@CDCMMWR reminds us that #polio eradication has a ways to go still

Wednesday, March 21, 2018

I tend to follow news related to polio outbreaks pretty closely, as the prospect of eradicating another disease (like we did smallpox) is tantalizing but seems to always be just out of reach. An article in last week's edition of MMWR serves as a sobering reminder that even if we do manage to wipe out wild poliovirus, we still have to contend with collateral in the form of vaccine-derived poliovirus:
Democratic Republic of the Congo has had cases of polio caused by vaccine-derived polioviruses (VDPVs) documented since 2004. The emergence of these VDPVs, which cause paralysis similar to wild polioviruses, can occur where population immunity to poliovirus is suboptimal.
Risk for VDPV emergence in DRC will remain unless population immunity to poliovirus is increased and maintained.
Perhaps I should bet on Guinea worm as the best candidate for the next disease to be eradicated.

#OpenData for surveillance: Flu and fires

Monday, March 19, 2018

I'm always intrigued to see analysts use traditional data (particularly government and/or open data) in novel ways, especially for monitoring or surveillance for health and human rights. Two such analyses crossed my feed last week. The first, a model built by an epidemiological team at the University of Iowa, used CDC influenza surveillance data combined with readings from an IoT-style thermometer called Kinsa to beef up predictions of flu transmission patterns:
Smart devices and mobile apps have the potential to reshape public health alerts and responses, health care industry analysts and researchers told The Bee. Over in San Francisco, for instance, the staff of smart thermometer maker Kinsa were receiving temperature readings that augured the surge of flu patients in emergency rooms there.
Computational researcher Aaron Miller worked with an epidemiological team at the University of Iowa to assess the feasibility of using Kinsa data to forecast the spread of flu. He said the team first built a model using surveillance data from the CDC and used it to forecast the spread of influenza. Then the team created a model where they integrated the data from Kinsa along with that from the CDC.

“We got predictions that were ... 10 to 50 percent better at predicting the spread of flu than when we used CDC data alone,” Miller said. “Potentially, in the future, if you had granular information from the devices and you had enough information, you could imagine doing analysis on a really local level to inform things like school closings.”
Setting aside my own unease with the "wild, wild west" nature of data collection by Internet of Things things, it was nice to see the study authors reinforce the value of CDC surveillance data (and not going the way of Google Flu):
Miller does not think, though, that these new sources of data have yet made the traditional CDC surveillance channels obsolete.

“When it comes to studying things like infectious diseases, the challenge is when we’re just getting things like temperature readings,” Miller said. “Because we’re not working with microbiological specimens, we can’t confirm that what we’re looking at is influenza. ... We went through a number of procedures in the paper to try to validate that what we were looking at influenza, but at the end of the day, we can’t necessarily confirm that.”
Unfortunately, the picture is not nearly as rosy for this analysis of arson in DRC described in the New York Times:
The clashes between the Hema and Lendu communities — on the eastern side of the Ituri province, bordering Uganda — started in December and escalated in early February.

Historically, these distant conflicts have been difficult to analyze. But new technologies allow us to investigate them in close to real time.

I immediately collected active-fire data from NASA — thermal anomalies, or hot spots, that are recorded daily. It showed dozens of fires on the densely forested mountain ridge and along the shoreline of Lake Albert, one of the African Great Lakes between Congo and Uganda.
Google and other online mapping platforms often show only blurry satellite images, or have no location names for remote areas such as the small fishing villages around Lake Albert. This makes it difficult to find places where people live. To deal with this challenge, I exported residential data from the online mapping site Openstreetmap.

I then overlaid the NASA data with this new data in Google Earth to look for recorded fires that were in or near populated places.
The author goes on to explain that they used this data in conjunction with traditional "shoe-leather reporting" to tell the story "in the most powerful and visual way." I have really appreciated that journalists have begun accompanying their reporting with pieces that explain their methodology in detail. One silver lining amid all the tempest over "fake news."

@LancetGH features a Bayesian analysis of nutrition survey data in #Afghanistan

Thursday, March 15, 2018

The current edition of Lancet Global Health features an analysis of health survey data using Bayesian modeling techniques to map nutritional status in the country:
The 2013 Afghanistan NNS is the largest, most comprehensive nutrition assessment of its kind to be done in the country. Designed to be representative at the national and provincial levels, the survey's aim was to provide estimates on various nutritional indicators, including anthropometry, infant and young child feeding, and micronutrient deficiencies, for women, children, adolescent girls, and the elderly in Afghanistan.
The specific objectives of our study were to estimate the district-level prevalence of nutritional status indicators among children (stunting, underweight, or wasting) and women of reproductive age (underweight or short stature) and to understand the major causes of undernutrition in women and children in Afghanistan through exploring a range of individual, household, community, and environmental risk factors.
What was interesting to me about this particular analysis (besides the maps) was the use of Bayesian modeling, which I now understand better after designing this visualization on county-level estimates of teen birth rates based on a Bayesian analysis. In addition to identifying socioeconomic factors correlated with the various nutritional variables of interest, the authors used the Bayesian model to populate a series of chloropleth maps on said variables:

Figure 2: Prevalence of child stunting, wasting, and underweight in districts of Afghanistan

Figure 3: Prevalence of underweight, obese, and overweight in women of reproductive age in districts of Afghanistan

Not surprisingly, nutritional indicators in children were directly related to things like household wealth, food insecurity, and maternal education and literacy. "Linear growth and weight of children younger than 5 years old were independently associated with household wealth, maternal literacy, maternal anthropometry, child age, food security, geography, and improved hygiene and sanitation conditions" - i.e., "children from richer households were taller, weighed more, and were less emaciated." Also not surprisingly, child malnutrition is at "alarming" levels in many areas, particularly those experiencing active conflict:
Districts with alarmingly high wasting prevalence (some exceeded 20%) were in central regions and regions bordering Pakistan, including the east, southeast, and south. The concurrent conflict and insecurity in these regions could be one explanation, particularly since a gradient of child emaciation across wealth status and maternal education was not evident.

Epidemiological miscellany: #PrEP, #gunviolence research, and the Great Recession

Wednesday, March 14, 2018

A couple of interesting tidbits have come across my radar over the last couple of days. The first is a handy new interactive state-level map on PrEP use by AIDSVu:
AIDSVu has released the first-ever interactive state-level maps visualizing a 73 percent increase year over year in persons using PrEP across the U.S. from 2012 to 2016, with 77,120 PrEP users in 2016. PrEP, or pre-exposure prophylaxis, is when people at high risk for HIV take HIV medicine daily to lower their chances of getting infected with HIV. AIDSVu’s maps visualize the growth in PrEP use at the state-level by year, and break down the data by age and sex. These data and maps offer important information and tools to public health officials, policymakers, and researchers to inform efforts to improve PrEP awareness and increase uptake where it is needed most.
The data comes primarily from Gilead:
De-identified, aggregate data were obtained from Source Healthcare Analytics, LLC (SHA) with the support of Gilead Sciences, Inc., and compiled by researchers at the Rollins School of Public Health at Emory University. SHA collects data from over 54,000 pharmacies, 1,500 hospitals, 800 outpatient facilities, and 80,000 physician practices across the U.S. SHA’s dataset contains prescription, medical, and hospital claims data for all payment types, including commercial plans, Medicare Part D, cash, assistance programs, and Medicaid. From this overall sample, AIDSVu presents a subset of data comprising prescriptions for TDF/FTC for PrEP.

There is also this piece in the Atlantic, which highlights a study done on health outcomes impacted by the Great Recession:
For the study, Teresa Seeman, an epidemiologist at UCLA, and her colleagues examined longitudinal data on 4,600 people between the ages of 45 and 84 collected between 2000 and 2012 to look for changes in their blood pressure and fasting blood-sugar levels.

They found that blood pressure increased significantly among all groups during the time period, and blood glucose did too, among certain groups. The authors speculate the reason for the spike was stress—potentially different stressors for different generations. The younger people in the cohort were either unemployed, or those still working were likely wondering how on Earth they would be able to retire. The older people may have owned their own homes and watched the housing market collapse. All of this, they found, likely drove up their stress levels, and blood pressure.

The authors also found that during the recession, many people stopped taking their medications—especially older homeowners, whose major sources of wealth were evaporating. “The evidence suggests that the stresses of the Great Recession took their greatest toll on those who are on medication,” they write—because they may not have been able to afford the drugs anymore.

These findings further confirm what other researchers have seen on a more cellular level: Economic hardship causes stress, and that stress can sneak under the skin, disrupting bodily systems.
The author takes a dig at economist Tyler Cowen, too, which was kind of fun.

Finally, guns are still in the news, despite The Donald having thrown in the towel. It would seem (for the moment, at least) that calls for more research into gun deaths and gun violence have managed to put down roots and put the spotlight on the Dickey Amendment:
The N.R.A. pushed Congress in 1995 to stop the C.D.C. from spending taxpayer money on research that advocated gun control. Congress then passed the Dickey Amendment in 1996, and cut funding that effectively ended the C.D.C.’s study of gun violence as a public health issue.

The result is that 22 years and more than 600,000 gunshot victims later, much of the federal government has largely abandoned efforts to learn why people shoot one another, or themselves, and what can be done to prevent gun violence.

After the Parkland school massacre in Florida last month, lawmakers and gun control experts have demanded that the agency take up the issue of studying gun violence again, arguing that the federal law doesn’t ban such research altogether but prohibits advocacy of gun control.
There is much ink to be spilled on the question of why the NRA and other conservatives feel that research on gun violence "advocates" for gun control - probably along the lines of the confirmation bias phenomenon and how people react when presented with evidence that challenges their cherished beliefs. Methodologically sound research does not "advocate" for anything. But I will leave that to more eloquent commentators. In the meantime, AJPH is working to bridge the research gap by making all of its published work on gun violence open access (it's typically behind a paywall).

@CDCMMWR article shows the #opioid epidemic is only getting worse

Tuesday, March 13, 2018

At the beginning of this month, David Greene interviewed Surgeon General Jerome Adams on NPR's Morning Edition about the opioid summit that was to be held later that day. It is always interesting to me to listen to serious public health officials do what I imagine to be a slightly painful dance in public interviews - communicate important messages while staying within partisan lines and painting the current administration with sunshine-and-daisy brush strokes. (Current CDC director Anne Schuchat is masterful at this.) I can only imagine what that was like for Dr. Adams, although he got plenty of experience managing Indiana's HIV outbreak under Pence while the latter was governing Indiana, including (by some miracle) persuading him to allow syringe exchange programs to operate. At any rate, during the interview, he pointed out something which even I did not realize. It turns out that America does not take our opioid problem seriously:
No. 1 we want America to understand this is a problem. And I'm an avid NPR listener, so I can speak from that point of view and tell you that a lot of your listeners may not believe that America doesn't see this as a problem. But the majority of the public does not see the opioid epidemic as rising to the level of an emergency. So it's important that we continue to say at the highest levels this is a problem in all communities, and it's getting worse.
I suppose I shouldn't be surprised, but every once in a while I forget that I live in an epi bubble. But in case anyone was wondering, last week's MMWR confirms that the opioid epidemic is getting worse:
From July 2016 through September 2017, a total of 142,557 ED visits (15.7 per 10,000 visits) from 52 jurisdictions in 45 states were suspected opioid-involved overdoses. This rate increased on average by 5.6% per quarter. Rates increased across demographic groups and all five U.S. regions, with largest increases in the Southwest, Midwest, and West (approximately 7%–11% per quarter). In 16 states, 119,198 ED visits (26.7 per 10,000 visits) were suspected opioid-involved overdoses. Ten states (Delaware, Illinois, Indiana, Maine, Missouri, Nevada, North Carolina, Ohio, Pennsylvania, and Wisconsin) experienced significant quarterly rate increases from third quarter 2016 to third quarter 2017, and in one state (Kentucky), rates decreased significantly. The highest rate increases occurred in large central metropolitan areas.

#OpenData highlights: Power lifting and more brain scans

Wednesday, March 7, 2018

The Data is Plural newsletter seems to have a thing for medical image databases (or at least an easy time finding them). This week's edition features another brain scan database, as well as a data set on power lifting:
More brain scans. Last year, the Stanford Center for Reproducible Neuroscience launched OpenNeuro, “a free and open platform for analyzing and sharing neuroimaging data.” (It’s the successor to the center’s earlier initiative, OpenfMRI.) You can, for instance, download scans of brains that were watching a particular episode of The Twilight Zone. Related: The Brain Imaging Data Structure, “a simple and intuitive way to organize and describe your neuroimaging and behavioral data.” Previously: The Open Access Series of Imaging Studies (DIP 2017.08.16).

Powerlifting. OpenPowerlifting.org “aims to create a permanent, accurate, convenient, accessible, open archive of the world's powerlifting data. In support of this mission, all of the OpenPowerlifting data and code is available for download in useful formats.” So far, that includes 400,000+ performances at 9,000+ competitions in dozens of countries.

#OpenData highlights: #WarandPeace and Radiation

Friday, March 2, 2018

This week's Data is Plural newsletter features two data sets that are of interest to those who work on health in conflict zones, as well as one on the EPA's radiation monitoring system.
Peace agreements. The PA-X Peace Agreements Database contains structured information about 1,500+ “formal, publicly-available documents” that address “conflict with a view to ending it.” The database covers more than 140 peace processes between 1990 and 2015, and each agreement has been coded for more than 200 variables — for instance, whether the agreement contains provisions about religious groups.

Historical battles. Political scientist Jeffrey Arnold has converted the U.S. Army Concepts Analysis Agency (CAA) Database of Battles from a series of Lotus 1-2-3 worksheets into tidier, easier-to-use CSV files. The dataset includes details of 660 battles — associated with several dozen wars — between 1600 and the mid/late-1900s. The fields indicate each battle’s “name, date, and location; the strengths and losses on each side; identification of the victor; temporal duration of the battle,” and more.

American radiation. The Environmental Protection Agency’s RadNet system“monitors the nation's air, precipitation and drinking water for radiation.” The radiation measurements, collected from 130+ stations in all 50 states plus the District of Columbia and Puerto Rico, are available on a “near-real-time” basis. Related: Randall Munroe’s radiation dose chart. Previously: SafeCast (DIP 2016.02.03).

At long (long, long) last: the APHA @ih_section's #GlobalHealth Jobs Analysis has been published!

Wednesday, February 28, 2018

Ah, sweet victory. The Global Health Jobs Analysis project that I spearheaded has finally been published in BMC Public Health. The project, which came to me as a completely insane idea at the end of the 2015 APHA Annual Meeting in Chicago, was done over the course of about eighteen months by a group of dedicated volunteers who collected, entered, and analyzed data completely outside of their day jobs. All publications, as well as a link to an up-to-date data repository, are listed on the project page linked above. Here is the abstract:
The number of university global health training programs has grown in recent years. However, there is little research on the needs of the global health profession. We therefore set out to characterize the global health employment market by analyzing global health job vacancies.

We collected data from advertised, paid positions posted to web-based job boards, email listservs, and global health organization websites from November 2015 to May 2016. Data on requirements for education, language proficiency, technical expertise, physical location, and experience level were analyzed for all vacancies. Descriptive statistics were calculated for the aforementioned job characteristics. Associations between technical specialty area and requirements for non-English language proficiency and overseas experience were calculated using Chi-square statistics. A qualitative thematic analysis was performed on a subset of vacancies.

We analyzed the data from 1007 global health job vacancies from 127 employers. Among private and non-profit sector vacancies, 40% (n = 354) were for technical or subject matter experts, 20% (n = 177) for program directors, and 16% (n = 139) for managers, compared to 9.8% (n = 87) for entry-level and 13.6% (n = 120) for mid-level positions. The most common technical focus area was program or project management, followed by HIV/AIDS and quantitative analysis. Thematic analysis demonstrated a common emphasis on program operations, relations, design and planning, communication, and management.

Our analysis shows a demand for candidates with several years of experience with global health programs, particularly program managers/directors and technical experts, with very few entry-level positions accessible to recent graduates of global health training programs. It is unlikely that global health training programs equip graduates to be competitive for the majority of positions that are currently available in this field.
BMC series journals are all open access, so the full paper is available on the web and as a PDF download.

This was quite the learning experience for me - almost a baptism by fire into the peer review process. I suppose it is a taste of what is to come when I begin my PhD in epidemiology at U Maryland's School of Public Health this fall(!). I also hear that it is considered bad juju in academia to go into the gory details of the peer review exchange (unless your reviewers are blatantly sexist), so I'll refrain for the moment.

More important than certain people's conclusions that descriptive analyses aren't worthy of publication is the fact that now there is an evidence base for what has long been anecdotally known by anyone who has ever tried to get a job in the global health field (or international development more broadly). The TL;DR version of the paper is there aren't enough jobs for MPH grads, and - based on the continued growth of global public health programs - nobody seems to be communicating that to prospective students who are looking down the barrel of a 50+K-student-loan-debt gun. Based on my reading of the literature, it looks like schools of public health have been leveraging the popularity of global health in the media to bring in more students:
Driven by global pandemics such as HIV, increased foreign aid budgets from the U.S. and other high-income nations, the emergence of new multilateral institutions and NGOs such as the Gates Foundation, and increasing prioritization of country ownership of health programs, both the politics and the funding structure of global health work have shifted. Global health has also experienced increased levels of attention and funding. Interest among students in high-income countries has increased as well, as evidenced by the impressive growth in the number of global health graduate programs.
This looks a whole lot like the law school crisis that hit headlines about five years ago:
Ninety-two percent of 2007 law school graduates found jobs after graduation, with 77 percent employed in a position requiring them to pass the bar. For the class of 2011 (the latest class for which there are data), the employment figure is 86 percent—with only 65 percent employed in a position that required bar passage. Preliminary employment figures for the class of 2012 are even worse. The median starting salary has declined from $72,000 in 2009 to $60,000 in 2012. A while back, the Bureau of Labor Statistics estimated that 218,800 new legal jobs would be created between 2010 and 2020. As law professor Paul Campos points out, because law schools graduate more than 40,000 students per year, those jobs should be snapped up by 2015—leaving only normal attrition and retirement spots left for the classes of 2016 to 2020. Meanwhile, tuition has increased dramatically over the last several decades.
For the record, we got lucky and managed to land a very thoughtful and thorough editor at BMC, who recommended that we share the results through CUGH and other avenues. I fully plan to do so to the extent I can (while still keeping my day job).

@NASTAD launches a website to help PLWHA find health insurance that covers #PrEP

The National Association for State and Territorial AIDS Directors (NASTAD) has a launched a website, PrEPcost.org, to help those interested in PrEP navigate the health insurance marketplace. It was featured in the New England AIDS Education and Training Center's "In Brief" newsletter last week:
Although most health insurance plans in the U.S. now cover PrEP, out-of-pocket costs can be a barrier to use for many persons. To address this concern, NASTAD recently developed PrEPcost.org – an online tool to help people find the most affordable health insurance plans available through the individual marketplace for PrEP coverage. According to NASTAD, the PrEPcost tool assesses how the PrEP medication is covered in different plans, and applies income-based savings to monthly premiums for each plan. “It then calculates out-of-pocket expenses for the clinical visits, labs, and the medication, and it applies the manufacturer’s co-pay card to that estimate.”
Here is the YouTube video explainer:

Legal #epidemiology of #HIV in sub-Saharan Africa: How different colonial legacies impact HIV rates in women

Tuesday, February 27, 2018

A recent paper set to be published in the American Economic Review presents an incredibly fascinating analysis on the differences in HIV rates among women in different countries in Africa (the only region in the world where more women than men are living with HIV). The paper finds a significant difference in female HIV rates between countries using a common law system (the legal tradition of the UK) and countries using a civil law system (the tradition of continental Europe), according to each country's colonial legacy (i.e., which European country originally colonized them). My former colleague Mark Leon Goldberg, who featured the paper on his website, UN Dispatch, explains:
The legal traditions mostly developed separately from each other for centuries. This includes how these different legal systems approached property rights for women in general and married women in particular.

In the common law tradition married women did not have any property rights independent from their husbands. That changed in the late 1800s, when the U.K adopted the “Married Women’s Property Act” which allowed married women to own their own separate property in some circumstances. But if the marriage ended by death or divorce, the woman did not have any right to any common property. The civil tradition, by contrast, presumed that married couples owned property jointly, and upon the dissolution of the marriage the woman would be entitled to an equal share.
The paper elaborates on the differences between male and female transmission routes in these countries and explains the epidemiological theory behind them:
The vast majority of HIV infection in Sub-Saharan Africa is through unprotected heterosexual contact (UNAIDS). Male HIV rates on the continent have been linked to high-risk cultural patterns; chief among them traditionally liberal attitudes towards the sexual activity of men. Multiple sexual partners, and both pre-marital and extra-marital sexual activity, is widely tolerated and in some cases even expected.

The high endemic areas are also characterised by disproportionately higher HIV rates for young women relative to their male counterparts. The WHO, the UN, and the World Bank have conjectured that gender inequality plays an important causal role in this ‘feminization’ of the disease. Accordingly, policy has shifted to altering power relations within households, since more than 80% of HIV positive women in Sub-Saharan Africa were infected through their spouse (UNAIDS).
The author then goes on to explain how the existence of women's legal property rights allow women to leverage them to negotiate safer sex practices with a potentially infected spouse:
Property regimes allowing women to leave marriage with a significant share of household assets...can increase female sexual autonomy, even if never exercised. Conversely, regimes limiting women’s control to assets brought to the marriage and to assets acquired personally, limit female power to negotiate sexual interaction with husbands, hence raising female vulnerability to infection. ...women in these countries are more likely to rely on contraception methods that do not require negotiations with their partners, but also do not reduce their risk of contracting HIV, such as injections, the pill, and IUDs. By contrast, women in civil law countries are more likely to use contraception techniques that reduce their chances of contracting HIV, but also require compliance from their partner, such as condoms, abstinence, and the withdrawal method.

#OpenData highlights: #Rohingya refugees, disaster recovery, and fire safety

Friday, February 23, 2018

I have just returned from a trip to Beijing to see my sister who lives there (and to meet my nephew, who was born there last July), so I have some catching up to do. The two most recent additions to the Data is Plural newsletter archive have featured health-related data sets. The Valentine's Day/Ash Wednesday edition included data sets on disaster recovery in Nepal after the 2015 earthquake, as well as data on fire safety in the UK:
Nepal, post-earthquake. In April 2015, the Ghorkha Earthquake killed more than 8,000 people in Nepal, and destroyed hundreds of thousands of homes. In early 2016, a team led by the not-for-profit Kathmandu Living Labs, in collaboration with Nepal’s government, undertook “ a massive household survey using mobile technology to assess building damage in the earthquake-affected districts.” The responses to that survey are now available at the 2015 Nepal Earthquake Open Data Portal; you can explore the data online or download it in bulk. In all, the datasets include details on millions of individuals, plus information about each surveyed household and building.

UK fire stats. The United Kingdom’s Home Office publishes dozens of fire-safety related datasets, including aggregate statistics on response times, smoke alarms, and fire department staffing; incident-level data on appliance fires, vehicle fires, and fatalities; and much more. Of the 100,000+ domestic appliance fires reported over a six-year span, 52% were believed to have been caused by a “cooker incl. oven,” 11% by a “grill/toaster,” 2% by dishwashers, and just over 1% by deep-fat fryers.
This week's edition included a data set on Rohingya refugee settlements in Bangladesh:
Rohingya refugees. The Humanitarian Data Exchange has collated dozens of datasets related to the Rohingya refugee crisis. Among them: the geographic boundaries of Rohingya refugee settlements in Bangladesh, the numbers of refugees living in those settlements, and the infrastructure available there.

@LancetGH examines the "collision" of #HIV and chronic disease (among other things)

Friday, January 26, 2018

The first thing that caught my eye in the February edition of Lancet Global Health was an article on the prevalence of COPD among persons living with HIV. The issue of care and treatment of non-communicable diseases among PLWH has become increasingly important as HIV itself has transitioned from a life-threatening condition to a chronic disease to be managed. However, what I found interesting about this particular meta-analysis was that its aim was to assess the hypothesis that HIV infection itself makes people more likely to develop COPD, even when controlling for tobacco use:
Results from several original observational studies and narrative reviews have suggested that the prevalence of chronic obstructive pulmonary disease (COPD) would be increased in people with HIV and even higher than in the general population. Findings from studies with similar designs also suggested an association between HIV infection and COPD.
Using strong and robust statistical methods, we found an association between HIV and COPD, even after adjustment for tobacco consumption, the leading risk factor for COPD. We have also shown a high prevalence of COPD in HIV-positive individuals. We identified three factors favouring an increase in the prevalence of COPD among HIV-positive people: tobacco consumption (a common factor between people with HIV and the general population), the presence of a detectable HIV viral load (in HIV-positive people only), and country level of income. We found that the prevalence of COPD in HIV-positive people increased with the level of income of the country.
Interestingly, the accompanying commentary also pointed out that, while the highest HIV burden is borne by LMICs, there were very few studies based on such countries that were robust enough to be included:
Although most of the included studies were done in high-income countries in Europe and North America, most of the people with COPD and HIV live in LMICs. Only four of the included studies were done in Africa, the WHO region with the most people living with HIV. This finding is similar to what we found in 2013, when we did a systematic review of COPD studies in sub-Saharan Africa and found only one high quality prevalence study. This Burden of Obstructive Lung Disease (BOLD) study was done in South Africa and found a high prevalence of COPD: 22% of men and 17% of women. Taken together, these observations highlight an important imbalance between where this kind of research is done and where the need is greatest.
The journal issue contains a number of other tasty morsels as well. I thought this piece on indigenous languages as a factor in access to care was particularly interesting, as well as this one on "equitable access" to (unpaid) WHO internships (and boy, do I have a soapbox about that). One contributor from Stanford even held up a mirror to the journal, analyzing the geographic focus and authorship of all of its articles to assess its progress toward its stated aim to represent “disadvantaged populations” in health-related scenarios around the world:
From all 236 articles, only about 35% (SD=0·31) of the authors were affiliated with or came from LMICs. Articles on Africa had 44% (SD=0·28) LMIC authorship, south Asia had 52% (SD=0·29), southeast Asia had 56% (SD=0·35), and the Middle East and north Africa had 28% (SD=0·33). The Americas had 33% (SD=0·41). Multiregional articles had 17% (0·24) LMIC authorship.

The apparent under-representation of authors from LMICs contributing to articles focusing on LMICs highlights several issues. These include so-called safari research that recruits LMIC specialists, with minimum involvement, into studies driven by high-income-country authors for perceived credibility, the scarcity of grants in LMICs, low awareness of fee waivers within open access journals, insufficient infrastructure for large-scale studies of high impact, and not enough funding directly to academic institutions in LMICs.
It is worth pointing out that even awareness of open access fee waivers does not make them easy to get. In my efforts to get a paper on the IH Section's global health jobs analysis published in BMC Public Health, I engaged in a snarky exchange with the waivers department to explain (repeatedly) that we were volunteers and not part of an academic institution - and didn't get the waiver until I publicly called them out on Twitter. I can't imagine being in a situation like that and trying to make my case in a language that is not my own.

However, my favorite bit by far came from a commentary piece on an outcomes assessment of a healthcare "social franchise" (whatever the heck that is) in Uttar Pradesh. The author throws some not-so-subtle shade toward aid-funded projects and their reticence to rigorously evaluate their own effectiveness:
More importantly, and perhaps inadvertently, the study has shed light on more fundamental questions: why has social franchising as a model expanded at an exponential rate when there was little rigorous evidence of the model's impact on population health? Why have millions of dollars, often taxpayer money, been poured into an unproven idea? Why is there a paucity of rigorous research in documenting effectiveness of this heavily invested idea?

Perhaps the last question might be the easiest to answer. [...] The remit of major bilateral donors is to provide services that will directly improve the health of recipient populations. They are not in the business of research. Consequently, most donors limit their data collection activities to before and after surveys under the rubric of evaluation. They tend to be averse to funding data collection from control sites where their programme was not implemented.

Additionally, bilateral donors, as custodians of taxpayer money, operate in environments characterised by structural disincentives to acknowledge when programme efforts are not achieving their intended results.

Using satellite data to predict cholera outbreaks

Thursday, January 25, 2018

I came across a nifty piece in Scientific American this week about a group of scientists whose algorithm to predict inland cholera outbreaks was unexpectedly proven to be accurate:
Quickly collecting ground data about [cholera epidemics] can be challenging, especially in chaotic locations. Yemen is a textbook case. “Yemen has massive civil unrest, people are moving around, [there is] political instability—there’s no way for us to get a single data point,” Jutla says. But satellites gave his team a way to assess the disease risk from the sky, and without being in the country.

At the American Geophysical Union annual meeting in December, Jutla presented the group’s prediction model of cholera for Yemen. The team used a handful of satellites to monitor temperatures, water storage, precipitation and land around the country. By processing that information in algorithms they developed, the team predicted areas most at risk for an outbreak over the upcoming month.

Weeks later an epidemic occurred that closely resembled what the model had predicted. “It was something we did not expect,” Jutla says, because they had built the algorithms—and calibrated and validated them—on data from the Bengal Delta in southern Asia as well as parts of Africa.
It's important to keep in mind that just because the model got this instance correct does not mean there is not room for improvement. However, it seems to have support from other experts:
“One of the things I like,” says Michael Wimberly, an ecologist at South Dakota State University, is that they are not looking “only at correlation to rainfall.” ...He says the cholera model is well grounded in hydrology and epidemiology. “They have an understanding of different types of epidemics that occur in different seasons; it’s very sophisticated."

#OpenData Highlights: Air pollution in London

Wednesday, January 24, 2018

Last week's edition of Data is Plural featured a data set on air pollution in London:
London air pollution. The London Air Quality Network, run by researchers at King's College London, gathers data on levels of nitrogen dioxide, ozone, fine particulate matter, and other pollutants from more than 100 monitoring sites. You can download the data as CSV files (for up to six metric and site combinations at a time) or fetch JSON and XML data from the site’s API. Related: London air pollution live data – where will be first to break legal limits in 2018? ” (The Guardian). Previously: Air quality data from the EPA (DIP 2017.10.04), OpenAQ (DIP 2017.03.29), Berkeley Earth (DIP 2017.03.22), and the World Health Organization (DIP 2016.06.15).
Air quality data "across the pond" here at home was featured last year. I like that I get to see some repeat themes in these newsletters, including medical image scans, foodborne illness, and air and water quality.

Last week in @CDCMMWR: #HIV among PWID in the US and young women in Africa

Monday, January 15, 2018

This week's edition of MMWR features two analyses on HIV. The first is on infection prevalence and risk among persons who inject drugs in 20 U.S. cities. The data comes from the National HIV Behavioral Surveillance system:
In 2015, National HIV Behavioral Surveillance found a 7% prevalence of HIV infection among persons who inject drugs which was lower than in 2012 (11%). Among HIV-negative respondents, 27% reported sharing syringes and 67% reported having vaginal sex without a condom in the previous 12 months; only 52% received syringes from a syringe services program and 34% received all syringes from sterile sources. HIV infection prevalence was higher among blacks (11%) than whites (6%) but more white persons who inject drugs shared syringes (white: 39%; black: 17%) and injection equipment (white: 61%; black: 41%) in the previous 12 months.
What I find interesting is that the prevalence of unsafe injection practices is so much higher among whites than blacks, although this may be related to there being so many new white PWID due to the opioid crisis (i.e., more black PWID have been injecting for longer). What does not surprise me, sadly, is that so few PWID were able to access sterile syringes from a syringe exchange program (SEP). Even after Congress lifted the federal funding ban on SEPs, states and other jurisdictions have been reluctant to operate them.

The second article (which boasts a jaw-dropping 82 co-authors from 22 institutions) reports HIV status and treatment cascade metrics for women aged 15-24 in seven countries in eastern and southern Africa:
Analysis of data from Population-based HIV Impact Assessment surveys conducted during 2015–2017 in seven countries in Eastern and Southern Africa found that the prevalence of HIV infection among adolescent girls and young women was 3.6%. Among those who were HIV-positive, 46.3% reported being aware of their status, and among those aware of their HIV-positive status, 85.5% reported current antiretroviral treatment (ART) use. Overall, viral load suppression among HIV-infected adolescent girls and young women, regardless of status awareness or current use of ART, was 45.0%, well below the UNAIDS target of 73%.
While low levels of awareness of status and viral suppression are pretty depressing, I was encouraged to see that so many who are aware of their infection are on ART. I was also fascinated to learn that the PHIA survey used is funded by PEPFAR:
The PHIA surveys are nationally representative, household-based surveys funded by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) and conducted under the leadership of the respective countries’ ministries of health, CDC, and ICAP at Columbia University). The objectives of the PHIA surveys are to provide national estimates of HIV incidence and subnational estimates of HIV prevalence and viral load suppression to assess the HIV epidemic and the impact of HIV prevention and ART programs in each country. During 2015–2017, PHIA surveys were conducted in Lesotho, Malawi, Swaziland, Uganda, Tanzania Zambia, and Zimbabwe.
Also super cool: the survey takers conduct HIV, CD4, and viral load testing on the spot:
The surveys included home-based HIV counseling and testing conducted in private locations within or around the home, using each country’s national HIV rapid testing algorithm, and employing CD4 testing technology, with results immediately returned to participants. Awareness of HIV status and current ART use (an indicator of ART coverage at the population level) were determined based on responses provided in the survey questionnaire. HIV viral load testing was conducted using plasma specimens or dried blood spots.

@CDCgov researchers report increases in HCV infection and #opioid admissions in @AMJPublicHealth

Friday, January 12, 2018

Just before Christmas, researchers from the CDC's Division of Viral Hepatitis published an article in the American Journal of Public Health reporting an increase in both acute hepatitis C (HCV) cases and admissions for injection drug use in substance abuse treatment centers:
The annual incidence rate of acute HCV infection increased more than 2-fold (from 0.3 to 0.7 cases/100 000) from 2004 to 2014, with significant increases among select demographic subgroups. Admissions for substance use disorder attributed to injection of heroin and prescription opioid analgesics increased significantly, with an almost 4-fold increase in prescription opioid analgesic injection. Significant increases in opioid injection mirrored those for reported cases of acute HCV infection among demographic subgroups.
CDC featured the article, along with several related graphics, in a press release. As a side note, HCV infection is considered a highly reliable proxy for injection drug use, although I would advise caution when looking at "acute" HCV figures. HCV infection is frequently asymptomatic (i.e., not acute), and surveillance for acute cases is spotty in some states. Overall HCV infection rates are most likely much higher, however, meaning that these numbers point to what is most likely a much larger overall infection rate.

The authors used national surveillance data for HCV infection and substance use treatment data from SAMHSA for IDU admissions:
We obtained confirmed cases of acute HCV infection and associated demographic and risk characteristics from the National Notifiable Disease Surveillance System (NNDSS) for 2004 to 2014.
TEDS is a national data system administered by SAMHSA. It collects information on annual admissions to SUD treatment facilities in the United States. TEDS contains data on admissions to publicly funded and state-certified SUD treatment facilities by year and by state of treatment facility for all persons aged 12 years or older. By state law, treatment facilities provide data to TEDS. TEDS is estimated to include 67% of all SUD treatment admissions and 83% of TEDS-eligible admissions in the United States.
Despite limitations of the data, this should add to the list of rather loud alarm bells that we have a serious injection drug use problem. HIV looms.

Interestingly, the same issue of AJPH featured a commentary on the national opioid crisis, co-authored by HIV/IDU heavyweight Daniel Ciccarone at UCF. After a brief historical overview that separates the crisis into three phases, the piece criticizes what it calls the "vector model" - the focus on supply of opioid prescription drugs as the root of the crisis - and argues that appropriate policy responses should instead consider the reasons behind the demand for such drugs. The authors present several related possiblities to explain demand, including "diseases of despair" and the structural aspects of poverty:
The “reversal of fortunes” in life expectancy saw rapid diffusion, going from largely limited to Appalachia and the Southwest in 2000 to nationwide by 2015. The unprecedented 20-year difference in life expectancy between the healthiest and least healthy counties is largely explained by socioeconomic factors correlated with race/ethnicity, behavioral and metabolic risk, and health care access. These indicators are the most recent evidence of a long-term process of decline: a multidecade rise in income inequality and economic shocks stemming from deindustrialization and social safety net cuts. The 2008 financial crisis along with austerity measures and other neoliberal policies have further eroded physical and mental well-being.
It's an excellent piece that looks at the data on structural factors behind other forms of substance use (e.g., alcoholism), issues of racism, and the inability of the current U.S. health care system to adequately address the problem. It urges a human-centered approach to the problem and says that we should "focus on suffering."

More #opendata highlights: @CDCgov's 500 Cities project!

Thursday, January 11, 2018

The 500 Cities project was featured in Data is Plural this week!
Local health metrics.The CDC’s 500 Cities Project provides “city and census tract-level data, obtained using small area estimation methods, for 27 chronic disease measures for the 500 largest American cities.” The metrics range from cancer prevalence to binge drinking to dental health to undersleeping. The latest data release was published in December and covers more than 28,000 Census tracts.
I'm irrationally excited about this initiative and the potential for discovery in the data. So much so that I mentioned it in an upcoming installment of an open data series I am working on for Cadence Group.

#Opendata highlights: Mammographies

Tuesday, January 9, 2018

The very last edition of Data is plural in 2017 featured an improved database of mammographies, overhauled by researchers at Stanford:
A better mammography database. The Digital Database for Screening Mammography was first released two decades ago, in 1997. It contains data and images from 2,620 mammographies — a mix of normal, benign, and malignant cases. In a Scientific Data article published last week, a team of Stanford University researchers describe a series of improvements they’ve made to the original database; their Curated Breast Imaging Subset of DDSM has modernized the database’s image formatting, added detailed “region-of-interest” annotations, and converted the metadata into CSV files.
This one hit home for me because my mother's sister goes in for surgery today for a lump they found in her mammary duct. Va com Deus, Tia.