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Open Epidemiology Project Coordinator

Billions have been spent trying to discover pharmaceutical treatments for dementia and mental illness. However, the effort has been a near-total failure to this point. This suggests that we may benefit from looking for an underlying cause and means of prevention.

Most people attribute depression and anxiety disorders primarily to life-events or genetics. Dementia is generally assumed to have genetic origins and something we just have to accept as a fact of life.

However, there is epidemiological evidence that some factors in our environment and behavior have a massive influence on the development of mental illness and dementia.

Patient: It hurts when I do this.

Doctor: Then don’t do that.

Currently hundreds of millions of people are hurting because of things that they’re doing. The problem is we have no idea what they are. Discovering this is the goal of the Open Epidemiology Initiative.

Temporal Evidence

Temporal Evidence That We Are Doing Something That Makes Dementia and Mental Illness Worse

According to hospital discharge data, from 1990 to 2010 the incidence of autism, Alzheimer’s disease, celiac disease, sleep disorders, inflammatory bowel disease, and depression all roughly doubled or tripled.

We are a product of our genes and our environment as are all diseases. The human genome didn’t start dramatically changing in 1990. So the increases must be attributed to one or multiple changes in our diets or environment or a very powerful witch put a curse on the world.

The strongest correlation with the rise in diseases is the increase in the use of glyphosate weed killer on the majority of soy, wheat, and corn we consume. The above charts illustrate a near-identical mirror in the increase in usage of this chemical and the incidence of these diseases.

Correlation Does Not Equal Causation

Of course, correlation is not the same as causation. The rise could also be influenced by many other factors as well. The only way to be confident in a causal relationship is through interventional experimentation.

However, we have limited resources available for this type of experimentation. So we need to prioritize which relationships are most likely to be worth further investigation. The presence of an observational correlation could be a prerequisite for devoting financial resources to more controlled studies. Conversely, the absence of a correlational relationship between an outcome and factor suggests we should not devote limited research dollars to further exploration. 

Given that nearly a billion people are suffering daily from all of these diseases combined, it’s extremely urgent that we collect and make publicly available data on the incidence of these diseases over time as well as data on all factors that could be exacerbating or improving them.

Absence of Correlation DOES Suggest Absence of Causation

Something caused the incidence of non-Hodgkin lymphoma (NHL), a cancer of the immune system to quadruple from 1979 to 2011.

In 2015, the World Health Organization’s International Agency for Research on Cancer classified glyphosate as “probably carcinogenic to humans.” Thousands of people have sued Monsanto based on the belief that exposure to the herbicide caused their non-Hodgkin’s lymphoma. It’s impossible to know the precise cause of any given case of cancer. However, based on the fact that this type of cancer steadily rose through the 1970s when glyphosate was not widely used on crops suggests that there more significant causes for the societal increase in non-Hodgkin lymphoma.

Geographic Evidence

Geographic Evidence That We Are Doing Something That Makes Dementia and Mental Illness Worse

There are small areas of the world known as “Blue Zones” where the incidence of Alzheimer’s and autoimmune disease is almost non-existent. (Learn more about how Alzheimer’s and autoimmune disease are strongly linked.) 5 areas were located using epidemiological data, statistics, birth certificates, and other research. In these Blue Zones people reach age 100 at 10 times greater rates than in the United States. 

The people in these regions are not significantly genetically different from the rest of the world, but significant differences in lifestyle (such as diet) have been identified.

Lifespan even varies significantly from state to state within the same country.

Regulations Are Invaluable Natural Experiments

Macro-level epidemiological data includes the incidence of various diseases over time combined with data on the amounts of different drugs or food additives. This is how it was initially discovered that smoking caused lung cancer. With macro-level data, it’s even harder to distinguish correlation from causation. However, different countries often enact different policies that can serve as very useful natural experiments.

For instance, 30 countries have banned the use of glyphosate. If the rates of Alzheimer’s, autism, and depression declined in these countries and did not decline in the countries still using glyphosate, this would provide very powerful evidence regarding its effects. Unfortunately, there is no global database that currently provides easy access to the incidence of these conditions in various countries over time and the levels of exposure to various chemicals.

We need to collect more data to take advantage of these geographic natural experiments. With enough data, we could discover hidden factors reducing or contributing to chronic illnesses. Then by providing real-time decision support to individuals, we could apply these lessons learned to reduce chronic disease burden throughout the world.

Specific Aims

The CDC should provide a simple website where one can enter any communicable or non-communicable diseases in a search box and see a longitudinal chart of overlaid incidence and prevalence over time for the entered diseases.

Future Aims

  • Correlation Matrix Heat Map – This would reveal which of the entered diseases have the greatest correlation in rise and fall over time. Higher correlations suggest a greater likelihood of a shared underlying root cause of the increase or decrease of the disease prevalence.
  • Comorbidity Heat Map – This would reveal which diseases were most often co-occurring in the same individuals
  • Factor Correlation Matrix – This would allow one to select a disease and identify the population-level environment, dietary, and treatment factors most highly correlated with the rise and fall of disease for a given geography. Environmental data could be obtained from the Environmental Protection Agency, dietary data would be obtained from the USDA and treatment data could be provided by the FDA.

Existing Solutions

Currently the CDC website provides a vast amount of data on many diseases. However, it is very fragmented and disparate which makes it very difficult to study relationships between diseases.

1. Hospital Discharge Data

Most studies examining the prevalence of disease are currently based on hospital discharge data. One can get a sense of the trends in various diseases over time by looking at the hospital discharge diagnoses collected from hundreds of hospitals by the United States Centers for Disease Control and Prevention (CDC). These data are available for free download.

Raw data files are available from 1998 through 2010. Each data file contains thousands of discharge records collected from hospitals using a statistically random sampling procedure. The records contain information about the age, sex, race, geographic location, and diagnoses for each discharge. The diagnoses are recorded by the International Classification of Diseases, Ninth Revision (ICD-9) codes. Up to seven diagnostic codes can be recorded for each discharge, with the first listed being the primary reason for the hospital admission. Currently, making use of this data requires writing computer programs to query the data file for specific ICD codes for each year.

A rate of increase, as an estimate of prevalence, over time for each particular diagnosis can be obtained as follows:


  • â is the normalized number of hospital discharges of a disease in a year;
  • a is the total number of the hospital discharge records of the disease in the year computed from the raw files;
  • T represents the total number of hospital discharge records in the sampled hospitals in that same year
  • P is the total population in the US for that year

Population estimates can be obtained from the CDC mortality database.

The drawbacks of using hospital discharge data are:

  1. Difficult to Work With –  The hospital discharge data is extremely denormalized and requires a lot of work to make it analyzable.
  2. Based on Changing Diagnostic Criteria – There are subjective biases in the hospital discharge data.  It is common that hospital admission routines change without any change of prevalence of a disorder. 

2. Institute for Health Metrics and Evaluation Global Health Data Exchange (GHDx)

The Institute for Health Metrics and Evaluation‘s Global Health Data Exchange (GHDx) is the world’s most comprehensive catalog of surveys, censuses, vital statistics, and other health-related data.

Here’s an example of using their Global Disease Burden (GBD) Compare tool to examine the disability-adjusted life years (DALYs) lost due to Alzheimer’s and Depression over time:


Additional Program Coordinator responsibilities include:

  • Planning and coordination of a program and its activities
  • Ensuring implementation of policies and practices
  • Maintaining budget and tracking expenditures/transactions

Job brief

We are looking for a competent Program Coordinator to undertake a variety of administrative and program management tasks. You will help in planning and organizing programs and activities as well as carry out important operational duties.

To be an excellent program coordinator, you must be organized and detail-oriented, comfortable working with diverse teams. If you have further skills in program development and human resources support, we’d like to meet you.

The goal will be to facilitate the effective management of programs according to the organization’s standards.


  • Support planning and coordination of a program and its activities
  • Ensure implementation of policies and practices
  • Maintain budget and track expenditures/transactions
  • Manage communications through media relations, social media etc.
  • Help build positive relations within the team and external parties
  • Schedule and organize meetings/events and maintain agenda
  • Ensure technology is used correctly for all operations (video conferencing, presentations etc.)
  • Prepare paperwork and order material
  • Keep updated records and create reports or proposals
  • Support growth and program development


  • Proven experience as program coordinator or relevant position
  • Knowledge of program management and development procedures
  • Knowledge of budgeting, bookkeeping, and reporting
  • Tech-savvy, proficient in MS Office
  • Ability to work with diverse and multi-disciplinary teams
  • Excellent time-management and organizational skills
  • Outstanding verbal and written communication skills
  • Detail-oriented and efficient

Operational Guidelines

We are attempting to implement solutions that produce exponential benefits that feedback and accelerate its own progress. That is one of the primary reasons we chose to focus on improving the human mind. Better brains have the ability to find solutions to produce even better brains. This produces a snowball effect of benefits. Not only are better brains inherently good, but they are also better able to find solutions to every other global problem.

Leveraging technology

Hiring an extra researcher is great. However, we could potentially leverage new technology to automate data collection, analysis, and reporting giving us a 1000x increase in speed or 1000x decrease in cost relative to the traditional methodology.

It costs $48k per subject in Phase III clinical trials.  So there’s not a sufficient profit incentive for anyone to do research on the effects of any factor besides a molecule that can be patented. FEDMI supports the Journal of Citizen Science where this research process has been automated.  This system of crowdsourced clinical research has collected over 10 million data points on symptom severity and influencing factors from over 10,000 people. This data has been used to freely publish 90,000 studies on the effects of various treatments and food ingredients on symptom severity.

Positive Feedback Loops

  • Evolution applies positive feedback in that the more capable methods resulting from one stage of evolutionary progress are used to create the next stage.
  • As a result, the rate of progress of an evolutionary process increases exponentially over time. Over time, the “order” of the information embedded in the evolutionary process (i.e., the measure of how well the information fits a purpose, which in evolution is survival) increases.
  • A correlate of the above observation is that the “returns” of an evolutionary process (e.g., the speed, cost-effectiveness, or overall “power” of a process) increase exponentially over time.
  • In another positive feedback loop, as a particular evolutionary process (e.g., computation) becomes more effective (e.g., cost-effective), greater resources are deployed toward the further progress of that process. This results in the second level of exponential growth (i.e., the rate of exponential growth itself grows exponentially).

Positive Feedback Loops and the Brain

Moore’s Law – the scaling property that has seen revolutions in technologies ranging from supercomputers to smart phones – has largely been driven by advances in materials science. As the ability to miniaturize transistors is coming to an end, there is increasing attention on new approaches to computation, including renewed enthusiasm around the potential of neural computation.

Advances in neurotechnologies have revealed neural computation insights into broader computing applications. As we understand more about the brain, we use these discoveries to improve artificial intelligence.

Examples of brain-derived computational techniques include deep learning and neuromorphic hardware. These advancements improve our ability to learn about the brain. and accordingly can be projected to give rise to even further insights.

This positive feedback will produce exponential scaling in computing emerging from our progressive understanding of the brain.

The project coordinator must be able to apply moonshot thinking to the challenge.

Moonshot thinking is when you pick a huge problem and set out to create a radical solution to the problem. To make this happen you have to abandon the idea of creating a 10% improvement. Instead, the focus is a solution that will bring tenfold (or 10x) improvements, or solve it altogether.

1. Huge Problem: Pick a massive problem that, if solved, would positively impact the lives of millions, even billions.

2. Radical Solution: Create and propose a radical new solution to that problem that seems crazy today.

3. Breakthrough Technology: Search for breakthroughs and emerging technologies that exist today and leverage those technologies in your solution. This provides evidence that the solution (though wild-sounding today) may be possible in the future. 

6 Habits of Highly Effective Program Directors

If you do what other successful people do, over and over again, nothing in the world can stop you from eventually getting the same results that they do. And if you don’t, nothing can help you.

So what do successful organizations do differently from unsuccessful ones? In a word, leverage.

Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.

From Forces for Good

The methods of attaining this leverage can be broken down into 6 steps.

1. Serve Individuals and Advocate on Their Behalf

Work with government and advocate for policy change

High-impact organizations don’t just focus on doing one thing well. They may start out providing great programs, but eventually, they realize that they cannot achieve systemic change through service delivery alone. So they add policy advocacy to access government resources or to change legislation, thus expanding their impact.

Other nonprofits start out doing advocacy and later add grassroots programs to supercharge their strategy. Ultimately, all of them bridge the divide between service and advocacy, and become good at doing both. And the more they advocate and serve, the greater the impact they achieve.

We serve directly by helping

– individuals collect data and discover hidden factors increasing their risk or severity of dementia or mental illness.

– companies, organizations, and researchers share anonymous data

We advocate by working with the government to

– provide resources to researchers as well as

– reducing regulations that impede data sharing, experimentation, and scientific progress.

2. Make Markets Work

Harness market forces and see business as a powerful partner

Tapping into the power of self-interest and the laws of economics is far more effective than appealing to pure altruism. Great nonprofits find ways to work with markets and help businesses “do well while doing good.”

Ways of leveraging market forces to achieve social change on a grander scale include:

  • influencing business practices
  • building corporate partnerships
  • developing earned-income ventures such as software development and data analysis services for business

We work with pharmacies, online grocers, and healthcare providers to give individuals access to their health, treatment, and diet data. We also work to provide an option for individuals to easily and anonymously share their data with the aggregated data pool to accelerate research.

3. Inspire Evangelists

Convert individual supporters into evangelists for the cause

Great nonprofits see volunteers as much more than a source of free labor or membership dues. They create meaningful ways to engage individuals in emotional experiences.

Ways We Inspire Evangelists

We reward citizen scientists for their data donations and researchers for publishing studies using this data.

4. Building Non-Profit Networks

Build and nurture nonprofit networks, treating other groups as allies

Ways We Build Non-Profit Networks
Open Source Software

We do this by creating open-source software that can be used by other research organizations to collect data and create studies.

Affiliate Organizations

We also sponsor local affiliate Crowdsourcing Cures Meetup groups. This involved bringing patients, physicians, researchers, data scientists, and programmers together to work on projects to solve challenging medical problems.

We strive for collaboration not competition. Wheel reinvention should be avoided at all costs.

5. Master the Art of Adaptation 

High-impact program directors are exceptionally adaptive, modifying their tactics as needed to increase their success. They respond to changing circumstances with one innovation after another. Mistakes and failures are an inevitable result of experimentation. But unlike ineffective nonprofits, they master the ability to listen, learn, and modify their approach based on external cues — allowing them to sustain their impact and stay relevant.

6. Share Leadership

High-impact program directors share power in order to be a stronger force for good. They distribute leadership throughout their organization and their nonprofit network — empowering others to lead. And they cultivate a strong second-in-command, build enduring teams with long tenure, and develop highly engaged boards in order to have more impact.

How We Implement These Lessons