scholarly journals Contextual Contact Tracing based on Stochastic Compartment Modeling and Spatial Risk Assessment

Author(s):  
Mateen Mahmood ◽  
Jorge Mateu ◽  
Enrique Hernández Orallo

Abstract The current situation of COVID-19 highlights the paramount importance of infectious disease surveillance, which necessitates early monitoring for effective response. Policymakers are interested in data insights identifying high-risk areas as well as individuals to be quarantined, especially as the public gets back to their normal routine. We investigate both requirements by the implementation of disease outbreak modeling and exploring its induced dynamic spatial risk in form of risk assessment, along with its real-time integration back into the disease model. This paper implements a contact tracing-based stochastic compartment model as a baseline, to further modify the existing setup to include the spatial risk. This modification of each individual-level contact's intensity to be dependent on its spatial location has been termed as Contextual Contact Tracing. The results highlight that the inclusion of spatial context tends to send more individuals into quarantine which reduces the overall spread of infection. With a simulated example of an induced spatial high-risk, it is highlighted that the new spatio-SIR model can act as a tool to empower the analyst with a capability to explore disease dynamics from a spatial perspective. We conclude that the proposed spatio-SIR tool can be of great help for policymakers to know the consequences of their decision prior to their implementation.

2018 ◽  
Vol 7 (9) ◽  
pp. 354 ◽  
Author(s):  
Xun Zhang ◽  
Min Jin ◽  
Jingying Fu ◽  
Mengmeng Hao ◽  
Chongchong Yu ◽  
...  

Terrorism has wreaked havoc on today’s society and people. The discovery of the regularity of terrorist attacks is of great significance to the global counterterrorism strategy. In this study, we improve the traditional location recommendation algorithm coupled with multi-source factors and spatial characteristics. We used the data of terrorist attacks in Southeast Asia from 1970 to 2016, and comprehensively considered 17 influencing factors, including socioeconomic and natural resource factors. The improved recommendation algorithm is used to build a spatial risk assessment model of terrorist attacks, and the effectiveness is tested. The model trained in this study is tested with precision, recall, and F-Measure. The results show that, when the threshold is 0.4, the precision is as high as 88%, and the F-Measure is the highest. We assess the spatial risk of the terrorist attacks in Southeast Asia through experiments. It can be seen that the southernmost part of the Indochina peninsula and the Philippines are high-risk areas and that the medium-risk and high-risk areas are mainly distributed in the coastal areas. Therefore, future anti-terrorism measures should pay more attention to these areas.


2020 ◽  
Vol 148 ◽  
Author(s):  
Lucy Li ◽  
Daniella Ross ◽  
Katherine Hill ◽  
Sarah Clifford ◽  
Louise Wellington ◽  
...  

Abstract We report two cases of respiratory toxigenic Corynebacterium diphtheriae infection in fully vaccinated UK born adults following travel to Tunisia in October 2019. Both patients were successfully treated with antibiotics and neither received diphtheria antitoxin. Contact tracing was performed following a risk assessment but no additional cases were identified. This report highlights the importance of maintaining a high index of suspicion for re-emerging infections in patients with a history of travel to high-risk areas outside Europe.


2021 ◽  
Vol 7 (3) ◽  
pp. e001127
Author(s):  
Patrick G Robinson ◽  
Andrew Murray ◽  
Volker Sheer ◽  
Graeme Close ◽  
Denis F Kinane

ObjectivesThe aim of this study was to assess whether a risk assessment and managed risk approach to contact tracing was practical and feasible at the Gran Canaria Lopesan Open 2021 and could inform further pilot work regarding disease transmission during elite sporting events.MethodsThis prospective cohort study included all international attendees. All participants required a minimum of one negative reverse transcriptase PCR (RT-PCR) test prior to travelling to each tournament. High-risk contacts were isolated for 10 days. Moderate-risk contacts received education regarding enhanced medical surveillance, had daily rapid antigen testing for 5 days, with RT-PCR day 5, mandated mask use and access to outside space for work purposes only. Low-risk contacts received rapid antigen testing every 48 hours and PCR testing on day 5.ResultsA total of 550 persons were accredited and were required to undergo RT-PCR testing before the event. Two of these tests were positive (0.36%). Of these, case 1 had 1 high, 23 moderate and 48 low-risk contacts. Case 2 did not have any significant travel history within 2 days of positive test and had one high-risk contact. There were no further positive tests on site in the wider cohort of attendees, from a total of 872 RT-PCR and 198 rapid antigen tests.ConclusionsThis pilot study showed it is practical, feasible and well accepted to provide enhanced (daily) virus testing and risk-mitigating measures at a professional golf event. Further study is required to assess the efficacy of these interventions; however, no transmission was found in this pilot study.


Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 685 ◽  
Author(s):  
Peng Hou ◽  
Xiaojian Yi ◽  
Haiping Dong

The identification of high risk regions is an important aim of risk-based inspections (RBIs) in pipeline networks. As the most vital part of risk-based inspections, risk assessment makes a significant contribution to achieving this aim. Accurate assessment can target high risk inspected regions so that limited resources can mitigate considerable risks in the face of increased spatial distribution of a pipeline network. However, the existing approaches for risk assessment face grave challenges due to a lack of sufficient data and an assessment’s vulnerability to human biases and errors. This paper attempts to tackle those challenges through spatial statistics, which is used to estimate the uncertainty of risk based on a dataset of locations of pipeline network failure events without having to acquire additional data. The consequence of risk in each inspected region is measured by the total cost caused by the failure events that have occurred in the region, which is also calculated in the assessment. Then, the risks of the different inspected regions are obtained by integrating the uncertainty and consequences. Finally, the feasibility of our approach is validated in a case study. Our results in the case study demonstrate that uncertainty is less instructive for prioritizing pipeline inspections than the consequences of risk due to the low significant difference in risk uncertainty in different regions. Our results also have implications for understanding the correlation between the spatial location and consequences of risk.


2021 ◽  
Author(s):  
Merlin Moni ◽  
Kiran G Kulirankal ◽  
Preetha Prasanna ◽  
Ann Mary ◽  
Elizabeth Mary Thomas ◽  
...  

AbstractBackgroundThe high exposure risk to COVID among frontline heathcare workers was a major challenge to healthcare systems across the globe that warranted close monitoring through risk assessment and contact tracing strategies. The objective of our study was to characterize exposure risk factors for transmission and subsequent COVID positivity among the frontlinehealthcare workers in our institution during the pandemic period.MethodsThe retrospective observational study conducted over a period of 6 months from June 2020 to November 2020 at a 1300-bedded South Indian tertiary care centre included frontline healthcare workers who were assessed for their identified encounter with COVID positive individual using a modified WHO COVID risk assessment tool. Additional risk attributes of exposure characterized among COVID positive healthcare workers comprised of shared space, cluster related transmissions and multiple instances of exposure to COVID.ResultsAmong a total of 4744 contacts with COVID positive individuals assessed for risk stratification during the study period, 942 (19.8%) were high risk and 3802 (80.2%) were low risk exposures respectively. 106 (2.2%) turned COVID positive during the surveillance period of 14 days. Frontline workers working in COVID areas had significant low COVID rates as compared to other areas (N=1, 0.9%). The average monthly COVID positivity rates being 1.66%, the attack rates among high risk and low risk contacts among the total HCWs screened were 5% (46/942) and 1.57% (60/3802) respectively. Shared space (70%) and IPC breaches (66%) were found to be highly prevalent in the COVID positive cohort, along with maskless encounters (43%) and multiple exposure (39%). The attack rate among the 6 identified COVID cluster groups (5.5%) were found to be higher than the attack rate (2.2%) noted among the total contacts screened and no significant association was observed between risk categories in the clusters.DiscussionOur study highlights higher risk of COVID positivity among high risk contacts as compared to low risk contacts. However, the high COVID positivity rate in low risk group among cluster transmissions and its lack of association with risk assessment highlight the suboptimal utility of the risk assessment strategy among cluster groups.


2020 ◽  
Vol 89 ◽  
pp. 8-19
Author(s):  
V. A. Minaev ◽  
◽  
N. G. Topolsky ◽  
A. O. Faddeev ◽  
R. O. Stepanov ◽  
...  

Introduction. The complex combination of natural and technogenic factors that lead to dangerous threats to the health and life of the population, as well as to material values, creates a need to develop special mathematical models for risk assessment in the relevant territories. Herewith it is important to take into account the significant differences between these factors. The new areas of research are models that describe natural and technogenic risks using differential equations that reflect different types of functions. The article presents the development of this research area. Goals and objectives. The goal of the article is to create a model for risk assessment in natural and technical systems (PTS), based on taking into account the influences of different natural and technogenic factors on them. Objectives include justification, construction and practical implementation of the mathematical model of risk assessment in the form of differential equations system. Methods include interpretation of the considered influences on PTS in terms of risks and assessment of the dynamic interaction of natural and technogenic factors in the form of inhomogeneous differential equations. Results and discussion. Solutions for models of assessing complex natural and technogenic risks in relation to two cases that differ in NTS are found: functionally different external natural and technogenic influences on PTS, which are understood as their type, in which the effects of both natural and technogenic factors are described by different mathematical functions. Conclusions. The first model considers parabolic (reflecting threats whose intensity gradually decreases with distance from the epicenter) and linear types of influences (reflecting sudden threats). The second model considers parabolic and hyperbolic (reflecting threats, the intensity of which decreases sharply over time) types of influences. It is concluded that it is necessary to create a special computer album of complex influences on the PTS in order to prevent "replay" of various situations and develop the most effective response to emerging dangers from the EMERCOM units and other structures. Key words: model, assessment, natural and technogenic risks, functionally different influences, counteraction, EMERCOM units.


Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Silvana Mirella Aliberti ◽  
Francesco De Caro ◽  
Giovanni Boccia ◽  
Rosario Caruso ◽  
Mario Capunzo

: Italy was the first western nation affected by the pandemic and was observed as a pilot case in the management of the new coronavirus epidemic. The outbreak of COVID-19 disease has been very difficult in Italy, on June 25, 2020 there are 239,821 total cases of which 33,592 deaths nationwide. Three lessons emerged from this experience that can serve as a blueprint to improve future plans for the outbreak of viruses. First, early reports on the spread of COVID-19 can help inform public health officials and medical practitioners in effort to combat its progression; second, inadequate risk assessment related to the urgency of the situation and limited reporting to the virus has led the rapid spread of COVID-19; third, an effective response to the virus had to be undertaken with coherent system of actions and simultaneously.


2021 ◽  
Vol 11 (12) ◽  
pp. 5367
Author(s):  
Amirarsalan Rajabi ◽  
Alexander V. Mantzaris ◽  
Ece C. Mutlu ◽  
Ozlem O. Garibay

Governments, policy makers, and officials around the globe are working to mitigate the effects of the COVID-19 pandemic by making decisions that strive to save the most lives and impose the least economic costs. Making these decisions require comprehensive understanding of the dynamics by which the disease spreads. In traditional epidemiological models, individuals do not adapt their contact behavior during an epidemic, yet adaptive behavior is well documented (i.e., fear-induced social distancing). In this work we revisit Epstein’s “coupled contagion dynamics of fear and disease” model in order to extend and adapt it to explore fear-driven behavioral adaptations and their impact on efforts to combat the COVID-19 pandemic. The inclusion of contact behavior adaptation endows the resulting model with a rich dynamics that under certain conditions reproduce endogenously multiple waves of infection. We show that the model provides an appropriate test bed for different containment strategies such as: testing with contact tracing and travel restrictions. The results show that while both strategies could result in flattening the epidemic curve and a significant reduction of the maximum number of infected individuals; testing should be applied along with tracing previous contacts of the tested individuals to be effective. The results show how the curve is flattened with testing partnered with contact tracing, and the imposition of travel restrictions.


2021 ◽  
Vol 13 (2) ◽  
pp. 826
Author(s):  
Meiling Zhou ◽  
Xiuli Feng ◽  
Kaikai Liu ◽  
Chi Zhang ◽  
Lijian Xie ◽  
...  

Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.


Sign in / Sign up

Export Citation Format

Share Document