Nana Nana

By Nate Bertone
Illustrated by James Claridades

This story about the effects of dementia and Alzheimer’s disease touches on topics that can be scary for kids, including a beloved grandparent’s sudden outbursts of frustration and anger, their personality changes, and their inability to recognize them or remember their name. The book is eye-catching and engaging for younger kids and written at their level without speaking down to them. The colorful and lighthearted illustrations pair well with Bertone’s writing to make a potentially confusing topic more accessible for kids aged three to eight and their families.

It Belongs to the World

By Lisa Katzenberg
Illustrated by Janina Gaudin (aka Miss Diabetes)

The story of Frederick Banting, the scientist who first identified and produced insulin, revolves around perseverance, curiosity, and selflessness. Banting’s scientific inquisitiveness and dedication help him push through numerous barriers and eventually identify insulin, the hormone messenger that controls blood sugar metabolism. He developed a treatment for diabetes and was told he could make a million dollars selling the recipe. He declined, saying, “Insulin does not belong to me. It belongs to the world.” The book offers an inspirational story for four- to 10-year-olds that demystifies diabetes. The book includes appendices on how insulin works that could help adults explain more to curious kids.

My Body Beeps

By Katherine Lockwood
Illustrated by Olga Sall

Katie has Type 1 diabetes and depends on a glucose monitor and insulin pump to stay healthy. As Katie plays hide and seek in the park, her glucose monitor starts beeping. Katie, irritated that the beeping could give away her hiding spot, ignores the monitor and feels ashamed for being different. Olivia, a new friend, joins Katie in her hiding spot and asks what the beeping is for. Olivia has asthma and uses her inhaler, which makes Katie feel better about having a glucose monitor. The book is written for three- to seven-year-olds and helps those who have Type 1 diabetes understand why it’s important to be responsible for their bodies’ needs.

Masked Hero

By Dr. Shan Woo Liu and Kaili Liu Gormley
Illustrated by Lisa Wee

In 1910, a doctor named Wu Lien-teh was asked to travel to Northeast China to stop the spread of a mysterious disease. He suspected it was pneumonic—spread by breathing in bacteria—and created a sturdy, thick mask that covered the face except the eyes. Through masking, isolation, and travel restrictions he put in place, the outbreak of plague soon burned out—and made masks a tool for fighting certain diseases. The book, written by Wu’s great-granddaughter and great-great granddaughter, shows his dedication, ingenuity, and stubborn refusal to bow to racism and opposition. The illustrations are eye-catching and transport the reader along Wu’s journeys. The book, written for seven- to 10-year-olds, ends with a few discussion questions about problem-solving and public health.

(Be Smart About) Screen Time!

by Rachel Brian

Being a kid can be hard, and Rachel Brian’s books, like Consent (for Kids!) and The Worry (Less) Book, provide guides for dealing with some big issues. (Be Smart About) Screen Time! features short chapters written in her usual humorous style accompanied by simple line drawings. The premise is to teach kids who’ve received a smartphone, tablet, or computer about risks and responsibilities, from caring for the device to judging which content to avoid. Boundaries around personal interactions are discussed in depth, as are trolls, bullies, and bots. So is nudity and what to do if it’s encountered (talk to a parent or another trusted adult). An excellent book for seven- to 12-year-olds, especially as a conversation starter about a family’s norms and expectations around devices, being online, and the potential mental health effects of social media.

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The federal government has bet big on the concept with a new nationwide network called Insight Net, which links academic disease modelers with public health practitioners. The network comprises 13 research consortia with participants in 24 states and is funded with up to $262 million from the Centers for Disease Control and Prevention (CDC). Insight Net members are piloting analytical techniques that combine novel data sources to guide surveillance and inform decision-making during outbreaks. The end goal is to create something akin to a National Weather Service for disease.

Such capacity would be a game-changer for state and local health authorities and for hospitals. At the height of the COVID-19 pandemic, “we were not good at forecasting the demand,” says Douglas Sawyer, chief academic officer of MaineHealth, that state’s biggest hospital system. “We didn’t steer the ship, so to speak, with high fidelity as we wish we could have. We couldn’t prepare and shift resources in thoughtful ways.”

Many hospitals struggled with the crush of patients who needed intensive, isolated care. Because hospitals could not accurately predict the size of impending infection waves, many delayed or canceled routine health care such as physicals or cancer screenings. Meanwhile, Covid care sites built or converted by federal and state authorities ended up being largely unneeded.

These forecasting issues had serious financial consequences for hospitals—and serious health consequences for the public. Insight Net’s progress toward closing that information gap has been steady and marked by small but important victories—as well as plenty of reminders that even the best forecasts are only as good as the data that feed them.

Forecasting more than the next crisis

By linking people working in public health directly with disease modelers, the CDC aims to fix the ad hoc approach it used for pandemic forecasting, which was panned from almost the start. In the summer of 2020, a critique in Foreign Affairs labeled the CDC’s approach “an arbitrary assortment of academics” reacting on the fly and asserted no one today would handle hurricane response in that fashion. In 2021, the CDC tapped Caitlin Rivers, one of the article’s coauthors and an epidemiologist at Johns Hopkins Bloomberg School of Public Health, as the first associate director of its new Center for Forecasting and Outbreak Analytics (CFA). In 2023 the CFA established Insight Net, and Rivers, who had returned to Johns Hopkins, became director of its node in the network (Dylan George, her Foreign Affairs coauthor, is the CFA’s current director). Their core message, then and now: Disease forecasting shouldn’t be improvised.

Policymakers and the public put their trust in major storm alerts, according to George, because the weather service is “applying the best models in an operational context on a day in and day out basis, cranking out results,” George says. “And then you have local meteorologists interpret those results for people to actually make decisions.” That process establishes a track record of monitoring and communicating forecasts, including their uncertainty, even when the weather is calm, sunny, and mild. “We’ve tried to pattern after that,” George adds.

That has meant investing in a dedicated program for disease forecasting, with formal working relationships between modelers and federal, state, and local health officials. It also means the CFA has been keen to demonstrate how modeling can help public health practice and communication. For instance, it has tapped data from the National Wastewater Surveillance System, launched by the CDC in 2020, to improve localized forecasts of Covid hospital admissions. It also helped the Chicago Department of Public Health confront a March 2024 measles outbreak at a temporary migrant shelter housing more than 1,400 people. As public health workers began vaccinating and screening shelter residents to identify and isolate the sick, department leaders reached out to the CFA, which rapidly refined a model of measles to mimic the outbreak’s timeline of infection, symptom onset, and recovery, which Chicago health officials could then use to predict its future course.

The model didn’t influence the department’s interventions, which were already underway. But it did reassure officials they’d correctly identified their patient zero: Outbreak simulations that assumed earlier, undetected infections generated far different case data from what was observed. The forecasts also helped set expectations for the outbreak’s severity by providing a range of potential case numbers and dates when infections would peak and subside. After a couple weeks of continuous updating with data on new measles cases, the model predicted there would be between 57 and 65 cases and the final rash would appear on April 16. In the end, the outbreak lasted about two months and infected 57 people.

“It really helped our own planning, and our thinking about staffing,” says Stephanie Gretsch, an epidemiologist at the Chicago Department of Public Health. “It was also incredibly helpful for communicating with our city agency partners responsible for housing and schooling; and the hospitals we asked to help isolate infected residents, to give them a sense of how long we thought this was going to last.”

After the outbreak, Chicago public health officials used the modeling to quantify the value of its interventions. Outbreak simulations where responses did not include mass vaccination or active case-finding efforts suggested it would have lasted seven weeks longer and more than quadrupled the number of infections. This finding suggests that modeling hypothetical scenarios might offer a tool for easing heightened skepticism of public health interventions and investments, say several Insight Net partners.

Syphilis is one target of the Insight Net consortium at the University of Utah. The disease, resurgent in the U.S., can infect a fetus during pregnancy and cause serious medical complications, including miscarriage, stillbirth, and infant death. The goal is to “address the issues and show how bad this problem could get if trends continue,” says principal investigator Matthew Samore, a professor of medicine and the division chief of epidemiology at the University of Utah. “We also want to get a deeper understanding of how STIs like this are spreading through different populations…and to calculate how much benefit do we get by investing in more intensive screening and contact tracing.” By helping establish the extent of the risk, the models could bolster requests to fund more screening and treatment of groups with high infection rates, such as people in prison.

The modeling could also improve disease forecasting dashboards used by the public to assess health threats. The Massachusetts Department of Public Health (MDPH) has dashboards that track severe respiratory illnesses statewide, but delays in data reporting from local hospitals limit their usefulness. In 2024, MDPH worked with the Insight Net researchers at the University of Massachusetts Amherst and the University of Texas at Austin to build models filling in those gaps, allowing it to add recent emergency room visits and hospital admissions due to Covid, RSV, and influenza broken down by demographics. Such small-scale adoptions are needed both to validate disease forecasting and to build trust in the models, says Meagan Burns, a senior informatics epidemiologist at MDPH. “These tools are very cool, but they’re also very new,” she says.

People in Massachusetts also are getting a look at disease forecasts as part of their weather news. In February, meteorologists at Boston’s CBS affiliate, WBZ-TV, began adding localized disease data visualizations to their weather reports. These are put together by the Insight Net team based at Johns Hopkins and arranged through a collaboration with the American Meteorological Society. The first one featured a colorful chart showing that emergency room visits due to COVID-19 were declining steadily from their post-Christmas peak. The original plan was to do weekly check-ins on infectious respiratory illnesses, but as the weather warmed, infection numbers plummeted and stayed low.

“There were several weeks where there wasn’t a whole lot to talk about with Covid or the flu,” says meteorologist Terry Eliasen, executive producer of WBZ’s weather team. While viewers might find sunny weather forecasts useful, there didn’t seem to be much news value in “sunny” public health numbers. So WBZ skipped a few weeks. Then Eliasen asked the Johns Hopkins team what else it could do. Over the summer, researchers responded with data visualizations related to outbreaks of norovirus and eastern equine encephalitis, as well as the risk of heat-related illnesses.

This quick shift in focus drew praise as a sign that the university-based modelers at Insight Net are serious about partnering with public health practitioners and communicators. The CFA worked with the Council of State and Territorial Epidemiologists (CTSE) on the legal and logistical issues of data-sharing, and to see what forecasting tools might be useful to its members. The two organizations convened a series of meetings with state and local health officials to ask what uses they might have for forecasting tools and whether there were specialized techniques they’d like. That was especially useful, says Janet Hamilton, the CSTE’s executive director. “We need to have enough time to talk to the modelers to say, ‘That’s a great model but it doesn’t help me. It doesn’t answer my questions.’”

Fixing public health data: everything, everywhere, all at once

Disease threats do not yet have the color-coded, real-time tracking maps the National Weather Service uses for potential hurricanes. Of course, there are no satellite images of developing disease threats, which not only are propelled by unique (and often mutating) biology, but also have to account for something that’s even harder to predict—human behavior. Several Insight Net forecasters are trying to meet this massive data challenge by mixing traditional data sources such as infection rates with the digital breadcrumbs of human activity like searches for symptoms, social media posts, and trends in medication purchases.

People spread diseases when they travel and gather, notes Alessandro “Alex” Vespignani, a physicist and computational scientist at Northeastern University whose lab models large-scale complex systems. He and his team are part of an Insight Net research consortium with Maine’s major hospital systems, MaineHealth and Northern Light Health, which are working on a pilot project to weave human mobility data into disease models. They draw on aggregated and anonymized mobile device location data, databases of global flight schedules, and traces of pathogens found in wastewater sampled from municipal sources and from international flights for analysis by the Boston biotech company Ginkgo Bioworks.

“Our models are like a layer cake,” Vespignani says, with each layer creating a virtual “business as usual world” the modelers use for outbreak simulations. Layers are only added if they significantly improve the model’s predictions or extend the timeline for an accurate forecast. For instance, the lab found that it could accurately forecast greater Boston hospital admission rates three weeks ahead of time by adding mobility and proximity data derived from about 82,000 mobile phones, compared to just two weeks using conventional public health data such as statewide Covid test results. That extra week for planning is “a big deal for hospitals” for scheduling staff and procedures, says Samuel Scarpino, director of Northeastern University’s Institute for Experiential AI and a member of the Insight Net team. Since hospitals aim for 90 percent capacity, even a slight uptick in the need for beds can complicate care.

This fall, the lab will tap retrospective data from Maine’s Covid hospitalization numbers to try to replicate that forecasting capability. It’s also planning to use the mobility-enhanced models to forecast hospitalizations for flu, RSV, and Covid at individual Maine hospitals for the winter of 2024-25. If these efforts are successful, Scarpino hopes to scale the models for use nationwide.

The Insight Net initiative also faces the labyrinthine way the U.S. gathers and shares core public health data such as test results and hospital records. Reducing those obstacles is a key target of the CDC’s Data Modernization Initiative, launched in 2019 to promote things like electronic case reporting, interoperability among different data collection systems, and standardized data use agreements between state, tribal, local and territorial, and federal health authorities. But the data pipeline’s bottlenecks aren’t simply technical and legal, according to infectious disease experts such as Jennifer Nuzzo, an epidemiologist who directs Brown University’s Pandemic Center. They also involve whether we’re asking the right questions about disease threats to get the data we need. “It’s great for us to invest in analytic approaches that can help us tell what could happen in the future,” says Nuzzo. “But what I want to see is a better utilization, analysis, and visualization of the data that we have to tell us what’s happening today.”

For instance, the fragmented efforts to track the H5N1 bird flu virus in the U.S. have drawn a chorus of concern from public health leaders and researchers. Earlier this year, the virus leapt from wild birds to more than 100 million poultry in 49 states as well as other domesticated species, including dairy cows and, more recently, pigs. A small but growing number of people have also been infected (mostly farm workers, but not all). Tracking the virus requires coordination among multiple federal agencies, including the Department of Agriculture, the Food and Drug Administration, and the CDC, as well as states that vary widely in the ways they test animals, people, and bulk milk tanks. The only federally mandated H5N1 screening is for lactating dairy cows being moved across state lines.

Thus far, most humans with bird flu have had minor symptoms, and there’s no evidence of the virus spreading from person to person, which could trigger a pandemic. But the risk increases with flu season, because different viruses infecting the same host can swap genes (known as genetic reassortment) and evolve into something new and more dangerous. If pandemics were hurricanes, having the avian flu virus circulating in cows along with regular flu infections in humans would be akin to a low pressure system in the Caribbean—it could dissipate, but it could also develop into huge trouble for the mainland United States. Nuzzo says we could better predict the outcome if we focused more on targeted surveillance about emerging health threats.

“An awareness of what’s happening this week, and last week, is the starting point for trying to figure out what’s going to happen in the next few weeks and beyond,” says Roni Rosenfeld, a professor of machine learning, language technologies, computer science, and computational biology in the School of Computer Science at Carnegie Mellon University and a cofounder of the Delphi Research Group, a global network of disease modelers working with Insight Net. “So, already before the pandemic, we shifted much of our effort to what I call situational awareness—being aware of what’s happening right now at as fine a geographic, pathogenic, syndromic, and demographic granularity as possible.”

Dylan George, director of the CFA, agrees that disease forecasts will require better raw data and more proactive surveillance. He argues now is the time to strengthen partnerships between researchers and public health practitioners, to build trust and a shared language, and to smooth frictions that can cripple effective collaboration during a crisis. The ultimate test of success for Insight Net, he says, will be seeing them in action:

“If a bunch of state and local health department folks are saying, ‘These forecasting tools are helping me do my job better,’ then I know that we deserve to live another day.”

Illustration: Mary Delaware / Source images: Adobe Stock

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That is the shorthand for an ambitious goal: By 2025, ninety-five percent of people in the world who are living with HIV should know their status; ninety-five percent of those people should be enrolled in anti-retroviral treatment; and ninety-five percent of those enrolled should achieve viral suppression, which means the virus is undetectable.

The targets were adopted by UN member states in 2021 to create momentum and milestones for ending the global AIDS crisis by 2030—which is, remarkably, a goal within reach. Because it is virtually impossible for people with undetectable levels of HIV to transmit the virus, reaching those targets would, effectively, end the transmission of the disease.

UNAIDS actually introduced its first targets for ending to the epidemic a decade ago. Those goals were lower—and, global health experts thought, ambitious. Yet nine countries have already reached the more demanding 95-95-95 target—Botswana, Denmark, Eswatini, Kenya, Malawi, Rwanda, Saudi Arabia, Zambia, and Zimbabwe—and ten more are on track to meet next year’s deadline.

Tendayi Westerhof, a health activist in Zimbabwe, says good policy management put Zimbabwe ahead. “Everyone who is working on HIV/AIDS has to fit into the national strategy,” she says, “which is derived from the targets.”

But she warns there are many challenges to achieving the milestone—challenges that extend well beyond Zimbabwe. 

From the outset, global health architects were concerned about whether the health systems most impacted by HIV had the capacity to provide testing and treatment at the scale required. These worries became more acute as officials recognized that, due to stigma, they could not rely on people to just show up at health facilities for HIV testing and treatment.

The stigma is particularly detrimental for people in communities that are already marginalized—and sometimes criminalized. Those communities include sex workers, men who have sex with men (MSM), and people who inject drugs. These are often the same people most at risk for contracting HIV. Discrimination against these communities is sometimes buttressed by laws and policies, including some that criminalize homosexuality or sex work. Yet ensuring their access to services is crucial to reaching 95-95-95 in most countries, says Mary Mahy, who heads the collection and analysis of data at UNAIDS.

Around the world, officials have also learned to innovate and closely track the outcomes of the services they deliver—including testing and adherence, among the metrics—to ensure they are taking best advantage of finite funding.

Though each country’s path to 95-95-95 will be unique, the experiences of successful countries offer lessons for those that have fallen behind. Here are three solutions that have been particularly instrumental in getting and keeping people on treatment:

Community health workers

Botswana, which realized the 95-95-95 targets in 2022, began with an effort to combat the stigma around HIV, according to Peter Chibatamoto, the projects coordinator of Humana People to People Botswana, a grassroots program that aims to make HIV services more accessible.

Speaking on the sidelines of the 2024 International AIDS Conference in Munich, Germany, Chibatamoto says it became clear early in HPP’s efforts that fear and misunderstanding about the disease left people reluctant to use HIV services no matter how easy his organization made it. People did not trust health workers who tried to convince them they should know their status and, if they were infected, initiate treatment.

“There were so many people who would not want to go there,” he says—until the government enlisted local residents as community health workers (CHWs) who delivered basic services and connected people to the health system. Because CHWs know the local culture and have relationships with the people they serve, they are inherently trusted. This helps demystify the disease and encourages people to get tested and, if necessary, start treatment, Chibatamoto says.

In Cambodia, CHWs are called “lay counselors,” and they have been crucial to the country’s progress, says Vichea Ouk, the director of the National Center for HIV/AIDS, Dermatology and STDs in Phnom Penh. Cambodia has surpassed the targets for treatment and for viral suppression, and Ouk is hopeful the country will reach the testing target by the deadline. Teams that include people living with HIV work at health clinics, where they help dispel misconceptions about the virus and smooth people’s interactions with the health system.

In the past, a newly diagnosed patient might be overwhelmed by the glut of information, including details about when to pick up their medicines. The lay counselors follow up to make sure people show up for those appointments and absorb the importance of adhering to their daily treatment regimen.

Care outside of the clinic

Lloyd Mulenga is the head of infectious diseases at the national health ministry in Zambia, where officials struggled for years to reach the first 95. It was particularly hard to convince men to come to health clinics and get tested. After talking with community representatives, officials understood that the problem was not only about stigma but also a lack of time and prioritization, particularly for men with low incomes who worked long hours or held down multiple jobs.

Zambia is not alone. Across countries and continents, officials speak of the challenges people face paying for travel to far-flung health centers or securing childcare during their visits. Many see the same problem Zambia faced with getting men to clinics to test.

Starting in Lusaka, the Zambian capital, and the central Copperbelt region and working in collaboration with U.S. aid organizations, Zambian health officials launched a program to share information about HIV and facilitate testing at workplaces. Some versions of the initiative offered HIV self-test kits. Officials also arranged for clinics to stay open late and on the weekends so the men who used the kits had a place to drop them off and, if someone tested positive, to enroll in treatment.

Although the results of the initiative are still being evaluated, Mulenga credits the service with increasing testing among men and helping Zambia reach all three targets in 2023. Now, having spotted a gap in women over 50 getting tested, Zambian officials are considering borrowing from this model to set up discreet HIV testing services for women in markets and other places where they gather.

The overriding goal emerging globally, says Brian Chirombo, the World Health Organization representative in Rwanda, is to develop “client-centered approaches, which simplify and adapt HIV services to better meet the needs of people living with HIV.”

That includes members of marginalized communities who might be reluctant to visit a clinic. Cambodia has begun to offer HIV self-testing kits to MSM and sex workers, among others who worry about the stigma. People can even bring testing kits home for partners who might be too busy or nervous to go in person.

Decisions based on data

In Malawi, health ministry officials sit down quarterly to look at the performance of more than 850 healthfacilities. They review statistics such as how many new patients have enrolled, whether patients are adhering to treatment and maintaining viral suppression, and the stocks of antiretroviral drugs.

If they spot any problems, says Rose Nyirenda, the director of the National HIV, Viral Hepatitis and STI Program in Malawi’s Ministry of Health, they can rapidly respond. That might mean deploying officials to dispatch additional medicines or provide training to improve any performance issues that are preventing people from accessing or sustaining services.

Malawi has achieved this capability through more than 18 years of digitalizing HIV/AIDS data, which Nyirenda estimates has cost upwards of $180 million, mostly paid for by donors. But the expense has been worthwhile, she says, “because it has allowed the program to be able to look at the trends in many of the variables we collect” and act on them.

Now, the country is integrating artificial intelligence into some of its data collection services. The idea is that AI will help monitor data input for potential discrepancies and improve the quality of the information collected at the health clinics. It should also help reduce the time and money spent analyzing and summarizing the data, Nyirenda says.

More work ahead

Chirombo says reaching 95-95-95 is not necessarily about a single intervention but the willingness of a country to innovate based on data and international guidance. It’s an ongoing process.

Even as the officials and activists celebrate their success, they do not want this achievement to mask shortcomings that remain. In Rwanda and Zambia, for instance, children still lag behind the national percentages when it comes to receiving treatment.
Chirombo points to the ongoing need “to develop tailored approaches to address some of these groups that have been left behind.” It is another code he is convinced these countries can crack.

Top image: Obed Zilwa / AP Photo

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Elsewhere, the bacterial consequences of these storms are preventing access to safe drinking water. More than 150,000 households in North Carolina were still living under boil-water notices nearly a month after Helene, and the Environmental Protection Agency detected E. coli in 30 percent of 900 private wells it tested in the storm-ravaged state.

Each major hurricane that has made landfall in recent years has had infectious fallout. Florida’s previous record for flesh-eating bacterial infections came after Hurricane Ian. Hurricane Maria resulted in a spike of leptospirosis in San Juan, Puerto Rico, especially for people who lived near a large, heavily polluted canal. Hurricane Harvey sent at least 31 million gallons of raw sewage streaming into Houston’s neighborhoods and was associated with a rise in deadly invasive mold infections and alarming levels of antibiotic-resistant bacteria found in flooded homes.

It is painfully evident that our antiquated stormwater and sewage systems cannot manage the downpours, tidal surges, and rising sea levels that climate change is delivering, and this situation strongly favors bacteria. This trend disproportionately affects poor and vulnerable communities, amplifying equity and justice concerns, and the repercussions will be dire if we do not better prepare.

Properly treating wastewater and stormwater is a pillar of public health, one imperiled by our collective lack of maintenance. We must modernize sewage infrastructure in hurricane-prone regions to mitigate the risk of infections. But doing so will require years of planning and negotiating before a shovel breaks ground. Complicating matters are the millions of private septic tanks in backyards across the country that are both teeming with human waste and prone to flooding. As one expert told The Washington Post, these septic tanks are “ticking time bombs.”

We need immediate strategies to mitigate the risk of infections before, during, and after hurricanes.

One practical step is clearly communicating the risk to those in a storm’s path. Florida health officials should be commended for their efforts ahead of Helene and Milton; they emphasized the danger of exposing open cuts or sores to floodwaters. Similarly, residents mucking out their flooded homes should follow the state’s emergency management agency recommendations for keeping proper protective equipment such as gloves, boots, and respirator masks in their kits. In the pathogenic aftermath of Hurricane Maria, lack of basic safety equipment increased infection risk during clean-up efforts.

It will help to expand and enhance wastewater monitoring programs deployed to track levels of COVID-19. A team led by Anthony Maresso at Baylor College of Medicine is using novel sequencing technologies to track all known human and animal viruses in a single test, and these technologies can be adapted to include bacterial threats. The current technology is being used across Texas and has the potential to be inexpensive enough to use in low- and middle-income countries. When antimicrobial resistance detection is added, such a system can inform public health authorities in real time about a wide range of hazards, including the emergence of drug-resistant pathogens. Knowing what specific threats lurk in the sewers before those systems fail and then flood homes could enable public health agencies and local health systems to better tailor their response plans. It could also guide physicians in each locale to use the most effective antibiotics to treat infections that arise in their area.

It is imperative that clinicians in flooded areas have access to effective antibiotics, not just a few old generics that may not be appropriate for the situation at hand. If a hurricane triggers a localized outbreak of a drug-resistant pathogen, the results could overwhelm entire health systems. Project BioShield, a federal initiative aimed at supporting the development and procurement of medical technologies that could be needed in the wake of certain disasters, should be expanded to include the threat of drug-resistant infections, and we should ensure the Strategic National Stockpile can directly procure and manage advanced antibiotics and antifungals so that they can be rapidly made available to communities in need.

This year’s hurricane season isn’t over yet, and it’s likely that Florida will record more cases of flesh-eating bacteria. The patients suffering from those infections—and families who lost loved ones to them—will not soon forget the ways in which a hurricane affected their health. Neither should we.

Image: A utility hole cover bubbles open in a road flooded by the remnants of Hurricane Ida in Rutherford, New Jersey in September 2021. (Ted Shaffrey / AP Photo)

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