Validation of Claims-Based Algorithm for Lyme Disease, Massachusetts, USA.

Compared with notifiable disease surveillance, claims-based algorithms estimate higher Lyme disease incidence, but their accuracy is unknown. We applied a previously developed Lyme disease algorithm (diagnosis code plus antimicrobial drug prescription dispensing within 30 days) to an administrative claims database in Massachusetts, USA, to identify a Lyme disease cohort during July 2000-June 2019. Clinicians reviewed and adjudicated medical charts from a cohort subset by using national surveillance case definitions. We calculated positive predictive values (PPVs). We identified 12,229 Lyme disease episodes in the claims database and reviewed and adjudicated 128 medical charts. The algorithm's PPV for confirmed, probable, or suspected cases was 93.8% (95% CI 88.1%-97.3%); the PPV was 66.4% (95% CI 57.5%-74.5%) for confirmed and probable cases only. In a high incidence setting, a claims-based algorithm identified cases with a high PPV, suggesting it can be used to assess Lyme disease burden and supplement traditional surveillance data.

One Pill, Once a Day: Simplified Treatment Regimens and Retention in HIV Care.

Simplified drug regimens may improve retention in care for persons with chronic diseases. In April 2013, South Africa adopted a once-daily single-pill human immunodeficiency virus (HIV) treatment regimen as the standard of care, replacing a multiple-pill regimen. Because the regimens had similar biological efficacy, the shift to single-pill therapy offered a real-world test of the impact of simplified drug-delivery mechanisms on patient behavior. Using a quasi-experimental regression discontinuity design, we assessed retention in care among patients starting HIV treatment just before and just after the guideline change. The study included 4,484 patients starting treatment at a large public sector clinic in Johannesburg, South Africa. The share of patients prescribed a single-pill regimen increased by over 40 percentage points between March and April 2013. Initiating treatment after the policy change was associated with 11.7-percentage-points' higher retention at 12 months (95% confidence interval: -2.2, 29.4). Findings were robust to different measures of retention, different bandwidths, and different statistical models. Patients starting treatment early in HIV infection-a key population in the test-and-treat era-experienced the greatest improvements in retention from single-pill regimens.

Validation of diagnosis codes to identify hospitalized COVID-19 patients in health care claims data.

PURPOSE: Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis. METHODS: We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C). RESULTS: The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%). CONCLUSION: Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.

A COVID-19-ready public health surveillance system: The Food and Drug Administration's Sentinel System.

The US Food and Drug Administration's Sentinel System was established in 2009 to use routinely collected electronic health data for improving the national capability to assess post-market medical product safety. Over more than a decade, Sentinel has become an integral part of FDA's surveillance capabilities and has been used to conduct analyses that have contributed to regulatory decisions. FDA's role in the COVID-19 pandemic response has necessitated an expansion and enhancement of Sentinel. Here we describe how the Sentinel System has supported FDA's response to the COVID-19 pandemic. We highlight new capabilities developed, key data generated to date, and lessons learned, particularly with respect to working with inpatient electronic health record data. Early in the pandemic, Sentinel developed a multi-pronged approach to support FDA's anticipated data and analytic needs. It incorporated new data sources, created a rapidly refreshed database, developed protocols to assess the natural history of COVID-19, validated a diagnosis-code based algorithm for identifying patients with COVID-19 in administrative claims data, and coordinated with other national and international initiatives. Sentinel is poised to answer important questions about the natural history of COVID-19 and is positioned to use this information to study the use, safety, and potentially the effectiveness of medical products used for COVID-19 prevention and treatment.

Do HIV treatment eligibility expansions crowd out the sickest? Evidence from rural South Africa.

OBJECTIVE: The 2015 WHO recommendation to initiate all HIV patients on antiretroviral therapy (ART) at diagnosis could potentially overextend health systems and crowd out sicker patients, mitigating the policy's impact. We evaluate whether South Africa's prior eligibility expansion from CD4 ≤ 200 to CD4 ≤ 350 cells/µl reduced ART uptake in the sickest patients. METHODS: Using data on all patients presenting to the Hlabisa HIV Treatment and Care Programme in KwaZulu-Natal from April 2010 to June 2012 (n = 13 809), we assessed the impact of the August 2011 eligibility expansion on the number of patients seeking care, number initiating ART and time from HIV diagnosis to ART initiation among patients always eligible (CD4 0-200), newly eligible (CD4 201-350) and not yet eligible by CD4 count (>350). We used interrupted time series methods to control for long-run trends and isolate the effect of the policy. RESULTS: Expanding ART eligibility led to an increased number of patients initiating ART per month [+95.5; 95% CI (-1.3; 192.3)]. Newly eligible patients (CD4 201-350) initiated treatment 47% faster than before (95% CI 19%; 82%), while the sickest patients (CD4 ≤ 200) saw no decline in the monthly number of patients initiating treatment or the rate of treatment uptake. CONCLUSION: The Hlabisa programme successfully extended ART to patients with CD4 ≤ 350 cells/µl, while ensuring that the sickest patients did not experience delays in ART initiation. Treatment programmes must be vigilant to maintain quality of care for the sickest as countries move to treat all patients irrespective of CD4 count.

The right combination - treatment outcomes among HIV-positive patients initiating first-line fixed-dose antiretroviral therapy in a public sector HIV clinic in Johannesburg, South Africa.

BACKGROUND: Long-term antiretroviral therapy (ART) adherence is critical for achieving optimal HIV treatment outcomes. Fixed-dose combination (FDC) single-pill regimens, introduced in South Africa in April 2013, has simplified pill taking. We evaluated treatment outcomes among patients initiated on a FDC compared to a similar multi-pill ART regimen in Johannesburg, South Africa. METHODS: We conducted a retrospective cohort study of ART-naïve HIV-positive non-pregnant adult (≥18 years) patients without tuberculosis who initiated first-line ART on tenofovir and emtricitabine or lamivudine with efavirenz at Themba Lethu Clinic in Johannesburg, South Africa. We compared those initiated on a multi-pill ART regimen (3-5 pills/day; September 1, 2011-August 31, 2012) to those initiated on a FDC ART regimen (one pill/day; September 1, 2013-August 31, 2014). Treatment outcomes included attrition (combination of lost to follow-up and mortality), missed medical visits, and virologic suppression (viral load <400 copies/mL) by 12 months post-ART initiation. Cox proportional hazards models and Poisson regression were used to estimate the association between FDCs vs multiple pills and treatment outcomes. RESULTS: We included 3151 patients in our analysis; 2230 (70.8%) patients initiated multi-pill ART and 921 (29.2%) patients initiated on a FDC. By 12 months post-initiation, attrition (adjusted hazard ratio: 0.98; 95% CI: 0.77-1.24) was similar across regimen types (FDC vs multi-pill). Although not significant, patients on a FDC were marginally more likely to achieve viral suppression by 6 (adjusted relative rate [aRR]: 1.10; 95% CI: 0.99-1.23) and 12 months (aRR: 1.12; 95% CI: 0.92-1.36) on ART. Patients initiated on a FDC were significantly less likely to miss medical visits during the first 12 months of treatment (aRR: 0.66; 95% CI: 0.52-0.83). CONCLUSION: Our results suggest FDCs may have a role to play in supporting patient adherence and medical monitoring through improved medical visit attendance. This may potentially improve treatment outcomes later on in treatment.

County-level assessment of United States kindergarten vaccination rates for measles mumps rubella (MMR) for the 2014-2015 school year.

United States kindergarten measles-mumps-rubella (MMR) vaccination rates are typically reported at the state level by the Centers for Disease Control and Prevention (CDC). The lack of local MMR data prevents identification of areas with low vaccination rates that would be vulnerable to the spread of disease. We collected county-level vaccination rates for the 2014-2015 school year with the objective of identifying these regions. We requested county-level kindergarten vaccination data from state health departments, and mapped these data to visualize geographic patterns in achievement of the 95% MMR vaccination target. We aggregated the county-level data to the state level for comparison against CDC state estimates. We also analyzed the relationship of MMR vaccination level with county-level and state-level poverty (using U.S. census data), using both a national mixed model with state as a random effect, and individual linear regression models by state. We received county vaccination data from 43 states. The median kindergarten MMR vaccination rate was 96.0% (IQR 89-98) across all counties, however, we estimated that 48.4% of the represented counties had vaccination rates below 95%. Our state estimates closely reflected CDC values. Nationally, every 10% increase in under-18 county poverty was associated with a 0.24% increase in MMR vaccination rates (95% CI: -0.07%; 0.54%), but the direction of this relationship varied by state. We found that county data can reveal vaccination trends that are unobservable from state-level data, but we also discovered that the current availability of county-level data is inadequate. Our findings can be used by state health departments to identify target areas for vaccination programs.

Disparities in digital reporting of illness: A demographic and socioeconomic assessment.

Although digital reports of disease are currently used by public health officials for disease surveillance and decision making, little is known about environmental factors and compositional characteristics that may influence reporting patterns. The objective of this study is to quantify the association between climate, demographic and socio-economic factors on digital reporting of disease at the US county level. We reference approximately 1.5 million foodservice business reviews between 2004 and 2014, and use census data, machine learning methods and regression models to assess whether digital reporting of disease is associated with climate, socio-economic and demographic factors. The results show that reviews of foodservice businesses and digital reports of foodborne illness follow a clear seasonal pattern with higher reporting observed in the summer, when most foodborne outbreaks are reported and to a lesser extent in the winter months. Additionally, factors typically associated with affluence (such as, higher median income and fraction of the population with a bachelor's degrees) were positively correlated with foodborne illness reports. However, restaurants per capita and education were the most significant predictors of illness reporting at the US county level. These results suggest that well-known health disparities might also be reflected in the online environment. Although this is an observational study, it is an important step in understanding disparities in the online public health environment.

Global Capacity for Emerging Infectious Disease Detection, 1996-2014.

The speed with which disease outbreaks are recognized is critical for establishing effective control efforts. We evaluate global improvements in the timeliness of outbreak discovery and communication during 2010-2014 as a follow-up to a 2010 report. For all outbreaks reported by the World Health Organization's Disease Outbreak News, we estimate the number of days from first symptoms until outbreak discovery and until first public communication. We report median discovery and communication delays overall, by region, and by Human Development Index (HDI) quartile. We use Cox proportional hazards regression to assess changes in these 2 outcomes over time, along with Loess curves for visualization. Improvement since 1996 was greatest in the Eastern Mediterranean and Western Pacific regions and in countries in the middle HDI quartiles. However, little progress has occurred since 2010. Further improvements in surveillance will likely require additional international collaboration with a focus on regions of low or unstable HDI.

Mortality Risk Factors for Middle East Respiratory Syndrome Outbreak, South Korea, 2015.

As of July 15, 2015, the South Korean Ministry of Health and Welfare had reported 186 case-patients with Middle East respiratory syndrome in South Korea. For 159 case-patients with known outcomes and complete case histories, we found that older age and preexisting concurrent health conditions were risk factors for death.

Online reports of foodborne illness capture foods implicated in official foodborne outbreak reports.

OBJECTIVE: Traditional surveillance systems capture only a fraction of the estimated 48 million yearly cases of foodborne illness in the United States. We assessed whether foodservice reviews on Yelp.com (a business review site) can be used to support foodborne illness surveillance efforts. METHODS: We obtained reviews from 2005 to 2012 of 5824 foodservice businesses closest to 29 colleges. After extracting recent reviews describing episodes of foodborne illness, we compared implicated foods to foods in outbreak reports from the U.S. Centers for Disease Control and Prevention (CDC). RESULTS: Broadly, the distribution of implicated foods across five categories was as follows: aquatic (16% Yelp, 12% CDC), dairy-eggs (23% Yelp, 23% CDC), fruits-nuts (7% Yelp, 7% CDC), meat-poultry (32% Yelp, 33% CDC), and vegetables (22% Yelp, 25% CDC). The distribution of foods across 19 more specific food categories was also similar, with Spearman correlations ranging from 0.60 to 0.85 for 2006-2011. The most implicated food categories in both Yelp and CDC were beef, dairy, grains-beans, poultry and vine-stalk. CONCLUSIONS: Based on observations in this study and the increased usage of social media, we posit that online illness reports could complement traditional surveillance systems by providing near real-time information on foodborne illnesses, implicated foods and locations.