This MMWR supplement summarizes the deliberations of | CDC/ATSDR scientists and managers who met in September | 2009 in Atlanta as part of the 2009 Consultation on CDC/ | ATSDR’s Vision for Public Health Surveillance in the 21st | Century. The meeting was convened to reflect on domestic and | global public health surveillance practice and to recommend | a strategic framework to advance public health surveillance | to meet continuing and new challenges. The first report is | an adaptation of the keynote address for the meeting, which | summarized the history of public health surveillance, the need | to reassess its usefulness, the rationale for topics selected for | discussion, and the charge to participants. Subsequent reports | summarize the discussions of workgroups that addressed | specific topics in surveillance science and practices. | Public health surveillance in the United States has evolved | from monitoring infectious diseases to tracking the occurrence | of many noninfectious conditions, such as injuries, birth | defects, chronic conditions, mental illness, illicit drug use, | environmental, and occupational exposures to health risks. | In 2001, the intentional dissemination of Bacillus anthracis | spores and subsequent cases of anthrax in the United States | provided an impetus for automating surveillance to enable | early detection, rapid characterization, and timely continuous | monitoring of urgent public health threats.

Lenert and Sundwall identify opportunities and challenges of the Meaningful Use (MUse) incentive programs that advance standardized electronic reporting to health departments at a time when there is limited funding to upgrade systems. We concur that cloud-based Platform as a Service (PaaS) is a possible remedy. However, we disagree with their conclusion that "the security risks inherent in BioSense 2.0's public cloud implementation may make this effort better suited to a demonstration project than a national level biodefense system." (Am J Public Health. Published online ahead of print July 19, 2012: e1. doi:10.2105/AJPH.2012.300800).

Public health funding formulas have received less scrutiny than those used in other government sectors, particularly health services and public health insurance. We surveyed states about their use of funding formulas for specific public health activities; sources of funding; formula attributes; formula development; and assessments of political and policy considerations. Results show that the use of funding formulas is positively correlated with the number of local health departments and with the percentage of public health funding provided by the federal government. States use a variety of allocative strategies but most commonly employ a "base-plus" distribution. Resulting distributions are more disproportionate than per capita or per-person-in-poverty allotments, an effect that increases as the proportion of total funding dedicated to equal minimum allotments increases.

Funding formulas are commonly used by federal agencies to allocate program funds to states. As one approach to evaluating differences in allocations resulting from alternative formula calculations, we propose the use of a measure derived from the Gini index to summarize differences in allocations relative to 2 referent allocations: one based on equal per-capita funding across states and another based on equal funding per person living in poverty, which we define as the "proportionality of allocation" (PA). These referents reflect underlying values that often shape formula-based allocations for public health programs. The size of state populations serves as a general proxy for the amount of funding needed to support programs across states. While the size of state populations living in poverty is correlated with overall population size, allocations based on states' shares of the national population living in poverty reflect variations in funding need shaped by the association between poverty and multiple adverse health outcomes. The PA measure is a summary of the degree of dispersion in state-specific allocations relative to the referent allocations and provides a quick assessment of the impact of selecting alternative funding formula designs. We illustrate the PA values by adjusting a sample allocation, using various measures of the salary costs and in-state wealth, which might modulate states' needs for federal funding.

CONTEXT: Multiple federal public health programs use funding formulas to allocate funds to states. OBJECTIVE: To characterize the effects of adjusting formula-based allocations for differences among states in the cost of implementing programs, the potential for generating in-state resources, and income disparities, which might be associated with disease risk. SETTING: Fifty US states and the District of Columbia. INTERVENTION: Formula-based funding allocations to states for 4 representative federal public health programs were adjusted using indicators of cost (average salaries), potential within-state revenues (per-capita income, the Federal Medical Assistance Percentage, per-capita aggregate home values), and income disparities (Theil index). MAIN OUTCOME: Percentage of allocation shifted by adjustment, the number of states and the percentage of US population living in states with a more than 20% increase or decrease in funding, maximum percentage increase or decrease in funding. RESULTS: Each adjustor had a comparable impact on allocations across the 4 program allocations examined. Approximately 2% to 8% of total allocations were shifted, with adjustments for variations in income disparity and housing values having the least and greatest effects, respectively. The salary cost and per-capita income adjustors were inversely correlated and had offsetting effects on allocations. With the exception of the housing values adjustment, fewer than 10 states had more than 20% increases or decreases in allocations, and less than 10% of the US population lived in such states. CONCLUSIONS: Selection of adjustors for formula-based funding allocations should consider the impacts of different adjustments, correlations between adjustors and other data elements in funding formulas, and the relationship of formula inputs to program objectives.

We evaluated the completeness of West Nile fever (WNF) surveillance within the U.S. public health system. We surveyed laboratory and surveillance programs on policies, practices, and capacities for testing, confirmation, and reporting (collectively called ascertainment) from 2003 through 2005. We calculated syndrome ascertainment ratios by dividing WNF counts by neuroinvasive disease counts; separately, we performed multilevel modeling. Jurisdictions were more likely to ascertain at least one WNF cases per West Nile neuroinvasive disease case when ≤ 1 testing restrictions existed (odds ratio [OR] = 7.7, 95% confidence interval [CI] = 1.3-46.4), when conducting ≥ 4 activities to enhance reporting (OR = 9.3, 95% CI = 1.6-54.8), and when ≥ 5.0 staff per million residents were dedicated to arboviral surveillance (OR = 6.4, 95% CI = 1.0-40.3). Ascertainment of WNF was less likely among Blacks (OR = 0.56, 95% CI = 0.31-0.99) and Hispanics (OR = 0.69, 95% CI = 0.48-0.98) than among Whites. Ascertainment was more complete when testing and reporting were enhanced, but differentially incomplete for minorities.

Opportunities for improved disease reporting are identified by describing physicians' reporting knowledge and practices as well as reporting knowledge and specimen referral patterns among clinical laboratories in the state of Georgia. In 2005, a sample of physicians (n = 177) and all Georgia clinical laboratories (n = 139) were surveyed about reporting knowledge and practices. Knowledge was greater among physicians who received their medical degree before 1980 (P = .04), accessed e-mail (P< .01), used the Internet to obtain public health information (P < .01), and reported frequently (P= .06). Increased knowledge was not associated with training in reporting (P = .14). Physicians were often unaware of reporting procedures and mechanisms and often did not report because they believed others would report (52%). Laboratory representatives (56%) more often received training on disease reporting than physicians (32%). All laboratories sent some specimens for diagnostic testing at reference laboratories and 35% sent the specimens outside of Georgia. Physicians' characteristics may affect reporting knowledge independent of training on disease reporting, and increased knowledge is associated with increased reporting. Investigation of physician characteristics that contribute to improved reporting, such as an active engagement with public health, could help to guide changes to reporting-related training and technology. Reporting by other health care providers and physicians' perceptions that others will report both indicate that studies of all reporting stakeholders and clear delineation of reporting responsibilities are needed. Extensive specimen referral by laboratories suggests the need for coordination of reporting regulations and responsibilities beyond local boundaries.