Watch the video Dog infects humans with plague for first time in U.S. on Yahoo Finance . Vet Emergency & Referral Group Director Dr. Brett Levitzke on a plague-infected dog that spread the disease to people in Colorado.   [Image source:  http://blogs.wsj.com/ideas-market/2012/06/26/the-plague-still-stalks-the-u-s-west/ ]

Source: finance.yahoo.com

When diseases are heavily dependent upon human populations and factors strongly related to human populations, like domestic pets, the standard behaviors for these diseases result in a diffusion pattern that can sometimes demonstrate preference for population centers.  This particular outbreak in Colorado appears to demonstrate this change in behavior.  Important to note however is that there is an ecological aspect to this cluster of plague cases that prevents the plague from easily migrating in an eastern direction.  However, an increase in the role of  domestic animals in forming the migration patterns could change these traditional diffuse patterns considerably.   

 

My review of the plague, in US EMR/EHR, does demonstrate a density in the population centers of the eastern US.  See https://www.youtube.com/watch?v=A78AZDxO0II 

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SEATTLE (AP) — A 16-year-old boy who fired two gunshots Monday inside a Washington state high school, hitting no one before a teacher tackled him, told detectives he never intended to hurt any students, a police spokesman said.

Source: news.yahoo.com

What are the spatial determinants for this?  Population density?  Rural versus urban?  Pop culture in the school setting?  Large schools versus small schools?  Socioeconomic Status?  Levels of Education? Social and cultural labels?  Race-ethnicity patterns?    

 

EMR/EHR should be capturing this data right now.  This means that in a year or two, maps like those on display can be produced using your HIT system.  The priorities to accomplishing this goal (in descending order) should be: data completeness, SQL, skillsets, SAS or equivalent (non-GIS), long term storage capacity, virtual space for rapid data description, analyses and reporting.  

 

The above dataset took just 7-15 minutes to pull and generate 750-1000 maps with, and another hour to produce the video.  For reporting purposes of course, there is no need to make the video.  No GIS was required.  Only the most basic, most standard systems HIT tools.  

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A simple way to tell the difference between neighboring regions is to magnify the results of your spatial data.   This method is used to define where the nidus or nest of a problem exists in the social or community setting.  It can also be used to define where to establish new clinics, or where to focus the bulk of of your intervention activities.    

 

The simple use of N versus N-squared for your indicator score helps define exactly where the highest risk regions exist.    

 

High risk is defined in two ways using this method.  The first is the standard amount of events or risk scores obtained per unit area evaluated statistically (n, incidence, prevalence, age-adjusted results, etc.).  The second is the simply square these results in order to identify the exactly location of your most needy community settings.  

 

This evaluation process requires just a few minutes to be run, in a standard HIT system.  It can be run at the local or neighborhood level, as well as the large area or regional level (like illustrated here).  

 

The two sets of figures provided come from the following two videos posted at YouTube:

 

N —   https://www.youtube.com/watch?v=lbg6Z8Ylfm8

 

N-squared —   https://www.youtube.com/watch?v=If-HKIdoiuc

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Venoms in the U.S.

Venoms in the U.S.

https://www.youtube.com/v/GvdzdBTyO2I?fs=1&hl=fr_FR

http://youtu.be/GvdzdBTyO2I NaturalPoisoningCases 0536 7

Source: www.youtube.com

Mapping out poisoning cases is a use for NPHG that is pretty much indisputable.  So what does it teach us?

This video is a demonstration of the natural versus human ecology of venomous animals, inferred by the distribution of envenomation cases related to these animals.  An interesting portrayal of cases related to outdoor activities, for comparison with animals with spatial distributions defined by indoor, personal pet keeping practices.

This result may also be related to in-migration of animal vectored disease patterns, and respiratory conditions generated by hypersensitivity to animal dander.

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The last two or three years have demonstrates that the diseases that affect the earth are changing, and migrating, and increasing the likelihood of new populations becoming infected.  The increase in polio cases more than a year ago was a reminder to remain active and avoid certainty or complacency, behaviors further removed by this past year’s measles outbreak in the U.S.  Vectored diseases are also in need of more attentiveness, and the fairly commonplace mosquito born disease patterns forming the top of this list.  

Mosquito born disease patterns like West Nile and  Chikungunya constitute a very small part of this evolutionary process.  There are other insect vectored disease in need of increased attention.

 

Onchocerciasis and filariasis need to be placed high on our re-emerging diseases watch list. 

 

Onchocerciasis was one of the first diseases that WHO designed global health focused preventive health programs.  The Onchocerciasis Control Programme in West Africa (OCP) was developed by WHO in 1974.  Its efforts focused on the use of widespread aerial spraying tactics of the insecticide ivermectin, hoping to kill most of the blackfly vectors.  Forty years later, the world still has a very large number of onchocerciasis cases–42 million approximately.

 

This high prevalence supports the ecology of the pathogen, host, vector and/or reservoir.  

 

The following are information resources for this disease, and its very common co-disease filariasis.

 

J. Blanks, F. Richards, F. Beltran, et al. The Onchocerciasis Elimination Program for the Americas: a history of partnership. Rev Panam Salud Publica/Pan Am J Public Health 3(6), 1998 . http://www.cartercenter.org/resources/pdfs/news/health_publications/river_blindness/panamjph-history%20of-oepa.pdf

 

Training in the management of Onchocerciasis (River Blindness) and Lymphatic Filariasis. From a 2013 Global Health and Disasters Course. https://www.youtube.com/watch?v=azlDp4M9vTo

 

Seth Elliott’s Onchocerciasis slide presentation. https://www.youtube.com/watch?v=vda5R6urnXg

 

Infective larvae ofwuchereria bancrofti (1947, Instructive Military video). https://www.youtube.com/watch?v=_AZ4IlPQehU

 

WHO. Preparing and Implementing a National Plan to Eliminate Lymphatic Filariasis (in countries where onchocerciasis is co-endemic). WHO/CDS/CPE/CEE/2000.16 .

http://www.filariasis.org/pdfs/Press%20Centre/Training%20Material/pmgico.pdf

 

Examples of related NPHG products (U.S. map videos):

Sickle Cell : https://www.youtube.com/watch?v=q7U9Z91ljRU

Bancroft Filaria : https://www.youtube.com/watch?v=8hgpCdf2W9Q

Malayan Filaria : https://www.youtube.com/watch?v=R3-5NfKrJ-Q

Elephantiasis , IP : https://www.youtube.com/watch?v=Uc6zvqutU3g

Foreign Born Zoonotic Diseases : https://www.youtube.com/watch?v=NWYslHBLzeI

 

My complete listing of these diseases from the preliminary dissertation work: http://brianaltonenmph.com/gis/global-health-mapping/foreign-disease-intrusion/

 

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President Barack Obama met on Wednesday with the leaders of three Ebola-stricken West African nations, vowing US help in wiping out the last vestiges of the often deadly disease. “We begin by noting the incredible losses that took place in all three countries,” Obama said during his meeting with Liberian President Ellen Johnson Sirleaf, Guinean President Alpha Conde, and Sierra Leonean President Ernest Bai Koroma. Obama hailed the “great courage and resolve” of the three nations where the current Ebola outbreak has claimed more than 10,000 lives, and promised continued US support to help prevent future outbreaks, even as the numbers of infected people subsides. Obama said in addition to the lives lost, Ebola has exacted a tremendous toll on the economies of the three West African countries.

Source: news.yahoo.com

Ecological diseases just don’t go away.  They cannot be easily eliminated.  

 

If this were the case, yellow fever would have been eradicated, or perhaps even Asiatic cholera and a host of other well studied vectored diseases.

 

Also working against this possibility is our lack of knowledge of the full history of ebola.  We only started documenting several decades ago, but my review of the historical epidemiology literature and translation of the documents, including an 1827 map which notes an ebola like disease, suggests this epidemic was first documented during late 17th, early 18th century colonial exploration periods, a hypothesis that is strengthened by two other events I uncovered for the 19th century colonization period, dealing specifically with the Ebola zones in Africa.   

 

This implies that we do not know the full extent of ebola history or capability of its diffusion processes.

 

Finally, all spatially (globally) spreading diseases progress as they continue to infect new parts of the globe.  Cholera’s spread increased in size and regional type (and biodiversity) as a result of this diffusion process.  So too will the ebolavirus species.  Once this epidemic is over, the next one could demonstrate an even greater impact–infecting new countries . . . or worse.  

 

Like cholera and yellow fever, the pests behind malaria, typhus, the plague, and others that seemed travel internationally in the past, I expect the ebolavirus to progress naturally, and reach its natural peak, establish some new ecological domain(s), and then reduce its number of chief events, stabilizing within these new domains.   Like Vibrio cholera variants accomplished for various deltaic settings over the past two centuries.

 

 

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The best way to reduce error in mapping is to convert from the use of square grids to hexagonal grids.  This reduced the 40%+ error generated by apices in the grid to 14%, a more than 25% reduction in total grid mapping and analytics error (this is allowing for the natural +/-3-5% error we often rely upon).

 

The popularity of this technique is demonstrated by the numbers of downloads my site is getting for the excel sheet I produced in winter of 2003/4.  There are also SQL formulas for this for limitless cells, but the traditional method uses a hexagon overlay for your analyses, calculated using the lat longs for your area, as defined by this page.  

 

To state bluntly what this method corrects for, if we are using grid analysis for intervention or surveillance (determining causality), there is error in our point-area relationships.  41% of the area mapped and assigned a point value for a findings may be assigned to the wrong centroid due to edge-centroid areal trigonomic or geometric features.  This math rule applies to all mapping techniques on a surface (flat or curved) with square grid monitoring techniques.  

 

Hex grid approaches to flat surfaces and sphere more accurately represent the area below, and produce results at least 25% more accurate than traditional grid mapping techniques.

 

We haven’t used hex grids in the past due to ease of producing square grids in GIS.  Manually or even pseudo-automatically calculating grids, before excel and the PC days, was a time (in not labor and thought) intensive process.  These limits no longer exist today.  So why do we keep using this method capable of generating so many errors?

 

Another question to ask is do you wish to produce contour or isoline related risk analyses products?  If you do, then hexagonal grids produce more accurate and understandable contour images (the lines are smoother and more real).

 

In general, I have asked – which cultures or countries excel in Medical GIS and especially the use of innovative ways to produce your results?

 

The stats for my site indicate US visitors are the most frequent, but based on feedback from emails, comments, etc., Great Britain and Canada are most engaged in the use of this new GIS technique.  

 

Moreover, based upon my years of researching geographic medicine in general, the support of geographic approaches to health and disease, in a statistical spatial sense, is mostly a skillset adhered to and frequently used by geographers in Great Britain.  I blame this on the lull in interest in "Geography" that this country had through the mid to late 20th century.  

 

The largest support of this method at the professional level, from Canada, is perhaps the result of an offshoot of British culture and traditions into Canadian academic patterns and behaviors.  Fortunately, Canadians make excellent use of this more accurate technique, the respondents tell me.  

 

There have been very few outcomes of hex grid work in general in the refereed, academic publications on GIS.  I have also found it hard to convince the companies to accept my help in making this a standard tool available to GIS technicians. (But I admit I am also very brazen about this result of professional jealousy, now 20 years into this profession.)

 

It is important to note–that two changes related to GIS need to happen in medical GIS to make it more accurate, and useful at the professional level.

 

1.  Agencies, organizations, insurance companies, PBMs have to become fully engaged in GIS and spatial analyses–not just for that occasional research project (which is now the case), but at the 1000s of analytics per year, for each program they attend to.  Managed Care insurance agents and facilities have to catch up with this technology.  The current outbreaks are happening due to the failure of these programs to evolve over the past decade, change with the time, initiate new thoughts, recruit new thinkers (us GIS pros are under-employed and not at all respected).

 

2.  These companies etc. also have to slow down, hire and make better use of the skills of better trained GIS individuals, check their data and work for errors, change to spatial analyses, and go beyond just "the experimental stage" (a status now 10-15 years old).  

It doesn’t help that some major GIS businesses or industries are non-supporting of the new ideas, methods, skillsets, and technology.  

It’s been well over a decade since I began promoting this use of GIS at the statistical and administrative-clinical level.

Think of this as getting the wrong address for an emergency call–We don’t want to send our services, products and staff to the wrong address.  We need to reduce that 41% error the traditional form of spatial grid analysis has, as much as possible.

RESOURCES:

 

My information sheets on Grid Analysis in general, and the hex grid technique I developed more than ten years ago, are as follows:

 

1.

Grid mapping health and disease in the United States –   

 http://brianaltonenmph.com/gis/population-health-surveillance/grid-mapping-disease-in-the-united-states/

 

2. Grid Cell Analysis (and Ecology) –

http://brianaltonenmph.com/6-gis-ecology-and-natural-history/grid-cell-analysis/

 

3.  Sequential Series analyses using Hexagonal Grid Cell techniques – 

http://brianaltonenmph.com/6-gis-ecology-and-natural-history/hexagonal-grid-analysis/gridcells/ 

 

4.  Applying Grids to Managed Care programs Medical GIS –

  http://brianaltonenmph.com/gis/populations-and-managed-care/applying-gis-to-managed-care/ 

 

6.  Downloads Page for Hex Grid formulas/calculation sheets (the stats for which are cited above) –  

http://brianaltonenmph.com/6-gis-ecology-and-natural-history/hexagonal-grid-analysis/hexagonal-cells-excel-spreadsheet/

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