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How IT could assist Outbreak Investigation Process?
Verification and Preparation
1. Establish the existence of an outbreak: by developing real-time dashboards to display case trends over time and place, as well as notifying authorities about unusual surges in cases.
2. Verify the diagnosis: through electronic laboratory reporting to public health authorities and relevant stakeholders, enabling timely data exchange across healthcare settings and supporting decision-making processes.
3. Prepare for field work: by using digital tools to collect field data and integrating GIS mapping to identify hotspots, allowing fast and secure information sharing.
Describe the outbreak
4. Construct a working case definition: by using collaborative digital tools to draft, review, and revise case definitions, which can then be easily shared with the technical working group without requiring in-person meetings.
5. Find cases systematically and record information: by using digital case investigation forms on mobile phones, tablets, or computers for faster reporting, synchronized with a central database so that public health officials can promptly review and make further decisions.
6. Perform descriptive epidemiology: by creating data visualizations and GIS maps to identify case patterns, trends, and clusters through interactive dashboards.
Hypothesis & Testing
7. Develop hypotheses and analytical studies: by applying digital data analysis and statistical tools to explore correlations or associations between cases and possible contributing factors. In addition, IT can support data collection through digital surveys and assessment forms for further analysis.
Response & action
8. Implementation of control measures and follow-up: by using automated communication systems such as SMS alerts and emails to inform affected communities about control and preventive measures. IT can also help create dashboards to monitor the progress of interventions and follow-up actions.
9. Communication including outbreak report: by generating automated data summaries and dashboards for stakeholders, and sharing accurate information with the public via social media platforms. At the same time, IT can assist in monitoring social media behavior to detect and address misinformation in real time.
In addition, IT can support the overall outbreak investigation process by enabling efficient data exchange among stakeholders and decision-makers, minimizing data errors, enhancing efficiency, ensuring scalability, and strengthening data security and control.
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Verification and Preparation Stage, there are 3 following steps to do.
1. Establish the existence of an outbreak
2. Verify the diagnosis
3. Prepare for field work
To verify the outbreak, the field team can report the data within short time and the response team can check whether it is over alert line or not by comparing the former database. The collected data in the central server will provide epidemiological information and can be used in authorization to mobilize the rapid response team. In preparation of field work, the documentation for knowledge and laboratory data can easily be extracted by information technology.
In describing an outbreak stage,
4. Construct a working case definition
5. Find case systematically and record information
6. Perform descriptive epidemiology
For case finding and line listing, the health information system will provide the fast and valid data to analyze by using GIS technology and can present by data visualization technology to monitor the distribution of the diseases. This can support the response team to start the prevention and control measures. Information technology can also provide the working case definitions and epidemiological analysis in real time.
Hypothesis and testing stage require data to perform the interview for population.
7. Develop hypothesis
8. Analytical studies to test hypotheses
9. Special study (environmental study, laboratory study)
If information technology has database of population and geographical area, it can support whether to do environmental study or laboratory study. We can create heatmap for the outbreak area and can-do contact tracing and find point of source for infection. If the information system has interoperability with other systems, we can detect the causal agent (emerging or re-emerging) and alert others to prevent the pandemic spread.
Response and action stage:
10. Implementation of control measures and follow up
11. Communication – including outbreak report
By using information technology, we can use dissemination tools for control measures such as text messaging and chatbots, wearable devices for contact tracing and follow up. For public awareness and stakeholder advocacy, we can announce the risk communication measures through dashboards and mass media with data visualization techniques.-
I agree with the point that text messaging and chatbots can be hugely useful nowadays, given the way of our communication in this era. Public health authorities can use these tools to deliver messages to people instantly. Also, IT devices can be useful in the reverse direction in that they aren’t only for communication but also for monitoring the effectiveness of the measures implemented.
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Verification and preparation
1. Establish the existence of an outbreak: IT systems like automated surveillance and real-time dashboards help detect unusual increases in cases and trigger early alerts.2. Verify the diagnosis: Laboratory Information Management Systems (LIMS) and teleconsultation tools enable accurate and rapid confirmation of the disease.
3. Prepare for field work: Mobile apps, GIS mapping, and digital data collection tools assist in planning logistics and organizing field investigation teams.
Describe the outbreak
4. Construct a working case definition: Shared online documents and digital collaboration platforms ensure consistent and updated case definitions across all investigators.5. Find cases systematically & record information: Digital data collection tools and EMR integration allow efficient case finding, data entry, and tracking with minimal errors.
6. Perform descriptive epidemiology: Data analysis and visualization software (e.g., R, Power BI) produce epidemic curves, maps, and summary tables instantly.
Hypothesis and testing
7. Develop hypothesis: Data mining and statistical software (e.g., R, Python) help identify potential exposure patterns and formulate preliminary hypotheses.8. Analytical studies to test hypotheses: Advanced analytics programs (e.g., R, Python, SPSS) are used to compare data between groups and test associations statistically.
9. Special studies (e.g., environmental, laboratory): Internet of Things (IoT) sensors and bioinformatics tools link environmental and genetic data to understand sources and transmission pathways.
Response and action
10. Implementation of control measures and follow-up: IT supports communication of interventions via alerts and tracks the effectiveness of control measures through dashboards.11. Communication – including outbreak report: Digital reporting platforms and dashboards enable timely sharing of findings and outbreak updates with stakeholders and the public.
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1. Verification and preparation
– IT can be used for verification of case numbers by comparing them to the normal baseline on IT-based surveillance systems
– It can send timely alerts when there’s an excess number, which also helps in identifying the Place.
– IT helps to deliver rapid information to the authorities responsible for verifying the diagnosis and communication for fieldwork.2. Describe the outbreak
– Fieldwork team can use IT devices and systems in the field for case finding and investigation
– IT tools create the digital line listing and deliver it online, allowing the whole team prompt access to the information.
– IT tools can generate the visualization, such as Epi curves, to see the pattern of outbreak (Time).
– It can also create a digital map to demonstrate the Place by showing case distribution, which benefits hypothesis generation and further investigation.3. Hypothesis and testing
– IT tools are used to test the hypothesis and obtain results useful for creating control measures.4. Response and action
– IT is used to deliver rapid and effective messages of the control measures to the stakeholders and the affected communities. -
Hi everyone,
In my opinion, information technology (IT) can play a critical role in every step of outbreak investigation, improving the speed, accuracy, and coordination of the response. I would like to share the example for application of IT in each process as follows:1. Verification & Preparation
– Surveillance systems & dashboards: Automated monitoring of electronic health records (EHR), lab reports, and syndromic surveillance can help detect abnormal trends early.
– Communication tools: Secure messaging platforms, videoconferencing, and cloud storage to coordinate field teams quickly.2. Describe the Outbreak
– Geographic Information Systems (GIS): Mapping cases to visualize spatial distribution and detect clusters.
– Electronic databases: Centralized case registries to record and retrieve patient data systematically.
– Data visualization tools: Automated epidemic curves, timelines, and heat maps.3. Hypothesis & Testing
– Statistical and analytical software: Tools like R, SAS, SPSS, or Python can be used to test hypotheses, calculate relative risks, odds ratios, and identify associations.
– Modeling tools: Simulation models to predict outbreak dynamics and evaluate control measures.4. Response & Action
– Real-time dashboards: Monitor intervention coverage, case numbers, and outcomes.
– Digital contact tracing: Mobile applications and proximity tracking to identify and notify contacts.
– Automated alerts: Text/email notifications to health workers and communities.Among these, the IT system can play an important role in various steps/tasks of outbreak investigation.
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In my opinion, IT can help the following:
Verification and Preparation
1. Establish the existence of an outbreak: IT can help to detect outbreaks early by using mobile apps and real-time dashboards to track case trends that enables quick alerts to health authorities when unusual case surges occur.
2. Verify the diagnosis: IT can improve diagnosis verification by enabling faster data exchange between local hospitals and public health officials, reducing delays in response.
3. Prepare for field work: Digital tools like GIS mapping and mobile data collection apps can help health workers in remote areas efficiently to track and manage outbreak data.Describe the Outbreak
1. Construct a working case definition: Digital collaboration tools can allow technical teams to draft and share case definitions quickly, ensuring consistent use without the need for in-person meetings.
2. Find cases and record information: Using mobile apps for case investigation, public health workers can quickly report cases in real time, syncing with a central database for faster decision-making.
3. Perform descriptive epidemiology: IT tools can create dashboards and GIS maps to identify patterns and clusters, allowing public health officials to focus resources on high-risk areas.Hypothesis and Testing
1. Develop hypotheses and analytical studies: IT supports data analysis and the development of hypotheses by using statistical software and digital surveys to explore factors contributing to the outbreak.Response and Action
1. Implementation of control measures: Automated SMS alerts and digital tools can be used to communicate control measures and follow-up actions to communities, especially in rural areas.
2. Communication including outbreak report: IT can generate automated reports and track social media to manage misinformation, ensuring accurate, timely updates to both stakeholders and the public.By improving data exchange, minimizing errors and ensuring secure information sharing, IT can enhance the ability to respond quickly and effectively to health emergencies.
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I think information technology really makes outbreak investigation much more efficient and accurate. In the past, everything relied on paper and manual reports, which took a long time. But now, with digital tools, each step can be done faster and more collaboratively.
For example:
During data collection, mobile apps or online systems help health workers report new cases instantly, which supports real-time monitoring.
For data analysis, software like GIS or R can visualize maps, show hotspots, and detect patterns that would be hard to see manually.
In communication, platforms like cloud storage or video meetings allow health teams and authorities to coordinate quickly, even from different locations.
For public communication, official websites and social media can share prevention messages and outbreak updates directly with the community.
Overall, I believe IT doesn’t just make the process faster, it also improves decision-making and collaboration among public health teams, which is essential for effective outbreak control.
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Verification and Preparation
• Establish the existence of an outbreak: Using National/ District level surveillance database can help collection, collation, analysis and use of data for disease surveillance for detecting abnormal trends.
For e.g.
Global level – WHO’s Global Outbreak Alert and Response Network (GOARN), ProMED-Mail
National/District level – DHIS 2
Specialized disease surveillance – MIS (malaria information system)
• Verify the diagnosis: Laboratory confirmation results can be shared to relevant stakeholders, through health information systems or other digital communication channels.
• Prepare for fieldwork: Preliminary meetings with decision makers and field team can be done via digital platforms, field data collection using mobile tools.Describe the Outbreak
• Find cases systematically and record information: Data can be recorded into the information systems and store collectively in central databases to avoid fragmentation and foster real-time data-driven decision making.
• Perform descriptive epidemiology: Using visualization tools and geological mapping (GIS) to generate insights into the disease distribution, magnitudes and hotspots.Hypothesis and Testing
• Develop hypothesis: Data visualization tools can provide insight into the possible sources, mode of transmission and the offending organisms.
• Analytical studies to test hypothesis: Using statistical software (e.g., SPSS, R, or STATA) to confirm the hypothesis.
• Special studies (environmental or laboratory): Environmental monitoring tools and Laboratory management information system enhance the surveillance system.Response and Action
• Implementation of control measures and follow-up: Broadcast and follow-up the control measures through various digital platforms for community awareness.
• Communication: Through out the process of surveillance, digital communication tools play a critical role, ensu -
Establish the existence of an outbreak: The surveillance system and dashboard can monitor the real-time disease trends, detect abnormal case increases and promote early detection.
Verify the diagnosis: Laboratory Management Information System enables rapid sharing of investigation results among public health professionals.
Prepare for field work: Mobile data collection and mapping tools enhance the early case detection and identify the hotspot.
Construct a working case definition: Electronic case reporting system can update case definitions and extract real-time case related information.
Find case systematically and record information: Mobile application allows real-time case data entry, cast listing and improve data quality.
Perform descriptive epidemiology: Statistical software and GIS tools can generate epidemic curves, maps and demographic summary.
Develop hypothesis: IT enables combination of multiple datasets and to identify possible exposure sources and transmission routes.
Analytical studies to test hypotheses: Statistical software is used to perform case-control or cohort analysis.
Special studies: Data management platforms support advanced modeling and analysis involving multiple teams.
Implementation of control measures and follow-up: Digital contract tracing tools and SMS alert systems are used for case monitoring and early warning.
Communication: Interactive dashboards, automated reporting systems and online platforms enhance results sharing with all relevant stakeholders.
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Here are some examples of how information technology was applied to assist in the outbreak investigation process:
1. Verification and Preparation
The Early Warning, Alert and Response System (EWARS) application of WHO can be used to improve disease outbreak detection in emergency settings, such as in countries in conflict or following a natural disaster. The app can be used to collect data from various sources, such as healthcare facilities and the community. Standard alert thresholds for a disease can be programmed into the app, and when the threshold is exceeded, it will send an alert to the surveillance officer.2. Describe the outbreak
Spreadsheet applications such as Microsoft Excel can be used in making a line list – a table containing basic information on each case (Unique ID number/case identifier, age, type of case, sex, etc.). A line list allows for organization of information and provides an overall picture. This will help in the creation of descriptive statistics and epi curve.3. Hypothesis and testing
For analytical studies to test hypotheses, OpenEpi can be used. It is a free and open source software that provides statistics for counts and measurements in descriptive and analytic studies, stratified analysis with exact confidence limits, matched pair and person-time analysis, sample size and power calculations, random numbers, sensitivity, specificity and other evaluation statistics, R x C tables, chi-square for dose-response, and links to other useful sites.4. Response and Action
The UK Health Security Agency (UKHSA) shares public health data (mostly from England and sometimes other UK nations) via the UKHSA Data Dashboard. This dashboard covers a range of topics such as respiratory viruses, healthcare-associated infections and antimicrobial resistance that inform public health decision making in England. It was developed to cater to different users, such as members of the general public, public health professionals, policy makers, and media. -
How could information technology be applied to assist the outbreak investigation process?
Information technology could assist in many aspect of an outbreak investigation.
1) In verification and preparation step;
IT can facilitate in real time data collection of data to calculate the magnitude of it. It can support insightful information for verification of diagnosis, location, case trend, contact tracing, history taking.
2) In description of outbreak;
Advanced epidemiological expression can be conducted by commanding the statistical and mathematical calculation to describe the outbreak.
3) In Hypothesis and Testing;
It can also play as a pivotal role in testing the result. IT can provide fast and reliable information of the result. IT can generate the information based on imported data and requested command like seasonal trend, onset of case, sensitivity, Predict value positive (PVP).
4) In Response and Action;
IT is essential to be an effective response and action plan. The response and case data can be display as dashboard and it can also be used to communicate with the stakeholders in developing action plan. -
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Verification and Preparation
Establish the existence of an outbreak: IT systems such as electronic health records (EHRs), and real-time dashboards help detect unusual rises in case numbers, triggering early warnings for potential outbreaks.
Verify the diagnosis: Digital Laboratory Systems, and teleconsultation facilitate rapid confirmation of the pathogen.
Prepare for field work: Mobile data collection apps, and Geographic Information Systems (GIS) assist in mapping affected areas, organizing field teams, and planning logistics efficiently.Describe the Outbreak
Construct a working case definition: Shared online documents and digital collaboration platforms (e.g., Google Workspace, Microsoft Teams) ensure clear understanding and updates of case definitions across all team members.
Find cases systematically and record information: Integration of digital data collection tools, mobile survey systems (e.g., ODK, KoBoToolbox), and EMRs enables efficient case finding, and data entry.
Perform descriptive epidemiology: Data analysis and visualization tools (e.g., R, Epi Info, Power BI) generate epidemic curves, distribution maps, and summary of statistics, helping investigators describe the outbreak in terms of time, place, and person.Hypothesis and Testing
Develop hypotheses: Data mining, statistical analysis, and machine learning tools (e.g., R, Python) help identify patterns of exposure and potential sources, leading to the formulation of preliminary hypotheses.
Conduct analytical studies to test hypotheses: Analytical software such as SPSS, Stata, and R allows investigators to compare data between affected and unaffected groups, testing associations statistically to validate hypotheses.
Conduct special studies (e.g., environmental or laboratory): Environmental monitoring systems, and bioinformatics tools link environmental and genetic data to understand the source, mode, and spread of the pathogen.Response and Action
Implement control measures and follow-up: IT facilitates communication of interventions through mobile alerts, supports contact tracing through digital tracking systems, and monitors the effectiveness of control measures using real-time dashboards.
Communicate findings and prepare reports: Digital reporting platforms, online dashboards, and visualization tools enable timely dissemination of findings to policymakers, health professionals, and the public, ensuring transparency and coordinated response. -
Information technology plays a crucial role in assisting the outbreak investigation process by enhancing data collection, analysis, communication, and decision-making at each stage. During the initial step of establishing the existence of an outbreak, electronic surveillance systems are used to monitor disease trends and detect abnormal increases in cases. These systems allow for real-time data collection and automated alerts, which help identify outbreaks quickly.
In the step of verifying the diagnosis, information technology supports laboratory confirmation through Laboratory Information Management Systems that record, track, and share laboratory test results efficiently. Electronic medical records (EMRs) also enable healthcare professionals to verify diagnoses remotely and ensure data accuracy.
When defining and identifying cases, electronic case reporting systems and mobile data collection tools such as KoBoToolbox assists field investigators in capturing standardized data directly from health facilities or communities. These tools improve the accuracy and timeliness of case finding, even in remote areas.
In descriptive epidemiology, IT applications such as Epi Info, Excel, and Geographic Information Systems (GIS) are used to analyze data according to time, place, and person. GIS helps to map cases geographically and visualize clusters, providing insights into the spatial distribution of diseases. Similarly, analytic and visualization software such as Tableau or Power BI helps to identify patterns and generate hypotheses about the possible sources and transmission routes.
During hypothesis testing and evaluation, statistical software support the analysis of relationships between exposures and disease outcomes.
When implementing control and prevention measures, information technology enables effective communication through mobile applications, SMS alerts, and social media platforms. Decision-support systems also provide real-time recommendations for interventions based on current data trends. Finally, during the step of communicating findings, digital dashboards, online reporting tools, and interactive data visualizations allow health authorities to present results clearly to policymakers, healthcare providers, and the public.
In conclusion, the application of information technology in outbreak investigations enhances the efficiency and accuracy of public health responses. It enables rapid data collection, real-time communication, and evidence-based decision-making, which are all essential for timely control of disease outbreaks.
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