Research

With Lyme and other tickborne diseases on the rise nationally and globally, the Johns Hopkins Lyme and Tickborne Diseases Dashboard aims to address this growing public health threat through the power of data and maps. The Dashboard tracks and contextualizes the impact of tickborne diseases and enables users to interactively visualize maps and download the data for further exploration. The Dashboard will advance understanding of the geography of tickborne diseases and highlight data limitations and gaps in knowledge, all in an effort to improve awareness and education and support research and scientific collaboration.

COVID Control: A Johns Hopkins Research Study Acquiring health data directly from individuals rather than relying on reports from hospitals or clinics could significantly increase the accuracy and efficiency of identifying COVID-19 outbreaks, and is likely to greatly expand disease surveillance capabilities in the general population.  In collaboration with researchers at the School of Medicine and Whiting School of Engineering, we have developed and released an app which allows user to record their self-measured body temperature regularly, and optionally other symptoms including, but not limited to, dry cough, breathing difficulties and change in smell or taste. Temperature and symptoms are then mapped geographically, and spatial statistical methods are used to identify emerging clusters of symptomatic individuals representing potential emerging COVID-19 outbreaks. Using confirmed COVID-19 data for ground truth validation, our analytical approach implements spatial statistical methods to identify regional changes in the likelihood of disease, thereby enabling a selective approach in health policy and resource allocation.

Non-cholera Vibrio species are a frequent cause of seafood-associated infections leading to an estimated 80,000 illnesses, 500 hospitalizations and 100 deaths annually in the United States. The NIH recently funded our proposal to characterize the spatial-temporal dynamics and human health risks of Vibrio parahaemolyticus Bacteria. Dr. Curriero and Dr. Ben Davis will lead the research to assess human health risks from this emerging pathogen in two large and economically significant estuarine environments, the Chesapeake Bay and Puget Sound. Research and analysis will focus on advancing spatial and spatial-temporal statistical methods to better quantify the uncertainty of spatial predictions for these bacteria in estuarine environments. Results will be used to support the development of region-specific quantitative microbial risk assessments (QMRAs) for vibriosis, extending the Food and Drug Administration’s (FDA’s) current national risk assessment model.  

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Understanding the effects of environmental exposures on child health and development is a priority for the National Institutes of Health. To advance knowledge in this area, NIH has launched a new seven-year initiative called the Environmental influences on Child Health Outcomes (ECHO) program. ECHO is designed to capitalize on existing participant populations of the former National Children’s Study and support approaches that can evolve with the science and take advantage of the growing number of clinical research networks and technological advances. 

SSPHC faculty Dr. Frank Curriero and Timothy Shields co-lead the Geospatial Working Group (GWG) of the ECHO-Data Analysis Center. The Geospatial Working Group provides an organizational structure where ECHO scientists can both learn about and provide input on the application of geospatial science within the ECHO Program.  The GWG ensures that geospatial tools, techniques, methods, and data are applied appropriately and consistently in meeting the scientific objectives of the Program. 

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The role of modifiable risk factors (RF), like physical activity (PA), sleep quality, social engagement, and cardiovascular (CV) risk is receiving greater attention to promote the cognitive health of an aging population and reduce risk of Alzheimer’s disease. Each of these risk factors is known to be influenced by environmental sources, such as neighborhood walkability, safety, noise, and access to low-cost transportation, retail, and healthy food sources. However, little is known about the role of neighborhood factors as drivers of cognitive aging and risk for Alzheimer’s disease. If neighborhood matters, adaptations in the use of available infrastructures have the potential to impact thousands at a time. Those neighborhood factors that most impact individual RF and cognitive health to reduce Alzheimer’s disease risk may further differ by race and sex. Evaluating the role of neighborhood characteristics on cognitive health is difficult to interpret from more widely used cross-sectional data due to residual confounding. Therefore, investigating how residentially stable older adults are affected by their local stable and changing contexts and how older adults who relocate to a new neighborhood may respond to their new context by changing health behaviors requires long-term study during the last 1/3 of life years prior to the onset of Alzheimer’s disease.

Using the 30-year Cardiovascular Health Study (CHS) we evaluate whether long-term exposure to neighborhood disadvantage may serve as a common cause of individual risk factors and neurocognitive and functional health, particularly in groups at elevated risk for Alzheimer’s disease by characterizing associations between long-term neighborhood exposures and: 1) individual rates of decline and impairment in cognition and physical function; 2) individual risk factors (physical activity, sleep quality, social support, and subclinical cardiovascular disease) for Alzheimer’s disease, which may mediate neighborhood differences in neurocognitive and functional risk, and; 3) whether specific neighborhood exposures account for racial and sex differences in cognitive and functional risk. Addressing these questions in the CHS provides an unmatched opportunity to examine the influence of a range of neighborhood factors on long-term trajectories of cognitive and functional aging prior to the onset of AD to inform future design of multi-level approaches to target those factors impacting multiple healthful activities.

SSPHC faculty Dr. Frank Curriero and Timothy Shields direct the Spatial Science Core (SSC) of the Johns Hopkins Malaria Research Institute (JHMRI) and the Johns Hopkins NIH funded International Center for Excellence in Malaria Research (ICEMR). ICEMR research, which aligns with JHMRI research, focuses on the epidemiology, vector biology and genetic diversity of malaria parasites in three endemic areas of Southern Africa with different levels of malaria transmission and stages of control.  

Objectives of the Spatial Science Core of the ICEMR include characterization of the social and physical environments in regions supporting ICEMR research projects. This has included developing mapped layers of climate variables, road networks, hydrology, topographical characteristics, and the use of satellite imagery for complete household location census. The SSC also includes a dedicated component in the research and application of spatial statistical methods, leading to publications involving the creation of malaria risk maps, cluster detection for identifying malaria hotspots, models to identify determinants of malaria both at the individual and environmental levels, and methods for analyzing and mapping mosquito vectors.

Vector-borne and waterborne diseases are sensitive to variability in environmental conditions, but reliable, timely data on these conditions can be difficult to obtain. SSPHC faculty work with advanced Earth system models and data assimilation systems to provide best-available, spatially and temporally complete monitoring and forecasts of variables known to predict the distribution of vectors or pathogens. Current projects include the use of land data assimilation systems to study and monitor malaria risk in the Amazon basin, the development of satellite-derived salinity estimates that are now used to monitor Vibrio risk in Chesapeake Bay, and high resolution seasonal forecasts of heat and moisture conditions to predict human and agricultural pests in East Africa and South Asia.

Remotely sensed and satellite imagery, GPS tracking devices, ecological momentary assessments (EMA), crowd sourcing; technologies to obtain, collect and create spatial information continues to advance. Developing and integrating spatial methods for studies utilizing these advancing technologies is an active area of research. A team led by Faculty Tim Shields have developed satellite-based methods for household level location census, a methodological approach that provides the sampling basis for JHMRI and ICEMR research studies. Procedures were also established to evaluate the temporal validity (shelf-life) of satellite images when used for human population studies. Current SSPHC research in this area incorporates spatial methods for GPS tracked/mobility data and also for characterizing environments in space and time for studies utilizing EMA.

SSPHC faculty continue to engage in translational research, developing and applying tools of spatial analysis supporting research across multiple public health applications.  A brief description of some previous and ongoing work is highlighted below:

• Clustering, cluster detection and spatial variation in risk of outcomes related to chronic diseases, infectious diseases and injury.
• Spatial attributes operating at the intersection of health and behavior, for example risky behaviors and sexual health, safety/crime, and mobility.
• Characterizing environments and their effects on health such as with the built environment, food environment, demographic, social and behavior environments, agriculture environment as well as exposure assessments for drug, crime, alcohol, air and water environments.

New collaborations and extending our current ones are always welcome.