For example, active case finding by using queries in an established syndromic surveillance system e. Data collected in the field electronically can be uploaded to central information systems. When data are collected by using paper forms, these forms can be scanned and sent to a separate data entry location where they can be digitized and rapidly integrated into a surveillance information system. This approach enables the field team to focus on establishing relationships necessary for supporting epidemiologic investigation and data collection activities or on laboratory specimen collection that can only be accomplished on-site.
Specialized staff can be assigned to the team; these staff remain at their desks to collect, manage, or analyze data in support of the field investigation. Staff might include data entry operators, medical record abstractors, data analysts, or statistical programmers. Implementing coordinated field and technology teams also enables more and highly skilled staff across multiple levels local, state, or federal to contribute effectively to an investigation.
How to coordinate data activities in multiple locations needs to be planned for early in the response. Field investigations often are led by personnel with extensive epidemiologic, disease, and scientific subject-matter expertise who are not necessarily expert in informatics and surveillance strategies.
From a data perspective, such leadership can result in the establishment of ineffective data collection and management strategies. To support effective data collection and management, for all outbreaks, field investigators should. Whatever title is assigned to the role, the person filling the role should have clearly delineated duties and responsibilities, including.
When preparing and packing for field deployments, two technology items are essential for each investigator: a portable laptop-style computer and a smartphone essentially a pocket computer providing access to a camera, video, geolocating and mapping services, and data collection capacities.
A mobile hotspot device to create an ad hoc wireless access point, separate from the smartphone, can be useful in certain situations. For example, after Hurricane Irma made landfall in Florida during September , widespread power losses lasted for days. Deployed epidemiology staff were housed in locations without consistent power and had to travel to established command centers to charge phones, laptops, and rechargeable batteries once a day.
Portable printers or scanners are other optional items to consider. Car-chargers for laptops and phones are also useful, although gas shortages can be a constraint and make car-chargers less optimal during certain types of responses. As far as possible, responders should be deployed with items similar to ones they have been using on a regular basis. This will ensure that the investigator is familiar with the equipment and how it functions in different settings e.
Equipment caches of laptops, tablets, or other devices purchased only for use during events can lead to considerable deployment problems e. Field investigators responding to out-of-jurisdiction locations most likely will need to be issued temporary laptops from within the response jurisdiction to ensure network and software compatibility, connectivity, and adherence to jurisdictional security requirements.
Data often move at the speed of trust. A field team should establish strong working relationships at the start of the response with those who invited the epidemiologic assistance. On-site visit time should be used to ensure that the relationship will, among other tasks, facilitate gathering data and meet the needs of local authorities.
Plans need to be made at the outset for sharing regular, timely data summaries and reports with local partners. Upon initial arrival, the field team should assess existing surveillance systems and the processes for data submission to these systems. The assessment should address.
If the team is deploying out of its own jurisdiction, the team leader should seek assistance and consultation from someone at the jurisdictional level who fills a role like that of the chief surveillance and informatics officer see previous section. An outbreak investigation and response has defined steps and phases see Chapter 3 , and each has specific technology and information needs. In recent years, public health agencies have benefitted from technologic advances that support outbreak detection—whether the outbreak is caused by a known or unknown agent.
This system enabled detection of the second largest US outbreak of community-acquired legionellosis by identifying a cluster of eight cases centered in the South Bronx days before any human public health monitor noticed it and before healthcare providers recognized the increase in cases 3.
The identification led to an extensive epidemiologic, environmental, and laboratory investigation to identify the source—a water cooling tower—and then implement measures to remediate it. Although technology is revolutionizing approaches to cluster detection, this chapter assumes the field team will be responding after a known event or outbreak has been detected; thus, the following discussion focuses on using technologies for conducting initial characterization, active case finding, enhanced surveillance, supporting and evaluating control measures, and situational awareness, and for monitoring the response and its effectiveness.
In an outbreak setting, routine data management often changes because of new stressors or novel circumstances, particularly the need to almost immediately gather data, produce reports, and inform decision makers and the public see also Chapters 2 and 3.
To assess population groups at highest risk, geographic extent, and upward or downward trends of disease incidence throughout a confirmed outbreak, investigators can use existing surveillance mechanisms. However, such mechanisms might need to be enhanced; for example, investigators might need to. Regardless of whether case detection is enhanced, the technology used should support production of a line-listing for tracking cases that are part of the investigation.
The system should also document what changes are made to individual cases and when those changes are made, including changes that result from new information gathered or learned or from epidemiologic findings. The system should ensure that laboratory data are easily made relational Box 5. Even if investigation data are collected entirely or partially on paper, those data usually are keypunched into electronic data systems for further analysis, and the paper forms are scanned and stored electronically.
The investigation determined that the patient possibly exposed others in four general settings: airplanes during travel from Saudi Arabia to Orlando, Florida; at home household contacts and visiting friends ; a hospital outpatient waiting room while accompanying a relative for an unrelated medical reason; and later, an emergency department waiting room where he sought care for his illness.
Multiple levels of contacts were tracked by the four exposure settings and risk for exposure e. The Epi Info 7 CDC, Atlanta, Georgia database that was created supported easy generation of line listings for tracking contacts and linking contact and laboratory information, including associated exposure settings, tracking isolation periods, contact method, attempts, signs and symptoms, final outcome, persons who should provide a clinical specimen, number and types of specimens collected multiple and over time , whether specimens were received for testing, and laboratory results.
The novel nature of the investigation required that additional data fields be captured as the scope of the investigation shifted. Because field investigators can control Epi Info 7 database management, these needed shifts were able to be met rapidly with no technical support. As a result, the progress of the contact investigation was able to be monitored in real time to identify priorities, optimally use personnel resources, and ensure leadership had current information on which to base decisions.
Effective database management and linking of epidemiologic and laboratory information in a single location supported the investigation. ITs can be used to improve the quality, completeness, and speed of information obtained in a field investigation and the speed and sophistication of reports that can be generated from that information at the individual or aggregate level.
To ensure that the full benefits of these technologies are realized, investigators need to perform the following actions:. The value and use of routine surveillance data systems should not be underestimated during outbreak investigations and ideally will be managed within a data preparedness framework. Many state reportable disease surveillance systems both commercially available or state-or in-house— designed now have outbreak management components 7.
To avoid duplicating efforts or processes, field investigators should understand and assess existing surveillance systems that support outbreak management before determining which technologies to use Box 5.
In addition to public health electronic disease surveillance systems supporting outbreak management components, reportable disease electronic laboratory reporting ELR is now a mainstay of reportable disease surveillance. Every state health department has operational ELR systems 9. Although ELR was designed for supporting individual identification and reporting of disease events, it can also be used to support outbreak response activities.
Using existing surveillance systems, including ELR processes, supports outbreak detection, characterization, outbreak identification, and control measure evaluation Box 5. Following the identification of the initial case of Zika virus infection attributed to likely local mosquito-borne transmission in Florida, the Florida Department of Health conducted active surveillance in selected areas of the state to identify locally acquired Zika virus infections and to assess whether ongoing transmission was occurring 8.
Data collected during these field surveys were managed in the outbreak module OM of the state health department—developed reportable disease surveillance application, Merlin.
Three types of OM events were used: index , cases and their contacts; urosurvey i. Data regarding residential urosurveys persons within a meter radius of a locally acquired index case , business urosurveys employees at a business or worksite , and clinic urosurveys persons who lived or worked in the area of interest were collected and analyzed. For each urosurvey OM event, an event-specific survey was generated in real time and used to capture the collected data.
In , door-to-door survey data were collected on a simple paper form. Surveys were faxed nightly to the central office staff in Tallahassee, where existing reportable disease data entry staff entered all the survey data collected; the digitized information was made available to local-and state-level investigators within 24 hours.
In , 87 OM events 49 index, 32 urosurvey, and 6 other were initiated. At that point, the tool uses Hachoir, PdfMiner and other libraries to lift the metadata from those documents. Recon-ng is a framework that stands apart from others due to its focus on web-based open source reconnaissance.
It helps users to pursue their reconnaissance work by way of modules. Towards that end, Recon-ng comes with several built-in modules, such as those that help users to uncover further domains related to a target domain. With Shodan , users can search the web for internet-connected devices.
Websites provide some insight into those assets, but Shodan takes its scans a step further by revealing assets like Internet of Things IoT products. This open source reconnaissance tool comes with over modules for data collection and analysis. This can help gain a broad view of their attack surfaces, including low-hanging fruit like unmanaged assets and exposed credentials. With more than 25 billion records stored about online assets, Spyse helps users to collect public data relating to websites, servers and devices connected on the web.
When your business relies on data, finding the best data collecting software tool is a crucial moment. You need a perfect platform to collect real-time information and show a comprehensive analysis to facilitate your decision-making process. There are many online, offline and mobile data collecting apps that have it all: Create, Collect, and Analyze.
Features like collecting customer feedback, lead capturing, audits, interactive kiosks, real-time reports and etc. So, before buying software, take your time to compare and examine all the features and capabilities of the platform.
Silvia Valcheva is a digital marketer with over a decade of experience creating content for the tech industry. She has a strong passion for writing about emerging software and technologies such as big data, AI Artificial Intelligence , IoT Internet of Things , process automation, etc. Currently you have JavaScript disabled. In order to post comments, please make sure JavaScript and Cookies are enabled, and reload the page.
Click here for instructions on how to enable JavaScript in your browser. This site uses Akismet to reduce spam. Learn how your comment data is processed. GoSpotCheck If your job or business depends on field data, then GoSpotCheck is one of the best data collection tools to gather real-time information and make an instant analysis. Features and benefits: User friendly mobile data collection app. Field-First CRM to keep up-to-date account information.
Field team management. Content distribution to share knowledge with your team. Key features and benefits: Lead Capture — to capture contact details and leads at events and shows. Unlimited data collection app — online and offline.
Use iPads, iPhones, and Android tablets or phones to collect data anywhere. In-person surveys to gain fast, actionable insights. Quick Setup — create the surveys in just a few minutes. Manage surveys remotely. These techniques possess parameters that can be set to give the optimal balance between data quality and data quantity to give the fastest improvement of the system. Documents: Advanced Search Include Citations. Authors: Advanced Search Include Citations.
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