Public Health Strategies and Surveillance

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Questions and Answers

Which of the following is a strategy for preventing cervical cancer?

Pap smears (correct)

Antibiotic treatments

Bacterial screening

Vaccination against measles

What is a crucial consideration when choosing combinations of prevention strategies?

Popularity among the population

Public interest

Involvement of media

Available resources (correct)

Which component is NOT part of effective public health surveillance?

Analysis of data

Guiding public health response

Personal opinions from community leaders (correct)

Dissemination of findings

What is the purpose of comparing the effectiveness of public health programs?

To generate evidence for best practices Signup and view all the answers

What type of diseases can benefit from antibiotic treatment of case contacts to prevent illness?

Bacterial infections like Gonorrhea Signup and view all the answers

Which of the following is an example of prevention through food supplementation?

Folic acid supplement for Neural tube defects Signup and view all the answers

What characteristic is NOT used in the analysis of public health surveillance data?

Personal preferences Signup and view all the answers

Which of the following best describes evidence-based public health?

Using collected data to support health actions Signup and view all the answers

What is a primary short-term need that public health surveillance data serves?

To respond to an acute infectious disease outbreak Signup and view all the answers

Which of the following is a challenge in public health surveillance?

Insufficient single data systems for comprehensive information Signup and view all the answers

How has technology recently impacted public health surveillance?

It has enhanced integrated sharing of health data across systems. Signup and view all the answers

Which type of software has improved analytical capabilities in public health?

Geographic information systems (GIS) Signup and view all the answers

What role does informatics play in public health practice?

It is a foundational science for effective public health. Signup and view all the answers

What critical data type has been essential for understanding drug overdose issues?

Mortality data Signup and view all the answers

How can public health surveillance data influence public understanding of health threats?

Through effective communication and data visualization Signup and view all the answers

Which system is NOT typically used for identifying overdoses and emerging threats?

Financial auditing systems Signup and view all the answers

What benefit does Electronic Laboratory Reporting (ELR) provide to Public Health?

Improvements in completeness and timeliness of disease reporting Signup and view all the answers

What is a consequence of rapidly transmitted electronic case reports?

Lack of error checking and missing data collection Signup and view all the answers

How does a local-level user benefit from simultaneous access to raw data from multiple sources?

They can interpret anomalies in surveillance data based on local conditions. Signup and view all the answers

What defines Electronic Laboratory Reporting (ELR) as an enhanced passive reporting system?

A formatted message is sent when lab results meet specific criteria. Signup and view all the answers

What challenge arises from the simultaneous availability of raw data to multiple agencies?

Confusion regarding the interpretation of local data Signup and view all the answers

What is a significant advantage of electronic case reports over traditional methods?

They allow for quicker communication to public health authorities. Signup and view all the answers

What capability does a user at a higher level gain from accessing widespread data?

Ability to identify multi-jurisdictional outbreaks Signup and view all the answers

How does technology facilitate disease detection through case reports?

By allowing rapid transmission of data to health authorities Signup and view all the answers

What is the primary purpose of Syndromic Surveillance Systems?

To support detection and characterization of community disease outbreaks Signup and view all the answers

Which data elements are commonly used in syndromic surveillance?

Chief complaints and diagnosis codes Signup and view all the answers

How are emergency department visits categorized in syndromic surveillance?

Using words from patients' chief complaints and nurse's notes Signup and view all the answers

What types of additional data sources can enhance the analytic environment of syndromic surveillance?

Death certificates and poison center consultations Signup and view all the answers

Which of the following best describes the nature of data used in syndromic surveillance?

Unfiltered, real-time electronic records without individual identifiers Signup and view all the answers

What type of visits were originally the most common data source for syndromic surveillance?

Emergency department visits Signup and view all the answers

What role does syndromic data play in public health?

It enables real-time monitoring of health trends and outbreaks. Signup and view all the answers

What is a common characteristic of the analysis conducted on syndromic data?

It identifies statistically significant clusters in specified time frames. Signup and view all the answers

What type of data does the Human Protein Reference Database (HPRD) primarily focus on?

Domain architecture and post-translational modifications of proteins Signup and view all the answers

Which database provides a global archive for protein structures and other macromolecules?

Protein Data Bank (PDB) Signup and view all the answers

What is the primary function of the STRING database?

Accessing known and predicted protein–protein interactions Signup and view all the answers

Which of the following databases is focused on large quantities of human proteomics data?

ProteomicsDB Signup and view all the answers

What is one of the potential benefits of bioinformatics?

Discovering future drug targets Signup and view all the answers

Which type of database primarily provides information about interactions and pathways of biological processes?

Pathway databases Signup and view all the answers

How does bioinformatics contribute to genetic engineering of plants?

By aiding genetic manipulation for disease resistance in plants Signup and view all the answers

Which of the following statements is true regarding the DATABASE of Interacting Proteins (DIP)?

It documents experimental protein-protein interactions involved in biological processes. Signup and view all the answers

What was the main aim of the Human Genome Project (HGP)?

To acquire the human genome Signup and view all the answers

Which sequencing technique was pivotal in completing the first human genome sequence?

Sanger sequencing Signup and view all the answers

What significant advancement in sequencing technology occurred in 2005?

Launch of 454-genome sequencer Signup and view all the answers

By 2010, what capability did a single gene chip possess?

Detecting 1 million variations Signup and view all the answers

What was the approximate cost of completing the Human Genome Project?

$3 trillion Signup and view all the answers

What does the Ion Torrent technology utilize for sequencing?

Semiconductor technology Signup and view all the answers

What is one of the recent focuses after the completion of the Human Genome Project?

Annotation of disease-related information onto chromosomes Signup and view all the answers

Which of the following is NOT a type of next-generation sequencing technology mentioned?

Sanger sequencer Signup and view all the answers

Study Notes

SN6006 Information Technology in Healthcare

Course title: SN6006 Information Technology in Healthcare
Course subtitle: Bioinformatics and Public Health Informatics
Lecturer: Dr. WK Chan ([email protected])
Subject: Information Technology in Healthcare, Bioinformatics, Public Health Informatics

Introduction

Bioinformatics: The biological application of information technology, focusing on data storage and analytics.
Bioinformatics involves researching, developing, or applying computational tools and approaches to expand the use of biological, medical, behavioral, or health data. This includes acquiring, storing, organizing, archiving, analyzing, or visualizing this data.
Computational Biology: The application of information technology in understanding biology, emphasizing analytical algorithms to analyze and understand biological processes.
The field merges biology, computer science, and information technology to form a single discipline.

Interdisciplinary

Bioinformatics development involves various scientific disciplines: biology, computer science, mathematics, statistics, physics, and chemistry
Examples of areas in biology: biophysics, biochemistry, cell and molecular biology, genomics, and evolutionary biology.
Examples of areas in computer science: programming, databases, data structures, machine learning, and artificial intelligence.
Examples of areas in mathematics and statistics: biostatistics, probability theory, linear algebra, discrete mathematics, differential equations, Bayesian statistics, and calculus.

Required Skills

Expertise in mathematical and statistical modeling
Probability theory, graph theory, descriptive and inferential statistics, and differential equations.
Computational skills to manage, store, and analyze large biological datasets using available algorithms and software.
Statistical programming (e.g., R and Python)
Knowledge of core biological subjects (e.g., genetics, genomics, biochemistry, molecular biology, and evolution)
Knowledge and application of state-of-the-art technologies (e.g., next-generation sequencing and mass spectrometry)
Computational thinking is different from computer programming. It's a logical thought process encompassing the formulation of complex problems and the possible computational solutions. Bioinformatics focuses on the ability to pose biological questions and find solutions via algorithmic thinking.

Computational Thinking

Four steps: Decomposition, Pattern Recognition, Abstraction, Algorithms.
- Decomposition: Breaking down complex problems into smaller, more manageable parts.
- Pattern Recognition: Identifying similarities and patterns within those smaller parts.
- Abstraction: Focusing on key information and identifying important underlying concepts.
- Algorithms: Developing a systematic set of steps to solve the problem step by step

Translational Bioinformatics

Involves development and use of computational methods to handle Biotechnology-generated data. This data is accumulated, assimilated, and analyzed to create new medical tools.
Purpose is to optimize the transformation of voluminous biomedical data into proactive, predictive, preventive, and participatory (P4) medicine
Focus on genomic, environmental, and clinical profiles to personalize medicine based on genomic data.
The difference from bioinformatics is its focus on human health and directly translating biological discoveries into future or existing medicine.

Areas of Translational Bioinformatics

Clinical Genomics: using patient genomes to inform clinical decision-making (developing biomarkers).
Genomic Medicine: using genomic information in a patient’s care for personalized medicine.
Pharmacogenomics: studying how genes affect responses to drugs, considering the patient's genetic material or genotype and its relationship with the drug target or phenotype.
Genetic Epidemiology: aggregation (compiling) of genome-based data to analyze the relationship between genes and human health/disease and how genes interact with the environment.

Biotechnology

Topics in Biotechnology: protein sequencing, evolutionary biology, molecular techniques, bioinformatic algorithms, DNA sequencing, and biological databases.

Protein Sequencing

Edman degradation: method of purifying protein by sequentially removing one residue at a time.
COMPROTEIN: Computer program designed to determine protein structure from amino acid sequences and developed the one-letter code in use today.
Atlas of Protein Sequence and Structure: The First database constructed in 1965 by Dayhoff and colleagues.

Evolutionary Biology

Molecular Clock: Evolutionary analysis of protein biomolecules (such as hemoglobin). An evolved sequence of protein (e.g., hemoglobin) is related to the evolutionary time of species (E.g., the fossil record). This observation suggests that the amount of difference in orthologous proteins is proportional to the evolutionary divergence between species.

Molecular Techniques

Gene cloning - 1972 method that uses enzymes to cutout and insert a DNA fragment into the circular SV40 viral DNA. The resulting DNA is replicated and amplified, which yields large quantities of copies of the insert.
Polymerase Chain Reaction (PCR): A laboratory technique to rapidly produce many copies of a specific DNA segment. It relies on primers, DNA polymerase, and dNTPs for rapid DNA replication.

Bioinformatics Algorithms

Needleman-Wunsch Algorithm: An algorithm for aligning two protein sequences; one of the first applications of dynamic programming.
Multiple sequence alignment (MSA): An extension of pairwise alignment, it's used to optimally match sequences.
Feng-Doolittle progressive sequence alignment: A practical approach combining pairwise alignments to build a final MSA. Widely used computer software for MSA like Clustal.

Amino acid substitutions:

Point accepted mutation (PAM): The replacement of a single amino acid in protein's primary structure by another single amino acid, which is accepted by natural selection processes as part of evolution.

DNA Sequencing

Central Dogma: Specifies that the DNA sequence holds the information to create proteins.
Plus and Minus method and Sanger method for DNA sequencing and their significance in sequencing history.
Advantage of DNA sequencing: Allows identification and analysis of organisms' whole genome, leading to identification of expressed proteins, and prediction of protein structure through gene reading.

Human Genome Project (HGP)

The development of DNA sequencing technology has paved the way for whole-genome sequencing of organisms.
Started in 1990 and finished in 2003.
DNA sequencing is now cheaper and faster.
Annotation of information associated with diseases.
Database searching and pattern matching.
Large amounts of data now available to computational biologists.

Next-Generation Sequencing (NGS)

Sanger sequencing was instrumental in the first human genome sequence.
Next-Generation Sequencing (NGS) technologies were developed that provide a much higher throughput, quicker, and cheaper process for sequencing.
Different generations of NGS technology (454, SOLiD, Illumina, Ion Torrent) and their significant roles in global health.

Biological Databases

Classification of biological databases (comprehensive, specialized, primary, secondary) and their significant contribution to the field.
Importance of sequence and structure databases, protein databases, and other biological databases.

Public Health Informatics

Definition: The systematic application of informatics methods and tools to support public health goals.
Focus on population prevention and public health policies.
Public Health Informatics contrasts with Medical Informatics in focusing on the health of the community versus the individual patient.

Public Health Surveillance

Definition, functions, and characteristics of public health surveillance.
Disease surveillance, reportable/notifiable diseases, differences between active and passive disease surveillance.
Syndromic surveillance: a specialized surveillance that identifies and tracks potential public health threats.

Privacy and Confidentiality

Concepts of privacy, confidentiality, and authorization in the context of health information.
Importance of legal and ethical principles in handling health data.

Public Health Ethics

The ethical considerations, importance, and concerns in the use of health data in public health research and policy.

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Description

This quiz explores essential strategies for preventing diseases such as cervical cancer, effective public health surveillance, and the role of technology in public health practices. Test your understanding of evidence-based public health and the significance of data in shaping health programs.