen as more capable, but participants mistrust their intentions, and small hospitality venues, local councils, and the National Health Service (ie, public health system) were seen as well-intentioned but there is mistrust in their ability to handle pandemic matters. Participants reported complying, or not, with T&T and pandemic guidance to different degrees but, overall, observed a drop in compliance over time. CONCLUSIONS: These findings contribute to the wider implications of changes in DCT app use over time for public health. Findings suggest that trust in the wider T&T app ecosystem could be linked to changes in the use of the app; however, further empirical and theoretical work needs to be done to generalize the results because of the small, homogeneous sample. Initial novelty effects occurred with the app, which lessened over time as public concern and media representation of the pandemic decreased and normalization occurred. Trust in the sociotechnical capabilities of the app, stakeholders involved, and salience maintenance of the T&T app in conjunction with other measures are needed for sustained use.


Subject(s)
COVID-19 , Mobile Applications , COVID-19/prevention & control , Contact Tracing/methods , Ecosystem , Humans , Pandemics/prevention & control , State Medicine , Trust , United Kingdom
6.
Public Health Rep ; : 333549221131372, 2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2098161

ABSTRACT

OBJECTIVES: We evaluated 2 innovative approaches that supported COVID-19 case investigation and contact tracing (CI/CT) in Chicago communities: (1) early engagement of people diagnosed with COVID-19 by leveraging the existing Healthcare Alert Network to send automated telephone calls and text messages and (2) establishment of a network of on-site case investigators and contact tracers within partner health care facilities (HCFs) and community-based organizations (CBOs). METHODS: The Chicago Department of Public Health used Healthcare Alert Network data to calculate the proportion of people with confirmed COVID-19 who successfully received an automated telephone call or text message during December 27, 2020-April 24, 2021. The department also used CI/CT data to calculate the proportion of cases successfully interviewed and named contacts successfully notified, as well as the time to successful case interview and to successful contact notification. RESULTS: Of 67 882 people with COVID-19, 94.3% (n = 64 011) received an automated telephone call and 91.7% (n = 62 239) received a text message. Of the 65 470 COVID-19 cases pulled from CI/CT data, 24 450 (37.3%) interviews were completed, including 6212 (61.3%) of the 10 126 cases diagnosed in HCFs. The median time from testing to successful case interview was 3 days for Chicago Department of Public Health investigators and 4 days for HCF investigators. Overall, 34 083 contacts were named; 13 117 (38.5%) were successfully notified, including 9068 (36.6%) of the 24 761 contacts assigned to CBOs. The median time from contact elicitation to completed notification by CBOs was <24 hours. CONCLUSIONS: Partnerships with HCFs and CBOs helped deliver timely CI/CT during the COVID-19 pandemic, suggesting a potential benefit of engaging non-public health institutions in CI/CT for existing and emerging diseases.

7.
Public Health Rep ; : 333549221129354, 2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2098160

ABSTRACT

OBJECTIVES: Toward common methods for system monitoring and evaluation, we proposed a key performance indicator framework and discussed lessons learned while implementing a statewide exposure notification (EN) system in California during the COVID-19 epidemic. MATERIALS AND METHODS: California deployed the Google Apple Exposure Notification framework, branded CA Notify, on December 10, 2020, to supplement traditional COVID-19 contact tracing programs. For system evaluation, we defined 6 key performance indicators: adoption, retention, sharing of unique codes, identification of potential contacts, behavior change, and impact. We aggregated and analyzed data from December 10, 2020, to July 1, 2021, in compliance with the CA Notify privacy policy. RESULTS: We estimated CA Notify adoption at nearly 11 million smartphone activations during the study period. Among 1 654 201 CA Notify users who received a positive test result for SARS-CoV-2, 446 634 (27%) shared their unique code, leading to ENs for other CA Notify users who were in close proximity to the SARS-CoV-2-positive individual. We identified at least 122 970 CA Notify users as contacts through this process. Contact identification occurred a median of 4 days after symptom onset or specimen collection date of the user who received a positive test result for SARS-CoV-2. PRACTICE IMPLICATIONS: Smartphone-based EN systems are promising new tools to supplement traditional contact tracing and public health interventions, particularly when efficient scaling is not feasible for other approaches. Methods to collect and interpret appropriate measures of system performance must be refined while maintaining trust and privacy.

8.
JMIR Public Health Surveill ; 8(10): e40233, 2022 Oct 27.
Article in English | MEDLINE | ID: covidwho-2089642

ABSTRACT

BACKGROUND: In the post-COVID-19 pandemic era, many countries have launched apps to trace contacts of COVID-19 infections. Each contact-tracing app (CTA) faces a variety of issues owing to different national policies or technologies for tracing contacts. OBJECTIVE: In this study, we aimed to investigate all the CTAs used to trace contacts in various countries worldwide, including the technology used by each CTA, the availability of knowledge about the CTA from official websites, the interoperability of CTAs in various countries, and the infection detection rates and policies of the specific country that launched the CTA, and to summarize the current problems of the apps based on the information collected. METHODS: We investigated CTAs launched in all countries through Google, Google Scholar, and PubMed. We experimented with all apps that could be installed and compiled information about apps that could not be installed or used by consulting official websites and previous literature. We compared the information collected by us on CTAs with relevant previous literature to understand and analyze the data. RESULTS: After screening 166 COVID-19 apps developed in 197 countries worldwide, we selected 98 (59%) apps from 95 (48.2%) countries, of which 63 (66.3%) apps were usable. The methods of contact tracing are divided into 3 main categories: Bluetooth, geolocation, and QR codes. At the technical level, CTAs face 3 major problems. First, the distance and time for Bluetooth- and geolocation-based CTAs to record contact are generally set to 2 meters and 15 minutes; however, this distance should be lengthened, and the time should be shortened for more infectious variants. Second, Bluetooth- or geolocation-based CTAs also face the problem of lack of accuracy. For example, individuals in 2 adjacent vehicles during traffic jams may be at a distance of ≤2 meters to make the CTA trace contact, but the 2 users may actually be separated by car doors, which could prevent transmission and infection. In addition, we investigated infection detection rates in 33 countries, 16 (48.5%) of which had significantly low infection detection rates, wherein CTAs could have lacked effectiveness in reducing virus propagation. Regarding policy, CTAs in most countries can only be used in their own countries and lack interoperability among other countries. In addition, 7 countries have already discontinued CTAs, but we believe that it was too early to discontinue them. Regarding user acceptance, 28.6% (28/98) of CTAs had no official source of information that could reduce user acceptance. CONCLUSIONS: We surveyed all CTAs worldwide, identified their technological policy and acceptance issues, and provided solutions for each of the issues we identified. This study aimed to provide useful guidance and suggestions for updating the existing CTAs and the subsequent development of new CTAs.


Subject(s)
COVID-19 , Mobile Applications , Humans , Contact Tracing/methods , Pandemics/prevention & control , Policy
9.
Eur Heart J Case Rep ; 6(10): ytac404, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2087760

ABSTRACT

Background: COVID-19 has affected individuals across the globe, and those with cardiac implantable electronic devices (CIEDs) likely represent a high-risk group. These devices can be interrogated to reveal information about the patient activity, heart rate parameters, and respiratory rate. Case summary: Four patients with CIEDs and left ventricular dysfunction were admitted to a single institution for COVID-19 infection. Each patient survived hospitalization, and none required intensive care. Retrospectively, CIED interrogation revealed each patient had decreased activity level prior to their reporting COVID-19 symptoms. Similarly, respiratory rate increased before symptom onset for three of the patients, while one did not have these data available. Of the three patients with heart rate variability (HRV) available, two had decreased HRV before they developed symptoms. After hospital discharge, these parameters returned to their baseline. Discussion: This case series suggests physiologic changes identifiable through interrogation of CIEDs may occur prior to the reported onset of COVID-19 symptoms. These data may provide objective evidence on which to base more sensitive assessments of infectious risk when performing contact tracing in communities.

10.
Inf Sci (N Y) ; 617: 103-132, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2086320

ABSTRACT

Digital contact tracing (DCT) is one of the weapons to be used against the COVID-19 pandemic, especially in a post-lockdown phase, to prevent or block foci of infection. As DCT systems can handle highly private information about people, great care must be taken to prevent misuse of the system and actions detrimental to people's privacy, up to mass surveillance. This paper presents a new centralized DCT protocol, called ZE2-P3T (Zero Ephemeral Exchanging Privacy-Preserving Proximity Protocol), which relies on smartphone localization but does not give any information about the user's location and identity to the server. Importantly, the fact that no exchange of ephemeral identities among users is required is the basis of the strong security of the protocol, which is proven to be more secure than the state-of-the-art protocol DP-3T/GAEN.

11.
J Med Virol ; : e28248, 2022 Oct 21.
Article in English | MEDLINE | ID: covidwho-2085071

ABSTRACT

With increased transmissibility and novel transmission mode, monkeypox poses new threats to public health globally in the background of the ongoing COVID-19 pandemic. Estimates of the serial interval, a key epidemiological parameter of infectious disease transmission, could provide insights into the virus transmission risks. As of October 2022, little was known about the serial interval of monkeypox due to the lack of contact tracing data. In this study, public-available contact tracing data of global monkeypox cases were collected and 21 infector-infectee transmission pairs were identified. We proposed a statistical method applied to real-world observations to estimate the serial interval of the monkeypox. We estimated a mean serial interval of 5.6 days with the right truncation and sampling bias adjusted and calculated the reproduction number of 1.33 for the early monkeypox outbreaks at a global scale. Our findings provided a preliminary understanding of the transmission potentials of the current situation of monkeypox outbreaks. We highlighted the need for continuous surveillance of monkeypox for transmission risk assessment.

12.
Proceedings of the Association for Information Science and Technology ; JOUR(1):845-847, 59.
Article in English | Scopus | ID: covidwho-2085201

ABSTRACT

The study explores the use of COVID-19 related apps for contact tracing deployed in New York State (NYS). The project seeks to understand potential differences in perception, adoption, or privacy concerns among racial and ethnic populations and across age groups. Using the Antecedent-Privacy Concerns-Outcomes (APCO) framework and the perceived usefulness construct, this study explores factors influencing the individual level adoption of these apps. Data collected from 120 Amazon Mechanical Turkers located in NYS was analyzed. The results indicate that race and gender are important factors to consider in expanding the Antecedent-Privacy Concerns-Outcomes (APCO) framework. Specifically, race impacted the perception of the seriousness of the pandemic, with Asians and Black being serious about the pandemic. Age played a role in privacy and security concerns. The youngest group of respondents, aged 18–24, did not have many privacy and security concerns about mobile apps. These results provided empirical results and evidence that can contribute to the expansion of the APCO model and help further the model's development. 85th Annual Meeting of the Association for Information Science & Technology ;Oct. 29 – Nov. 1, 2022 ;Pittsburgh, PA. Author(s) retain copyright, but ASIS&T receives an exclusive publication license.

13.
Applied Mathematics and Computation ; JOUR:127601, 439.
Article in English | ScienceDirect | ID: covidwho-2082768

ABSTRACT

In the situation of insufficient vaccines and rapid mutation of the virus, detection and contact tracing have been argued to be effective interventions in the containment of emergent epidemics. However, most of previous studies are devoted to data-driven, leading to insufficient understanding of quantifying their effectiveness, especially when individuals’ interactions evolve with time. Here, we aim at quantifying the effectiveness of detection and contact tracing interventions in suppressing the epidemic in time-varying networks. We propose the Susceptible-Exposed-Infected-Removed-Dead-Hospitalized (SEIRDH) model with detection and contact tracing. Under the framework of time-varying networks and with a mean-field approach, we analyze the epidemic thresholds under different situations. Experimental results show that detection can effectively suppress the epidemic spread with an increased epidemic threshold, while the role of tracing depends on the characteristics of the epidemic. When an epidemic is infectious in the incubation period, contact tracing has an obvious effect in suppressing the epidemic spread, but not when the epidemic is not infectious in the incubation. Thus, we apply this framework in real networks to explore possible contact tracing measures by taking use of individuals’ properties. We find that contact tracing based on activity and historical information is more efficient than random contact tracing. Moreover, individuals’ attractiveness and aging effects also affect the efficiency of detection and contact tracing. In conclusion, making full use of individuals’ properties can remarkably improve the effectiveness of detection and contact tracing. The proposed method is expected to provide theoretical guidance for coping with the COVID-19 or other emergent epidemics.

14.
Non-conventional in Russian | WHOIRIS, Grey literature | ID: grc-754839

ABSTRACT

Отслеживание контактов стало краеугольным камнем ответа стран на пандемию COVID-19 и остается одной из ключевых стратегий по прерыванию цепочек распространения SARS-CoV-2 и снижению заболеваемости и смертности, связанной с COVID-19. Хотя пандемия еще не закончилась, многие страны переходят к более устойчивому и комплексному подходу к реагированию на COVID-19. Системы отслеживания контактов приспосабливаются к новым условиям;при этом, чтобы учесть произошедшие изменения в долгосрочной перспективе, адаптацию необходимо углубить. Описанное совещание по отслеживанию контактов в связи с COVID-19 совместно организовано ЕРБ ВОЗ и ECDC и проведено 1 марта 2022 г. В совещании участвовали специалисты по отслеживанию контактов в связи с COVID-19 из 39 стран и территорий Европейского региона ВОЗ, в том числе 24 стран Европейского союза/ Европейской экономической зоны (ЕЭЗ). Полный перечень стран-участниц приведен в приложении 1. Основное внимание уделялось двум ключевым темам: 1) опыт, сложности и решения, относящиеся к отслеживанию контактов в связи с COVID-19;2) как лучше интегрировать отслеживание контактов в процесс укрепления систем здравоохранения и планирование мер по обеспечению готовности к пандемиям. Для того чтобы все страны могли активно поучаствовать в обсуждении вышеуказанных тем, организовано два сеанса работы в отдельных группах.

15.
SSRN;
Preprint in English | SSRN | ID: ppcovidwho-346217

ABSTRACT

In the early days of the COVID-19 pandemic, a multitude of mobile apps were deployed to complement manual contact tracing, quarantine and isolation efforts by central, state and local authorities in India. This was the first time that digital tools were used to augment disease surveillance efforts on a large scale. At the time of deployment and even today, these mobile apps remain experimental tools with no conclusive evidence of their effectiveness, but with known risks to privacy and data security. The public discourse examining these mobile apps has also raised several privacy and data security concerns. We add to this literature through an examination of COVID-19 mobile apps deployed by state governments and local authorities, using public health perspectives on infectious disease surveillance. We develop a framework of analysis that factors state capacity concerns, public engagement, processes and methods that facilitate continuous effectiveness evaluation, and privacy and ethical concerns. We then examine COVID-19 mobile apps against this framework of analysis. Our analysis highlights several instances of duplication due to lack of coordination amongst various stakeholders engaged in COVID-19 disease surveillance;absence of any oversight and public engagement in the development and deployment processes;mixed evidence on the integration of COVID-19 mobile apps with public health protocols, a prerequisite for conducting any effectiveness evaluation;and, weak data protection. Our findings underscore the need for a systems level approach to deploying digital disease surveillance tools, particularly the need for integrating effectiveness evaluations in the implementation process.

16.
JMIR Public Health Surveill ; 8(11): e40977, 2022 Nov 15.
Article in English | MEDLINE | ID: covidwho-2079997

ABSTRACT

BACKGROUND: Contact tracing is an important public health tool for curbing the spread of infectious diseases. Effective and efficient contact tracing involves the rapid identification of individuals with infection and their exposed contacts and ensuring their isolation or quarantine, respectively. Manual contact tracing via telephone call and digital proximity app technology have been key strategies in mitigating the spread of COVID-19. However, many people are not reached for COVID-19 contact tracing due to missing telephone numbers or nonresponse to telephone calls. The New York City COVID-19 Trace program augmented the efforts of telephone-based contact tracers with information gatherers (IGs) to search and obtain telephone numbers or residential addresses, and community engagement specialists (CESs) made home visits to individuals that were not contacted via telephone calls. OBJECTIVE: The aim of this study was to assess the contribution of information gathering and home visits to the yields of COVID-19 contact tracing in New York City. METHODS: IGs looked for phone numbers or addresses when records were missing phone numbers to locate case-patients or contacts. CESs made home visits to case-patients and contacts with no phone numbers or those who were not reached by telephone-based tracers. Contact tracing management software was used to triage and queue assignments for the telephone-based tracers, IGs, and CESs. We measured the outcomes of contact tracing-related tasks performed by the IGs and CESs from July 2020 to June 2021. RESULTS: Of 659,484 cases and 861,566 contact records in the Trace system, 28% (185,485) of cases and 35% (303,550) of contacts were referred to IGs. IGs obtained new phone numbers for 33% (61,804) of case-patients and 11% (31,951) of contacts; 50% (31,019) of the case-patients and 46% (14,604) of the contacts with new phone numbers completed interviews; 25% (167,815) of case-patients and 8% (72,437) of contacts were referred to CESs. CESs attempted 80% (132,781) of case and 69% (49,846) of contact investigations, of which 47% (62,733) and 50% (25,015) respectively, completed interviews. An additional 12,192 contacts were identified following IG investigations and 13,507 following CES interventions. CONCLUSIONS: Gathering new or missing locating information and making home visits increased the number of case-patients and contacts interviewed for contact tracing and resulted in additional contacts. When possible, contact tracing programs should add information gathering and home visiting strategies to increase COVID-19 contact tracing coverage and yields as well as promote equity in the delivery of this public health intervention.


Subject(s)
COVID-19 , Contact Tracing , Humans , Contact Tracing/methods , COVID-19/epidemiology , Quarantine , Telephone , Public Health
17.
Public Health Rep ; : 333549221125891, 2022 Oct 18.
Article in English | MEDLINE | ID: covidwho-2079212

ABSTRACT

OBJECTIVES: We conducted a survey to understand how people's willingness to share information with contact tracers, quarantine after a COVID-19 exposure, or activate and use a smartphone exposure notification (EN) application (app) differed by the person or organization making the request or recommendation. METHODS: We analyzed data from a nationally representative survey with hypothetical scenarios asking participants (N = 2157) to engage in a public health action by health care providers, public health departments, employers, and others. We used Likert scales and ordered logistic regression to compare willingness to take action based on which person or organization made the request, and we summarized findings by race and ethnicity. RESULTS: The highest levels of willingness to engage in contact tracing (adjusted odds ratio [aOR] = 1.74; 95% CI, 1.55-1.96), quarantine (aOR = 1.91; 95% CI, 1.69-2.15), download/activate an EN app (aOR = 1.30; 95% CI, 1.16-1.46), and notify other EN users (aOR = 1.43; 95% CI, 1.27-1.60) were reported when the request came from the participant's personal health care provider rather than from federal public health authorities. When compared with non-Hispanic White participants, non-Hispanic Black participants reported significantly higher levels of willingness to engage in contact tracing (aOR = 1.32; 95% CI, 1.18-1.48), quarantine (aOR = 1.49; 95% CI, 1.37-1.63), download/activate an EN app (aOR = 2.19; 95% CI, 2.01-2.38), and notify other EN users (aOR = 1.63; 95% CI, 1.49-1.79). CONCLUSIONS: Partnering with individuals and organizations perceived as trustworthy may help influence people expressing a lower level of willingness to engage in each activity, while those expressing a higher level of willingness to engage in each activity may benefit from targeted communications.

18.
R Soc Open Sci ; 9(10): 211927, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-2078022

ABSTRACT

Traditional contact tracing tests the direct contacts of those who test positive. But, by the time an infected individual is tested, the infection starting from the person may have infected a chain of individuals. Hence, why should the testing stop at direct contacts, and not test secondary, tertiary contacts or even contacts further down? One deterrent in testing long chains of individuals right away may be that it substantially increases the testing load, or does it? We investigate the costs and benefits of such multi-hop contact tracing for different number of hops. Considering diverse contact networks, we show that the cost-benefit trade-off can be characterized in terms of a single measurable attribute, the initial epidemic growth rate. Once this growth rate crosses a threshold, multi-hop contact tracing substantially reduces the outbreak size compared with traditional tracing. Multi-hop even incurs a lower cost compared with the traditional tracing for a large range of values of the growth rate. The cost-benefit trade-offs can be classified into three phases depending on the value of the growth rate. The need for choosing a larger number of hops becomes greater as the growth rate increases or the environment becomes less conducive toward containing the disease.

19.
J Ambient Intell Humaniz Comput ; : 1-18, 2022 Oct 20.
Article in English | MEDLINE | ID: covidwho-2075694

ABSTRACT

The world we live in has been taken quite surprisingly by the outbreak of a novel virus namely SARS-CoV-2. COVID-19 i.e. the disease associated with the virus, has not only shaken the world economy due to enforced lockdown but has also saturated the public health care systems of even most advanced countries due to its exponential spread. The fight against COVID-19 pandemic will continue until majority of world's population get vaccinated or herd immunity is achieved. Many researchers have exploited the Artificial intelligence (AI) knacks based IoT architecture for early detection and monitoring of potential COVID-19 cases to control the transmission of the virus. However, the main cause of the spread is that people infected with COVID-19 do not show any symptoms and are asymptomatic but can still transmit virus to the masses. Researcher have introduced contact tracing applications to automatically detect contacts that can be infected by the index case. However, these fully automated contact tracing apps have not been accepted due to issues like privacy and cross-app compatibility. In the current study, an IoT based COVID-19 detection and monitoring system with semi-automated and improved contact tracing capability namely COVICT has been presented with application of real-time data of symptoms collected from individuals and contact tracing. The deployment of COVICT, the prediction of infected persons can be made more effective and contaminated areas can be identified to mitigate the further propagation of the virus by imposing Smart Lockdown. The proposed IoT based architecture can be quite helpful for regulatory authorities for policy making to fight COVID-19.

20.
Ieee Access ; 10:103806-103818, 2022.
Article in English | Web of Science | ID: covidwho-2070268

ABSTRACT

Throughout the various containment phases of a pandemic, such as Covid-19, digital tools and services have proven to be essential measures to counteract the ensuing disrupting effects in social and working interactions. In such scenarios, Nausica@DApp, the comprehensive solution proposed in this paper, eases compatibility of the in-presence activities of a campus-based corporation with the organizational constraints posed by the virus during the pandemic, or at a later endemic stage. This is accomplished throughout several intervention areas, such as personnel contact tracing, crowd gathering surveillance, and epidemiological monitoring. These operational requirements, in particular indirect contact tracing and overcrowd monitoring, call for the adoption of an absolute device localization paradigm, which, in the proposed solution, has been devised on top of the campus WiFi infrastructure, proving to be encouragingly accurate in most cases. Absolute localization, on the other hand, entails a certain amount of server-based centralized operations, which might affect the preservation of user data privacy. The novelty of the proposed solution consists in maximizing confidentiality and integrity in the handling of sensitive personal information, in spite of the centralized aspects of the localization system. This is accomplished by decentralizing contact tracing matching operations, which are entirely carried out locally, by apps running on the users' mobile devices. Contact data are pseudonymized and their authenticity is guaranteed by a blockchain. Furthermore, the proposed novel solution improves privacy preservation by eschewing recourse to the Bluetooth app-to-app channel for user data exchange, in fact a typical choice of most current contract tracing solutions. Thanks to a sensible use of the blockchain features, integrated into Nausica@DApp's microservice-based back-end, a higher degree of operation transparency can be relied upon, thus boosting the user's level of trust and enhancing the availability and reliability of data about people gathering within the campus premises. Moreover, contact tracing only requires the mobile device WiFi interface to be on, so that users are neither forced to adopt new habits, nor to grant additional device access permissions to contact tracing apps (potentially undermining their own privacy). The overall system has been analysed in terms of performance and costs, and the experiments have shown that its adoption is viable and effective.

SELECTION OF CITATIONS
SEARCH DETAIL