Machine Learning model developed to identify bat species that can spread Nipah

Agencies
June 29, 2019

Researchers have developed a model using Machine Learning (ML) to identify bat species with the potential to host the Nipah virus, with a focus on India. Four new bat species were flagged as surveillance priorities.

"While there is a growing understanding that bats play a role in the transmission of Nipah virus in Southeast Asia, less is known about which species pose the most risk. 

"Our goal was to help pinpoint additional species with a high likelihood of carrying Nipah, to target surveillance and protect public health," said Barbara Han from Cary Institute of Ecosystem Studies in the US. 

India is home to an estimated 113 bat species. Just 31 of these species have been sampled for the Nipah virus, and 11 have been found to have antibodies that signal host potential, according to the study published in the journal PLOS Neglected Tropical Diseases.

The Nipah virus is a highly lethal, emerging henipavirus that can be transmitted to people from the body fluids of infected bats. Eating fruit or drinking date palm sap that has been contaminated by bats has been flagged as a transmission pathway. Domestic pigs are also bridging hosts that can infect people.

Once infected, people can spread the virus directly to other people, sparking an outbreak. There is no vaccine and the virus has a high mortality rate.

For the study, Machine Learning, a form of Artificial Intelligence, was used to flag bat species with the potential to harbour Nipah. 

"By looking at the traits of bat species known to carry Nipah globally, our model was able to make predictions about additional bat species residing in India with the potential to carry the virus and transmit it to people. These bats are currently not on the public health radar and are worthy of additional study," Han said.

For the study, the research team compiled published data on bat species known to carry Nipah and other henipaviruses globally. 

Data included 48 traits of 523 bat species, including information on foraging methods, diet, migration behaviours, geographic ranges and reproduction. 

During the study, their algorithm identified known Nipah-positive bat species with 83 per cent accuracy. 

It also identified six bat species that occur in Asia, Australia and Oceania that have traits that could make them competent hosts and should be prioritised for surveillance. Four of these species occur in India, two of which are found in Kerala.

"We set out to make trait-based predictions of likely henipavirus reservoirs near Kerala. Our focus was narrow, but the model was successful in identifying Nipah hosts, demonstrating that this method could serve as a powerful tool in guiding surveillance for Nipah and other disease systems," said Raina K. Plowright from Montana State University in the US.

"Identifying which species harbour disease is an important first step in surveillance planning. We also need to prioritise research on which virus strains pose the greatest risk to people. Ultimately, the goal is to extinguish risk, not fight fires," Han concluded.

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Agencies
July 14,2020

UN, Jul 14: There will be no return to the "old normal" for the foreseeable future as a result of the ongoing COVID-19 pandemic, and too many countries were still headed in the wrong direction, the chief of the World Health Organization (WHO) warned.

"The virus remains public enemy number one, but the actions of many governments and people do not reflect this," Xinhua news agency quoted WHO Director-General Tedros Adhanom Ghebreyesus at as saying a regular briefing on Monday.

He noted that mixed messages from leaders are undermining trust, which is the most critical ingredient of any response, while the only aim of the virus is to find people to infect.

Things are going to "get worse and worse and worse", he warned, unless governments communicate clearly with their citizens and roll out a comprehensive strategy focused on suppressing transmission and saving lives, while populations follow the basic public health principles of physical distancing, hand washing, wearing masks, coughing etiquette and staying home when sick.

COVID-19 has been gaining its momentum lately.

According to Tedros, Sunday saw a record of 230,000 cases reported to WHO, of which almost 80% were from just 10 countries and about half from just two countries.

"But it does not have to be this way," he said, asking every single leader, government and individual "to do their bit to break the chains of COVID-19 transmission and end the collective suffering".

To control the disease and get on with people's lives, Tedros said, three things are required. The first is to focus on reducing mortality and suppressing transmission; the second is to focus on an empowered, engaged community that takes individual behaviour measures in the interest of each other.

And the third is a strong government leadership and coordination of comprehensive strategies that are communicated clearly and consistently.

"We weren't prepared collectively, but we must use all the tools we have to bring this pandemic under control. And we need to do it right now," he added.

At the WHO briefing on Monday, health experts also said there was evidence to suggest that children under the age of 10 were only very mildly affected by Covid-19, while those over 10 seemed to suffer similar mild symptoms to young adults.

To what extent children can transmit the virus, while it appears to be low, remains unknown.

On Tuesday, the number of global coronavirus cases cross the 13 million mark, according to the Johns Hopkins University.

The total number of cases currently stood at 13,070,097, while the fatalities rose to 572,411, the University's Center for Systems Science and Engineering (CSSE) revealed in its latest update.

The US accounted for the world's highest number of infections and fatalities at 3,363,056 and 135,605, respectively, according to the CSSE.

Brazil came in the second place with 1,884,967 infections and 72,833 deaths.

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News Network
May 11,2020

Panaji, May 11: Amid the COVID-19 outbreak, most of the people are more concerned about the health of their near and dear ones than their own well-being, says a study conducted by a leading business school in Goa.

People are now more conscious about any bodily changes, and even mild cold, cough and sneezing, it says.

The study, on public's reaction towards COVID-19 outbreak by gauging their psychological response in terms of anxiety and their coping behaviour, was conducted by the Goa Institute of Management's Dr Divya Singhal and Prof Padhmanabhan Vijayaraghavan.

It took into account inputs from 231 respondents residing in various parts of the country.

"Nearly 82.25 per cent of the respondents were more worried about the health of their loved ones than their own well-being," Singhal said.

"Majority of the respondents have become conscious of any bodily changes, sensations, a mild cold, cough, sneezing and experience concern, and attribute those changes to the symptoms of COVID-19," she said.

Besides, more than 50 per cent of the respondents said their social media usage has gone up as well as their time spent on watching movies and shows through online medium, the official said.

The respondents agreed that their technology usage to connect with friends and relatives has gone up, she said.

The study also indicated that a large group of respondents found it "depressing" to read forwarded messages on the deadly disease.

"An overwhelming majority of the respondentsagreed that they discourage unverified forwarded messages about COVID-19 on social media," says the study.

It also found that 41 per centof the respondents were not doing any physical activity, like yoga, during the lockown period, while another 19 per cent were not sure about engaging themselves in physical activities.

Besides, 57 per cent of the respondents were not engaged in any mind-calming practices like meditation, and 18 per cent were not sure about taking up meditative practices, the study said.

The respondents included 145 men and 86 women, aged 18 and above, with nearly 60 per cent of them residing in non- metro cities and rest from metros.

About 47.62 per cent of the respondents were employed in private or government sectors, and the remaining included students, retired persons and homemakers.

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News Network
February 26,2020

New York, Feb 26:  A new wearable sensor that works in conjunction with artificial intelligence (AI) technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs, says a study.

The researchers said the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

"This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong," says the study's lead author Josef Stehlik from University of Utah in the US.

"Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalisation and stave off worsening heart failure," Stehlik added.

According to the researchers, even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalisations.

"This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status," Stehlik said.

For the findings, published in the journal Circulation: Heart Failure, the researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four veterans administration (VA) hospitals in Utah, Texas, California, and Florida.

After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months.

The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities.

Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient's heart failure was getting worse.

Overall, the system accurately predicted the impending need for hospitalization more than 80 per cent of the time.

On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days), the study said.

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