Category Archives: global health

How to move data from KoboToolbox to SmartVA-Analyze

Barbara Muffoletto and I figured out how to export verbal autopsy data from KoboToolbox in a format suitable for running through SmartVA-Analyze. It was not too hard, but it was not too easy, either!

She recorded a 4.5 minute video of how to do it, so that it will be easier for others in the future, which I share with you here:

I hope everyone who needs this finds it!

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New Data: A de-identified database of 11,979 verbal autopsy open-ended responses

There is a new sort of publication model in Global Health, and I just gave it a try (editor’s note: just = in the last year). Gates Open Research offers “author-led publication and open peer review”, and is available now to Gates Foundation-funded researchers.

I used it to publish a Data Note, which is a dataset together with a short description of what is in the dataset.

Have a look here: https://gatesopenresearch.org/articles/2-18/v1

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SIAM Mini-tutorial Recording online

Dear AN16 speakers, this one contains the correct link,

The sessions recorded at the Annual Meeting (AN16) in Boston are now available on SIAM Presents…Featured Lectures from Our Archives

https://www.pathlms.com/siam/courses/3028

You are welcome to link to your talk from your personal web pages and point to the site. You can find your presentation using the search box on the upper right.

We will post links from the SIAM web site to the presentations and will send out notification to attendees shortly. I expect the recorded sessions from the Conference on the Life Sciences (LS16) to also be available soon.

Please do not hesitate to contact me if you have questions.

Sorry about the error in the first email.

Sincerely,

Linda

Linda C. Thiel
SIAM Director, Programs and Services

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Vaccine Delivery, the case of HPV prevention

Tough choices are when and how much. http://jamanetwork.com/journals/jama/fullarticle/2588253

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Write-up of my SIAM Tutorial

That was nice of them to do: https://sinews.siam.org/Details-Page/machine-learnings-impact-on-global-public-health

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Pretty good alphabet book

This was not designed for kids, but it seems to have captured my 4 year old’s attention for the moring: https://www.cdc.gov/dpdx/az.html

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Now available: Big Data and Analytics for Infectious Disease Research, Operations, and Policy: Proceedings of a Workshop

Hay spoke of the difficulty of conveying the uncertainty that goes along with
these predictions. For example, his team spends half of its time developing the
correct uncertainty envelopes for the maps, and he does not have a good idea
on how to communicate this uncertainty to the many constituencies that would
find the maps useful. One aspect of these maps that he finds particularly vexing
is the tendency for people to just look at the map and ignore all of the richer
detail about uncertainty that his team provides with the maps.

https://www.nap.edu/download/23654

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Mapping from SmartVA-Analyze output to ICD-10 causes

There has got to be a quick way to format this better:

Cause list for SmartVA against ICD-10 codes

ADULT CAUSES
Code to ICD-10 WHO ICD definition and comments
GBD Cause Group A: Communicable, maternal, neonatal and nutritional disorders
AIDS B24 Unspecified human immunodeficiency virus [HIV] disease
Diarrhea/Dysentery A09 Other gastroenteritis and colitis of infectious and unspecified origin
Malaria B54 Unspecified malaria
Maternal O95 Obstetric death of unspecified cause: Maternal death from unspecified cause occurring during pregnancy, labour and delivery, or the puerperium
Other Infectious Diseases B99 Other and unspecified infectious diseases
Pneumonia J22 Unspecified acute lower respiratory infection
TB A16 Respiratory tuberculosis, not confirmed bacteriologically or histologically
GBD Cause Group B: Non-communicable diseases
Acute Myocardial Infarction I24 Other acute ischaemic heart diseases (as for WHO 2014)
Asthma J45 Asthma
Breast Cancer C50 Malignant neoplasm of breast
COPD J44 Other chronic obstructive pulmonary disease
Cervical Cancers C53 Malignant neoplasm of cervix uteri (WHO VA has C55 for all female reproductive neoplasms)
Cirrhosis K74 Fibrosis and cirrhosis of liver
Colorectal Cancer C18 Malignant neoplasm of colon
Diabetes E14 Unspecified diabetes mellitus
Epilepsy G40 Epilepsy
Esophageal Cancer C15 Malignant neoplasm of oesophagus
Leukemia/Lymphomas C96 Other and unspecified malignant neoplasms of lymphoid, haematopoietic and related tissue
Lung Cancer C34 Malignant neoplasm of bronchus and lung
Other Cardiovascular Diseases I99 Other and unspecified disorders of circulatory system
Other Non-communicable Diseases R99 Other ill-defined and unspecified causes of mortality
Prostate Cancer C61 Malignant neoplasm of prostate
Renal Failure (due to renal disease) N19 Unspecified kidney failure
Stomach Cancer C16 Malignant neoplasm of stomach
Stroke I64 Stroke, not specified as haemorrhage or infarction
Other Cancers C76 Malignant neoplasm of other and ill-defined sites
GBD Cause Group C: Injuries
Bite of Venomous Animal X27 Contact with other specified venomous animals
Drowning W74 Unspecified drowning and submersion
Falls W19 Unspecified fall
Fires X09 Exposure to unspecified smoke, fire and flames
Homicide (assault) Y09 Assault by unspecified means
Other Injuries X58 Exposure to other specified factors
Poisonings (accidental) X49 Accidental poisoning by and exposure to other and unspecified chemicals and noxious substances
Road Traffic V89 Motor- or nonmotor-vehicle accident, type of vehicle unspecified
Suicide (intentional self-harm) X84 Intentional self-harm by unspecified means
CHILD CAUSES
GBD Cause Group A: Communicable, maternal, neonatal and nutritional disorders
AIDS B24 Unspecified human immunodeficiency virus [HIV] disease
Diarrhea/Dysentery A09 Other gastroenteritis and colitis of infectious and unspecified origin
Encephalitis G04 Encephalitis, myelitis and encephalomyelitis
Hemorrhagic fever A99 Unspecified viral haemorrhagic fever
Malaria B54 Unspecified malaria
Measles B05 Measles
Meningitis G03 Meningitis due to other and unspecified causes
Other Infectious Diseases B99 Other and unspecified infectious diseases
Pneumonia J22 Unspecified acute lower respiratory infection
Sepsis A41 Other sepsis
GBD Cause Group B: Non-communicable diseases
Other Cancers C76 Malignant neoplasm of other and ill-defined sites
Other Cardiovascular Diseases I99 Other and unspecified disorders of circulatory system
Other Defined Causes of Child Deaths R99 Other ill-defined and unspecified causes of mortality
Other Digestive Diseases K92 Other diseases of digestive system
GBD Cause Group C: Injuries
Bite of Venomous Animal X27 Contact with other specified venomous animals
Drowning W74 Unspecified drowning and submersion
Falls W19 Unspecified fall
Fires X09 Exposure to unspecified smoke, fire and flames
Poisonings X49 Accidental poisoning by and exposure to other and unspecified chemicals and noxious substances
Road Traffic V89 Motor- or nonmotor-vehicle accident, type of vehicle unspecified
Violent Death Y09 Assault by unspecified means
NEONATE CAUSES
Birth asphyxia P21 Birth asphyxia
Congenital malformation Q89 Other congenital malformations, not elsewhere classified
Meningitis/Sepsis P36 Bacterial sepsis of newborn
Pneumonia P23/J22 Congenital pneumonia/Unspecified acute lower respiratory infection
Preterm Delivery P07 Disorders related to short gestation and low birth weight, not elsewhere classified
Stillbirth P95 Fetal death of unspecified cause

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U.S. county mortality paper

The U.S. county mortality paper, a study analyzing 21 cause groups of death in every U.S. county from 1980 through 2014, was published in JAMA on December 13th along with a trove of other useful resources on county health including updated county profiles, an updated US Health Map data tool, a new US Data GHDx page, a new animated GIF, and two videos produced by JAMA.

Congratulations to IHME study authors Laura Dwyer-Lindgren, Amelia Bertozzi-Villa, Rebecca Stubbs, Chloe Morozoff, Michael Kutz, Chantal Huynh, Ryan Barber, Katya Shackleford, Abraham Flaxman, Mohsen Naghavi, Ali Mokdad, and Christopher Murray.

Additional congrats to the Global Engagement Team (GET) members and alumni involved in the dissemination of these important findings: Dean Owen, Kevin O’Rourke, Kate Muller, Bill Heisel, Dawn Shepard, Sofia Cababa Wood, Katie Leach-Kemon, Adrienne Chew, Pauline Kim, Rachel Fortunati, and Kayla Albrecht.

Stories by CNN, HealthDay, NBC, and Reuters were picked up by hundreds of local news stations and papers across the nation, totaling nearly 500 media mentions since 8:00am Tuesday. Here are a few of the top news stories covering the paper; many include their own graphics using IHME county mortality data:
• Janet Adamy with the Wall Street Journal wrote What kills Americans varies widely by region. ““It’s much more complicated than saying ‘Everything’s bad in Mississippi and Alabama, and everything’s good in places with high life expectancy,’” said Christopher J. L. Murray, director of the Institute for Health Metrics and Evaluation at the University of Washington and an author of the study.”
• Olga Khazan with the Atlantic wrote Why are so many Americans dying young? “’A place like Colorado, there’s an incredibly low death rate for heart disease, one of the lowest in the world, and low rate for diabetes,’ Murray said. ‘If you look at places like West Virginia, things are getting worse, and it’s not just opioids.’”
• Jacqueline Howard with CNN wrote What’s the most common cause of death in your county? “’We know that unequal access and quality of care create health disparities in the US for many causes of death, while other causes are linked to risk factors or policies. The results of this study prompt future research to further identify what drives health disparities in our country,’ said Dr. Christopher Murray, a professor and director of the Institute for Health Metrics and Evaluation at the University of Washington, who was a co-author of the new study.”
• Anna Maria Barry-Jester with FiveThirtyEight wrote How Americans die may depend on where they live. “Lead author Laura Dwyer-Lindgren, a researcher at the Institute for Health Metrics and Evaluation at the University of Washington, says she hopes the data can be useful to local health workers and the public. ‘If you go to any state health coordinator, they probably know what was recorded on the death certificates. But it can be really difficult to interpret them,’ she said. She hopes that collapsing the various causes of death down to 21, rather than looking at everything that can kill a person, will make it easier to target regional problems.”
• Maggie Fox with NBC News wrote Where you live determines what kills you. “’Heart disease is particularly high in the southeast of the United States,’ said Murray, who has pioneered many different ways to crunch health statistics. Experts know lifestyle — poor diet, a lack of exercise and less access to good medical care — are mostly to blame.”
• Andrew Seaman with Reuters wrote U.S. death rates vary drastically by county. “’Within any individual county, knowing how big of a problem a condition is’ can help counties know which conditions need attention, resources and policies, said the study’s lead author Laura Dwyer-Lindgren, of the Institute for Health Metrics and Evaluation at the University of Washington in Seattle.”
• Dennis Thompson with HealthDay wrote Where you live may determine how you die, which was picked up by U.S. News and World Report. “Armed with this sort of information, county and city health departments can focus their efforts on the specific problems affecting their communities, said lead researcher Ali Mokdad. He is a professor with the department of global health at the University of Washington, in Seattle.”
• Julia Belluz and Sarah Frostenson wrote These maps show how Americans are dying younger. It’s not just the opioid epidemic. “Different geographic regions are experiencing extreme variations in despair-related outcomes like suicides, drug overdoses, and heart disease, said Abraham Flaxman of the University of Washington, one of the authors of the new JAMA paper. ‘If you look at geographic patterns, you can say it’s despair that’s leading people to drink and do drugs. But then why wouldn’t that apply to leading people to overeat and become obese and diabetic? These trends are happening in different places.’”
• Agata Blaszczak-Boxe with Live Science wrote Leading causes of death in US vary greatly by region. “The reasons why higher death rates vary across geographic areas are not completely clear, but the authors suggested some ideas. For example, the higher death rates from cardiovascular diseases might have something to do with higher rates of obesity in these areas, said study co-author Christopher J. L. Murray.
• Carolyn Gregoire with the Huffington Post wrote This GIF sums up the impact of addiction and mental illness on America. “In a cluster of counties in Kentucky, West Virginia and Ohio, researchers uncovered striking death toll increases of 1,000 percent or more. Topping the list were Clermont County, Ohio (the site of one of the worst heroin epidemics in the state), which saw a 2,206 percent spike, and opioid-stricken Boone County, West Virginia, with a 2,030 percent increase.”
• (UK) Mia De Graff with the Daily Mail wrote What is the typical cause of death in YOUR county? Incredible maps show leading killers in each region of America. “Where you live determines how you die. That is the conclusion of a new study that lays bare the most common causes of death county-by-county across the United States, and how it has changed since 1980.”
• (UK) Celine Gounder with the Guardian wrote How long will you live? That depends on your zip code. “In an analysis of 80 million deaths in the United States between 1980 and 2014, a study published on Tuesday finds dramatic differences not only in life expectancy, but also in cause of death from county to county. ‘We’re not narrowing the gap. The gap is widening,’ said Christopher JL Murray, one of the authors of the study.”

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2016 Stephen Stewart Gloyd Endowed lecture: Sanjay Basu

Dr. Sanjay Basu gave the 2016 Stephen Stewart Gloyd Endowed lecturer on May 19, 2016. He spoke on the challenges and importance of measuring the health impact of government programs and policies. The Stephen Stewart Gloyd Endowed Lecture was established in 1982 to recognize Dr. Park Willis Gloyd. The lectureship was renamed by the family to recognize Park’s son, Stephen Gloyd, who is the Associate Chair for Education and Curriculum for the UW Department of Global Health, and a professor in Health Services at the School of Public Health.

Sanjay Basu, MD, PhD, is an Assistant Professor of Medicine at Stanford University. He is a primary care physician and an epidemiologist, focusing on the study of how population health is influenced by social and economic programs. Dr. Basu received his education from MIT, Oxford, and Yale, and serves on advisory panels for the United Nations, World Health Organization, the American Heart Association, and the Global Burden of Disease Project. In 2013, he was named one of the “top 100 global thinkers” by Foreign Policy Magazine, and in 2015 he won the New Innovator Award from the Director of the National Institutes of Health. Dr. Basu is the co-author of “The Body Economic: Why Austerity Kills,” which discusses recessions, budget battles, and the politics of life and death.

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