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Harmful algal blooms (HABs) are the rapid growth of algae that can produce toxic or harmful effects in people and animals. Potential health effects include respiratory illness, gastrointestinal illness, skin and eye irritation, and sometimes more severe toxic effects such as liver damage. Defining HAB exposure and related illness is challenging for many reasons, including characterizing the exposure. Large electronic health record databases present an opportunity to study health encounters specifically related to HAB exposure through querying medical diagnostic codes. We queried the MarketScan Research Databases between January 2009 and April 2019 for use of the International Classification of Diseases (ICD) codes for HAB exposure. We found a total of 558 records that used either the ICD-9 or ICD-10 code for HAB exposure. Respiratory illness was most commonly reported along with the HAB exposure code. Use of HAB exposure codes showed seasonal fluctuations during 2012–2019. We found that although the HAB-related ICD-9 and ICD-10 codes were used infrequently, they were most often recorded during bloom seasons in warmer months. This analysis is the first that utilizes a large-scale national database of de-identified health records to understand the use of medical diagnostic codes related to algae exposure.

Coronavirus disease 2019 (COVID-19) is a viral respiratory illness caused by SARS-CoV-2. During January 21-July 25, 2020, in response to official requests for assistance with COVID-19 emergency public health response activities, CDC deployed 208 teams to assist 55 state, tribal, local, and territorial health departments. CDC deployment data were analyzed to summarize activities by deployed CDC teams in assisting state, tribal, local, and territorial health departments to identify and implement measures to contain SARS-CoV-2 transmission (1). Deployed teams assisted with the investigation of transmission in high-risk congregate settings, such as long-term care facilities (53 deployments; 26% of total), food processing facilities (24; 12%), correctional facilities (12; 6%), and settings that provide services to persons experiencing homelessness (10; 5%). Among the 208 deployed teams, 178 (85%) provided assistance to state health departments, 12 (6%) to tribal health departments, 10 (5%) to local health departments, and eight (4%) to territorial health departments. CDC collaborations with health departments have strengthened local capacity and provided outbreak response support. Collaborations focused attention on health equity issues among disproportionately affected populations (e.g., racial and ethnic minority populations, essential frontline workers, and persons experiencing homelessness) and through a place-based focus (e.g., persons living in rural or frontier areas). These collaborations also facilitated enhanced characterization of COVID-19 epidemiology, directly contributing to CDC data-informed guidance, including guidance for serial testing as a containment strategy in high-risk congregate settings, targeted interventions and prevention efforts among workers at food processing facilities, and social distancing.

Caffeine, a mild central nervous system stimulant, is a natural component of common hot and cold beverages like coffee, tea, sodas and cocoa. Animal studies have demonstrated caffeine’s teratogenic effects when administered at high concentrations; however, epidemiologic studies have yielded inconsistent results in humans. Because caffeine containing beverages are commonly consumed by pregnant women, we examined the prevalence of use and explored possible associations of maternal caffeine consumption with cardiovascular malformations in 3,274 cases matched with 3,519 controls enrolled in the 1981-89 “Baltimore-Washington Infant Study,” a population-based case-control investigation. We explored several key aspects of the quality of and distribution of measurements of caffeine consumption among mothers in the study population. We concluded with recommendations for refining data collection to reduce potential bias associated with assessing both caffeine content and changes in caffeine consumption during pregnancy in order to inform future research studies and birth defects/adverse birth outcomes surveillance programs.