OBJECTIVES: The US Centers for Disease Control and Prevention (CDC)-funded Preparedness and Emergency Response Research Centers (PERRCs) conducted research from 2008 to 2015 aimed to improve the complex public health emergency preparedness and response (PHEPR) system. This paper summarizes PERRC studies that addressed the development and assessment of criteria for evaluating PHEPR and metrics for measuring their efficiency and effectiveness. METHODS: We reviewed 171 PERRC publications indexed in PubMed between 2009 and 2016. These publications derived from 34 PERRC research projects. We identified publications that addressed the development or assessment of criteria and metrics pertaining to PHEPR systems and describe the evaluation methods used and tools developed, the system domains evaluated, and the metrics developed or assessed. RESULTS: We identified 29 publications from 12 of the 34 PERRC projects that addressed PHEPR system evaluation criteria and metrics. We grouped each study into 1 of 3 system domains, based on the metrics developed or assessed: (1) organizational characteristics (n = 9), (2) emergency response performance (n = 12), and (3) workforce capacity or capability (n = 8). These studies addressed PHEPR system activities including responses to the 2009 H1N1 pandemic and the 2011 tsunami, as well as emergency exercise performance, situational awareness, and workforce willingness to respond. Both PHEPR system process and outcome metrics were developed or assessed by PERRC studies. CONCLUSIONS: PERRC researchers developed and evaluated a range of PHEPR system evaluation criteria and metrics that should be considered by system partners interested in assessing the efficiency and effectiveness of their activities. Nonetheless, the monitoring and measurement problem in PHEPR is far from solved. Lack of standard measures that are readily obtained or computed at local levels remains a challenge for the public health preparedness field. (Disaster Med Public Health Preparedness. 2018;page 1 of 13).

Public health surveillance is focused on the detection of acute, chronic, and emerging threats to the health of the population to direct disease control and prevention efforts.1 Public health surveillance relies on health care providers to report to public health agencies conditions or outbreaks that may impact the broader population. This case reporting is mandated through laws and regulations at the state and local levels. Notification of cases to the Centers for Disease Control and Prevention (CDC) is facilitated by agreements between states and the federal government.2 Historically, case reporting has been based on paper reports or Internet-based entry of reports to state health department systems, but these reports are often slow or incomplete and place a substantial burden of work on health care providers and public health agencies.3 The future of surveillance is electronic case reporting (eCR), by which cases of reportable conditions are automatically generated from electronic health record (EHR) systems and transmitted to public health agencies for review and action. | eCR holds promise for enhancing the quality and effectiveness of public health surveillance.4 Greater use of eCR could result in (1) more complete and accurate case data in near real time for public health action; (2) earlier detection of cases, permitting earlier intervention and lowered transmission of disease; (3) improved detection of outbreaks to allow earlier investigation and, potentially, earlier identification of risk factors for the spread of disease; and (4) creation of a new infrastructure to support rapid reporting of newly recognized and emerging conditions. In this commentary, we review the promise of eCR and present our vision for a nationally interoperable eCR system that allows for timely reporting to public health and information sharing among jurisdictions.

Surveillance is critical for improving population health. Public health surveillance systems generate information that drives action, and the data must be of sufficient quality and with a resolution and timeliness that matches objectives. In the context of scientific advances in public health surveillance, changing health care and public health environments, and rapidly evolving technologies, the aim of this article is to review public health surveillance systems. We consider their current use to increase the efficiency and effectiveness of the public health system, the role of system stakeholders, the analysis and interpretation of surveillance data, approaches to system monitoring and evaluation, and opportunities for future advances in terms of increased scientific rigor, outcomes-focused research, and health informatics. Expected final online publication date for the Annual Review of Public Health Volume 38 is March 20, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

BACKGROUND: The utility of healthcare utilization data from US emergency departments (EDs) for rapid monitoring of changes in influenza-like illness (ILI) activity was highlighted during the recent influenza A (H1N1) pandemic. Monitoring has tended to rely on detection algorithms, such as the Early Aberration Reporting System (EARS), which are limited in their ability to detect subtle changes and identify disease trends. OBJECTIVE: To evaluate a complementary approach, change point analysis (CPA), for detecting changes in the incidence of ED visits due to ILI. METHODOLOGY AND PRINCIPAL FINDINGS: Data collected through the Distribute project (isdsdistribute.org), which aggregates data on ED visits for ILI from over 50 syndromic surveillance systems operated by state or local public health departments were used. The performance was compared of the cumulative sum (CUSUM) CPA method in combination with EARS and the performance of three CPA methods (CUSUM, structural change model and Bayesian) in detecting change points in daily time-series data from four contiguous US states participating in the Distribute network. Simulation data were generated to assess the impact of autocorrelation inherent in these time-series data on CPA performance. The CUSUM CPA method was robust in detecting change points with respect to autocorrelation in time-series data (coverage rates at 90% when -0.2≤rho≤0.2 and 80% when -0.5≤rho≤0.5). During the 2008-9 season, 21 change points were detected and ILI trends increased significantly after 12 of these change points and decreased nine times. In the 2009-10 flu season, we detected 11 change points and ILI trends increased significantly after two of these change points and decreased nine times. Using CPA combined with EARS to analyze automatically daily ED-based ILI data, a significant increase was detected of 3% in ILI on April 27, 2009, followed by multiple anomalies in the ensuing days, suggesting the onset of the H1N1 pandemic in the four contiguous states. CONCLUSIONS AND SIGNIFICANCE: As a complementary approach to EARS and other aberration detection methods, the CPA method can be used as a tool to detect subtle changes in time-series data more effectively and determine the moving direction (ie, up, down, or stable) in ILI trends between change points. The combined use of EARS and CPA might greatly improve the accuracy of outbreak detection in syndromic surveillance systems.

The authors applied a time-series approach to assess the temporal trend of racial disparity in chlamydia prevalence between young, socioeconomically disadvantaged blacks and whites entering the US National Job Training Program. Racial disparity was defined as the arithmetic difference between age group-, specimen type-, and region of residence-standardized chlamydia prevalences in blacks and whites. A regression with autoregressive moving average errors model was employed to adjust for serial correlation. Data from 46,849 women (2006-2008) and 136,892 men (2004-2008) were analyzed. Racial disparity significantly decreased among women (by an average of 0.122% per 2-month interval; P < 0.05) but not among men (-0.010%, P = 0.57). Chlamydia prevalence significantly declined for black women (-0.139% per 2-month interval; P = 0.004), black men (-0.045%, P < 0.001), and white men (-0.035%, P = 0.002) but not for white women (-0.028%, P = 0.413). Despite the decreases among black women and black men, the black-white disparities remained high for both sexes; in 2008, the racial disparity was 8.1% (95% confidence interval: 6.8, 9.3) for women and 9.0% (95% confidence interval: 8.4, 9.6) for men. These findings suggest that current chlamydia control efforts may be reaching young black men and women but need to be scaled up or modified to address the excess risk among blacks.

The Integrated Disease Surveillance and Response (IDSR) strategy was developed by the Africa Regional Office (AFRO) of the World Health Organisation (WHO) and proposed for adoption by member states in 1998. The goal was to build WHO/AFRO countries' capacity to detect, report and effectively respond to priority infectious diseases. This evaluation focuses on the outcomes in four countries that implemented this strategy. Major successes included: integration of the surveillance function of most of the categorical disease control programmes; implementation of standard surveillance, laboratory and response guidelines; improved timeliness and completeness of surveillance data and increased national-level review and use of surveillance data for response. The most challenging aspects were: strengthening laboratory networks; providing regular feedback and supervision on surveillance and response activities; routine monitoring of IDSR activities and extending the strategy to sub-national levels.

Social, political, and economic disruptions caused by natural and human-caused public health emergencies have catalyzed public health efforts to expand the scope of biosurveillance and increase the timeliness, quality, and comprehensiveness of disease detection, alerting, response, and prediction. Unfortunately, efforts to acquire, render, and visualize the diversity of health intelligence information are hindered by its wide distribution across disparate fields, multiple levels of government, and the complex interagency environment. Achieving this new level of situation awareness within public health will require a fundamental cultural shift in methods of acquiring, analyzing, and disseminating information. The notion of information "fusion" may provide opportunities to expand data access, analysis, and information exchange to better inform public health action.