scholarly journals Creation of Center for Public Health and Medical Prevention of Moscow as a structure for population-level prevention in metropolis

2021 ◽  
Vol 2 (1) ◽  
pp. 7-21
Author(s):  
Larisa А. Larisa А. Mylnikova ◽  
Natalya N. Kamynina
Keyword(s):  
Public Health ◽  
Organizational Support ◽  
Urban Policy ◽  
Large Scale ◽  
Healthy Lifestyle ◽  
Population Level ◽  
Noncommunicable Diseases ◽  
Management Decision ◽  
Medical Prevention ◽  
Health Authorities

Introduction. Since 2011, Moscow has been implementing a three-level model for prevention of noncommunicable diseases. At the first (population) level, as part of interagency interaction, health authorities are developing measures to promote population's commitment to a healthy lifestyle. Aims. To provide rationale for management decision on creation of the Center for Public Health and Medical Prevention of Moscow in State Budgetary Institution “Research Institute for Healthcare Organization and Medical Management of Moscow Healthcare Department”. The goal of the Center is to develop new urban policy in improving public health based on interdepartmental interaction by providing scientific, methodological and organizational support to promote population’s commitment to a healthy lifestyle. Materials and methods. Authors analyzed and assessed development issues of primary prevention at the population level using open data on the Internet, statistical databases of Rosstat and Mosgorstat. Content, statistical and documentary analyses were also used. Results. Currently, Moscow puts an emphasis on prevention, and for this purpose implemented a three-tier model for prevention of non-communicable diseases. At the population level, as part of interdepartmental interaction, it is required to develop measures aimed at improving healthcare, creating a health-preserving environment in the city, and forming a commitment to a healthy lifestyle among the population. Implementation gaps to a decree have been narrowed; and health authorities have created an institution that works towards the goal of strengthening public health in Moscow, covering the entire population of Moscow, and that interacts in the interests of healthcare with government bodies, departments, media and civil society. The current situation, including challenges due to COVID-19 pandemic, required wider participation of authorities and departments, leadership of administrative districts in strengthening public health, coordination and monitoring of all business processes to improve public health. Conclusion. It has been substantiated that public participation in preventive measures is not enough. To solve the issues one should develop and implement large-scale programs and projects to improve public health with more active involvement of authorities and departments of administrative districts, consultative and methodological support, taking into account the existing territorial characteristics of administrative and municipal districts of Moscow, including improving health quality of workers.

scholarly journals Measuring the scientific effectiveness of contact tracing: Evidence from a natural experiment

2021 ◽  
Vol 118 (33) ◽  
pp. e2100814118
Author(s):  
Thiemo Fetzer ◽  
Thomas Graeber
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Natural Experiment ◽  
Controlled Trial ◽  
Contact Tracing ◽  
Public Health Approach ◽  
The Public ◽  
Random Breakdown ◽  
Randomized Controlled ◽  
Health Authorities

Contact tracing has for decades been a cornerstone of the public health approach to epidemics, including Ebola, severe acute respiratory syndrome, and now COVID-19. It has not yet been possible, however, to causally assess the method’s effectiveness using a randomized controlled trial of the sort familiar throughout other areas of science. This study provides evidence that comes close to that ideal. It exploits a large-scale natural experiment that occurred by accident in England in late September 2020. Because of a coding error involving spreadsheet data used by the health authorities, a total of 15,841 COVID-19 cases (around 20% of all cases) failed to have timely contact tracing. By chance, some areas of England were much more severely affected than others. This study finds that the random breakdown of contact tracing led to more illness and death. Conservative causal estimates imply that, relative to cases that were initially missed by the contact tracing system, cases subject to proper contact tracing were associated with a reduction in subsequent new infections of 63% and a reduction insubsequent COVID-19–related deaths of 66% across the 6 wk following the data glitch.

scholarly journals Can Wastewater be Used to Improve our COVID-19 Surveillance Efforts?

CommonHealth ◽  
2020 ◽  
Vol 1 (3) ◽  
pp. 141-147
Author(s):  
Shannon McGinnis ◽  
Shane Mclouglin ◽  
Tiffany Buturla ◽  
Nishita D'Souza ◽  
José Logo ◽  
...  
Keyword(s):  
Public Health ◽  
Control Strategies ◽  
Population Level ◽  
The United States ◽  
Control Measures ◽  
Clear Understanding ◽  
Health Control ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Wastewater Samples

As the spread of COVID-19 continues to significantly impact daily life in the United States and globally, there is a need for a clear understanding of disease prevalence in communities. Traditional methods that rely on counting individual cases often result in underreporting due to limited access to testing or healthcare. This issue is further exacerbated by the spread of COVID-19 by asymptomatic or presymptomatic individuals who may not seek testing. Historically, wastewater surveillance has been used to provide population-level data on the prevalence of infectious diseases in communities. Data collected through wastewater surveillance has been used to advise public health control measures, such as vaccination campaigns, and to detect local outbreaks before cases are reported to public health authorities. For this reason, researchers around the globe have been analyzing wastewater samples for SARS-CoV-2 to assist in our response to the existing COVID-19 pandemic. This commentary discusses the potential utility of wastewater-based surveillance to advise public health control strategies for COVID-19 and discusses how it may be used to strengthen local surveillance efforts in Philadelphia.

The role of volunteerism in the prevention of chronic noncommunicable diseases and in increasing adherence to a healthy lifestyle

2020 ◽  
Vol 1 (2) ◽  
pp. 115-120
Author(s):  
E. V. Chaplygina ◽  
S. V. Shlyk ◽  
O. I. Sylka ◽  
A. N. Fisunova
Keyword(s):  
Large Scale ◽  
Preventive Measures ◽  
Healthy Lifestyle ◽  
Public Awareness ◽  
Social Activity ◽  
Noncommunicable Diseases ◽  
Medical Volunteerism ◽  
Medical Volunteers ◽  
Medical University

Medical volunteerism gives an opportunity for future specialists to provide free assistance to practical healthcare, as well as to acquire personal and professional qualities required for a student at a medical university. Medical volunteers are implementing many large-scale campaigns and projects aimed at the prevention of chronic non-communicable diseases and other socially significant diseases, and at promoting a healthy lifestyle. The results of the work are to increase public awareness, as preventive measures are an important component of the healthcare system, aimed at the formation of the population's medical and social activity and motivation for a healthy lifestyle.

scholarly journals A methodological approach to the analysis of egocentric social networks in public health research: a practical example

2016 ◽  
Vol 55 (4) ◽  
pp. 256-263 ◽  
Author(s):  
Janet Klara Djomba ◽  
Lijana Zaletel-Kragelj
Keyword(s):  
Public Health ◽  
Social Networks ◽  
Social Network ◽  
Numerical Analysis ◽  
Large Scale ◽  
Healthy Lifestyle ◽  
Methodological Approach ◽  
Size Composition ◽  
Public Health Research ◽  
Population Based

Abstract Introduction Research on social networks in public health focuses on how social structures and relationships influence health and health-related behaviour. While the sociocentric approach is used to study complete social networks, the egocentric approach is gaining popularity because of its focus on individuals, groups and communities. Methods One of the participants of the healthy lifestyle health education workshop ‘I’m moving’, included in the study of social support for exercise was randomly selected. The participant was denoted as the ego and members of her/his social network as the alteri. Data were collected by personal interviews using a self-made questionnaire. Numerical methods and computer programmes for the analysis of social networks were used for the demonstration of analysis. Results The size, composition and structure of the egocentric social network were obtained by a numerical analysis. The analysis of composition included homophily and homogeneity. Moreover, the analysis of the structure included the degree of the egocentric network, the strength of the ego-alter ties and the average strength of ties. Visualisation of the network was performed by three freely available computer programmes, namely: Egonet.QF, E-net and Pajek. The computer programmes were described and compared by their usefulness. Conclusion Both numerical analysis and visualisation have their benefits. The decision what approach to use is depending on the purpose of the social network analysis. While the numerical analysis can be used in large-scale population-based studies, visualisation of personal networks can help health professionals at creating, performing and evaluation of preventive programmes, especially if focused on behaviour change.

scholarly journals Managing Pandemics with Health Informatics

2021 ◽  
Vol 30 (01) ◽  
pp. 069-074
Author(s):  
Brian E. Dixon ◽  
John H. Holmes ◽  
Keyword(s):  
Public Health ◽  
Health Informatics ◽  
Selection Process ◽  
Critical Role ◽  
Population Level ◽  
The Body ◽  
Editorial Committee ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Internal Operations

Summary Objective: To summarize significant research contributions on managing pandemics with health informatics published in 2020. Methods: An extensive search using PubMed and Scopus was conducted to identify peer-reviewed articles published in 2020 that examined health informatics systems used during the global COVID-19 pandemic. The selection process comprised three steps: 1) 15 candidate best papers were first selected by the two section editors; 2) external reviewers from internationally renowned research teams reviewed each candidate best paper; and 3) the final selection of three best papers was conducted by the editorial committee of the International Medical Informatics Association (IMIA) Yearbook. Results: Selected best papers represent the important and diverse ways that health informatics supported clinical and public health responses to the global COVID-19 pandemic. Selected papers represent four groups of papers: 1) Use of analytics to screen, triage, and manage patients; 2) Use of telehealth and remote monitoring to manage patients and populations; 3) Use of EHR systems and administrative systems to manage internal operations of a hospital or health system; and 4) Use of informatics methods and systems by public health authorities to capture, store, manage, and visualize population-level data and information. Conclusion: Health informatics played a critical role in managing patients and populations during the COVID-19 pandemic. Health care and public health organizations both leveraged available information systems and standards to rapidly identify cases, triage infected individuals, and monitor population trends. The selected best papers represent a fraction of the body of knowledge stemming from COVID-19, most of which is focused on pandemic response. Future work will be needed to help the world recover from the pandemic and strengthen the health information infrastructure in preparation for the next pandemic.

scholarly journals Mass Sporting and Physical Activity Events—Are They “Bread and Circuses” or Public Health Interventions to Increase Population Levels of Physical Activity?

2007 ◽  
Vol 4 (2) ◽  
pp. 193-202 ◽  
Author(s):  
Niamh M. Murphy ◽  
Adrian Bauman
Keyword(s):  
Public Health ◽  
Physical Activity ◽  
Large Scale ◽  
Grey Literature ◽  
Health Benefit ◽  
Population Level ◽  
Evaluation Framework ◽  
Sporting Events ◽  
The Individual ◽  
Evidence Of Impact

Background:Large-scale, one-off sporting or physical activity (PA) events are often thought to impact population PA levels. This article reviews the evidence and explores the nature of the effect.Methods:A search of the published and grey literature was conducted to July 2005 using relevant databases, web sources, and personal contacts. Impacts are described at the individual, societal and community, and environmental levels.Results:Few quality evaluations have been conducted. While mass sporting events appear to influence PA-related infrastructure, there is scant evidence of impact on individual participation at the population level. There is some evidence that events promoting active transport can positively affect PA.Conclusions:The public health potential of major sporting and PA events is often cited, but evidence for public health benefit is lacking. An evaluation framework is proposed.

scholarly journals Infection Testing at Scale: An Examination of Pooled Testing Diagnostics

2021 ◽  
Vol 46 (1) ◽  
pp. 13-26
Author(s):  
Tarun Jain ◽  
Bijendra Nath Jain
Keyword(s):  
Public Health ◽  
Infection Rate ◽  
Large Scale ◽  
Early Stage ◽  
Infection Prevalence ◽  
Additional Time ◽  
Pooled Testing ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Wide Testing

Executive Summary In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals without adequate testing kits. We propose a testing protocol to accelerate infection diagnostics by combining multiple samples, and in case of positive results, re-test individual samples. The key insight is that a negative result in the first stage implies negative infection for all individuals. Thus, a single test could rule out infection in multiple individuals. Using simulations, we show that this protocol reduces the required number of testing kits, especially when the infection rate is low, alleviating a key bottleneck for public health authorities in times of pandemics and epidemics such as COVID-19. Our proposed protocol is expected to be more effective when the infection rate is low, which suggests that it is better suited for early stage and large-scale, population-wide testing. However, the managerial trade-off is that the protocol has costs in additional time for returning test results and an increased number of false negatives. We discuss applications of pooled testing in understanding population-wide testing to understand infection prevalence, to diagnose infections in high-risk groups of individuals, and to identify disease cold spots.

Behavioral Consequences of Disasters: A Five-Stage Model of Population Behavior

2014 ◽  
Vol 8 (6) ◽  
pp. 497-504
Author(s):  
Sasha Rudenstine ◽  
Sandro Galea
Keyword(s):  
Public Health ◽  
Qualitative Analysis ◽  
Population Health ◽  
Large Scale ◽  
Traumatic Events ◽  
Population Level ◽  
Stage Model ◽  
Improve Population Health ◽  
The World ◽  
The Moment

ABSTRACTObjectiveWe propose a model of population behavior in the aftermath of disasters.MethodsWe conducted a qualitative analysis of an empirical dataset of 339 disasters throughout the world spanning from 1950 to 2005.ResultsWe developed a model of population behavior that is based on 2 fundamental assumptions: (i) behavior is predictable and (ii) population behavior will progress sequentially through 5 stages from the moment the hazard begins until is complete.ConclusionsUnderstanding the progression of population behavior during a disaster can improve the efficiency and appropriateness of institutional efforts aimed at population preservation after large-scale traumatic events. Additionally, the opportunity for population-level intervention in the aftermath of such events will improve population health. (Disaster Med Public Health Preparedness. 2014;8:497-504)

PENERAPAN CLUSTERING PADA PENDUDUK YANG MEMPUNYAI KELUHAN KESEHATAN DENGAN DATAMINING K-MEANS

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Nurul Rofiqo ◽  
Agus Perdana Windarto ◽  
Dedy Hartama
Keyword(s):  
Public Health ◽  
Data Mining ◽  
Population Level ◽  
Research Data ◽  
Health Complaints ◽  
Public Health Services ◽  
National Statistics ◽  
Central Java ◽  
Indonesian Population ◽  
The Government

This study aims to utilize Clushtering Algorithm in grouping the number of people who have health complaints with the K-means algorithm in Indonesia. The source of this research data was collected based on the documents of the provincial population which had health complaints produced by the National Statistics Agency. The data used in this study are data from 2013-2017 consisting of 34 provinces. The method used in this research is K-means Algorithm. Data will be processed by clushtering in 3 clushter, namely clusther high health complaints, clusther moderate and low health complaints. Centroid data for high population level clusters 37.48, Centroid data for moderate population level clusters 27.08, and Centroid data for low population level clusters 14.89. So that obtained an assessment based on the population index that has health complaints with 7 provinces of high health complaints, namely Central Java, Yogyakarta, Bali, West Nusa Tenggara, East Nusa Tenggara, South Kalimantan, Gorontalo, 18 provinces of moderate health complaints, and 9 other provinces including low health complaints. This can be an input to the government to give more attention to residents in each region who have high health complaints through improving public health services so that the Indonesian population becomes healthier without health complaints.Keywords: data mining, health complaints, clustering, K-means, Indonesian residents

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