COVID-19 and Digital Contact Tracing: Regulating the Future of Public Health Surveillance

2020 ◽  
Author(s):  
Divya Ramjee ◽  
Pollyanna Sanderson ◽  
Imran Malek
Scientifica ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-26 ◽  
Author(s):  
Bernard C. K. Choi

This paper provides a review of the past, present, and future of public health surveillance—the ongoing systematic collection, analysis, interpretation, and dissemination of health data for the planning, implementation, and evaluation of public health action. Public health surveillance dates back to the first recorded epidemic in 3180 B.C. in Egypt. Hippocrates (460 B.C.–370 B.C.) coined the terms endemic and epidemic, John Graunt (1620–1674) introduced systematic data analysis, Samuel Pepys (1633–1703) started epidemic field investigation, William Farr (1807–1883) founded the modern concept of surveillance, John Snow (1813–1858) linked data to intervention, and Alexander Langmuir (1910–1993) gave the first comprehensive definition of surveillance. Current theories, principles, and practice of public health surveillance are summarized. A number of surveillance dichotomies, such as epidemiologic surveillance versus public health surveillance, are described. Some future scenarios are presented, while current activities that can affect the future are summarized: exploring new frontiers; enhancing computer technology; improving epidemic investigations; improving data collection, analysis, dissemination, and use; building on lessons from the past; building capacity; enhancing global surveillance. It is concluded that learning from the past, reflecting on the present, and planning for the future can further enhance public health surveillance.


2021 ◽  
Author(s):  
Bingyi Yang ◽  
Tim K. Tsang ◽  
Huizhi Gao ◽  
Eric H. Y. Lau ◽  
Yun Lin ◽  
...  

Abstract Background: Testing of an entire community has been used as an approach to control COVID-19. In Hong Kong, a universal community testing programme (UCTP) was implemented at the fadeout phase of a community epidemic in July to September 2020, to determine the prevalence of unrecognised cases and limit any remaining transmission chains. We described the utility of the UCTP in finding unrecognised cases, and analysed data from the UCTP and other sources to characterise transmission dynamics.Methods: We described the characteristics of people participating in the UCTP, and compared the clinical and epidemiological characteristics of COVID-19 cases detected by the UCTP versus those detected by clinical diagnosis and public health surveillance. We developed a Bayesian model to estimate the age-specific incidence of infection and the proportion of cases detected by clinical diagnosis and public health surveillance.Findings: 1.77 million people, 24% of the Hong Kong population, participated in the UCTP from 1 to 14 September 2020. The UCTP identified 32 new infections (1.8 per 100,000 samples tested), consisting of 29% of all local cases reported during the two-week UCTP period. Compared with the existing clinical diagnosis and public health surveillance, the UCTP detected a higher proportion of sporadic cases (62% versus 27%, p <0.01) and identified 6 (out of 18) additional transmission chains during that period. We estimated that 27% (95% credible interval: 22%, 34%) of all infections were detected by the existing clinical diagnosis and public health surveillance in the third wave.Interpretation: We reported empirical evidence of the utility of population-wide COVID-19 testing in detecting unrecognised infections and transmission chains. Around three quarters of infections have not been identified through existing surveillance approaches including contact tracing.


2004 ◽  
Author(s):  
Michael M. Wagner ◽  
F-C. Tsui ◽  
J. Espino ◽  
W. Hogan ◽  
J. Hutman ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document