Tag Archives: bioinformatics

How can we avoid another virus outbreak?

By: Maja Malmberg, Researcher at the Section of Virology at the Department of Biomedical Sciences and Veterinary Public Health at SLU and Ekaterina Bessonova, Communications Officer at SIANI. This blog was originally posted at SIANI website

Photo: Peter Schaefer (EyeEm) / Getty Images.

Few of us have ever imagined living through a pandemic. With all the global progress and achievements in medicine, a contagion seemed like something from the dark ages. And here we are, battling a noxious virus that set foot in every country, bringing disease, disruption and dismay.

Covid-19 outbreak is still unfolding, and we are yet to fully experience its effect on our societies and lives. However, it’s worth looking into how this coronavirus came about and reflecting on what can be done to diminish the possibility of another pandemic.

How did Covid-19 emerge?

SARS-CoV-2 or Severe Acute Respiratory Syndrome Coronavirus 2, the virus that causes Covid-19, is most closely related to coronaviruses in bats, meaning it’s a zoonosis – a disease that pass from an animal or insect to a human.

Other examples of zoonotic diseases include such scary names as HIV, Zika and Ebola. But Covid-19 belongs to the same family of coronaviruses as SARS and MERS.

The outbreak of SARS in 2002 resulted in 8,098 cases and 774 deaths in 26 countries. Emerging in Saudi Arabia in 2012, MERS brought about 2,494 cases and 858 deaths in 27 countries. Both of them are thought to be bat viruses that got to humans through an intermediate host (civet cat and camel).

Comparing to its “family members”, SARS-CoV-2 has certainly been more effective in infecting humans – the number of reported cases has already passed over 400 000 and rising. The virus was only discovered in January 2020 and much more research is needed to fully understand it. Nevertheless, there are things we already know.

Thanks to its structure, which is essentially a spiky ball, the virus easily attaches to the surface of certain human cells, initiating infection. Unlike most of the respiratory viruses that infect either upper or lower airways, SARS-Cov-2 seems to infect both. Generally, upper-respiratory infections are easily transmitted and usually mild; lower-respiratory infections don’t spread as easily but are more severe. Additionally, the new coronavirus can be stable on surfaces for as long as 24 hours, which along with the fact that humans do not have immunity against it, facilitated such rapid spread around the world.

Exactly when and how the virus has first infected humans remains to be determined. It could have come from bats to humans directly or passed through another animal. Coronaviruses are famous for their ability to exchange part of its genome, the so-called recombination, something that makes them prone to change hosts.

Covid-19 is believed to originate from a wildlife market in Wuhan, China where alive wild animals were sold and butchered on the spot, usually using the same slaughtering tools for different species, which creates favorable conditions for the virus to jump from animals to humans. Such markets are a perfect melting pot for new viruses to emerge and spread. However, there are reports of early cases of Covid-19 in people with no links to the market, suggesting the initial point of infection may have been in a different place.

Photo: Ulet Ifansasti (Stringer) / Getty Images

Biodiversity, biosafety, bioinformatics: A virus risk management strategy

Prompt by the ongoing epidemic, China announced a permanent ban on wildlife trade and consumption. The global community greeted this measure as a major step, though the ban has already been criticized because it allows the trade of animals for fur, medicinal purposes and research. Additionally, China announced a similar ban in 2002 in connection to the SARS outbreak, but enforcement was relaxed after the epidemic was over and the trade rebounded.

Banning trade of wild animals is a straightforward measure to limit exposure to new pathogens. However, it is not the only reason behind the Covid-19 outbreak. Diminishing the emergence of new zoonotic diseases requires holistic strategies that reduce risks across several dimensions and make our societies more resilient to virus outbreaks.

First, all development strategies and activities must prioritize biodiversity and find a way to create jobs, generate incomes and increase wellbeing, without destroying nature.

The emergence of new pathogens tends to happen in places where a dense population has been changing the landscape – agricultural expansion, deforestation, construction, mining – all contribute to the loss of natural habitat. So, the area occupied by human activity is becoming larger, while wild animals are squeezed into shrinking spaces. That is why animals that wouldn’t normally come in contact with humans do so to a higher extent, increasing the risk for exposure and spread of viruses wild animals carry and that we have not experienced before.

For instance, recent research from the Swedish University of Agricultural Sciences (SLU) indicates that large forest fires can increase the spread of rodent-borne diseases in Sweden. However, the risks of emerging zoonotic diseases are especially high in the forested tropical regions experiencing rapid land-use changes and with high wildlife biodiversity.

Second, livestock industry and farmers have to implement adequate biosafety measures

Covid-19 sparked discussion about whether animal-based diets play a role in the emergence and spread of unknown and dangerous viruses. While there is plenty of research pointing that moderate consumption of meat has strong health and climate benefits, to what extent livestock production represents a risk of emergence of zoonosis depends on production management factors and country context.

For instance, small scale organic livestock farming is based on the principle that animals roam close to natural forests. This method is praised for animal wellbeing and lower environmental impact, but it makes contact between domestic animals and wildlife more likely. At the same time, industrial farms would usually keep animals isolated, creating conditions that prevent the spread of diseases from wild animals, however, because the animals are kept so densely to each other, diseases spread fast within the herd. Furthermore, plant-based diets that utilize a lot of commodities like almonds, soy, avocadoes and cocoa aren’t necessarily deforestation-free.

Another key point to consider is that vegan diets may not be the best option for people in low-income countries with high malnutrition. Milk, eggs and meat are highly nutritious, so many people keep animals at home for food and for insurance in times of need. There are also traditional pastoralist communities who live in drylands. For them animal husbandry is not only a source of food security, but also the core of culture.

For these reasons, increasing biosafety standards may offer a more appropriate way to reduce the risk of zoonotic diseases than excluding animal-based foods. Some common measures include keeping animals outside of the house, introducing designated areas for slaughtering and ensuring these facilities and people who work there practice well-executed hygiene and sanitation of all processes and equipment.

Third, funders need to ramp up investment in virology and bioinformatics, while the international community needs to improve cooperation, increase local capacities and raise awareness about these fields of knowledge.

The risk that new viruses can emerge and spread will always be there. But it is possible to minimize the losses by means of fast accurate detection and early response. Mapping the existing viruses in all animals will help us know what is out there and start developing technologies and strategies that can help us prepare and cope with possible outbreaks, pivoting from reactive to a proactive response. Advancing bioinformatics and virology will not only help us develop vaccines, but also anticipate pandemics through monitoring of threats while they are still evolving in animal populations.

Raising general awareness about what viruses are, how they spread and how one can protect from them is also key. Knowledge can conquer panic and prevent the creation and spread of conspiracy theories and fake news.

How can Artificial Intelligence improve African agriculture?

By: Erik Bongcam-Rudloff, Professor of Bioinformatics at the Department of Animal Breeding and Genetics, SLU

As climates change and populations increase, Artificial Intelligence (AI) will be a key player in Africa in the creation of technological innovations that will improve and protect crop yield and livestock. 

Participants at “Network of Excellence in Artificial Intelligence for Development in sub-Saharan Africa” in Nairobi, Kenya, April 2019. Photo: Erik Bongcam-Rudloff

The work creating technologies that allows computers and machines to function in an intelligent manner is known as Artificial Intelligence or AI. The advantages of using AI based devices or systems are their low error rate and huge analysis capacity. If properly coded the AI systems have incredible precision, accuracy, and speed. They can also work independently in many, for humans, hard conditions and environments. One of the most interesting areas where AI is breaking into is agriculture. 

One area using AI and attracting a lot of attention is the area more known as “Precision Farming”. Precision Farming generates accurate and controlled technologies for water and nutrient management. It also gives optimal harvesting, planting times and produce solutions in many other aspects of modern agriculture.

In April 2019 a workshop was held at Strathmore University, Nairobi in with the aim to set up a “Network of Excellence in Artificial Intelligence for Development in sub-Saharan Africa”. There where 60 international participants by invitation. The meeting was supported by Swedish SIDA and organised by the International Development Research Centre and Knowledge 4 Foundation (K4A).

Plenary discussions. Photo: Erik Bongcam-Rudloff

The main goal of the workshop was to discuss the AI field with a bottom-up approach. The objectives of the workshop were to define the African Machine Learning and Artificial Intelligence (ML/AI) landscape, to create an African research roadmap and to find ways to incorporate cross continental development. Around these objectives, four thematic areas of discussion were developed: governance, skills/capacity building, applications and others. 

Discussions during a break. Photo: Erik Bongcam-Rudloff

On the last day of the workshop we visited the IBM Research – Africa in Nairobi. The staff at IBM-Africa presented several AI projects and one example related to the future of AI in agriculture was presented by Juliet Mutahi, a software Engineer working at the IBM Nairobi THINKLab. She presented “Hello Tractor” a system comparable to Uber for taxi but in this case a system that allows farmers to share tractor resources by using an app on their smartphones. This is the kind of initiatives that are created in Africa as a bottom-up approach. Juliet told the audience that she got the idea to create this system inspired by the work and needs of her parents that are coffee farmers in Kenya.

Juliet Mutahi software Engineer, IBM Nairobi THINKLab. Photo: Erik Bongcam-Rudloff

While identifying the different AI actors in the African continent, another initiative stood out among many: the “Deep Learning Indaba” initiative. This is an annual meeting of the African machine learning community. In 2018 the meeting took place in Stellenbosch, South Africa and gathered 600 participants from many African countries. The next annual meeting will take place in Nairobi, Kenya in August 2019 and the aim for this year is to gather over 700 participants. This shows the strength and vitality for this area of research in the Africa continent.

Many issues connected to agriculture will in the future be better handled using machine learning and artificial intelligence because AI can automate tasks that require human-level intelligence or beyond. This makes solutions that integrate AI better than today’s technologies. Most researchers involved in development research will in the near future learn how to use and how to incorporate AI in their work. Our young colleagues in the “Deep Learning Indaba” community are showing the way. The work in creating the “Network of Excellence in Artificial Intelligence for Development in sub-Saharan Africa” is just one of the building blocks in this process and SLU will be part of it.

Final panel discussion. Photo: Erik Bongcam-Rudloff

Watch an interview with Erik Bongcam-Rudloff talking about African bioinformatics and AI filmed at the Network of Excellence in Artificial Intelligence for Development in Nairobi, Kenya.