Identifying risks of human flea infestations in plague-endemic areas of Madagascar

A home in the Central Highlands of Madagascar. Residential structures vary greatly in rural areas. (Photos by Adelaide Miarinjara)

By Carol Clark

Madagascar is one of the last places where outbreaks of human bubonic plague still happen regularly. 

Fleas carrying the plague bacterium Yersinia pestis can spread the disease through their bites. And while a species commonly known as “the rat flea” has been fingered as the main culprit in plague outbreaks, a species known as “the human flea” may play a secondary role. 

As an investigator during plague outbreaks in rural Madagascar, medical entomologist Adelaide Miarinjara knew that many households were teeming with these human fleas. Miarinjara grew up in the island nation off the east coast of Africa and is now a postdoctoral fellow at Emory University, collaborating with the Pasteur Institute in Madagascar. 

“We have observed huge variability in the number of fleas in different households in the same village,” she says. “We might collect three or five fleas in one house and hundreds of them in another house.” 

Miarinjara led a study to solve the mystery of this variability. 

PLoS Neglected Diseases published her team’s findings: The abundance of human fleas is primarily associated with households that have a traditional dirt floor covered by a plant-fiber mat, as opposed to households with cement or board floors. A secondary risk factor was keeping animals in the house at night. 

“Flea larvae need humidity, but not too much humidity, to survive,” Miarinjara says, “so the dirt covered by the plant-fiber mat may be holding just the right amount of moisture for them to thrive.” 

She hopes that agencies seeking to improve people’s lives in plague-endemic areas of Madagascar focus on upgrading the flooring in homes and constructing sheds separate from the households for animals.

“Flea infestation raises the risk for getting diseases and it has a big impact on the quality of life,” Miarinjara says. “The constant bites are annoying and lead to lack of sleep.” 

Household flea infestations also promote the overuse of insecticides. Surveys by the researchers reveal that 80% of the households use insecticide to try to battle the fleas. Many people are buying liquid insecticides that are repackaged in empty plastic or glass containers, without labels or instructions for how to apply them, and sold in small, open-air markets. 

Improper use of insecticides is a health risk to people who may be overexposed to the chemicals.

“Overuse of these chemicals is also dangerous because some fleas are developing resistance to insecticides — the frontline tools for battling plague outbreaks,” Miarinjara says. 

“Poverty related to housing construction is a primary challenge that this research identified,” adds Thomas Gillespie, senior author of the study and professor and chair of Emory’s Department of Environmental Sciences. “Resurfacing dirt floors in homes with concrete could improve a range of health and quality-of-life issues, from reducing flea populations in homes to making the floors easier to clean of contaminants such as fecal matter tracked in from the outside.” 

The Gillespie lab is a pioneer in the “one health” approach to epidemics — studying the interactions of people, domestic animals, wildlife and ecosystems to understand how germs jump across species. 

Village residents gather to hear the research team brief them on the purpose of their visit. The women in the foreground are sitting on a traditional plant-fiber mat.

The plague has afflicted humans at least as far back as the Bronze Age and has persisted through the centuries. The advent of antibiotics — which can effectively treat plague — turned the disease into a horror story from the past for much of the world. 

In Madagascar, however, plague returns regularly to claim new victims. Cases typically originate in the rural rice-growing region of the central Highlands during the rainy season. Outbreaks there are associated with agriculture, deforestation, the black rat — and fleas. 

Different flea species have evolved to prefer the blood of one animal over another, although they may feed on a variety of organisms if they are hungry enough. 

Most plague research is centered on the rat flea, or Xenopsylla cheopis. Just one of its bites can transmit enough bacteria to infect someone with plague. In contrast, several bites from the human flea, Pulex irritans, are required to transmit the bacteria, making it a less potent spreader of plague but still a threat. 

For the current paper, the researchers collected fleas from 126 households in four different villages. Rural Madagascar homes typically consist of more than one level. The bottom level is often used to keep livestock overnight and the second and third floors are where members of the family sleep, cook and eat. 

Researchers collect the fleas captured overnight in a candle trap while members of a household watch.

The fleas were collected overnight on the second floor of the homes using simple traps — a lit candle set in a dish of soapy water. The fleas are attracted to the flickering light and drown when they hop into the dish. 

The researchers painstakingly removed each drowned flea using tweezers, set them to dry on absorbent paper, and then transferred them to test tubes for laboratory identification and analyses. 

The results showed that around 95% of the species collected in households were human fleas, mixed at times with a few rat fleas and a few from a third species that prefers to feed on cats and dogs. Collections were conducted in both the dry and rainy seasons with similar results. 

“We’re now looking deeper into what’s going on with insecticide use in households,” Miarinjara says. “We want to both sort out what is driving insecticide resistance among fleas and find ways to help people use insecticides safely and more effectively.” 

Co-authors of the current study include: Annick Reveloson, a PhD student at the University of Antananarivo in Madagascar; Stephen Mugel, an Emory PhD student set to graduate this May; Nick An, who graduated last year from Emory’s BS/MPH program; Andry Andriamiadanarivo, a technician at Centre ValBio in Madagascar; and Minoarisoa Rajerison, Rindra Randremanana and Romain Girod, research scientists at the Pasteur Institute in Madagascar. 

The research was funded by the Branco Weiss Society in Science Fellowship and the American Society of Tropical Medicine and Hygiene.

Related:

A medical entomologist battles bubonic plague in Madagascar

Tracking ticks in Georgia to help monitor emerging diseases

Madagascar: An island on the brink

Tracking ticks in Georgia to help monitor emerging diseases

Mapping the lone star tick is another step in a comprehensive Emory project to track and monitor the array of tick species in Georgia and the diseases that they can spread — including those caused by emerging pathogens.

By Carol Clark 

The most common tick found on humans in Georgia is the lone star tick — an aggressive seeker of blood that can spread dangerous pathogens through its bites. 

Emory University researchers combined field data with spatial-analysis techniques to map the distribution of the lone star tick across the state. The journal Parasites & Vectors published the research, which identifies specific environmental conditions associated with this tick species, Amblyomma americanum, in Georgia. 

The areas with the highest probability for the presence of lone star ticks include parts of the Southeastern Plains and Piedmont ecoregions of the state, including metro Atlanta. 

“We found that these regions contain sweet spots for the lone star tick,” says Stephanie Bellman, first author of the study and an MD/PhD student in Emory’s School of Medicine and Rollins School of Public Health. “They tend to be more prevalent in forested areas of mid-elevation — not too high or too low — and in soils that retain moisture but are not swampy.” 

The study maps the distribution at the scale of one square kilometer. That resolution is far finer than the currently available information, which is limited to the county level and does not encompass the state. 

“As the weather warms and people start getting into the outdoors more, we hope our data can be used to target areas for tick-bite prevention messaging,” says Gonzalo Vazquez-Prokopec, professor in Emory’s Department of Environmental Sciences and senior author of the study. 

Vazquez-Prokopec is a leading expert in vector-borne diseases — infections transmitted among humans and animals by the bite of a living organism, such as a tick or a mosquito. 

Diseases the lone star tick is known to transmit include ehrlichiosis, southern tick-associated rash illness (STARI) and Heartland virus disease — which was first identified in the United States in 2009. The bite of the lone star tick is also associated with a potentially life-threatening allergy to red meat and dairy products known as alpha-gal syndrome. 

First author Steph Bellman, far right, in the field last summer with fellow Emory students and co-authors, from left, Josie Pilchik, Isabella Roeske, Ellie Fausett and Audrey Long.

Mapping the lone star tick is another step in a comprehensive Emory project to track and monitor the array of tick species in Georgia and the diseases that they can spread — including those caused by emerging pathogens. 

Tickborne diseases are on the rise, far surpassing the incidence of diseases spread by mosquitos in the United States. While Lyme disease is the most common, the Centers for Disease Control and Prevention (CDC) currently recognizes 18 tickborne diseases in the country. 

“We need to educate people that the environment that they grew up in is likely very different in terms of the number and types of ticks and the pathogens that they are carrying,” Vazquez-Prokopec says. 

Anne Piantadosi, assistant professor in Emory School of Medicine’s Department of Pathology and Laboratory Medicine, is co-author of the study. Co-authors also include five Emory students who conducted fieldwork: Ellie Fausett (who has since graduated with a joint environmental sciences/MPH degree); Leah Aeschleman and Audrey Long (who have since received master’s of public health degrees from Rollins School of Public Health); Josie Pilchik, (who graduated with a bachelor’s in biology) and Isabella Roeske (an Emory senior majoring in environmental sciences). 

Climate change is fueling warmer and shorter winters, increasing opportunities for some species of ticks to breed more frequently and expand their ranges. Land-use changes are also strongly associated with tickborne diseases, as more human habitats encroach on wooded areas and the loss of natural habitat forces wildlife to live in denser populations. 

“Georgia is a tick haven in general,” Bellman says, “since we have a long warm season and such a diversity of habitats.” 

An aggressive biter

The researchers decided to focus first on mapping the distribution of the lone star tick because it is the dominant tick species in Georgia and can spread an array of pathogens. In 2019, the Emory researchers found that Heartland virus is circulating in lone star ticks in Georgia, an emerging pathogen that is not well understood. 

The lone star tick (CDC)

Named for a bright, yellowish-white spot on its back, the lone star tick is widely distributed in wooded areas across the Southeast, Eastern and Midwest United States. It is tiny —in the nymph stage it is about the size of a sesame seed and as an adult it is barely a quarter-of-an-inch in diameter as an adult.

Despite its tiny size, the lone star tick is aggressive in its quest for blood meals. “They can sense carbon dioxide from your exhaled breath and the vibrations from your movement in a forest,” Bellman says. “They climb up onto vegetation and reach out their legs to grab onto you as you pass by.” 

For the current study, Bellman led crews of Emory students, known as “the tick team,” in field surveys. They used “flagging” as a tick-collection technique. A white flannel cloth attached to a pole is swished in a figure-eight motion through the underbrush. Tweezers are used to transfer any ticks found on the flannel into a vial. 

Tick team members surveyed 198 locations at 43 state parks and wildlife management areas across the state, from March to July 2022. Analyses combined the site-sampling data with environmental variables — including type of vegetation, land use, climate, elevation and other factors — characteristic for six different ecoregions of Georgia. 

Lone star ticks were found in all of the ecoregions except for the mountainous Blue Ridge ecoregion in the northeast corner of the state. The majority of the ticks were found in forested areas of the Piedmont, Southeastern Plains and Southern Coastal Plains ecoregions. 

The researchers encourage people to follow the recommendations of the CDC for preventing tick bites. 

An array of ticks

And while the map for the lone star tick provides guidance on the likelihood of encountering the most prevalent human-biting tick in the state, there are other tick species that the researchers have yet to map. The black-legged tick (Ixodes scapularis), which can transmit the bacterium that causes Lyme disease, for instance, is also established in Georgia. Lyme disease, however, is relatively uncommon in in the state for reasons that are not yet well-understood. 

The researchers are also investigating the Asian longhorned tick (Haemaphysalis longicornis) in Georgia. Long established in China, Japan, Russia and parts of the Pacific, the Asian longhorned tick was first detected in the United States in 2017, in New Jersey, and has since spread to 19 states. It was found on farm animals in Pickens County, Georgia in 2021. 

The Asian longhorned tick (CDC)

The Asian longhorned tick reproduces asexually and a single female can generate as many as 100,000 eggs, rapidly producing massive amounts of offspring that feed on livestock. So many ticks can be covering a single sheep or cow that the loss of blood physically weakens or, in extreme cases, kills the animal. 

While it is often associated with livestock, the Emory research team recently found Asian longhorned ticks in the Buck Shoals Wildlife Management Area in White County, Georgia. 

The Asian longhorned tick carries bacterial and viral pathogens that can infect humans, including severe fever with thrombocytopenia syndrome virus (SFTSV), also known as Dabie bandavirus. Human cases of SFTS, a hemorrhagic fever, emerged in China in 2009 and have since been identified in other parts of Asia, although not in the United States. 

Also of concern is the fact that the Heartland virus shares genomic similarities with SFTS, which suggests the Asian longhorn tick could potentially transmit this emerging pathogen. The Emory team has been finding the Heartland virus in lone star ticks collected from central Georgia starting in 2019. They have continued to find Heartland virus in at least some of the ticks collected from that area nearly annually through 2023. (They did not perform collections in 2020 due to the COVID-19 pandemic.)

More than 60 cases of Heartland virus disease have been reported in the United States, according to the latest CDC statistics. Many of the identified cases were severe enough to require hospitalization, and a few individuals with co-morbidities have died. The actual number of people who may have been infected with Heartland virus is believed to be higher, however, since the virus is not well known and tests are rarely ordered for it. 

Complicating the issue is the fact that symptoms of Heartland virus are akin to those of many tickborne illnesses: fever, fatigue, headache, nausea, diarrhea and muscle or joint pain. 

“Human cases of Heartland virus are rare now, but we don’t know whether that could change,” Bellman says. “We need to gather more baseline data and learn how it spreads in the environment so that we have the evidence we need to potentially prevent, or limit, its spread.” 

Anne Piantadosi, assistant professor in Emory School of Medicine’s Department of Pathology and Laboratory Medicine, is co-author of the study. Co-authors also include five Emory students who conducted fieldwork: Ellie Fausett (who has since graduated with a joint environmental sciences/MPH degree); Leah Aeschleman and Audrey Long (who have since received master’s of public health degrees from Rollins School of Public Health); Josie Pilchik, (who graduated with a bachelor’s in biology) and Isabella Roeske (an Emory senior majoring in environmental sciences). 

Work on the current paper was funded by grants from the U.S. Department of Agriculture, National Institutes of Health, Emory University and the Emory MP3 Initiative and Infectious Disease Across Scales Training Program. 

Related stories: 

Heartland virus identified in lone star ticks in Georgia 

Building boom boosts malaria-carrying mosquito in Ethiopia 

Big data zeros in on a mosquito menace

A new estimate of U.S. soil organic carbon to improve Earth system models

"To understand how soil carbon will change under a changing climate, we first need accurate estimates of current soil organic carbon levels and the key factors that influence them," says Emory environmental scientist Debjani Sihi, senior author of the study.

By Carol Clark

Soil contains about twice as much carbon as the atmosphere and plants combined. It is a major carbon sink, capable of absorbing more carbon dioxide from the atmosphere than it releases. Management of soil carbon is key in efforts to mitigate climate change, in addition to being vital to soil health and agricultural productivity. 

Measuring soil carbon, however, is a painstaking, expensive process. Samples must be dug from the ground and sent to a lab for analysis, making upscaling measurements on a large spatial scale challenging. 

Now environmental scientists have combined field-level data with machine-learning techniques to estimate soil organic carbon at the U.S. continental scale. The Journal of Geophysical Research — Biogeosciences published the new soil organic carbon estimate, which improves the overall estimate for the United States and gives new insights into the effects of environmental variables on soil organic carbon. 

“There is growing recognition that soil organic carbon is important and that we should invest in building it up through sustainable land management practices,” says Debjani Sihi, senior author of the study and assistant professor of environmental sciences at Emory University. “Our estimate is more accurate than existing estimates and provides a better benchmark to guide policymakers and land managers in adopting climate-smart practices.” 

Land is far more efficient than the ocean at retaining carbon, Sihi notes, and offers one possible nature-based solution to help mitigate climate change. “We could potentially create conditions,” she explains, “that are favorable for soil to capture carbon dioxide from the atmosphere and lock it there for a really long time — over millennia.” 

Sihi is a biogeochemist who studies environmental and sustainability issues at the nexus of soil and climate. 

First author of the current paper is Zhuonan Wang, a former postdoctoral fellow in Sihi’s lab who is now at Colorado State University. 

Digging into soil data 

Soil organic carbon is made up of plant and animal matter in various states of decomposition. While inorganic carbon is also found in the soil in the form of carbonate minerals, organic carbon is usually the largest proportion and the most important driver of soil biology and quality. 

The U.S. Department of Agriculture maintains the National Cooperative Soil Survey soil characterization database. This data was gathered over decades both by walking over the land and observing and by digging up core samples and sending them to laboratories for analysis. Measuring soil organic carbon, for example, requires digging a core to the root zone, about 30 centimeters deep to obtain a topsoil profile and until the core hits bedrock to obtain an entire soil profile. 

Soil sampling is done in other parts of the world as well. The International Soil Organic Carbon Network encompasses more than 430,000 soil profiles, drawn from across the globe. Scientists use such data to create “soil maps,” or estimates of soil characteristics in various regions. One well-known soil map is the Harmonized World Soil Database, developed by the United Nations’ Food and Agricultural Organization and collaborators. Another is SoilGrids, supported by the International Soil Reference and Information Center in the Netherlands. 

Significant inconsistencies exist in the estimates of soil organic carbon within both the Harmonized World Soil Database and SoilGrids. Sihi and her team set out to see if they could resolve these inconsistencies within the United States estimates by finding more effective ways to scale up the soil-sampling data. 

The researchers divided the United States — including all 50 states and Puerto Rico — into 20 different regions and created machine-learning models for each region. They obtained nearly 50,000 soil samples, ranging from 30 centimeters to one meter deep, from across these regions. They built their algorithms using these data samples for soil organic carbon, matched to precise geographic information system locations. 

They also drew from additional open-source data to feed their models with 36 environmental variables, including details about the climate, topographical features of the land, biogeochemical properties of the soil and the amount of vegetation on the landscape. 

A better benchmark for modeling Earth systems 

The results showed that the new method provided more accurate estimates than both the Harmonized World Soil Database and SoilGrids for the top 30 centimeters of soil, where the most biologically active soil organic carbon tends to be concentrated. 

The new method also revealed how the effects of environmental variables on soil organic carbon vary across regions. While climate was the most common predictor of soil organic carbon across most of the regions, the vegetation index tended to be more important in the arid areas of the southwest. Elevation was a key variable in regions that were mountainous or included a major river delta. 

The researchers hope that others will apply their approach to other countries and continents where enough on-the-ground data is available. 

“The beauty of our approach is that it gives us the power to identify regions with high uncertainty in our estimates and that helps us to guide future sampling efforts,” Sihi says. 

Considering environmental variables also increases the new model’s flexibility as global temperatures rise due to climate change, causing soils to warm and alter rainfall patterns. It remains unclear, Sihi notes, if soils will continue to serve as a carbon sink or transform into a carbon source. 

“To understand how soil carbon will change under a changing climate, we first need accurate estimates of current soil organic carbon levels and the key factors that influence them,” Sihi says. “Our new estimate is a step toward getting more accurate baseline data to improve Earth system models for climate change.” 

Co-authors of the new estimate include Jitendra Kumar (Oak Ridge National Laboratory), Samantha Weintraub-Leff (National Ecological Observatory Network), Katherine Todd-Brown (University of Florida) and Umakant Mishra (Sandia National Laboratories). 

The work was supported by the National Science Foundation and the U.S. Department of Energy.

Related:

Emory breaking new ground for climate-smart agriculture in Southeast

Soil quality critical to help some U.S. crops weather heat stress from climate change

Paint color-matcher quantifies iron levels in soil

'Jeopardy!' contestant creates buzz with psychological study of trivia experts

'Jeopardy!' contestant and Emory psychologist Monica Thieu, shown with host Ken Jennings, during the 2024 "Jeopardy!" Invitational Tournament.

Monica Thieu is a four-time "Jeopardy!" contestant and a postdoctoral fellow in Emory's Department of Psychology. Psychonomic Bulletin & Review recently published her finding that two memory systems — one for facts and another for personal experiences  are more entwined in the minds of top trivia experts compared to others. 

"In trivia experts, it appears that these two systems are talking to each other in unique ways," Thieu says. "Our findings for this special population may help us better understand how memory works in normative populations."

Thieu says her personal experience in trivia competitions helped in the design of the study. 

"It's trick to make sure that lab experiments are both rigorous and reflect lived experience," Thieu says. "I know the world of trivia experts well."

Read the full story here.

Related:

Psychologists document the age our earliest memories fade

Primatologist Frans de Waal remembered for bringing apes 'a little closer to humans'

Frans de Waal shown overlooking the chimpanzee habitat at the Emory National Primate Research Center.

By Carol Clark

Emory University primatologist Frans de Waal — who pioneered studies of animal cognition while also writing best-selling books that helped popularize the field around the globe — passed away March 14, 2024, from stomach cancer. 

De Waal, Charles Howard Candler Professor Emeritus of Psychology and former director of the Living Links Center for the Advanced Study of Ape and Human Evolution at the Emory National Primate Research Center, was 75. From his groundbreaking 1982 book “Chimpanzee Politics: Power and Sex Among Apes” to 2019’s “Mama’s Last Hug: Animal Emotions and What They Tell Us About Ourselves,” de Waal shattered long-held ideas about what it means to be an animal and a human. 

“One thing that I’ve seen often in my career is claims of human uniqueness that fall away and are never heard from again,” de Waal said in 2014. “We always end up overestimating the complexity of what we do. That’s how you can sum up my career: I’ve brought apes a little closer to humans but I’ve also brought humans down a bit.” 

 Read the full story here by clicking here.

Atlanta Science Festival returns to inspire discovery for all ages

A middle-school student experiences an Emory chemistry lab during a recent community outreach event. 

The Atlanta Science Festival returns March 9 to 23, inviting curious kids and adults to explore all things science, technology, engineering and mathematics (STEM). Experts in these fields — including many members of the Emory community — will serve as educational guides for more than 150 interactive events. 

“The Atlanta Science Festival aims to bring the community together through their shared love of science,” says Meisa Salaita, co-founder and co-executive director of Science ATL, the engineers of the festival. “Through these events, we hope to inspire and empower the next generation to pursue their dreams.” 

Participants can take a crash course on the basics of AI, create an herbarium of medicinal plants, go into the field with researchers studying microplastic pollution in a stream, take a behind-the-scenes tour of the latest advances in healthcare technology and even get a taste of the physics of cheese making. 

Now in its 11th year, the Atlanta Science Festival was co-founded by Emory, Georgia Tech and the Metro Atlanta Chamber. 

“We have grown into a mainstay of Atlanta,” says Salaita, noting that many of the events fill up quickly. “The festival is something that people look forward to every spring.” 

 Click here for highlights of this year's festival with an Emory connection.

Spatial model predicts bumblebee exposure to pesticide use

Field experiments were conducted using yellow-faced bumblebees, a species native to the West Coast and an important pollinator.

By Carol Clark

It has long been known that agricultural pesticides are one of the greatest threats to bees and other essential pollinators. What farmers have lacked is an understanding of how different pesticides, applied at various times on a variety of crops, affect the risk of exposure to bees living near the fields. 

Researchers have drawn from real-world data to try to address this gap, developing and testing a spatial model for predicting pesticide exposure in bumblebees. The journal Science of the Total Environment published the work, based on the interactions of the yellow-faced bumblebee (Bombus vosnesenskii) with crops in California. 

“We were able to explain nearly 75% of the spatial variation in pesticide exposure among the bumblebee hives using our model,” says Eric Lonsdorf, first author of the study and assistant professor in Emory’s Department of Environmental Sciences. 

Relatively simple models were more effective at preventing exposures than the researchers expected.

“Our results suggest that simply data on where and when a pesticide was sprayed is all that you need to make a good prediction for the threat to nearby hives,” Lonsdorf says. 

Including data on how long a particular chemical lingers in the landscape or how attractive the flowers in a particular crop are to the bees did not make a significant difference in the model’s predictive power. 

“We found that even if a crop is not that attractive to the bees, the chemicals from that crop are still going to be found in their pollen,” Lonsdorf says. “The bees may be picking up the chemical due to drift of the pesticide onto nearby weeds where they are foraging.” 

Providing tools for conservation 

Lonsdorf studies natural capital, or nature’s contributions to humans. He translates ecological principles and knowledge into predictive models that enable industry leaders and policymakers to better manage natural resources. 

He’s currently using models he developed to help the U.S. Fish and Wildlife Service identify bee conservation priority areas in the United States. 

More research is needed, Lonsdorf says, to determine whether the bumblebee risk-prediction model will scale up across different landscapes and for different species of bees. The current study also did not delve into how the amount of a particular pesticide found in the pollen translated into toxicity for the bees. 

Co-authors of the paper include Neal Williams from the University of California, Davis, and Maj Rundlöf and Charlie Nicholson, who are affiliated with the University of California, Davis, and Lund University in Sweden. 

Drawing from fine-scaled data 

The researchers began with experiments set amid a variety of crops in northern California’s Yolo County. Fourteen pairs of yellow-faced bumblebee colonies were placed around the agricultural landscape. This species of bumblebee is native to the West Coast and the most abundant wild species of bee in this range, found in both urban and agricultural areas. 

Pollen that bees in each hive collected were sampled at six different times during the growing season. The pollen samples were then assessed for exposure to 52 different active ingredients encompassing a range of pesticides. 

Data from these experiments were combined with field-level data from the California Department of Pesticide Regulation on what pesticides were sprayed and what days they were sprayed. 

“California is unique in providing such fine-scaled, public data,” Lonsdorf says. “In most places in the United States, information on what pesticides are being sprayed is only collected at the county level and summarized on an annual basis.” 

The detailed data allowed the researchers to consider a range of factors in their predictive model to identify those factors with the most predictive power. 

“Our risk-prediction model marks another step toward evaluating pollinator-conservation issues to help guide policies for pollinator landscapes,” Lonsdorf says. “The next step is to do a field-toxicity assessment to get a better understanding of how pesticides are affecting bee health.” 

He and colleagues are now conducting such a study with honeybees, he adds. 

The current paper was supported by the National Science Foundation, California Department of Food and Agriculture, Almond Board of California, KIND Foundation Fund for Pollinator Health and the Swedish Research Council.

Related:

Analyzing ways to help golden eagle populations weather wind-energy growth

Antibiotic used on food crops affects bumblebee behavior, lab study finds

Pollinator extinctions alter structure of ecological networks

Computer scientists create simple method to speed cache sifting

"Computer performance fascinates me," says Emory graduate student Yazhuo Zhang, co-first author of the discovery, shown on a visit to Switzerland. Set to receive her PhD in May,Zhang accepted a post-doctroal fellowship at the Federal Institute of Technology Zurich (ETH Zurich).

By Carol Clark

Computer scientists have invented a highly effective, yet incredibly simple, algorithm to decide which items to toss from a web cache to make room for new ones. Known as SIEVE, the new open-source algorithm holds the potential to transform the management of web traffic on a large scale. 

SIEVE is a joint project of computer scientists at Emory University, Carnegie Mellon University and the Pelikan Foundation. The team’s paper on SIEVE will be presented at the 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI) in Santa Clara, California, in April. 

A preprint of the paper is already making waves. SIEVE became a hot topic on Hacker News and the subject of a feature in the influential tech newsletter TLDR, driving tens of thousands of visits to the SIEVE website. 

“SIEVE is bigger and greater than just us,” says Yazhuo Zhang, an Emory PhD student and co-first author of the paper. “It is already performing well but we are getting a lot of good suggestions to make it even better. That’s the beauty of the open-source world.” 

Zhang shares first authorship of the paper with Juncheng (Jason) Yang, who received his master’s degree in computer science at Emory and is now a PhD candidate at Carnegie Mellon. 

“SIEVE is an easy improvement of a tried-and-true cache-eviction algorithm that’s been in use for decades — which is literally like centuries in the world of computing,” says Ymir Vigfusson, associate professor in Emory’s Department of Computer Science. 

Vigfusson is co-senior author of the paper, along with Rashmi Vinayak, an associate professor in Carnegie Mellon’s computer science department. Yao Yue, a computer engineer at the Pelikan Foundation, is also a co-author. 

In addition to its speed and effectiveness, a key factor sparking interest in SIEVE is its simplicity, lending it scalability. 

“Simplicity is the ultimate sophistication,” Vigfusson says. “The simpler the pieces are within a system designed to serve billions of people within a fraction of a second, the easier it is to efficiently implement and maintain that system.” 

Keeping ‘hot objects’ handy 

Many people understand the value of regularly reorganizing their clothing closet. Items that are never used can be tossed and those that are rarely used can be moved to the attic or some other remote location. That leaves the items most commonly worn within easy reach so they can be found quickly, without rummaging around. 

A cache is like a well-organized closet for computer data. The cache is filled with copies of the most popular objects requested by users, or “hot objects” in IT terminology. The cache maintains this small collection of hot objects separately from a computer network’s main database, which is like a vast warehouse filled with all the information that could be served by the system. 

Caching hot objects allows a networked system to run more efficiently, rapidly responding to requests from users. A web application can effectively handle more traffic by popping into a handy closet to grab most of the objects users want rather than traveling down to the warehouse and searching through a massive database for each request. 

“Caching is everywhere,” Zhang says. “It’s important to every company, big or small, that is using web applications. Every website needs a cache system.” 

And yet, caching is relatively understudied in the computer science field. 

A logo for SIEVE, designed by Zhang, portrays hotter objects in shades of red and colder objects in shades of blue. Zhang also designed a web site for SIEVE, including a motion graphic demonstrating how it works.

A sense of wonder 

Zhang, who received her undergraduate and master’s degrees at universities in her hometown of Guangzhou, China, started off majoring in software engineering. “It’s fun to code and to make a website,” she says, “but it’s not fundamentally challenging once you learn how to do it. I wanted to gain more understanding of the backbone of technology. Computer performance fascinates me.” 

Zhang applied to Emory to work with Vigfusson given his focus on fundamental topics such as computer security and caching, and his skill at talking about them in simple terms. “It’s important to make complex ideas easy to understand,” she says. 

In turn, Vigfusson appreciates how Zhang approaches intractable problems with a sense of wonder. “She’s doing science for all the right reasons,” he says. “She is delighted by the process of exploration and by traversing the frontiers of the unknown.” 

In 2016, Vigfusson received a National Science Foundation Faculty Early Career Development Program (CAREER) grant to explore cache systems. Yang took the lead on the project while he was an Emory master’s student. As a PhD student at Carnegie Mellon, Yang continued to collaborate with Vigfusson and helped to mentor Zhang when she arrived at Emory in 2019. 

How caching works 

While caching can be thought of as a well-organized closet for a computer, it is difficult to know what should go into that closet when millions of people, with constantly changing needs, are using it. 

The fast memory of the cache is expensive to run yet critical to a good experience for web users. The goal is to keep the most useful, future information within the cache. Other objects must be continuously winnowed out, or “evicted” in tech terminology, to make room for the changing array of hot objects.

Cache-eviction algorithms determine what objects to toss and when to do so. 

FIFO, or “first-in, first-out,” is a classic eviction algorithm developed in the 1960s. Imagine objects lined up on a conveyor belt. Newly requested objects enter on the left and the oldest objects get evicted when they reach the end of the line on the right. 

In the LRU, or “least recently used,” algorithm the objects also move along the line towards eviction at the end. However, if an object is requested again while it moves down the conveyor belt, it gets moved back to the head of the line. 

Hundreds of variations of eviction algorithms exist but they have tended to take on greater complexity to gain efficiency. That generally means they are opaque to reason about and require high maintenance, especially when dealing with massive workloads. 

“If an algorithm is very complicated, it tends to have more bugs, and all of those bugs need to be fixed,” Zhang explains. 

A simple idea 

Like LRU and some other algorithms, SIEVE makes a simple tweak on the basic FIFO scheme. 

SIEVE initially labels a requested object as a “zero.” If the object is requested again as it moves down the belt, its status changes to “one.” When an object labeled “one” makes it to the end of the line it is automatically reset to “zero” and evicted. 

A pointer, or “moving hand,” also scans the objects as they travel down the line. The pointer starts at the end of the line and then jumps to the head, moving in a continuous circle. Anytime the pointer hits an object labeled “zero,” the object is evicted. 

“It’s important to evict unpopular objects as quickly as possible, and SIEVE is very fast at this task,” Zhang says. 

In addition to this quick demotion of objects, SIEVE manages to maintain popular objects in the cache with minimal computational effort, known as “lazy promotion” in computer terminology. The researchers believe that SIEVE is the simplest cache-eviction algorithm to effectively achieve both quick demotion and lazy promotion. 

A lower miss ratio 

The purpose of caching is to achieve a low miss ratio — the fraction of requested objects that must be fetched from “the warehouse.” 

To evaluate SIEVE, the researchers conducted experiments on open-source web-cache traces from Meta, Wikimedia, X and four other large datasets. The results showed that SIEVE achieves a lower miss ratio than nine state-of-the-art algorithms on more than 45% of the traces. The next best algorithm has a lower miss ratio on only 15%. 

The ease and simplicity of SIEVE raise the question of why no one came up with the method before. The SIEVE team’s focus on how patterns of web traffic have changed in recent years may have made the difference, Zhang theorizes. 

“For example,” she says, “new items now become ‘hot’ quickly but also disappear quickly. People continuously lose interest in things because new things keep coming up.” 

Web-cache workloads tend to follow what are known as generalized Zipfian distributions, where a small subset of objects account for a large proportion of requests. SIEVE may have hit a Zipfian sweet spot for current workloads. 

“It is clearly a transformative moment for our understanding of web-cache eviction,” Vigfusson says. “It changes a construct that’s been used blindly for so long.” 

Marquee companies that manage massive amounts of web traffic are making inquiries, he notes, adding, “Even a tiny improvement in a web-caching system can save millions of dollars at a major data center.”

Zhang and Yang are on track to receive their PhDs in May. 

“They are doing incredible work,” Vigfusson says. “It’s safe to say that both of them are now among the world experts on web-cache eviction.”

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