Applying Human-Centered Design Principles to Digital Syndromic Surveillance at a Mass Gathering in India: Viewpoint.

In the wake of the COVID-19 pandemic, digital health tools have been deployed by governments around the world to advance clinical and population health objectives. Few interventions have been successful or have achieved sustainability or scale. In India, government agencies are proposing sweeping changes to India's digital health architecture. Underpinning these initiatives is the assumption that mobile health solutions will find near universal acceptance and uptake, though the observed reticence of clinicians to use electronic health records suggests otherwise. In this practice article, we describe our experience with implementing a digital surveillance tool at a large mass gathering, attended by nearly 30 million people. Deployed with limited resources and in a dynamic chaotic setting, the adherence to human-centered design principles resulted in near universal adoption and high end-user satisfaction. Through this use case, we share generalizable lessons in the importance of contextual relevance, stakeholder participation, customizability, and rapid iteration, while designing digital health tools for individuals or populations.

Burden of disease and health status among Hurricane Katrina-displaced persons in shelters: a population-based cluster sample.

STUDY OBJECTIVE: Anecdotal evidence suggests that the population displaced to shelters from Hurricane Katrina had a significant burden of disease, socioeconomic vulnerability, and marginalized health care access. For agencies charged with providing health care to at-risk displaced populations, knowing the prevalence of acute and chronic disease is critical to direct resources and prevent morbidity and mortality. METHODS: We performed a 2-stage 18-cluster sample survey of 499 evacuees residing in American Red Cross shelters in Louisiana 2 weeks after landfall of Hurricane Katrina. In stage 1, shelters with a population of more than 100 individuals were randomly selected, with probability proportional to size sampling. In stage 2, 30 adult heads of household were randomly chosen within shelters by using a shelter log or a map of the shelter where no log existed. Survey questions focused on demographics, socioeconomic indicators, acute and chronic burden of disease, and health care access. RESULTS: Two thirds of the sampled population was single, widowed, or divorced; the majority was female (57.6%) and black (76.4%). Socioeconomic indicators of under- and unemployment (52.9%), dependency on benefits or assistance (38.5%), lack of home ownership (66.2%), and lack of health insurance (47.0%) suggested vulnerability. One third lacked a health provider. Among those who arrived at shelters with a chronic disease (55.6%), 48.4% lacked medication. Hypertension, hypercholesterolemia, diabetes, pulmonary disease, and psychiatric illness were the most common chronic conditions. Risk factors for lacking medications included male sex (odds ratio [OR] 1.58; 95% confidence interval [CI] 0.96 to 2.59) and lacking health insurance (OR 2.25; 95% CI 1.21 to 4.20). More than one third (34.5%) arrived at the shelter with symptoms warranting immediate medical intervention, including dehydration (12.0%), dyspnea (11.5%), injury (9.4%), and chest pain (9.7%). Risk factors associated with presenting to shelters with acute symptoms included concurrent chronic disease with medication (OR 2.60; 95% CI 1.98 to 3.43), concurrent disease and lacking medication (OR 2.22; 95% CI 1.36 to 3.63), and lacking health insurance (OR 1.83; 95% CI 1.10 to 3.02). CONCLUSION: A population-based understanding of vulnerability, health access, and chronic and acute disease among the displaced will guide disaster health providers in preparation and response.