DVBD Innovations: A Mobile Application for Field Work Data Collection Needs
Mobile technology allows community health workers to easily capture and store data as they go from house to house for community-based research studies. However, no single mobile data application provides everything needed to conduct a home visit. Community health workers end up using multiple mobile devices and applications, paper maps, and personal knowledge of a community. This disjointed approach presents data collection challenges and logistical difficulties, particularly for large studies. Further, many mobile applications do not comply with strict agency and U.S. government data security requirements.
Data collected during home visits are crucial to the success of the DVBD-led Communities to Prevent Arboviruses (COPA) project in Ponce, Puerto Rico. COPA project staff visit 3,800 participants annually to determine how many got infected with a virus spread by mosquitoes and to assess disease outcomes. For this big task, Dania Rodriguez from DVBD’s Dengue Branch Data Team created HTrack (Household Tracking), a mobile application that provides COPA staff with integrated components needed for a successful home visit.
HTrack offers offline navigation using pre-loaded maps, pre-populated data collection forms to eliminate data reentry after each visit, and additional data visualization components. HTrack also allows COPA staff to track their progress and pending home visits in real time. These features save COPA staff time and resources during home visits. Additionally, data are stored locally in the mobile device in compliance with data security requirements. Finally, HTrack can securely link to other popular data collection platforms used by community health workers. Therefore, other public health studies requiring home visits and navigation, particularly in remote settings, may benefit from using HTrack for data collection and logistics management.
Q fever on U.S. Goat Farms
Goat ownership is increasing in the United States, however 76% of goat producers are not familiar with a germ goats can carry that can make goats and people sick1. Goats are one of the main sources of Coxiella burnetii, the cause of Q fever. In goats, Q fever can cause loss of pregnancy and affect the overall health of the herd. People can get infected by breathing in dust that has been contaminated by infected goat feces, urine, milk, and birth products. Therefore, certain professions, such as goat producers, are at increased risk for exposure to C. burnetii. Signs and symptoms of Q fever in people include fever, chills, fatigue, and muscle pain. Not everyone who is infected may get sick.
The National Animal Health Monitoring System (NAHMS) Goat Study looked at the presence of C. burnetii among goats in the United States in 2019. About 779 goat producers from 25 states were eligible to participate.
DVBD’s Rickettsial Zoonoses Branch (RZB) Q fever team has been supporting the NAHMS study by providing laboratory testing for animal samples collected in 2019 and early 2020. More than 2,000 serum samples have been tested for antibodies against C. burnetii. More than 4,200 swabs collected from goats have been tested for the presence of C. burnetii. A positive swab indicates that a goat is spreading bacteria into the environment. These results are currently being analyzed to better describe C. burnetii positive herds in the United States.
The results of this NAHMS study supports goat producers in understanding the impact of Q fever on herd health. “This work is [also] important for public health because most cases and outbreaks of Q fever in the United States are associated with goats,” explains RZB scientist Halie Miller. Continued surveillance of Q fever in both goats and people may allow public health and agricultural officials to promote Q fever prevention and control efforts more precisely. To learn more about preventing Q fever in people, see RZB’s Q fever fact sheets, available in 6 languages. For more details about the NAHMS Goat Study visit the USDA APHIS websiteexternal icon.
1U.S. Department of Agriculture, Animal and Plant Health Inspection Service. Disease and Mortality on US Goat Operationspdf iconexternal icon [online]. 2012. [cited 2021 March 1].
Finding new data sources to estimate burden of Lyme disease
One of the most commonly asked questions about Lyme disease is, “How many people are diagnosed and treated each year?” In the February issue of Emerging Infectious Diseases, researchers from DVBD’s Bacterial Diseases Branch (BDB) explore the potential for commercial insurance claims to provide reliable data on Lyme disease diagnoses (Schwartz et al.), and then use those data to estimate the number of people who are diagnosed with Lyme disease annually in the United States (Kugeler et al.). Although 30,000–40,000 cases of Lyme disease are reported through surveillance each year, substantial underreporting occurs, as is typical for passively reported surveillance data. Because Lyme disease is so common and not all cases are captured by traditional surveillance, BDB researchers look for alternate ways to get this information.
Using data from anonymous insurance claims is one of these ways. A previous analysis of insurance claims data for 2005-2010 that estimated Lyme disease was diagnosed in about 329,000 people annually in the United States. With this new effort, CDC researchers use similar though updated methods to estimate that an average of 476,000 people were diagnosed with and treated for Lyme disease annually in the United States during 2010-2018.
Although direct comparison with the prior estimate is limited by differences in methodology, this new estimate underscores that Lyme disease is an important public health issue and suggests that the number of Americans diagnosed with Lyme disease is increasing. The authors also note that diagnoses may not all be true infections, and that the estimate likely includes some degree of overdiagnosis.
The high frequency of people being diagnosed with Lyme disease underscores the need for effective and widely acceptable tick bite prevention techniques, as well as increasing awareness about tick bite prevention.
DVBD’s Arboviral Diseases Branch (ADB) works globally to combat the threat of mosquito-borne diseases, including yellow fever which kills an estimated 30,000 people annually. As a World Health Organization (WHO) Collaborating Centre for Arboviral Reference and Research, ADB contributes to the WHO’s Eliminate Yellow Fever Epidemics strategy (EYE). This strategy aims to end yellow fever outbreaks by 2026 through improved laboratory and epidemiologic surveillance as well as routine vaccinations. ADB staff provide technical assistance, conduct training and research, and seek funding for yellow fever vaccination campaigns in endemic countries, as needed.
In 2020, the COVID-19 pandemic threatened yellow fever prevention campaigns in many at-risk countries. As the pandemic continued to spread among resource poor countries in Africa, preventing a secondary disease outbreak became increasingly important. However, safety precautions due to COVID-19 presented an additional hurdle for WHO and its partners.
For example, a campaign targeting 5.6 million people in Ghana was planned for November 2020, but an assessment before the campaign start date showed inadequate personal protective equipment (PPE) and infection prevention and control (IPC) supplies to prevent COVID-19. An upcoming election further complicated the situation. Ghana uses a semi-permanent stamp to indicate who has already voted, which is similar to the stamp typically used during yellow fever vaccination campaigns. To avoid confusion, officials decided to use “yellow cards” to note who was vaccinated; however, this required additional supplies the country did not have.
Fulfilling their role as a partner in EYE, ADB worked with Division and Center personnel to quickly secure over $7 million in internal funds and funds from CDC Foundation to purchase the needed PPE, IPC, and yellow cards. The vaccination campaign in Ghana was successfully carried out at the end of November 2020. The funding will also allow more yellow fever vaccination campaigns to move forward in Nigeria and the Democratic Republic of the Congo. The ability to carry out a vaccination campaign safely during the COVID-19 pandemic is critical. A yellow fever outbreak amidst a pandemic would devastate the already strained healthcare systems of these countries and lead to unnecessary lives lost.
Epidemic Forecasting Challenges Move Research Into Action
What if public health experts could accurately forecast the next epidemic much like a weather forecast? Epidemic forecasting aims to predict the trajectory, peak, and intensity of epidemics using statistical and mathematical models. Forecasting researchers develop and refine models using historical data to create a forecasting model. The more precise forecast models become, the more they can help public health officials determine when and where diseases spread.
CDC’s Division of Vector-Borne Diseases (DVBD) forecasting and modeling researchers Michael Johansson, Talia Quandelacy, Sarah Kada, and Velma Lopez, with the help of Sarabeth Mathis and Juan Sanchez Montalvo, are improving the science of forecasting and modeling to predict the spread of mosquito-borne diseases. In 2014, DVBD joined forces with CDC’s Influenza Division to drive innovation in dengue and influenza forecasting, creating the CDC Epidemic Prediction Initiative. The initiative was founded to address barriers to the implementation of forecasts in public health such as variable data access, the absence of systems for real-time forecasting, and limited assessment and comparison of forecast methods.
In 2015, the Dengue Fever Forecasting Challenge received approximately 10,000 forecasts for dengue epidemics in Iquitos, Peru and San Juan, Puerto Rico. The 2019 and 2020 Aedes Forecasting Challenges aim to predict the presence of these mosquitoes and where their geographic range may be expanding. The 2020 West Nile virus (WNV) Forecasting Challenge aims to predict the total number of neuroinvasive WNV cases using county level data from across the United States.
These annual challenges open new research opportunities offering extensive long-term datasets from multiple jurisdictions, allowing forecasting researchers to improve their models and share methodologies. The challenges also asses level of forecast skill and utility of forecasting for public health by engaging public health stakeholders directly in the development of next generation tools that support their work.
Forecasting has the potential to help predict and prevent more illnesses, including mosquito-borne diseases. Promoting modeling and forecasting research collaboration and access to datasets can help to improve the precision of forecasting models. In turn, models can help direct interventions to save and better target limited public health prevention and control resources.
Yellow fever is one of the oldest-recognized mosquito-borne diseases in the world. Those who become infected are at risk for severe liver disease with bleeding and jaundice. Between 30 to 60% of those who develop this severe form of the disease will die. Despite having an effective vaccine since the 1930s, outbreaks continue to occur, particularly in Africa and South America.
Being able to quickly identify yellow fever infections is crucial to stopping an outbreak. However, recognizing cases of yellow fever can be difficult. Not everyone has symptoms. For those who do, symptoms are similar to other diseases that cause fever, aches, and pains.
Diagnosing yellow fever can be difficult. Traditional diagnostic testing is technically challenging, particularly in resource-limited settings. The traditional test requires skilled staff and takes days to perform. To address these technical challenges, Jane Basile and Christin Goodman led a team of DVBD researchers to create pre-measured, calibrated test components that allow the traditional serologic test (YF IgM ELISA) to be performed easily in resource-limited settings. This new diagnostic kit, the Yellow Fever M-antibody Capture-half Day (YF MAC-HD), cuts processing time from 3 days to just 4 hours. The most critical kit components are freeze dried to improve stability, and the user simply adds water. Each kit can test up to 24 samples and can be refrigerated for at least one year.
CDC validated the new YF MAC-HD test kits during the 2016 Angola outbreak. Professional laboratory staff found the test easy to use and provided results comparable to the serologic test. Recent trainings in both Africa and South America included attendees from 46 countries. Trainings are crucial for national laboratories across Africa and South America. As a result, laboratories are better prepared to assist with surveillance efforts across the continents.
Since most yellow fever outbreaks occur in resource-limited countries, where electricity, water, and even reliable shipping can be an issue, this new diagnostic kit is a valuable tool in combatting yellow fever outbreaks. Basile hopes when the next outbreak happens, laboratory staff will not only have easy-to-use tests but also the training to use them. CDC is working with an external manufacturer to create a consistent supply of the YF MAC-HD kits. Now the biggest hurdle researchers have is how to distribute large numbers of kits.
Advanced molecular detection (AMD) integrates the latest next-generation genomic sequencing technologies with bioinformatics and epidemiology expertise across CDC and the nation to help us find, track, and stop disease-causing pathogens faster than ever before. Scientists at DVBD are using AMD to uncover, detect more of, and advance knowledge of pathogens spread through tick bites and about the ticks that are responsible for spreading these pathogens.
DVBD scientists, Luke Kingry, Stephanie Oatman, Sarah Sheldon, and partners used an AMD method called 16S metagenomics to analyze over 13,000 samples from patients who were suspected of having a tickborne illness. Twelve tickborne species of bacteria that cause illness in people were detected, including two not previously known to cause illness in people. The AMD method increased the number of tickborne bacteria identified by 100 percent as compared to using typical diagnostic testing methods.
DVBD scientists, Maria Galletti, Joy Hecht, and Chris Paddock, are using another AMD method to reveal new information about ticks that could help us better understand tickborne pathogens and how ticks spread those pathogens. The AMD method is known as MALDI-TOF, matrix-assisted laser desorption/ionization time-of-flight. This method will complement currently used methods and expand understanding of tick life stages and how certain germs adapt to become more or less capable of infecting people. The data collected will be used to establish a database of genetic information about the pathogens spread by ticks; the first of its kind in the Western Hemisphere. Scientists worldwide can use the database to improve the accuracy and speed of tick identification and tickborne disease surveillance. The team says, “We are excited to see what new information MALDI will reveal about the identification of medically relevant ticks that could be associated to pathogen prevalence in geographical areas with important disease burden. The results might help us better understand tick-borne disease dynamics in those areas.”
AMD activities at DVBD are improving tickborne disease detection, discovery, and surveillance, and are improving our understanding of how ticks spread germs. For more information about AMD activities across CDC, visit the CDC AMD website.