Archive for the ‘Public Private Partnerships’ Category
It’s been more than two years since we reported on Seattle as the new Geneva, that is, as the new epicenter of global health activity. An article in this morning Journal-Sentinel (Water-engineering firms see potential, challenge in developing countries) – which includes an exclusive interview with the Acumen Fund’s chief executive Jacqueline Novogratz – suggests that Milwaukee is angling to do the same for water technology:
It’s an issue that almost certainly will preoccupy business leaders in metro Milwaukee in their strategy to brand the region as an international hub of water technology. The metro area is home to scores of water-engineering companies. Gov. Jim Doyle and the University of Wisconsin-Milwaukee this month announced plans to invest millions of dollars for UWM to become a center of freshwater research.
An 2008 article from the same newspaper (Area’s tide could turn on water technology) provides more evidence:
[F]our of the world’s 11 largest water-technology companies have a significant presence in southeastern Wisconsin, according to an analysis of data from a new Goldman Sachs report.
Wall Street has tracked automakers, railroads and retailers almost since there were stocks and bonds. But water remains a novelty. Goldman Sachs Group Inc. didn’t begin to research water treatment as a stand-alone industrial sector until late 2005.
While several large MNCs have shown an active interest in clean water in developing countries (e.g., Procter and Gamble, Vestergaard Frandsen, Dow) open questions remain as to what role large MNCs will play in providing access to safe water for the one billion people who don’t have it.
(Thanks to Dr. Jessica Granderson for sending the link)
I was just sent this information (thanks to Becky!) about a new round of funding for microbicides, which comes on the heels of promising results from a trial of the PRO2000 microbicide candidate. We covered this a couple of years ago and at the time I said – the potential of this drug is revolutionary. With microbicides there was great excitement and hope, then there was failure and now there is some maturity. Okay, maybe I am overstating the case, the take home point is that we still don’t have a product and this is not cheap, easy, or quick. Developing a drug is complicated, involves huge risk, can take decades and is highly uncertain. Let’s review the drug development time line again for those of you not familiar – the graph below gives the most simplistic picture:
The early microbicide discussions took place almost 15 years ago (International Working Group on Vaginal Microbicides, source). Over half that amount of time, from 2000-2007, $1.1 Billion has already been invested in microbicide R&D! It takes anywhere from $200M to $1 Billion to bring a single novel drug to market. Let’s hope one of these compounds works and makes it through phase III. But how much will we have spent? $2 Billion, $3 billion? If it works, it will have been worth the money, however, we must ask if we took the most efficient financial route to get to the end point and if there were better financial models – that is a valid question.
“The Partnership for Quality Medical Donations (PQMD) Mapping Tool, provides unprecedented access to information about the medical product donations being made…to the world’s most vulnerable populations. [Anyone] can easily determine where PQMD member donations are sent, find information on how the donations are being used by the communities who receive them and access a library of medical donation resources…” Source: Google Map Technology Enhances First Global Medical Donations Map
I was alerted to the newly launched donation mapping tool by Jessica over at GHP (Global Health Progress). Thanks to her I got to sit in on a presentation of the tool which I found fascinating (but not sure anyone else did based on the lack of questions in the audience). The tool is a mashup of Google maps and donation metrics globally (location, type of donation, organizations involved, what type of supplies, volume, staffing on the ground to name some). The goal is to help collaboration, answer questions and facilitate the process of identifying who is working where and what are they doing? Second they wanted to bring to life the impact of donations (places, faces and outcomes). Other things I took away from the presentation:
- Massive unmet need for medical supplies. Poor infrastructure & distribution are key challenges
- Donations are meeting up to 40% of health needs in some areas
- PQMD has 27 members total (non cash EX US dollar volume was $4 Billion dollars, including non PQMD members)
- Private sector + NGO + Academia combo mix: The tool was incubated at Loma Linda School of Public health and is a joint effort with PQMD and industry.
They have put a lot of work into this and I think they have lots of neat information. The data comes from primary and secondary data sources. For example they use actual donor member shipping records and augment that with onsite data collection, interviews and site visits on ground with facility staff (location, staffing, needs). The public view is different from the private view so as not to compromise security of the facilities. There is a lot more I could write about this, but I’ll stop here and let you play around with the tool yourself:
A few other things to note – the PQMD site has various interesting resources. Here are some more notes, and things to check out:
- PQMD case studies
- PQMD fellowships
- PQMD educational resources on proper documentation, storage, distribution, see their basic primer on health care logistics
Have comments about the tool, leave them here:
A few days back Aman wrote a post about Google Flu Trends. Thought I’d add a few thoughts here after reading the draft manuscript that the Google-CDC team posted in advance of its publication in Nature.
By the way, here’s what Nature says: Because of the immediate public-health implications of this paper, Nature supports the Google and the CDC decision to release this information to the public in advance of a formal publication date for the research. The paper has been subjected to the usual rigor of peer review and is accepted in principle. Nature feels the public-health consideration here makes it appropriate to relax our embargo rule
Ginsberg J, Mohebbi MH, Patel RS, Brammer L, Smolinski MS, Brilliant L. Detecting influenza epidemics using search engine query data. Draft manuscript for Nature. Retrieved 14 Nov 2008.
Assuming that few folks will read the manuscript or the article, here’s some highlights. I should say I appreciated that the article was clearly written. If you need more context, check out Google Flu Trends How does this work?…
- Targets health-seeking behavior of Internet users, particularly Google users [not sure those are different anymore], in the United States for ILI (influenza-like illness)
- Compared to previous work attempting to link online activity to disease prevalence, benefits from volume: hundreds of billions of searches over 5 years
- Key result – reduced reporting lag to one day compared to CDC’s surveillance system of 1-2 weeks
- Spatial resolution based on IP address goes to nearest big city [for example my current IP maps to Oakland, California right now], but the system is right now only looking to the level of states – this is more detailed CDC’s reporting, which is based on 9 U.S. regions
- CDC data was used for model-building (linear logistic regression) as well as comparison [for stats nerds – the comparison was made with held-out data]
- Not all states publish ILI data, but they were still able to achieve a correlation of 0.85 in Utah without training the model on that state’s data
- There have attempted to look at disease outbreaks of enterics and arboviruses, but without success.
- For those familiar with GPHIN and Healthmap, two other online , the major difference is in the data being examined – Flu Trends looks at search terms while the other systems rely on news sources, website, official alerts, and the such
- There is a possibility that this will not model a flu pandemic well since the search behavior used for modeling is based on non-pandemic variety of flu
- The modeling effort was immense – “450 million different models to test each of the candidate queries”
So what does this mean for developing world applications?
Here’s what the authors say: “Though it may be possible for this approach to be applied to any country with a large population of web search users, we cannot currently provide accurate estimates for large parts of the developing world. Even within the developed world, small countries and less common languages may be challenging to accurately survey.”
The key is whether there are detectable changes in search in response to disease outbreaks. This is dependent on Internet volume, health-seeking search behavior, and language. And if there is no baseline data, like with CDC surveillance data, then what is the best strategy for model-building? How valid will models be from one country to another? That probably depends on the countries. Is it perhaps possible to have a less refined output, something like a multi-level warning system for decision makers to followup with on-the-ground resources? Or should we be focusing on news+ like GPHIN and Healthmap?
Another thought is that we could mine SMS traffic for detecting disease outbreaks. The problem becomes more complicated, since we’re now looking at data that is much more complex than search queries. And there is often segmentation due to the presence of multiple phone providers in one area. Even if the data were anonymized, this raises huge privacy concerns. Still it could be a way to tap in to areas with low Internet penetration and to provide detection based on very real-time data.
‘The Biggest Challenge Is There Is No Organized Supply Chain’
This headline in Wharton’s newsletter intrigued me, only time for a quick posting, but this is certainly food for thought. Wal Mart is expanding operations in India and there are two quotes of note that we should think about in the context of culture; delivery and distribution of medical/health goods to those in need; and in the context of refrigeration of medication and/or vaccinations:
“The biggest challenge is that there is no organized supply chain in India. We’ve even been surprised by some of the leading manufacturers in India like Unilever, Procter & Gamble, and some other big names, who are actually welcoming the arrival of organized supply chains in India and Wal-Mart pioneering that effort. Because of the lack of that supply chain today, there is no forecasting, there is no understanding of how demand is. It’s largely a push based system. So, I think, getting that transparency across the supply chain will be very unique.”
“The other thing is, there is no refrigerated cold chain for fresh produce in India, so therefore a lot gets wasted. By McKinsey’s own work, which the consulting firm has done, almost 40% of fresh produce in India gets wasted from farmland to the time it reaches the consumer.”
“India is very unique. In fact, I have lived in China, so maybe I can say it with a little bit more liberty that the only thing common between India and China is the one billion people. If you really operate in the two countries, I think, there are very different consumers, very different kinds of legislation, very different levels of economic development, social infrastructure, and governmental management of the economy.”