scholarly journals Veterans' Preference in Public Health Agencies of the United States—Declarations by the Committee on Professional Education, American Public Health Association

1945 ◽  
Vol 35 (3) ◽  
pp. 253-256
Keyword(s):  
Public Health ◽  
United States ◽  
Professional Education ◽  
The United States ◽  
American Public Health Association ◽  
Public Health Agencies ◽  
Health Agencies ◽  
Health Association

scholarly journals International Perspectives on COVID-19 Communication Ecologies: Public Health Agencies’ Online Communication in Italy, Sweden, and the United States

2021 ◽  
pp. 000276422199283
Author(s):  
Serena Tagliacozzo ◽  
Frederike Albrecht ◽  
N. Emel Ganapati
Keyword(s):  
Public Health ◽  
United States ◽  
Social Groups ◽  
Online Communication ◽  
The United States ◽  
Negative Consequences ◽  
Public Health Agencies ◽  
Communication Ecology ◽  
Health Agencies ◽  
National Public Health

Communicating during a crisis can be challenging for public agencies as their communication ecology becomes increasingly complex while the need for fast and reliable public communication remains high. Using the lens of communication ecology, this study examines the online communication of national public health agencies during the COVID-19 pandemic in Italy, Sweden, and the United States. Based on content analysis of Twitter data ( n = 856) and agency press releases ( n = 95), this article investigates two main questions: (1) How, and to what extent, did national public health agencies coordinate their online communication with other agencies and organizations? (2) How was online communication from the agencies diversified in terms of targeting specific organizations and social groups? Our findings indicate that public health agencies relied heavily on internal scientific expertise and predominately coordinated their communication efforts with national government agencies. Furthermore, our analysis reveals that agencies in each country differed in how they diversify information; however, all agencies provided tailored information to at least some organizations and social groups. Across the three countries, information tailored for several vulnerable groups (e.g., pregnant women, people with disabilities, immigrants, and homeless populations) was largely absent, which may contribute to negative consequences for these groups.

Case Studies and Caveats

2019 ◽  
pp. 83-101
Author(s):  
Jonathan H. Marks
Keyword(s):  
Public Health ◽  
United States ◽  
Case Studies ◽  
The United States ◽  
Framing Effects ◽  
Noncommunicable Diseases ◽  
Systemic Effects ◽  
Public Health Agencies ◽  
Health Agencies ◽  
Food And Beverage

This chapter outlines several partnership case studies involving the food and beverage sector, especially soda companies. These case studies are drawn from the United States, Britain, and India. The analysis highlights certain problematic features—for example, use of corporate logos, trademarks, and color schemes that are likely to promote consumption of products that are exacerbating obesity and diet-related noncommunicable diseases (NCDs). But, more fundamentally, the analysis ties the case studies to the broader systemic effects discussed in the preceding chapters. These include framing effects, agenda distortion, and impacts on the integrity of and trust in public health agencies.

Infant, Perinatal, Maternal, and Childhood Mortality in the United States: Vital and Health Statistics Monographs, American Public Health Association, by Sam Shapiro, Edward R. Schlesinger, M.D., and Robert E.L. Nesbitt, Jr., M.D. Cambridge, Massachusetts: Harvard University Press, 1968, 388 pp., $7.95

PEDIATRICS ◽  
1969 ◽  
Vol 44 (3) ◽  
pp. 467-468
Author(s):  
Bea J. van den Berg
Keyword(s):  
Public Health ◽  
United States ◽  
Geographic Area ◽  
The United States ◽  
Vital Statistics ◽  
Childhood Mortality ◽  
Mortality Data ◽  
Health Statistics ◽  
American Public Health Association ◽  
Health Association

This book, one in the series of "Vital and Health Statistics Monographs" of the American Public Health Association, is a well documented study of childhood mortality in the United States up to 1964. The data, supplemented by information from special studies, are mainly derived from vital statistics of the United States and upstate New York. Some 80 tables and figures in the text and about half this number in the Appendix review mortality data in different age periods from 1935 to 1964, with emphasis on comparison of the years around 1950 with those around 1960 in relation to such variables as sex, birth weight, ethnic group, cause of death, age of mother, parity, geographic area, and socioeconomic group.

scholarly journals Inclusion of environmentally themed search terms improves Elastic Net regression nowcasts of regional Lyme disease rates

2021 ◽  
Author(s):  
Eric Kontowicz ◽  
Grant Brown ◽  
Jim Torner ◽  
Margaret Carrel ◽  
Kelly Baker ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Lyme Disease ◽  
Disease Burden ◽  
The United States ◽  
Elastic Net ◽  
Disease Symptom ◽  
Public Health Agencies ◽  
Free Data ◽  
Health Agencies

AbstractLyme disease is the most widely reported vector-borne disease in the United States. 95% of human cases are reported in the Northeast and upper Midwest. Human cases typically occur in the spring and summer months when an infected nymph Ixodid tick takes a blood meal. Current federal surveillance strategies report data on an annual basis, leading to nearly a year lag in national data reporting. These lags in reporting make it difficult for public health agencies to assess and plan for the current burden of Lyme disease. Implementation of a nowcasting model, using historical data to predict current trends, provides a means for public health agencies to evaluate current Lyme disease burden and make timely priority-based budgeting decisions. The objective of this study was to develop and compare the performance of nowcasting models using free data from Google Trends and Centers of Disease Control and Prevention surveillance reports for Lyme Disease. We developed two sets of elastic net models for five regions of the United States first using monthly proportional hit data from 21 disease symptoms and tick related terms and second using monthly proportional hit data from all terms identified via Google correlate plus 21 disease symptom and vector terms. Elastic net models using the larger term list were highly accurate (Root Mean Square Error: 0.74, Mean Absolute Error: 0.52, R2: 0.97) for four of the five regions of the United States. Including these more environmental terms improved accuracy 1.33-fold while reducing error 0.5-fold compared to predictions from models using disease symptom and vector terms alone. Models using Google data similar to this could help local and state public health agencies accurately monitor Lyme disease burden during times of reporting lag from federal public health reporting agencies.

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