01-09-2020, 05:29 AM
Boosting the global fight against mosquito-borne diseases
<div style="margin: 5px 5% 10px 5%;"><img src="https://www.sickgaming.net/blog/wp-content/uploads/2020/01/boosting-the-global-fight-against-mosquito-borne-diseases.gif" width="600" height="338" title="" alt="" /></div><div><div><img src="https://www.sickgaming.net/blog/wp-content/uploads/2020/01/boosting-the-global-fight-against-mosquito-borne-diseases.gif" class="ff-og-image-inserted"></div>
<p><span lang="EN-US">Australia’s Far North Queensland has been declared essentially dengue-free for the first time in about a century, following an intensive release campaign. Other targeted efforts are making strong progress in Asia and South America, where authorities have long tried to wipe out mosquito populations with insecticides.</span></p>
<p><span lang="EN-US">“Our <em>Wolbachia </em>method is natural and self-sustaining,” Green says. “As a large-scale public health intervention, we believe that this a cost-effective way. The evidence so far is that it can sustain itself in local populations for up to seven years. And we expect it will continue.”</span></p>
<p><strong><span lang="EN-US">How machine learning and AI will help take the fight global </span></strong></p>
<p><span lang="EN-US">The Program’s data science partner, <a href="https://news.microsoft.com/en-in/features/gramener-ai-for-earth-save-penguin/">Gramener</a>, is developing machine learning for the AI model. It will tap the Program’s existing release point records as well as many other datasets on human population densities, land use, industrial sites, weather, and other variables. Satellite imagery will be a big part of mapping out large urban areas with strategic and granular accuracy. </span></p>
<p><span lang="EN-US">The aim is to have the ability to pinpoint multiple impactful release points within blocks of as little as 100 square meters.</span></p>
<p><a href="https://news.microsoft.com/en-in/features/gramener-ai-for-earth-save-penguin/"><strong>READ MORE: Gramener is building AI tools to help biodiversity conservation</strong></a></p>
<p><span lang="EN-US">“We want to target the areas where our intervention is needed most,” Green says. “We will be able to release <em>Wolbachia </em>mosquitoes where they will have the most effect with analysis at a countrywide scale instead of at a neighborhood scale. Our ambition is to be able to look at a whole country and run the model over all its urban areas and let it give an unprecedented snapshot of where we can have the most impact.”</span></p>
<p><span lang="EN-US">[embedded content]<button class="cookie-consent-btn">Click here to load media</button></span></p>
<p>Joppa says machine learning and AI are potent tools for not-for-profits that want to tackle big challenges but have limited resources.</p>
<p>“The World Mosquito Program started with the objective of figuring out how to attack a problem. In this case, they worked out how to neutralize the disease-carrying ability of mosquitoes. Then they worked out where they needed to release these mosquitoes.</p>
<p>“They started collecting tons of data. It then became a really messy data problem as they tried to compare a bunch of different data sets to work out where they could be most efficient.</p>
<p>“Ultimately, this is where machine learning comes in. It allows you to take all of that data, abstract it down to a single estimate of probability and map it out. It is cost-effective, and it is super scalable. Instead of figuring out data visualization and analytics for one particular area, you can now do it for an entire city, for an entire country, for the entire world.</p>
<p>“That is because the data sets they are using are globally generalizable. One model that works here can work everywhere.”</p>
<p><em>Top imagery: Wolbachia mosquitoes are released in rural Fiji.</em></p>
</div>
https://www.sickgaming.net/blog/2020/01/...-diseases/
<div style="margin: 5px 5% 10px 5%;"><img src="https://www.sickgaming.net/blog/wp-content/uploads/2020/01/boosting-the-global-fight-against-mosquito-borne-diseases.gif" width="600" height="338" title="" alt="" /></div><div><div><img src="https://www.sickgaming.net/blog/wp-content/uploads/2020/01/boosting-the-global-fight-against-mosquito-borne-diseases.gif" class="ff-og-image-inserted"></div>
<p><span lang="EN-US">Australia’s Far North Queensland has been declared essentially dengue-free for the first time in about a century, following an intensive release campaign. Other targeted efforts are making strong progress in Asia and South America, where authorities have long tried to wipe out mosquito populations with insecticides.</span></p>
<p><span lang="EN-US">“Our <em>Wolbachia </em>method is natural and self-sustaining,” Green says. “As a large-scale public health intervention, we believe that this a cost-effective way. The evidence so far is that it can sustain itself in local populations for up to seven years. And we expect it will continue.”</span></p>
<p><strong><span lang="EN-US">How machine learning and AI will help take the fight global </span></strong></p>
<p><span lang="EN-US">The Program’s data science partner, <a href="https://news.microsoft.com/en-in/features/gramener-ai-for-earth-save-penguin/">Gramener</a>, is developing machine learning for the AI model. It will tap the Program’s existing release point records as well as many other datasets on human population densities, land use, industrial sites, weather, and other variables. Satellite imagery will be a big part of mapping out large urban areas with strategic and granular accuracy. </span></p>
<p><span lang="EN-US">The aim is to have the ability to pinpoint multiple impactful release points within blocks of as little as 100 square meters.</span></p>
<p><a href="https://news.microsoft.com/en-in/features/gramener-ai-for-earth-save-penguin/"><strong>READ MORE: Gramener is building AI tools to help biodiversity conservation</strong></a></p>
<p><span lang="EN-US">“We want to target the areas where our intervention is needed most,” Green says. “We will be able to release <em>Wolbachia </em>mosquitoes where they will have the most effect with analysis at a countrywide scale instead of at a neighborhood scale. Our ambition is to be able to look at a whole country and run the model over all its urban areas and let it give an unprecedented snapshot of where we can have the most impact.”</span></p>
<p><span lang="EN-US">[embedded content]<button class="cookie-consent-btn">Click here to load media</button></span></p>
<p>Joppa says machine learning and AI are potent tools for not-for-profits that want to tackle big challenges but have limited resources.</p>
<p>“The World Mosquito Program started with the objective of figuring out how to attack a problem. In this case, they worked out how to neutralize the disease-carrying ability of mosquitoes. Then they worked out where they needed to release these mosquitoes.</p>
<p>“They started collecting tons of data. It then became a really messy data problem as they tried to compare a bunch of different data sets to work out where they could be most efficient.</p>
<p>“Ultimately, this is where machine learning comes in. It allows you to take all of that data, abstract it down to a single estimate of probability and map it out. It is cost-effective, and it is super scalable. Instead of figuring out data visualization and analytics for one particular area, you can now do it for an entire city, for an entire country, for the entire world.</p>
<p>“That is because the data sets they are using are globally generalizable. One model that works here can work everywhere.”</p>
<p><em>Top imagery: Wolbachia mosquitoes are released in rural Fiji.</em></p>
</div>
https://www.sickgaming.net/blog/2020/01/...-diseases/