Author Archives: Priyanka Vyas

Interesting crowdsourced applications developed by GIS Corps in response to the pandemic

During the time of pandemic, GISCorps —group of volunteers who contribute in spatial data creation for humanitarian cause —  developed interesting crowdsourced applications and web-mapping applications. These included allowing users to find vaccination sites based on where they live, identify grocery stores that practice social distancing and follow the safety protocol as well as report those that don’t adhere to the guidelines.

Below are some interesting applications developed by GIS Corps:

Here is an example of COVID-19 testing sites, type of site such as drive-through or not and the type of test that is offered.

Here is another example of a crowdsourced app on safety and  customer experience at grocery stores during the pandemic. This is how users can report their overall experience and alert other consumers about the safety protocols followed by the store, waiting time, and information that would help other consumers make a decision about visiting a particular store.


Additional examples of the apps related to COVID-19 can be found here.


Book Review: Steal Like An Artist


As an academic or as someone who enjoys writing to discover new trends and patterns, I view my quest to come up with research ideas as a creative endeavor. I also associate being creative requires an entrepreneurial spirit — with the difference being that a real entrepreneur  invests capital in some form to get returns, while a scientist or a writer has to invest his or her time to come up with ideas that might bear a return or not, depending on whether that research gets funded or whether that idea makes it into a fine editorial piece or not.

If you view that your work requires some degree of creativity, then Steal like An Artist is just a less than 100 pages book that would inspire you to develop some principles in your pursuit of creative ideas. Interestingly, the entire book consists of cartoons/graphics with short notes around different principles that the author recommends.

The three principles that resonated with me the most are:

  1. Start from the mundane to make something extraordinary: Often we are trying to think “outside the box”. But one has to be inside the box first and be able to see things from multiple perspectives before one can step outside the box and see a different paradigm. The book discusses examples of successful artists and painters and singers who first emulated their role models and in the process by doing so, they found their distinct identity.  Drawing a parallel to this, as a researcher or scientist, this could be following an existing method applied by several others in the field; then identifying a flaw in it or a marginal improvement that adds one’s distinct identity and viewpoint, to produce something new.
  1. Go unwired from technology:  I really love this because it is so easy to get swamped in the flood of information at a click of a mouse and multiple tabs open in your browser. As a researcher when I want to come up with new ideas, I like to stay away from screen and draw mind maps around a central theme that I would like to explore. By doing so I am often able to discover what I already know on the topic, or the different areas that I’d like to explore around the topic, and if nothing then at least it gives me a structure around the idea that I need to build on my writing or my search query in Google scholar. Similarly, when I already have a lot of information, I again step back from the screen, and do the same exercise – in this instance, to develop a coherent structure around all the information that I already have and then use my laptop to type it.
  1. Go on a creative date everyday and consistently: All creative work is a pile up of “boring”, “mundane” tasks performed consistently to make something extraordinary. I agree to this by far the most because consistency is the most important principle in writing or solving a problem. There are several days when we feel we are being “unproductive”, but being consistent in working on it is the only way to get a breakthrough. As Woody Allen said that success is about 80 percent just showing up.

Book Review: Geek Heresy: Rescuing Social Change from the Cult of Technology


Why is it that a job posted on LinkedIn is for anyone to apply, but the person who is most likely to get an interview call is someone who either knows the HR or knows someone inside the company who is on his LinkedIn network? Why is it that even though internet is widely available in China, it cannot break the censorship walls built by the Chinese government? Even when technology is available to everyone, why is it that highly motivated individuals use it very differently and for very different purpose then those who are less educated and have very less aspirations in life?

While technology can give equal access to everyone, it cannot replace social access that only few privileged people have, which  guarantees their entry for a job interview after controlling for skills and education. Similarly, without the right political and social institutions, freely available internet access to everyone still does not guarantee access to unbridled information. Or even when technology is available for anyone, the more educated, ambitious, and highly motivated individual will be very discerning in the use of internet for educational purpose as opposed to someone who would use it more for entertainment.  Sounds like common sense, isn’t it? As much as it sounds so obvious, Kentaro’s book is an eye-opener for anyone who believes that technology can be an end in itself in solving certain social problems. Kentaro Toyoma  makes a compelling case that technology cannot have any impact without  nurturing the right political and social institutions; it cannot transform an individual who lacks the right motivation, judgment to make the right choices, and self-discipline and control to follow through the right choices . Though written by a computer scientist, this book is more written from the perspective of ethics and philosophy.

I met Kentaro when I had just started my career as a journalist. Kentaro was heading then Microsoft India Research Foundation where he was involved in interesting initiatives that harnessed technology for social change. The book is based on Kentaro’s experiences in India as a part of Microsoft Research Foundation. It was during this journey that he encountered several non-profits and organizations that were intending to drive social change through the use of technology such as one laptop per child and similar initiatives, but these intentions were not matched with the right outcome.

While the book has numerous examples and case studies of organizations that were successful in harnessing technology along with building human capacity to use it, it falls short to a certain degree on rigorous scientific evidence. Several examples are from education and micro lending space and based on anecdotal evidence based on his personal experiences with these organizations. The book could have been enriched by including more evidence from public health where it is commonly used to target patient adherence to treatment, follow-up plans, using text-based services that are designed to change key behaviors towards reducing the risk of certain diseases.  Despite its shortcoming on rigorous scientific evidence from other fields like public health, the book is well-written, engaging, and drives home some of the fundamental principles that can predict success of a technology based program in transforming social change.

From macro-economists versus micro-economists to macro statisticians versus micro statistician: The gulf between big data and small data scientists

VW -think-small-adsIn the 1950’s and 60’s it was “Think small” ad for Volksgen’s Beatle car that marked a radical shift in an era that was dominated by large cars in the US. For anyone who studied advertising or works in the industry would recall this iconic add – considered as a classic in the field in several ways — but for the most part it created a new way of consumer thinking for the advantages of small cars versus big cars.

Today for someone in the field of data science, “big data” is the buzzword. More and more jobs are emerging in this area. Every day on my LinkedIn, I see several opportunities in this area. So I see the world of data science also facing a similar divide – big data versus small data. While we don’t hear much about small data as much as we hear about the term “big data” as it is more fancy, sexy, and requires highly sophisticated programming skills to model the problem, there are distinct problems and areas of application where each has its own place and utility.

Big data and some of its applications: Big data is associated with machine learning and applying algorithms to extract data from the web to search for pattern and trends based on millions of records. For instance, in text based analysis this would mean web crawling through millions of newspaper articles and editorials through which a computer can identify specific articles that a researcher or analyst is looking for. For a spatial statistician, this could mean employing computer algorithm to extract location information from millions of records about specific events of interest. The world of big data analytics is dominated by computer scientists, statisticians, political scientists interested in studying issues pertaining to conflicts, or public opinion. It is also dominated by companies and industries that are looking to capture consumer behavior and trends. So companies like Amazon and Google can model consumer pattern and forecast demand or decision-making.

Small data and its application: We don’t hear much of the term “small data”, but as a public health and policy professional, I see a lot of problems that need to be addressed in the field of public health, epidemiology, census that require one to deal with counts and small numbers that can be modeled correctly and be used to make valid inferences. This requires domain knowledge of distinct set of statistical models and tools. Organizations where knowledge of small area analysis and estimation would be helpful would be CDC, Census Bureau, and community level program planning and evaluation.

a) Survey methodology: For large scale health and population surveys implemented in developing countries, the sample is representative of the population at a larger regional scale, but often not for small geographic scale. In such a situation small area estimation techniques or interpolation is of interest to make inference about a geographic unit where sampling was not done on specific health outcome.

b) Sentinal Surveillance: This involves surveillance at a specific site or a location for detecting disease outbreaks or new cases of specific diseases. According to WHO sentinel surveillance is appropriate to gather high quality data when passive surveillance system ( generally based on data reported by health workers and health facilities) is not adequate to identify causal factors for certain diseases. However, because data is monitored at specific sites, hospitals, or locations, it may not be appropriate for detecting cases outside of the selected sites.

c) Community based program planning: In case of community and program planning, an application area would be improving a health intervention at a specific site and location. For instance, USAID allocates funds for HIV testing and treatment at specific sites and in several countries. Hence it might be interested in knowing which clinics are doing better in comparison to other clinics. According to the PEPFAR Annual report to the Congress, there exists a wide variation in disease burden and HIV risk at the sub-national level and sub-populations level. Hence, knowledge about distribution of cases around specific sites, uptake in the service utilization can help improve programs. Similarly, AidData, a collaboration between three universities, to track where aid money is going and in which programs by country and by year and based on the type of the project, works in the area of geospatial impact evaluation. Hence, it borrows traditional statistical methods such as difference-in difference and propensity score matching and other methods, but also takes into account site location of the project. It identifies sites where World Bank did not implement a project, thus acts as a control site. By accounting for location of the project implementation site, it considers heterogeneity in program outcomes while conducting impact assessments.

Economics as a discipline has always been demarcated between marco and micro economics. Is it time we divide statistics also as a discipline between macro and micro?

Where is the map, honey?

Last month I attended the International Geocomputation Conference hosted at University of Texas at Dallas. As a health policy researcher with a keen interest in the application of geospatial tools to solve problems related to services delivery and reduce disease burden, I was hoping to hear at least a few examples of what the next big trend would look like with the use of such tools for disease surveillance, preventing disease outbreaks, among others. However, the big trends discussed during the keynote session included applications mostly in the commercial space, while social and development sectors such as health sector trailing far behind. With increasing availability of smart phones, location based services are used commonly to obtain directions, find the nearest restaurant, or the drive time to the nearest clinic and so on. Companies like Uber, ride sharing app and community-traffic management and navigation app Waze have tapped on the location information of individuals.

But how about an app like Waze to know the waiting time and availability of doctors at crowded government or private hospitals in South Asia? Can such an app help a women who is in labor and about to deliver a child go to the right hospital instead of going to a crowded government facility, just to find that there is a long wait time after reaching there.
This is certainly utopian at this point, but it can be a possibility in the future. Health ministries in some countries have started using google map to display their health facility location information.

Here is the google application of BD hospital facilities data:
BD facilities

Brazil health facility search application
:Brazil facilities search

Argentina health ministry displays its health facilities infrastructure:


Several developing countries are using google maps for consumers to visualize health facilities location, type of health facilities, and the drive time to different health facilities However, in order for consumers to find utility with such visualization requires integration with other health indicators such as waiting time, availability of doctors, customer satisfaction rating, and other health infrastructure related indicators. This would help consumers make informed choices with regard to where to go for care. For policy makers, such health facilities data base needs to be integrated with information related to patient catchments i.e where are the patients coming from and for what type of services? Such information can help policy makers plug the gap in the system or identify specific locations or hot spots for certain diseases. There have been small scale initiatives ( in specific parts of some countries), mostly led by researchers and academicians in partnership with government and other institutions, but many of them have not been developed at the national level.
Most efforts to map health disparities, access, inequities come from health geographers and researchers instead of it being driven by the government and the policy planners. Hence the current scenario resembles more of a push rather than a pull strategy. To put it simply, it is more driven by supply from the researchers and academic community than it being a demand driven approach for decision making, where the health planners ask the question, “Where is the map, honey”? And only when health planners start asking such questions and demanding such information, we can expect location information to realize its full potential in the public health domain.

A marriage yet to happen: Donor coordination — from investment front towards intervention

When I took a class in International Development at Duke, one of the lessons I learnt from my Professor, who has been herself a county manager for World Bank for several years, was on donor coordination. While this was a theoretical lesson that I harbored for a few years, it was not until very recently that my own research brought me close to this reality. Lack of donor coordination has long been a buzzword when it comes to prioritizing development investments and strategies, but not much is said about the lack of coordination on the intervention front. Since I have been working on Bangladesh since the past one year, I think it is a fertile battle ground for donors investing in different projects, implementing different interventions, and producing evidence. But what is missing is connecting the dots between these different interventions:

Full vaccination districtsBelow70 districts

For example, in 2006 UNICEF identified about 14 low-performing districts to improve vaccination coverage. In 2007 WHO adopted another 23 districts that it regarded low on certain vaccine indicators. If you look at the above maps, you will see the districts adopted by WHO and those adopted by UNICEF.  Each point on the map represents vaccination coverage for a community-level of 20-30 households has been high or very low  based on the Demographic and Household Survey for Bangladesh, Historically, Sylhet and Chittgong have always had low health indicators because of hilltracts and low-lying areas. And this pattern is also evident on the map. Most of the pockets of communities with below 70 percent vaccination coverage fall in these intervention districts. The good news is that the interventions are targeted in the right geography and most communities with full vaccination coverage are outside these low-performing districts. But what can we say about communities with vaccination coverage between 80 to 90 percent and 90 to 95 percent coverage? There are several pockets of high immunization coverage in these low-performing districts and those which lie outside of these districts.

While WHO and UNICEF have been adopting districts for intervention, the Demographic and Health Surveys — which also provide GPS location data—- provide a classic opportunity to target interventions at the community level . Since district level aggregate data often mask variations in terms of pockets of low coverage and those with high coverage, location information at the community level can be a very useful tool. Unfortunately, despite all the efforts underway to collect spatial data, integrating it as a policy tool among different development agencies seems like a marriage yet to happen!

From a nose for news to cultivating a nose for geography:

As a PhD student in public policy and political economy, often my colleagues who see me working with maps ask, “Are you getting a dual doctorate in GIS (Geographic Information Systems) and Public Policy? I reply “no”. Then someone will counter argue, “But you have taken so many classes in the GIS department? Why don’t you just write their qualifying exam?”. When I still deny my intent to do so, then one of them will ask, “at least you can get a master’s in GIS”. Even during my field work in South Asia last year, few were complete surprised. One of them asked,”What is the connection between social sciences and what you do with GIS?”

So then what explains this transition from being a student of political science and studying government, public administration to my recent focus on theories in geography and my drive to acquire a plethora of tools in spatial analysis? The answer is my nose for news and I still continue to be a journalist at heart. In 2009 I left a glamorous, well-paying job at a leading financial daily in New Delhi to pursue higher education in the US. This also meant sacrificing financial comforts, and the power I could command then as a reporter to starting from scratch and making a humble beginning. Stepping down from a senior reporter’s position to making my entry as an intern and then climbing the ladder again seemed like an arduous job. But looking back 5 years when I left a career in journalism and moved into academia, my love for finding news and a story still remains the same though it now gets reflected more in my research rather than in what used to be daily writing marathons!Back in those days, I used to find news by looking at statistics and data from government reports, auto industry sales reports. Today I look at the maps and models to tell me what is the underlying story.

Full vaccination districtsBelow70 districts

Take a look at the maps I created above. For example, what is the stark observation when you look at the above maps? Isn’t it the east-west immunization divide? Based on the division maps in the top row, one would notice that there is only one dot in the Sylhet region, and couple of dots in the Chittgong . Each dot on the map represents vaccination coverage at the community level ,comprising of 20-30 households based on the Demographic and Health Survey Data for Bangladesh, 2011. On the other hand if one looks at the division map of communities with full vaccination coverage most dots are located in Raungpur, Khulna, and Rajshahi, with few communities in the Dhaka and Barisal division. Similarly, if one looks at the district maps in the bottom row, then one finds certain districts painted in purple. These were hard to reach or low performing districts where UNICEF intervened in 2007 to raise the full vaccination coverage at the national level, according to the EPI coverage evaluation surveys. And those in pink are the 23 districts where WHO launched an intervention and continues to work in these regions. What is the obvious pattern? Most communities with full vaccination coverage are outside these low-performing districts while communities with below 70 percent immunization coverage lie in these hard to reach and low performing areas.

What is the natural question that follows after investigating where are communities with low vaccination coverage? Well, it would be a why question. Isn’t that’s where the story lies? Why is it that these regions have communities with low vaccination and vice-versa. How can I know that without really understanding the geographical context among other aspects of these regions.Development practitioners would say context matters. Geographers say location matters. Anthropologists would term this as culture matters and would view the same issue through the lens of the culture to explain certain patterns in health utilization. Then how is it that what I am doing with geography is very different than what I am doing in public policy? So from cultivating a nose for news for my journalism career to having one for geography to thrive in my academic career, I have proven once again the cliché —- once a journalist always a journalist — to be nevertheless true.

Glimpse of my fieldwork in Bangladesh, May 2014

On the banks of the river Padma. The town of Rajshahi where I visited is located close to the river.

On the banks of the river Padma. The town of Rajshahi where I visited is located close to the river.

En route to different health facilities in an electric rickshaw -- a popular means of transport to go to nearby towns and villages

En route to different health facilities in an electric rickshaw — a popular means of transport to go to nearby towns and villages


This  was a community clinic I visited in Rajshahi

This was a community clinic I visited in Rajshahi



This map was on the wall of the health care center, showing the high risk areas of Malaria and educating women on maternal and child health issues through visual aid

This map was on the wall of the health care center, showing the high risk areas of Malaria and educating women on maternal and child health issues through visual aid

Malaria high risk areas