On Linkages; Using GIS for Administrative Decision-Making in a Local Public Health Setting

Abstract Since spring 2020, Ukraine has experienced at least two COVID-19 waves and has just entered a third wave in autumn 2021. The use of real-time genomic epidemiology has enabled the tracking of SARS-CoV-2 circulation patterns worldwide, thus informing evidence-based public health decision making, including implementation of travel restrictions and vaccine rollout strategies. However, insufficient capacity for local genetic sequencing in Ukraine and other Lower and Middle-Income countries limit opportunities for similar analyses. Herein, we report local sequencing of 24 SARS-CoV-2 genomes from patient samples collected in Kyiv in July 2021 using Oxford Nanopore MinION technology. Together with other published Ukrainian SARS-COV-2 genomes sequenced mostly abroad, our data suggest that the second wave of the epidemic in Ukraine (February-April 2021) was dominated by the Alpha variant of concern (VOC), while the beginning of the third wave has been dominated by the Delta VOC. Furthermore, our phylogeographic analysis revealed that the Delta variant was introduced into Ukraine in summer 2021 from multiple locations worldwide, with most introductions coming from Central and Eastern European countries. This study highlights the need to urgently integrate affordable and easily-scaled pathogen sequencing technologies in locations with less developed genomic infrastructure, in order to support local public health decision making.

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School Closure Decisions Made by Local Health Department Officials During the 2009 H1N1 Influenza Outbreak

Disaster Medicine and Public Health Preparedness ◽

10.1017/dmp.2015.72 ◽

2015 ◽

Vol 9 (4) ◽

pp. 464-471 ◽

Cited By ~ 2

Author(s):

Harvey Kayman ◽

Sarah Salter ◽

Maanvi Mittal ◽

Winifred Scott ◽

Nicholas Santos ◽

...

Keyword(s):

Public Health ◽

Decision Making ◽

H1n1 Influenza ◽

School Closure ◽

Local Public Health ◽

Public Health Decision ◽

Health Decision ◽

Decision Making Processes ◽

Public Health Officials ◽

2009 H1n1

AbstractObjectivesThe goal of this study was to gain insights into the decision-making processes used by California public health officials during real-time crises. The decision-making processes used by California public health officials during the 2009 H1N1 influenza pandemic were examined by a survey research team from the University of California Berkeley.MethodsThe survey was administered to local public health officials in California. Guidelines published by the Centers for Disease Control and Prevention had recommended school closure, and local public health officials had to decide whether to follow these recommendations. Chi-squared tests were used to make comparisons in the descriptive statistics.ResultsThe response rate from local public health departments was 79%. A total of 73% of respondents were involved in the decision-making process. Respondents stated whether they used or did not use 15 ethical, logistical, and political preselected criteria. They expressed interest in receiving checklists and additional training in decision-making.ConclusionsPublic health decision-makers do not appear to have a standard process for crisis decision-making and would benefit from having an organized decision-making model. The survey showed that ethical, logistical, and political criteria were considered but were not prioritized in any meaningful way. A new decision-making tool kit for public health decision-makers plus implementation training is warranted. (Disaster Med Public Health Preparedness. 2015;9:464–471)

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The use of evidence in English local public health decision-making: a systematic scoping review

Implementation Science ◽

10.1186/s13012-017-0577-9 ◽

2017 ◽

Vol 12 (1) ◽

Cited By ~ 14

Author(s):

Dylan Kneale ◽

Antonio Rojas-García ◽

Rosalind Raine ◽

James Thomas

Keyword(s):

Public Health ◽

Decision Making ◽

Scoping Review ◽

Local Public Health ◽

Public Health Decision ◽

Health Decision Making ◽

Health Decision

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How can additional secondary data analysis of observational data enhance the generalisability of meta‐analytic evidence for local public health decision making?

Research Synthesis Methods ◽

10.1002/jrsm.1320 ◽

2018 ◽

Vol 10 (1) ◽

pp. 44-56 ◽

Cited By ~ 4

Author(s):

Dylan Kneale ◽

James Thomas ◽

Alison O'Mara‐Eves ◽

Richard Wiggins

Keyword(s):

Public Health ◽

Decision Making ◽

Data Analysis ◽

Observational Data ◽

Secondary Data ◽

Secondary Data Analysis ◽

Local Public Health ◽

Public Health Decision ◽

Health Decision Making ◽

Health Decision

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Local Decision Making for Implementing Social Distancing in Response to Outbreaks

Public Health Reports ◽

10.1177/0033354918819755 ◽

2019 ◽

Vol 134 (2) ◽

pp. 150-154 ◽

Cited By ~ 6

Author(s):

Rebecca Katz ◽

Andrea Vaught ◽

Samuel J. Simmens

Keyword(s):

Public Health ◽

Decision Making ◽

Online Survey ◽

Health Impact ◽

The United States ◽

Health Departments ◽

Local Public Health ◽

Social Distancing ◽

Local Decision ◽

Population Demographic

Objectives: Social distancing is the practice of restricting contact among persons to prevent the spread of infection. This study sought to (1) identify key features of preparedness and the primary concerns of local public health officials in deciding to implement social distancing measures and (2) determine whether any particular factor could explain the widespread variation among health departments in responses to past outbreaks. Methods: We conducted an online survey of health departments in the United States in 2015 to understand factors influencing health departments’ decision making when choosing whether to implement social distancing measures. We paired survey results with data on area population demographic characteristics and analyzed them with a focus on broad trends. Results: Of 600 health departments contacted, 150 (25%) responded. Of these 150 health departments, 63 (42%) indicated that they had implemented social distancing in the past 10 years. Only 10 (7%) health departments had a line-item budget for isolation or quarantine. The most common concern about social distancing was public health impact (n = 62, 41%). Concerns about law, politics, finances, vulnerable populations, and sociocultural issues were each identified by 7% to 10% of health departments. We were unable to clearly predict which factors would influence these decisions. Conclusions: Variations in the decision to implement social distancing are likely the result of differences in organizational authority and resources and in the primary concerns about implementing social distancing. Research and current social distancing guidelines for health departments should address these factors.

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