scholarly journals A survey of core and support activities of communicable disease surveillance systems at operating-level CDCs in China

2010 ◽  
Vol 10 (1) ◽  
Author(s):  
Weiyi Xiong ◽  
Jun Lv ◽  
Liming Li
Keyword(s):  
Disease Surveillance ◽  
Communicable Disease ◽  
Surveillance Systems ◽  
Operating Level

scholarly journals Investigating the Impact of Asymptomatic Carriers on COVID-19 Transmission

2020 ◽  
Author(s):  
Jacob B. Aguilar ◽  
Jeremy Samuel Faust ◽  
Lauren M. Westafer ◽  
Juan B. Gutierrez
Keyword(s):  
Disease Surveillance ◽  
Reproduction Number ◽  
Clinical Symptoms ◽  
Communicable Disease ◽  
Average Rate ◽  
Point Estimate ◽  
Surveillance Systems ◽  
Average Case ◽  
Asymptomatic Carriers ◽  
The Impact

Coronavirus disease 2019 (COVID-19) is a novel human respiratory disease caused by the SARS-CoV-2 virus. Asymptomatic carriers of the virus display no clinical symptoms but are known to be contagious. Recent evidence reveals that this sub-population, as well as persons with mild disease, are a major contributor in the propagation of COVID-19. The asymptomatic sub-population frequently escapes detection by public health surveillance systems. Because of this, the currently accepted estimates of the basic reproduction number (ℛ0) of the disease are inaccurate. It is unlikely that a pathogen can blanket the planet in three months with an ℛ0 in the vicinity of 3, as reported in the literature (1–6). In this manuscript, we present a mathematical model taking into account asymptomatic carriers. Our results indicate that an initial value of the effective reproduction number could range from 5.5 to 25.4, with a point estimate of 15.4, assuming mean parameters. The first three weeks of the model exhibit exponential growth, which is in agreement with average case data collected from thirteen countries with universal health care and robust communicable disease surveillance systems; the average rate of growth in the number of reported cases is 23.3% per day during this period.

scholarly journals Community perspectives on the benefits and risks of technologically enhanced communicable disease surveillance systems: a report on four community juries

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Chris Degeling ◽  
Stacy M. Carter ◽  
Antoine M. van Oijen ◽  
Jeremy McAnulty ◽  
Vitali Sintchenko ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Communicable Disease ◽  
Surveillance Systems ◽  
Community Perspectives

Establishing communicable disease surveillance systems

2021 ◽  
pp. bmjmilitary-2021-001803
Author(s):  
Thomas Falconer Hall ◽  
D A Ross
Keyword(s):  
Data Collection ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Control Measures ◽  
Public Health Approach ◽  
Recent Experience ◽  
Surveillance Systems ◽  
Military Health ◽  
Humanitarian Emergencies ◽  
Disaster Relief Operations

Humanitarian emergencies can result in an increase of communicable diseases, leading to a rise in mortality and/or morbidity in vulnerable populations. This requires a public health approach to re-establish control of communicable disease. Communicable disease surveillance systems play a key role, providing the information required for disease control measures, through systematic data collection, analysis, interpretation and dissemination. In humanitarian emergencies, they use the principles, practices and processes of wider surveillance systems, while being more focused on urgent priorities. However, communicable disease surveillance systems in humanitarian emergencies are constrained by multiple environmental, epidemiological and sociopolitical factors. Basic data collection, the bedrock of surveillance systems, can be extremely challenging and may require additional methods to estimate population size and prioritise diseases. Surveillance systems may be operating in conditions of weak state capacity with little physical or institutional infrastructure to support their operation. However, there are examples of successful self-sustaining disease surveillance systems in these circumstances, such as the deployment of WHO’s Early Warning Alert and Response System in a Box. Individuals and organisations charged with establishing communicable disease surveillance systems in emergencies would be well advised to learn from recent examples of success, use the sources of planning guidance outlined in this article and seek advice from organisations with recent experience. This is a paper commissioned as a part of the Humanitarian and Disaster Relief Operations special issue of BMJ Military Health.

scholarly journals Advances in spatiotemporal models for non-communicable disease surveillance

2020 ◽  
Vol 49 (Supplement_1) ◽  
pp. i26-i37
Author(s):  
Marta Blangiardo ◽  
Areti Boulieri ◽  
Peter Diggle ◽  
Frédéric B Piel ◽  
Gavin Shaddick ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Communicable Disease ◽  
Surveillance Systems ◽  
Complex Data ◽  
Bayesian Hierarchical ◽  
Complex Models ◽  
Intervention Policy ◽  
Spatiotemporal Models ◽  
Modelling Process ◽  
Non Communicable Disease

Abstract Surveillance systems are commonly used to provide early warning detection or to assess an impact of an intervention/policy. Traditionally, the methodological and conceptual frameworks for surveillance have been designed for infectious diseases, but the rising burden of non-communicable diseases (NCDs) worldwide suggests a pressing need for surveillance strategies to detect unusual patterns in the data and to help unveil important risk factors in this setting. Surveillance methods need to be able to detect meaningful departures from expectation and exploit dependencies within such data to produce unbiased estimates of risk as well as future forecasts. This has led to the increasing development of a range of space-time methods specifically designed for NCD surveillance. We present an overview of recent advances in spatiotemporal disease surveillance for NCDs, using hierarchically specified models. This provides a coherent framework for modelling complex data structures, dealing with data sparsity, exploiting dependencies between data sources and propagating the inherent uncertainties present in both the data and the modelling process. We then focus on three commonly used models within the Bayesian Hierarchical Model (BHM) framework and, through a simulation study, we compare their performance. We also discuss some challenges faced by researchers when dealing with NCD surveillance, including how to account for false detection and the modifiable areal unit problem. Finally, we consider how to use and interpret the complex models, how model selection may vary depending on the intended user group and how best to communicate results to stakeholders and the general public.

scholarly journals Changes in public preferences for technologically enhanced surveillance following the COVID-19 pandemic: a discrete choice experiment

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e041592
Author(s):  
Chris Degeling ◽  
Gang Chen ◽  
Gwendolyn L Gilbert ◽  
Victoria Brookes ◽  
Thi Thai ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Discrete Choice ◽  
Data Security ◽  
Surveillance System ◽  
Disease Surveillance ◽  
Choice Experiment ◽  
Personal Autonomy ◽  
Communicable Disease ◽  
Public Acceptance ◽  
Surveillance Systems

ObjectivesAs governments attempt to navigate a path out of COVID-19 restrictions, robust evidence is essential to inform requirements for public acceptance of technologically enhanced communicable disease surveillance systems. We examined the value of core surveillance system attributes to the Australian public, before and during the early stages of the current pandemic.DesignA discrete choice experiment was conducted in Australia with a representative group of respondents, before and after the WHO declared COVID-19 a Public Health Emergency of International Concern. We identified and investigated the relative importance of seven attributes associated with technologically enhanced disease surveillance: respect for personal autonomy; privacy/confidentiality; data certainty/confidence; data security; infectious disease mortality prevention; infectious disease morbidity prevention; and attribution of (causal) responsibility. Specifically, we explored how the onset of the COVID-19 outbreak influenced participant responses.Setting and participants2008 Australians (general public) completed the experiment: 793 before COVID-19 outbreak onset (mean age 45.9 years, 50.2% male) and 1215 after onset (mean age 47.2 years, 49% male).ResultsAll seven attributes significantly influenced respondents’ preferences for communicable disease surveillance systems. After onset, participants demonstrated greater preference for a surveillance system that could prevent a higher number of illnesses and deaths, and were less concerned about their personal autonomy. However, they also increased their preference for a system with high data security.ConclusionsPublic acceptance of technology-based communicable disease surveillance is situation dependent. During an epidemic, there is likely to be greater tolerance of technologically enhanced disease surveillance systems that result in restrictions on personal activity if such systems can prevent high morbidity and mortality. However, this acceptance of lower personal autonomy comes with an increased requirement to ensure data security. These findings merit further research as the pandemic unfolds and strategies are put in place that enable individuals and societies to live with SARS-CoV-2 endemicity.

scholarly journals The lessons of COVID-19 pandemic for communicable diseases surveillance system: A qualitative study in the Kurdistan region-Iraq

2021 ◽  
Author(s):  
Soran Amin Hamalaw ◽  
Ali Hattem Bayati ◽  
Muhammed Babakir-Mina ◽  
Amirhossein Takian
Keyword(s):  
Disease Surveillance ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
Surveillance Systems ◽  
Kurdistan Region ◽  
Structured Interviews ◽  
Policy Makers ◽  
System A ◽  
Health Authorities ◽  
Training And Supervision

Abstract Background Coronavirus disease 2019 (COVID-19) has revealed a series of unprecedented challenges to Communicable Disease Surveillance Systems (CDSS) globally. This study aimed to determine the opportunities of and barriers to CDSS during the COVID-19 pandemic, and the extent to which the disease integrated into the CDSS in the Kurdistan region of Iraq. Methods A descriptive qualitative approach was applied. We conducted 7 semi-structured interviews and one focus group discussions (FGD) with purposefully identified Key Informants (KI) from June to December 2020. All interviews were digitally recorded and transcribed verbatim. We adopted a mixed deductive-inductive approach for thematic analysis of data, facilitated by using MAXQDA20 software for data management. Results Although the CDSS was considered appropriate and flexible, the COVID-19 was interpreted not to be integrated into the system due to political concerns. The lack of epidemic preparedness, timeliness, and partial cessation of training and supervision during the pandemic were the main concerns regarding core and support activities. The existence of reasonable surveillance infrastructure, i.e. trained staff was identified as an opportunity for improvement. The main challenges include: staff deficiency, absence of motivation and financial support for present staff, scarce logistics, managerial and administrative issues, and lack of cooperation, particularly among stakeholders and surveillance staff. Conclusion Our findings revealed that due to political barriers, COVID-19 was not integrated into the CDSS. It also highlighted the main facilitators of and barriers to CDSS in the region. We advocate health authorities and policy-makers to prioritize the surveillance and effective management of communicable diseases.

Communicable Disease Surveillance Systems in Disasters: Application of the Input, Process, Product, and Outcome Framework for Performance Assessment

2018 ◽  
Vol 13 (02) ◽  
pp. 158-164 ◽  
Author(s):  
Javad Babaie ◽  
Ali Ardalan ◽  
Hasan Vatandoost ◽  
Mohammad Mahdi Goya ◽  
Ali Akbarisari
Keyword(s):  
Performance Assessment ◽  
Disease Surveillance ◽  
Communicable Disease ◽  
Communicable Diseases ◽  
Surveillance Systems ◽  
Analytic Hierarchy ◽  
Disease Surveillance System ◽  
Outcome Framework ◽  
A Chain ◽  
Process Product

AbstractObjectiveOne of the most important measures following disasters is setting up a communicable disease surveillance system (CDSS). This study aimed to develop indicators to assess the performance of CDSSs in disasters.MethodIn this 3-phase study, firstly a qualitative study was conducted through in-depth, semistructured interviews with experts on health in disasters and emergencies, health services managers, and communicable diseases center specialists. The interviews were analyzed, and CDSS performance assessment (PA) indicators were extracted. The appropriateness of these indicators was examined through a questionnaire administered to experts and heads of communicable diseases departments of medical sciences universities. Finally, the designed indicators were weighted using the analytic hierarchy process approach and Expert Choice software.ResultsIn this study, 51 indicators were designed, of which 10 were related to the input (19.61%), 17 to the process (33.33%), 13 to the product (25.49%), and 11 to the outcome (21.57%). In weighting, the maximum score was that of input (49.1), and the scores of the process, product, and outcome were 31.4, 12.7, and 6.8, respectively.ConclusionThrough 3 different phases, PA indicators for 4 phases of a chain of results were developed. The authors believe that these PA indicators can assess the system’s performance and its achievements in response to disasters. (Disaster Med Public Health Preparedness. 2019;13:158–164)

scholarly journals Best Paper Selection

2021 ◽  
Vol 30 (01) ◽  
pp. 282-282
Keyword(s):  
Primary Care ◽  
Deep Learning ◽  
Disease Surveillance ◽  
Early Warning System ◽  
Communicable Disease ◽  
Warning System ◽  
Surveillance Systems ◽  
Health Records ◽  
Community Perspectives ◽  
Risk Patients

Zheng L, Wang O, Hao S, Ye C, Liu M, Xia M, Sabo AL, Markovic L, Stearns F, Kanov L, Sylvester KL, Widen R, McElhinney DB, Zhang W, Liao J, Ling XB. Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033212/ Roope LSJ, Tonkin-Crine S, Herd N, Michie S, Pouwels KB, Castro-Sanchez E, Sallis A, Hopkins S, Robotham JV, Crook DW, Peto T. Peters M, Butler CC, Walker AS, Wordsworth S. Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear-based messages about antimicrobial resistance. https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-020-01553-6 Degeling C, Carter SM, van Oijen AM McAnulty J, Sintchenko V, Braunack-Mayer A, Yarwood T, Johnson J, Gilbert GL. Community perspectives on the benefits and risks of technologically enhanced communicable disease surveillance systems: a report on four community juries. https://bmcmedethics.biomedcentral.com/articles/10.1186/s12910-020-00474-6

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