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Electronic health information systems can reshape the practice of public health including public health surveillance, disease and injury investigation and control, decision making, quality assurance, and policy development. While these opportunities are potentially transformative, and the federal program for the Meaningful Use (MU) of electronic health records (EHRs) has included important public health components, significant barriers remain. Unlike incentives in the clinical care system, scant funding is available to public health departments to develop the necessary information infrastructure and workforce capacity to capitalize on EHRs, personal health records, or Big Data. Current EHR systems are primarily built to serve clinical systems and practice rather than being structured for public health use. In addition, there are policy issues concerning how broadly the data can be used by public health officials. As these issues are resolved and workable solutions emerge, they should yield a more efficient and effective public health system.

BackgroundHIV transmitted drug resistance (TDR) is a public health concern because it has the potential to compromise antiretroviral therapy (ART) at the population level. In New York State, high prevalence of TDR in a local cohort and a multiclass resistant case cluster led to the development and implementation of a statewide resistance surveillance system.MethodologyWe conducted a cross-sectional analysis of the 13,109 cases of HIV infection that were newly diagnosed and reported in New York State between 2006 and 2008, including 4,155 with HIV genotypes drawn within 3 months of initial diagnosis and electronically reported to the new resistance surveillance system. We assessed compliance with DHHS recommendations for genotypic resistance testing and estimated TDR among new HIV diagnoses.Principal FindingsOf 13,109 new HIV diagnoses, 9,785 (75%) had laboratory evidence of utilization of HIV-related medical care, and 4,155 (43%) had a genotype performed within 3 months of initial diagnosis. Of these, 11.2% (95% confidence interval [CI], 10.2%–12.1%) had any evidence of TDR. The proportion with mutations associated with any antiretroviral agent in the NNRTI, NRTI or PI class was 6.3% (5.5%–7.0%), 4.3% (3.6%–4.9%) and 2.9% (2.4%–3.4%), respectively. Multiclass resistance was observed in <1%. TDR did not increase significantly over time (p for trend = 0.204). Men who have sex with men were not more likely to have TDR than persons with heterosexual risk factor (OR 1.0 (0.77–1.30)). TDR to EFV+TDF+FTC and LPV/r+TDF+FTC regimens was 7.1% (6.3%–7.9%) and 1.4% (1.0%–1.8%), respectively.Conclusions/SignificanceTDR appears to be evenly distributed and stable among new HIV diagnoses in New York State; multiclass TDR is rare. Less than half of new diagnoses initiating care received a genotype per DHHS guidelines.

The incidence of tuberculosis (TB) in the United States has stabilized, and additional interventions are needed to make progress toward TB elimination. However, the impact of such interventions depends on local demography and the heterogeneity of populations at risk. Using state-level individual-based TB transmission models calibrated to California, Florida, New York, and Texas, we modeled 2 TB interventions: 1) increased targeted testing and treatment (TTT) of high-risk populations, including people who are non–US-born, diabetic, human immunodeficiency virus (HIV)-positive, homeless, or incarcerated; and 2) enhanced contact investigation (ECI) for contacts of TB patients, including higher completion of preventive therapy. For each intervention, we projected reductions in active TB incidence over 10 years (2016–2026) and numbers needed to screen and treat in order to avert 1 case. We estimated that TTT delivered to half of the non–US-born adult population could lower TB incidence by 19.8%–26.7% over a 10-year period. TTT delivered to smaller populations with higher TB risk (e.g., HIV-positive persons, homeless persons) and ECI were generally more efficient but had less overall impact on incidence. TTT targeted to smaller, highest-risk populations and ECI can be highly efficient; however, major reductions in incidence will only be achieved by also targeting larger, moderate-risk populations. Ultimately, to eliminate TB in the United States, a combination of these approaches will be necessary.

Objective Targeted testing and treatment of persons with latent tuberculosis infection (LTBI) is a critical component of the US tuberculosis (TB) elimination strategy. In January 2016, the California Department of Public Health issued a tool and user guide for TB risk assessment (California tool) and guidance for LTBI testing, and in September 2016, the US Preventive Services Task Force (USPSTF) issued recommendations for LTBI testing in primary care settings. We estimated the epidemiologic effect of adherence to both recommendations in California. Methods We used an individual-based Markov micro-simulation model to estimate the number of cases of TB disease expected through 2026 with baseline LTBI strategies compared with implementation of the USPSTF or California tool guidance. We estimated the risk of LTBI by age and country of origin, the probability of being in a targeted population, and the probability of presenting for primary care based on available data. We assumed 100% adherence to testing guidance but imperfect adherence to treatment. Results Implementation of USPSTF and California tool guidance would result in nearly identical numbers of tests administered and cases of TB disease prevented. Perfect adherence to either recommendation would result in approximately 7000 cases of TB disease averted (40% reduction compared with baseline) by 2026. Almost all of this decline would be driven by a reduction in the number of cases among non–US-born persons. Conclusions By focusing on the non–US-born population, adherence to LTBI testing strategies recommended by the USPSTF and the California tool could substantially reduce the burden of TB disease in California in the next decade.