scholarly journals Dynamic Metrics for Public Health Surveillance Are Imperative to Gain Control of the COVID-19 Pandemic in America: Longitudinal Trend Analysis (Preprint)

10.2196/24286 ◽  
2020 ◽  
Author(s):  
Lori Ann Post ◽  
Tariq Ziad Issa ◽  
Michael J Boctor ◽  
Charles B Moss ◽  
Robert L Murphy ◽  
...  
Keyword(s):  
Public Health ◽  
Trend Analysis ◽  
Public Health Surveillance ◽  
Gain Control ◽  
Health Surveillance ◽  
Longitudinal Trend ◽  
Dynamic Metrics

scholarly journals Middle East and North Africa SARS-CoV-2 Surveillance: A Longitudinal Trend Analysis (Preprint)

2020 ◽  
Author(s):  
Lori Post ◽  
Emily Marogi ◽  
Charles B Moss ◽  
Robert Leo Murphy ◽  
Michael G Ison ◽  
...  
Keyword(s):  
Public Health ◽  
Saudi Arabia ◽  
Middle East ◽  
Trend Analysis ◽  
North Africa ◽  
Public Health Surveillance ◽  
Generalized Method Of Moments ◽  
Health Surveillance ◽  
Infection Rates ◽  
Longitudinal Trend

BACKGROUND The COVID-19 global pandemic has disrupted the lives of millions and forced countries to devise public health policies to reduce the pace of transmission. In the Middle East and North Africa, falling oil prices, disparities in wealth and public health infrastructure, and large refugee populations have significantly increased the COVID-19 disease burden. In light of these exacerbating factors, public health surveillance is particularly necessary to help leaders understand and implement effective disease control policies to reduce Sars-CoV-2 persistence and transmission. OBJECTIVE The goal of this study is to provide advanced surveillance metrics, in combination with traditional surveillance, for COVID-19 transmission that account for weekly shifts in the pandemic speed, acceleration, jerk and persistence, to better understand country risk for explosive growth and to better inform those who are managing the pandemic. Existing surveillance coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until an effective vaccine is developed. METHODS Using a longitudinal trend analysis study design, we extracted 30 days of COVID-19 data from public health registries. We use an empirical difference equation to measure the daily number of cases in the Middle East and North Africa as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments (GMM) approach by implementing the Arellano-Bond estimator in R. RESULTS The regression Wald statistic is significant (χ^2 (5)=859.5, P<.001). The Sargan test is not significant, failing to reject the validity of over identifying restrictions (χ^2 (294)= 16 P=.99). Countries with the highest cumulative caseload of the novel coronavirus include Iran, Iraq, Saudi Arabia, and Israel with 530,380, 426,634, 342,202, and 303,109 cases respectively. Many of the smaller countries in MENA have higher infection rates than those countries with the highest caseloads. Oman has 33.3 new infections per 100,000 population while Bahrain has 12.1, Libya has 14, and Lebanon has 14.6. In order of most to least number of cumulative deaths since January 2020, Iran, Iraq, Egypt, and Saudi Arabia have 30,375, 10,254, 6,120, and 5,185 respectively. Israel, Bahrain, Lebanon, and Oman had the highest rates of COVID-19 persistence which are the number of new infections statistically related to new infections 7 days ago. Bahrain had positive speed, acceleration and jerk signaling the potential for explosive growth. CONCLUSIONS Static and dynamic public health surveillance metrics provide a more complete picture of pandemic progression across countries in MENA. Static measures capture data at a given point in time such as infection rates and death rates. By including speed, acceleration, jerk, and 7-day persistence, public health officials may design policy with an eye to the future. Iran, Iraq, Saudi Arabia, and Israel all demonstrated the highest rate of infections, acceleration, jerk, and 7-day persistence rates prompting public health leaders to increase prevention efforts. CLINICALTRIAL

National Retail Data Monitor for Public Health Surveillance

2004 ◽  
Author(s):  
Michael M. Wagner ◽  
F-C. Tsui ◽  
J. Espino ◽  
W. Hogan ◽  
J. Hutman ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Health Surveillance

Disaggregation of Latina/o Child and Adult Health Data: A Systematic Review of Public Health Surveillance Surveys in the United States

2021 ◽  
Vol 40 (1) ◽  
pp. 61-79
Author(s):  
Carmela Alcántara ◽  
Shakira F. Suglia ◽  
Irene Perez Ibarra ◽  
A. Louise Falzon ◽  
Elliot McCullough ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Systematic Review ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Data ◽  
Health Surveillance ◽  
Adult Health

Assessment of genotoxic effects on elderly populations exposed to high traffic areas: Results for supporting public health surveillance

2019 ◽  
Vol 179 ◽  
pp. 108752
Author(s):  
Boscolli Barbosa Pereira ◽  
Vanessa Santana Vieira Santos ◽  
Érica Prado Domingues ◽  
Guilherme Gomes Silva ◽  
Paolla Brandão da Cunha ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Genotoxic Effects ◽  
Elderly Populations

Public Health Surveillance for Coccidioidomycosis in Arizona

2007 ◽  
Vol 1111 (1) ◽  
pp. 96-102 ◽  
Author(s):  
R. H. SUNENSHINE ◽  
S. ANDERSON ◽  
L. ERHART ◽  
A. VOSSBRINK ◽  
P. C. KELLY ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Health Surveillance

scholarly journals A COVID ‐19‐ready public health surveillance system: The FDA 's Sentinel System

2021 ◽  
Author(s):  
Noelle M. Cocoros ◽  
Candace C. Fuller ◽  
Sruthi Adimadhyam ◽  
Robert Ball ◽  
Jeffrey S. Brown ◽  
...  
Keyword(s):  
Public Health ◽  
Surveillance System ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Public Health Surveillance System

scholarly journals Digital Disease Detection — Harnessing the Web for Public Health Surveillance

2009 ◽  
Vol 360 (21) ◽  
pp. 2153-2157 ◽  
Author(s):  
John S. Brownstein ◽  
Clark C. Freifeld ◽  
Lawrence C. Madoff
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Disease Detection ◽  
Digital Disease Detection ◽  
The Web
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