Latest news with #CommunicationsMedicine
Time of India
28-05-2025
- Health
- Time of India
Local weather conditions, access to cities can impact prevalence of tuberculosis, study finds
New Delhi: Researchers who mapped tuberculosis cases in African countries found that local weather conditions and access to cities can influence prevalence of the bacterial disease. The study's methodology of identifying disease patterns could help fight tuberculosis in a more targeted manner around the world -- particularly in regions where resources are limited, they said. Tuberculosis (TB) mostly affects the lungs and can be deadly if untreated. The disease -- symptoms of which include persistent cough, chest pain and fever -- spreads through the air when an infected person coughs or sneezes. Focusing on 14 nations, including Nigeria and Mozambique, the team, including researchers from Curtin University and The Kids Research Institute Australia, analysed prevalence of tuberculosis from 50 population-based surveys, involving over 15 lakh people. The researchers estimated how common the disease is at a local level, breaking each country down into grids, each five square kilometres in area, to identify hotspots. "Here we estimate 1.28 million TB cases across 14 countries, with marked spatial variations," the authors wrote in the study published in the journal Communications Medicine. "Factors such as temperature, precipitation, and access to cities are positively associated with higher TB prevalence, while higher altitude is linked to lower TB prevalence," they wrote. For example, rainfall tends to keep one spends indoors, thereby increasing person-to-person contact, crowding, and affecting ventilation levels -- all of which have been linked to spreading of tuberculosis, the researchers explained. Lead researcher Alemneh Liyew, PhD candidate from Curtin University's school of population health, said the study uncovered dramatic differences in disease burden between local regions within countries -- which could prove vital in reducing the impact of tuberculosis. "This study highlights how factors such as higher temperatures, rainfall, altitude and better access to cities can influence the prevalence of tuberculosis. "With this data, health resources can be better targeted towards the communities that need them most," Liyew said. The study is also the first to provide local-level tuberculosis maps across Africa, the researcher said. "Until now, we haven't been able to see where within countries the disease is most concentrated," Liyew said. Author Kefyalew Alene, associate professor Curtin University, said the study's findings could potentially help fight the disease outside of Africa. "While some aspects of the study are Africa-specific, using mapping to identify patterns associated with tuberculosis could help battle the disease in a more targeted manner elsewhere," Alene said. "One-size-fits-all national strategies aren't as effective, particularly in regions where resources are limited," the researcher said.
The Hindu
27-05-2025
- Health
- The Hindu
Local weather conditions, access to cities can impact prevalence of tuberculosis, study finds
Researchers who mapped tuberculosis cases in African countries found that local weather conditions and access to cities can influence prevalence of the bacterial disease. The study's methodology of identifying disease patterns could help fight tuberculosis in a more targeted manner around the world -- particularly in regions where resources are limited, they said. Tuberculosis (TB) mostly affects the lungs and can be deadly if untreated. The disease -- symptoms of which include persistent cough, chest pain and fever -- spreads through the air when an infected person coughs or sneezes. Study highlights Focusing on 14 nations, including Nigeria and Mozambique, the team, including researchers from Curtin University and The Kids Research Institute Australia, analysed prevalence of tuberculosis from 50 population-based surveys, involving over 15 lakh people. The researchers estimated how common the disease is at a local level, breaking each country down into grids, each five square kilometres in area, to identify hotspots. "Here we estimate 1.28 million TB cases across 14 countries, with marked spatial variations," the authors wrote in the study published in the journal Communications Medicine. "Factors such as temperature, precipitation, and access to cities are positively associated with higher TB prevalence, while higher altitude is linked to lower TB prevalence," they wrote. For example, rainfall tends to keep one spends indoors, thereby increasing person-to-person contact, crowding, and affecting ventilation levels -- all of which have been linked to spreading of tuberculosis, the researchers explained. Lead researcher Alemneh Liyew, PhD candidate from Curtin University's school of population health, said the study uncovered dramatic differences in disease burden between local regions within countries -- which could prove vital in reducing the impact of tuberculosis. "This study highlights how factors such as higher temperatures, rainfall, altitude and better access to cities can influence the prevalence of tuberculosis. Possibilities of expansion "With this data, health resources can be better targeted towards the communities that need them most," Liyew said. The study is also the first to provide local-level tuberculosis maps across Africa, the researcher said. "Until now, we haven't been able to see where within countries the disease is most concentrated," Liyew said. Author Kefyalew Alene, associate professor Curtin University, said the study's findings could potentially help fight the disease outside of Africa."While some aspects of the study are Africa-specific, using mapping to identify patterns associated with tuberculosis could help battle the disease in a more targeted manner elsewhere," Alene said. "One-size-fits-all national strategies aren't as effective, particularly in regions where resources are limited," the researcher said.
NDTV
27-05-2025
- Health
- NDTV
Local Weather Conditions Can Impact Prevalence Of Tuberculosis: Study
New Delhi: Researchers who mapped tuberculosis cases in African countries found that local weather conditions and access to cities can influence prevalence of the bacterial disease. The study's methodology of identifying disease patterns could help fight tuberculosis in a more targeted manner around the world -- particularly in regions where resources are limited, they said. Tuberculosis (TB) mostly affects the lungs and can be deadly if untreated. The disease -- symptoms of which include persistent cough, chest pain and fever -- spreads through the air when an infected person coughs or sneezes. Focusing on 14 nations, including Nigeria and Mozambique, the team, including researchers from Curtin University and The Kids Research Institute Australia, analysed prevalence of tuberculosis from 50 population-based surveys, involving over 15 lakh people. The researchers estimated how common the disease is at a local level, breaking each country down into grids, each five square kilometres in area, to identify hotspots. "Here we estimate 1.28 million TB cases across 14 countries, with marked spatial variations," the authors wrote in the study published in the journal Communications Medicine. "Factors such as temperature, precipitation, and access to cities are positively associated with higher TB prevalence, while higher altitude is linked to lower TB prevalence," they wrote. For example, rainfall tends to keep one spends indoors, thereby increasing person-to-person contact, crowding, and affecting ventilation levels -- all of which have been linked to spreading of tuberculosis, the researchers explained. Lead researcher Alemneh Liyew, PhD candidate from Curtin University's school of population health, said the study uncovered dramatic differences in disease burden between local regions within countries -- which could prove vital in reducing the impact of tuberculosis. "This study highlights how factors such as higher temperatures, rainfall, altitude and better access to cities can influence the prevalence of tuberculosis. "With this data, health resources can be better targeted towards the communities that need them most," Liyew said. The study is also the first to provide local-level tuberculosis maps across Africa, the researcher said. "Until now, we haven't been able to see where within countries the disease is most concentrated," Liyew said. Author Kefyalew Alene, associate professor Curtin University, said the study's findings could potentially help fight the disease outside of Africa. "While some aspects of the study are Africa-specific, using mapping to identify patterns associated with tuberculosis could help battle the disease in a more targeted manner elsewhere," Alene said. "One-size-fits-all national strategies aren't as effective, particularly in regions where resources are limited," the researcher said.
Axios
12-03-2025
- Health
- Axios
AI failed to detect critical health conditions: study
AI systems designed to predict the likelihood of a hospitalized patient dying largely aren't detecting worsening health conditions, a new study found. Why it matters: Some machine learning models trained exclusively on existing patient data didn't recognize about 66% of injuries that could lead to patient death in the hospital, according to the research published in Nature's Communications Medicine journal. State of play: Hospitals increasingly use tools that harness machine learning, a subset of AI that focuses on systems that continuously learn and adjust as they're given new data. A separate study recently published in Health Affairs found that about 65% of U.S. hospitals use AI-assisted predictive models, most commonly to figure out inpatient health trajectories. Zoom in: Researchers looked at several machine learning models commonly cited in medical literature for use in predicting patient deterioration and fed them publicly available sets of data about the health and metrics of patients in ICUs or with cancer. The researchers then created test cases for the models to predict potential health issues and risk scores if some patient metrics were altered from the initial data set. The models for in-hospital mortality prediction could only recognize an average of 34% of patient injuries, the study found. What they're saying:"We are asking the models to make big decisions, and so we really need to figure out ... in what kind of situations they can perform," said Danfeng (Daphne) Yao, an author of the study and a computer science professor at Virginia Tech University. It's extremely important for technology being used in patient care decisions to incorporate medical knowledge, Yao said. The study shows that "purely data-driven training alone is not sufficient," she added. What we're watching: Large language models — think ChatGPT-type AI systems — could be more useful in medical settings if they're trained on medical literature. But more research on their trustworthiness is needed before they're deployed in clinical settings, the study says.
