Caregiving in U.S. Gulf States During Natural Disasters and COVID-19.

Objectives: To ascertain common experiences and needs of a diverse group of caregivers challenged by hurricanes/floods and COVID-19. Methods: In-depth interviews with unpaid caregivers in U.S. Southeast/Gulf Coast states who had experienced caregiving during a natural disaster and during COVID-19. Results: Caregivers report challenges including daily living disruption, altered social supports, complicated health management, additional disaster planning, and emotional/financial impacts. Caregivers suggested helpful resources, policy options, and preparatory tools at individual, local, and health system levels to mediate discontinuity. Conclusions: Our data describe combined caregiver experiences of hurricanes/floods and the pandemic. Caregivers experience unique burdens related to care recipient diagnosis, location, and veteran status. Access to community supports varies as they manage the tasks required for care recipients' health and safety. Our findings indicate the need for public health reinforcement of caregiving though caregiver pre-planning and targeted support. Bolstering understanding of communities' caregiving capacity though first responder trainings and caregiver registries may enhance health and safety.

Individual and program Characteristics May Drive Variability in Outcomes After Caregivers Participate in a Tailored Support Intervention.

Critically needed programs designed to support family caregivers have shown inconsistent reductions in stress and burden. To explore drivers of improvement in caregiver outcomes after participation in a support intervention we analyzed data from a one-on-one, tailored problem-solving intervention targeting caregiver wellbeing (2015-2019, n = 503). We explored data patterns across 21 individual, household, and program-level variables using elastic net regression to identify drivers of improvements, and their relative importance. Baseline subjective burden, baseline depressive symptom scores, baseline caregiver problem solving, African American race, and site and coach fixed effects were the most consistent drivers of changes across the explored caregiver outcomes. Caregiver and program characteristics may be promising avenues to target to decrease distress and burden during intervention design. Interventions focusing on highly distressed caregivers may lead to greater improvements. More research is needed to identify how site or interventionists characteristics drive positive intervention effects.

Prioritizing Support Offered to Caregivers by Examining the Status Quo and Opportunities for Enhancement When Using Web-Based Self-reported Health Questionnaires: Descriptive Qualitative Study.

BACKGROUND: The Rosalynn Carter Institute for Caregivers (RCI) offers evidence-based interventions to promote caregivers' health and well-being. Trained coaches regularly meet with caregivers to offer education and instructions to improve caregiver health, build skill sets, and increase resilience. Two of these interventions, RCI Resources for Enhancing Alzheimer's Caregiver Health (REACH) and Operation Family Caregiver (OFC), use a set of caregiver-reported questionnaires to monitor caregivers' health status and needs. OBJECTIVE: This study aims to describe how web-based assessment questionnaires are used to identify and monitor caregiver status in the RCI REACH and OFC programs and outlines perceived enhancements to the web-based system that could support caregiver-coach encounters by directing priorities. METHODS: This was a descriptive, qualitative study. Data were collected via semistructured interviews with caregivers and coaches in the RCI REACH and OFC programs from July 2020 to October 2020. During the interviews, participants were asked to describe how the assessment questionnaires were used to inform caregiver-coach encounters, perceived usefulness of enhancements to web-based display, and preference for the structure of score results. The interviews were recorded, transcribed, and coded using structural and interpretive codes from a structured codebook. Qualitative content analysis was used to identify themes and summarize the results. RESULTS: A total of 25 caregivers (RCI REACH: 13/25, 52%; OFC: 12/25, 48%) and 11 coaches (RCI REACH: 5/11, 45%; OFC: 6/11, 55%) were interviewed. Most caregivers indicated that the assessment questions were relevant to their caregiving experience. Some caregivers and coaches indicated that they thought the assessment should be administered multiple times throughout the program to evaluate the caregiver progress. Overall, caregivers did not want their scores to be compared with those of other caregivers, and there was heterogeneity in how caregivers preferred to view their results at the question or topic level. Coaches were uncertain as to which and how much of the results from the self-reported questionnaires should be shared with caregivers. Overall, the results were very similar, regardless of program affiliation (RCI REACH vs OFC). CONCLUSIONS: Web-based and procedural enhancements were identified to enrich caregiver-coach encounters. New and enhanced strategies for using web-based assessment questionnaires to direct priorities in the caregiver-coach encounters included integrating figures showing caregiver progress at the individual caregiver level, ability to toggle results through different figures focused on individual versus aggregate results, and support for interpreting scores. The results of this qualitative study will drive the next steps for RCI's web-based platform and expand on current standards for administering self-reported questionnaires in clinical practice settings.

Mechanisms Through Which a Family Caregiver Coaching Intervention Might Reduce Anxiety Among Children in Military Households.

OBJECTIVES: Children of injured or disabled veterans and service members may be at risk for mental health and adjustment problems due to household stress. Yet, there are few widely available interventions to address the needs of this population. Reducing distress and improving coping skills of the parent who cares for the injured or disabled adult may improve child outcomes. This paper examines whether changes in caregiver psychosocial outcomes after a caregiver coaching intervention are associated with decreases in child anxiety. METHODS: Using programmatic data collected between 2015 and 2019 from participants in a family caregiver coaching intervention (170 caregivers, 294 children), we apply linear mixed models to assess associations between changes in family caregiver well-being, including problem solving, depressive symptoms, burden, health complaints and quality of life, and changes in parent-reported child anxiety. RESULTS: The baseline median Spence Children's Anxiety Scale-Parent score was 17; children aged 6-11 had slightly higher scores. Child anxiety scores decreased on average 2.8 points (SD 8.4) between baseline and follow-up. In adjusted models, decreases in caregiver depressive symptoms and health complaints were associated with decreases in child anxiety. Caregiver problem-solving skills, quality of life, and subjective burden were not associated with changes in child anxiety. CONCLUSION: Family caregiver-focused interventions that decrease caregiver stress may positively affect children in the household. Few resources are directed at military children; therefore, practitioners should consider ways to leverage caregiver interventions to address child well-being, such as incorporating information on parenting strategies and addressing issues faced by military children.

Participatory Disease Surveillance: Engaging Communities Directly in Reporting, Monitoring, and Responding to Health Threats.

BACKGROUND: Since 2012, the International Workshop on Participatory Surveillance (IWOPS) has served as an informal network to share best practices, consult on analytic methods, and catalyze innovation to advance the burgeoning method of direct engagement of populations in voluntary monitoring of disease. OBJECTIVE: This landscape provides an overview of participatory disease surveillance systems in the IWOPS network and orients readers to this growing field of practice. METHODS: Authors reviewed participatory approaches that include human and animal health surveillance, both syndromic (self- reported symptoms) and event-based, and how these tools have been leveraged for disease modeling and forecasting. The authors also discuss benefits, challenges, and future directions for participatory disease surveillance. RESULTS: There are at least 23 distinct participatory surveillance tools or programs represented in the IWOPS network across 18 countries. Organizations supporting these tools are diverse in nature. CONCLUSIONS: Participatory disease surveillance is a promising method to complement both traditional, facility-based surveillance and newer digital epidemiology systems.

Finding Outbreaks Faster.

Rapid detection, reporting, and response to an infectious disease outbreak are critical to prevent localized health events from emerging as pandemic threats. Metrics to evaluate the timeliness of these critical activities, however, are lacking. Easily understood and comparable measures for tracking progress and encouraging investment in rapid detection, reporting, and response are sorely needed. We propose that the timeliness of outbreak detection, reporting, laboratory confirmation, response, and public communication should be considered as measures for improving global health security at the national level, allowing countries to track progress over time and inform investments in disease surveillance.

Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review.

OBJECTIVE: Research studies show that social media may be valuable tools in the disease surveillance toolkit used for improving public health professionals' ability to detect disease outbreaks faster than traditional methods and to enhance outbreak response. A social media work group, consisting of surveillance practitioners, academic researchers, and other subject matter experts convened by the International Society for Disease Surveillance, conducted a systematic primary literature review using the PRISMA framework to identify research, published through February 2013, answering either of the following questions: Can social media be integrated into disease surveillance practice and outbreak management to support and improve public health?Can social media be used to effectively target populations, specifically vulnerable populations, to test an intervention and interact with a community to improve health outcomes?Examples of social media included are Facebook, MySpace, microblogs (e.g., Twitter), blogs, and discussion forums. For Question 1, 33 manuscripts were identified, starting in 2009 with topics on Influenza-like Illnesses (n = 15), Infectious Diseases (n = 6), Non-infectious Diseases (n = 4), Medication and Vaccines (n = 3), and Other (n = 5). For Question 2, 32 manuscripts were identified, the first in 2000 with topics on Health Risk Behaviors (n = 10), Infectious Diseases (n = 3), Non-infectious Diseases (n = 9), and Other (n = 10). CONCLUSIONS: The literature on the use of social media to support public health practice has identified many gaps and biases in current knowledge. Despite the potential for success identified in exploratory studies, there are limited studies on interventions and little use of social media in practice. However, information gleaned from the articles demonstrates the effectiveness of social media in supporting and improving public health and in identifying target populations for intervention. A primary recommendation resulting from the review is to identify opportunities that enable public health professionals to integrate social media analytics into disease surveillance and outbreak management practice.

Flu Near You: Crowdsourced Symptom Reporting Spanning 2 Influenza Seasons.

OBJECTIVES: We summarized Flu Near You (FNY) data from the 2012-2013 and 2013-2014 influenza seasons in the United States. METHODS: FNY collects limited demographic characteristic information upon registration, and prompts users each Monday to report symptoms of influenza-like illness (ILI) experienced during the previous week. We calculated the descriptive statistics and rates of ILI for the 2012-2013 and 2013-2014 seasons. We compared raw and noise-filtered ILI rates with ILI rates from the Centers for Disease Control and Prevention ILINet surveillance system. RESULTS: More than 61 000 participants submitted at least 1 report during the 2012-2013 season, totaling 327 773 reports. Nearly 40 000 participants submitted at least 1 report during the 2013-2014 season, totaling 336 933 reports. Rates of ILI as reported by FNY tracked closely with ILINet in both timing and magnitude. CONCLUSIONS: With increased participation, FNY has the potential to serve as a viable complement to existing outpatient, hospital-based, and laboratory surveillance systems. Although many established systems have the benefits of specificity and credibility, participatory systems offer advantages in the areas of speed, sensitivity, and scalability.

Optimizing the Use of Chief Complaint & Diagnosis for Operational Decision Making: An EMR Case Study of the 2010 Haiti Earthquake.

INTRODUCTION: Data from an electronic medical record (EMR) system can provide valuable insight regarding health consequences in the aftermath of a disaster. In January of 2010, the U.S. Department of Health and Human Services (HHS) deployed medical personnel to Haiti in response to a crippling earthquake. An EMR system was used to record patient encounters in real-time and to provide data for decision support during response activities. PROBLEM: During the Haiti response, HHS monitored the EMR system by recoding diagnoses into seven broad categories. At the conclusion of the response, it was evident that a new diagnosis categorization process was needed to provide a better description of the patient encounters that were seen in the field. After examining the EMRs, researchers determined nearly half of the medical records were missing diagnosis data. The objective of this study was to develop and test a new method of categorization for patient encounters to provide more detailed data for decision making. METHODS: A single researcher verified or assigned a new diagnosis for 8,787 EMRs created during the Haiti response. This created a new variable, the Operational Code, which was based on available diagnosis data and chief complaint. Retrospectively, diagnoses recorded in the field and Operational Codes were categorized into eighteen categories based on the ICD-9-CM diagnostic system. RESULTS: Creating an Operational Code variable led to a more robust data set and a clearer depiction emerged of the clinical presentations seen at six HHS clinics set up in the aftermath of Haiti's earthquake. The number of records with an associated ICD-9 code increased 106% from 4,261 to 8,787. The most frequent Operational Code categories during the response were: General Symptoms, Signs, and Ill-Defined Conditions (34.2%), Injury and Poisoning (18.9%), Other (14.7%), Respiratory (4.8%), and Musculoskeletal and Connective Tissue (4.8%). CONCLUSION: The Operational Code methodology provided more detailed data about patient encounters. This methodology could be used in future deployments to improve situational awareness and decision-making capabilities during emergency response operations.

The perfect storm of information: combining traditional and non-traditional data sources for public health situational awareness during hurricane response.

BACKGROUND: Hurricane Isaac made landfall in southeastern Louisiana in late August 2012, resulting in extensive storm surge and inland flooding. As the lead federal agency responsible for medical and public health response and recovery coordination, the Department of Health and Human Services (HHS) must have situational awareness to prepare for and address state and local requests for assistance following hurricanes. Both traditional and non-traditional data have been used to improve situational awareness in fields like disease surveillance and seismology. This study investigated whether non-traditional data (i.e., tweets and news reports) fill a void in traditional data reporting during hurricane response, as well as whether non-traditional data improve the timeliness for reporting identified HHS Essential Elements of Information (EEI). METHODS: HHS EEIs provided the information collection guidance, and when the information indicated there was a potential public health threat, an event was identified and categorized within the larger scope of overall Hurricane Issac situational awareness. Tweets, news reports, press releases, and federal situation reports during Hurricane Isaac response were analyzed for information about EEIs. Data that pertained to the same EEI were linked together and given a unique event identification number to enable more detailed analysis of source content. Reports of sixteen unique events were examined for types of data sources reporting on the event and timeliness of the reports. RESULTS: Of these sixteen unique events identified, six were reported by only a single data source, four were reported by two data sources, four were reported by three data sources, and two were reported by four or more data sources. For five of the events where news tweets were one of multiple sources of information about an event, the tweet occurred prior to the news report, press release, local government\emergency management tweet, and federal situation report. In all circumstances where citizens were reporting along with other sources, the citizen tweet was the earliest notification of the event. CONCLUSION: Critical information is being shared by citizens, news organizations, and local government representatives. To have situational awareness for providing timely, life-saving public health and medical response following a hurricane, this study shows that non-traditional data sources should augment traditional data sources and can fill some of the gaps in traditional reporting. During a hurricane response where early event detection can save lives and reduce morbidity, tweets can provide a source of information for early warning. In times of limited budgets, investing technical and personnel resources to efficiently and effectively gather, curate, and analyze non-traditional data for improved situational awareness can yield a high return on investment.