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    New clean air and water labs to bring together researchers, policymakers to find climate solutions

    MIT’s Abdul Latif Jameel Poverty Action Lab (J-PAL) is launching the Clean Air and Water Labs, with support from Community Jameel, to generate evidence-based solutions aimed at increasing access to clean air and water.

    Led by J-PAL’s Africa, Middle East and North Africa (MENA), and South Asia regional offices, the labs will partner with government agencies to bring together researchers and policymakers in areas where impactful clean air and water solutions are most urgently needed.

    Together, the labs aim to improve clean air and water access by informing the scaling of evidence-based policies and decisions of city, state, and national governments that serve nearly 260 million people combined.

    The Clean Air and Water Labs expand the work of J-PAL’s King Climate Action Initiative, building on the foundational support of King Philanthropies, which significantly expanded J-PAL’s work at the nexus of climate change and poverty alleviation worldwide. 

    Air pollution, water scarcity and the need for evidence 

    Africa, MENA, and South Asia are on the front lines of global air and water crises. 

    “There is no time to waste investing in solutions that do not achieve their desired effects,” says Iqbal Dhaliwal, global executive director of J-PAL. “By co-generating rigorous real-world evidence with researchers, policymakers can have the information they need to dedicate resources to scaling up solutions that have been shown to be effective.”

    In India, about 75 percent of households did not have drinking water on premises in 2018. In MENA, nearly 90 percent of children live in areas facing high or extreme water stress. Across Africa, almost 400 million people lack access to safe drinking water. 

    Simultaneously, air pollution is one of the greatest threats to human health globally. In India, extraordinary levels of air pollution are shortening the average life expectancy by five years. In Africa, rising indoor and ambient air pollution contributed to 1.1 million premature deaths in 2019. 

    There is increasing urgency to find high-impact and cost-effective solutions to the worsening threats to human health and resources caused by climate change. However, data and evidence on potential solutions are limited.

    Fostering collaboration to generate policy-relevant evidence 

    The Clean Air and Water Labs will foster deep collaboration between government stakeholders, J-PAL regional offices, and researchers in the J-PAL network. 

    Through the labs, J-PAL will work with policymakers to:

    co-diagnose the most pressing air and water challenges and opportunities for policy innovation;
    expand policymakers’ access to and use of high-quality air and water data;
    co-design potential solutions informed by existing evidence;
    co-generate evidence on promising solutions through rigorous evaluation, leveraging existing and new data sources; and
    support scaling of air and water policies and programs that are found to be effective through evaluation. 
    A research and scaling fund for each lab will prioritize resources for co-generated pilot studies, randomized evaluations, and scaling projects. 

    The labs will also collaborate with C40 Cities, a global network of mayors of the world’s leading cities that are united in action to confront the climate crisis, to share policy-relevant evidence and identify opportunities for potential new connections and research opportunities within India and across Africa.

    This model aims to strengthen the use of evidence in decision-making to ensure solutions are highly effective and to guide research to answer policymakers’ most urgent questions. J-PAL Africa, MENA, and South Asia’s strong on-the-ground presence will further bridge research and policy work by anchoring activities within local contexts. 

    “Communities across the world continue to face challenges in accessing clean air and water, a threat to human safety that has only been exacerbated by the climate crisis, along with rising temperatures and other hazards,” says George Richards, director of Community Jameel. “Through our collaboration with J-PAL and C40 in creating climate policy labs embedded in city, state, and national governments in Africa and South Asia, we are committed to innovative and science-based approaches that can help hundreds of millions of people enjoy healthier lives.”

    J-PAL Africa, MENA, and South Asia will formally launch Clean Air and Water Labs with government partners over the coming months. J-PAL is housed in the MIT Department of Economics, within the School of Humanities, Arts, and Social Sciences. More

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    M’Care and MIT students join forces to improve child health in Nigeria

    Through a collaboration between M’Care, a 2021 Health Security and Pandemics Solver team, and students from MIT, the landscape of child health care in Nigeria could undergo a transformative change, wherein the power of data is harnessed to improve child health outcomes in economically disadvantaged communities. 

    M’Care is a mobile application of Promane and Promade Limited, developed by Opeoluwa Ashimi, which gives community health workers in Nigeria real-time diagnostic and treatment support. The application also creates a dashboard that is available to government health officials to help identify disease trends and deploy timely interventions. As part of its work, M’Care is working to mitigate malnutrition by providing micronutrient powder, vitamin A, and zinc to children below the age of 5. To help deepen its impact, Ashimi decided to work with students in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) course 6.S897 (Machine Learning for Healthcare) — instructed by professors Peter Szolovits and Manolis Kellis — to leverage data in order to improve nutrient delivery to children across Nigeria. The collaboration also enabled students to see real-world applications for data analysis in the health care space.

    A meeting of minds: M’Care, MIT, and national health authorities

    “Our primary goal for collaborating with the ML for Health team was to spot the missing link in the continuum of care. With over 1 million cumulative consultations that qualify for a continuum of care evaluation, it was important to spot why patients could be lost to followup, prevent this, and ensure completion of care to successfully address the health needs of our patients,” says Ashimi, founder and CEO of M’Care.

    In May 2023, Ashimi attended a meeting that brought together key national stakeholders, including the representatives of the National Ministry of Health in Nigeria. This gathering served as a platform to discuss the profound impact of M’Care’s and ML for Health team’s collaboration — bolstered by data analysis provided on dosage regimens and a child’s age to enhance continuum of care with its attendant impact on children’s health, particularly in relation to brain development with regards to the use of essential micronutrients. The data analyzed by the students using ML methods that were shared during the meeting provided strong supporting evidence to individualize dosage regimens for children based on their age in months for the ANRIN project — a national nutrition project supported by the World Bank — as well as policy decisions to extend months of coverage for children, redefining health care practices in Nigeria.

    MIT students drive change by harnessing the power of data

    At the heart of this collaboration lies the contribution of MIT students. Armed with their dedication and skill in data analysis and machine learning, they played a pivotal role in helping M’Care analyze their data and prepare for their meeting with the Ministry of Health. Their most significant findings included ways to identify patients at risk of not completing their full course of micronutrient powder and/or vitamin A, and identifying gaps in M’Care’s data, such as postdated delivery dates and community demographics. These findings are already helping M’Care better plan its resources and adjust the scope of its program to ensure more children complete the intervention.

    Darcy Kim, an undergraduate at Wellesley College studying math and computer science, who is cross-registered for the MIT machine learning course, expresses enthusiasm about the practical applications found within the project: “To me, data and math is storytelling, and the story is why I love studying it. … I learned that data exploration involves asking questions about how the data is collected, and that surprising patterns that arise often have a qualitative explanation. Impactful research requires radical collaboration with the people the research intends to help. Otherwise, these qualitative explanations get lost in the numbers.”

    Joyce Luo, a first-year operations research PhD student at the Operations Research Center at MIT, shares similar thoughts about the project: “I learned the importance of understanding the context behind data to figure out what kind of analysis might be most impactful. This involves being in frequent contact with the company or organization who provides the data to learn as much as you can about how the data was collected and the people the analysis could help. Stepping back and looking at the bigger picture, rather than just focusing on accuracy or metrics, is extremely important.”

    Insights to implementation: A new era for micronutrient dosing

    As a direct result of M’Care’s collaboration with MIT, policymakers revamped the dosing scheme for essential micronutrient administration for children in Nigeria to prevent malnutrition. M’Care and MIT’s data analysis unearthed critical insights into the limited frequency of medical visits caused by late-age enrollment. 

    “One big takeaway for me was that the data analysis portion of the project — doing a deep dive into the data; understanding, analyzing, visualizing, and summarizing the data — can be just as important as building the machine learning models. M’Care shared our data analysis with the National Ministry of Health, and the insights from it drove them to change their dosing scheme and schedule for delivering micronutrient powder to young children. This really showed us the value of understanding and knowing your data before modeling,” shares Angela Lin, a second-year PhD student at the Operations Research Center.

    Armed with this knowledge, policymakers are eager to develop an optimized dosing scheme that caters to the unique needs of children in disadvantaged communities, ensuring maximum impact on their brain development and overall well-being.

    Siddharth Srivastava, M’Care’s corporate technology liaison, shares his gratitude for the MIT student’s input. “Collaborating with enthusiastic and driven students was both empowering and inspiring. Each of them brought unique perspectives and technical skills to the table. Their passion for applying machine learning to health care was evident in their unwavering dedication and proactive approach to problem-solving.”

    Forging a path to impact

    The collaboration between M’Care and MIT exemplifies the remarkable achievements that arise when academia, innovative problem-solvers, and policy authorities unite. By merging academic rigor with real-world expertise, this partnership has the potential to revolutionize child health care not only in Nigeria but also in similar contexts worldwide.

    “I believe applying innovative methods of machine learning, data gathering, instrumentation, and planning to real problems in the developing world can be highly effective for those countries and highly motivating for our students. I was happy to have such a project in our class portfolio this year and look forward to future opportunities,” says Peter Szolovits, professor of computer science and engineering at MIT.

    By harnessing the power of data, innovation, and collective expertise, this collaboration between M’Care and MIT has the potential to improve equitable child health care in Nigeria. “It has been so fulfilling to see how our team’s work has been able to create even the smallest positive impact in such a short period of time, and it has been amazing to work with a company like Promane and Promade Limited that is so knowledgeable and caring for the communities that they serve,” shares Elizabeth Whittier, a second-year PhD electrical engineering student at MIT. More

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    Urbanization: No fast lane to transformation

    Accra, Ghana, “is a city I’ve come to know as well as any place in the U.S,” says Associate Professor Noah Nathan, who has conducted research there over the past 15 years. The booming capital of 4 million is an ideal laboratory for investigating the rapid urbanization of nations in Africa and beyond, believes Nathan, who joined the MIT Department of Political Science in July.

    “Accra is vibrant and exciting, with gleaming glass office buildings, shopping centers, and an emerging middle class,” he says. “But at the same time there is enormous poverty, with slums and a mixing pot of ethnic groups.” Cities like Accra that have emerged in developing countries around the world are “hybrid spaces” that provoke a multitude of questions for Nathan.

    “Rich and poor are in incredibly close proximity and I want to know how this dramatic inequality can be sustainable, and what politics looks like with such ethnic and class diversity living side-by-side,” he says.

    With his singular approach to data collection and deep understanding of Accra, its neighborhoods, and increasingly, its built environment, Nathan is generating a body of scholarship on the political impacts of urbanization throughout the global South.

    A trap in the urban transition

    Nathan’s early studies of Accra challenged common expectations about how urbanization shifts political behavior.

    “Modernization theory states that as people become more ‘modern’ and move to cities, ethnicity fades and class becomes the dominant dynamic in political behavior,” explains Nathan. “It predicts that the process of urbanization transforms the relationship between politicians and voters, and elections become more ideologically and policy oriented,” says Nathan.  

    But in Accra, the heart of one of the fastest-growing economies in the developing world, Nathan found “a type of politics stuck in an old equilibrium, hard to dislodge, and not updated by newly wealthy voters,” he says. Using census data revealing the demographic composition of every neighborhood in Accra, Nathan determined that there were many enclaves in which forms of patronage politics and ethnic competition persist. He conducted sample surveys and collected polling-station level results on residents’ voting across the city. “I was able to merge spatial data on where people lived and their answers to survey questions, and determine how different neighborhoods voted,” says Nathan.

    Among his findings: Ethnic politics were thriving in many parts of Accra, and many middle-class voters were withdrawing from politics entirely in reaction to the well-established practice of patronage rather than pressuring politicians to change their approach. “They decided it was better to look out for themselves,” he explains.

    In Nathan’s 2019 book, “Electoral Politics and Africa’s Urban Transition: Class and Ethnicity in Ghana,” he described this situation as a trap. “As the wealthy exit from the state, politicians double down on patronage politics with poor voters, which the middle class views as further evidence of corruption,” he explains. The wealthier citizens “want more public goods, and big policy reforms, such as changes in the health-care and tax systems, while poor voters focus on immediate needs such as jobs, homes, better schools in their communities.”

    In Ghana and other developing countries where the state’s capacity is limited, politicians can’t deliver on the broad-scale changes desired by the middle class. Motivated by their own political survival, they continue dealing with poor voters as clients, trading services for votes. “I connect urban politics in Ghana to the early 20th-century urban machines in the United States, run by party bosses,” says Nathan.

    This may prove sobering news for many engaged with the developing world. “There’s enormous enthusiasm among foreign aid organizations, in the popular press and policy circles, for the idea that urbanization will usher in big, radical political change,” notes Nathan. “But these kinds of transformations will only come about with structural change such as civil service reforms and nonpartisan welfare programs that can push politicians beyond just delivering targeted services to poor voters.”

    Falling in love with Ghana

    For most of his youth, Nathan was a committed jazz saxophonist, toying with going professional. But he had long cultivated another fascination as well. “I was a huge fan of ‘The West Wing’ in middle school” and got into American politics through that,” he says. He volunteered in Hillary Clinton’s 2008 primary campaign during college, but soon realized work in politics was “both more boring and not as idealistic” as he’d hoped.

    As an undergraduate at Harvard University, where he concentrated in government, he “signed up for African history on a lark — because American high schools didn’t teach anything on the subject — and I loved it,” Nathan says. He took another African history course, and then found his way to classes taught by Harvard political scientist Robert H. Bates PhD ’69 that focused on the political economy of development, ethnic conflict, and state failure in Africa. In the summer before his senior year, he served as a research assistant for one of his professors in Ghana, and then stayed longer, hoping to map out a senior thesis on ethnic conflict.

    “Once I got to Ghana, I was fascinated by the place — the dynamism of this rapidly transforming society,” he recalls. “Growing up in the U.S., there are a lot of stereotypes about the developing world, and I quickly realized how much more complicated everything is.”

    These initial experiences living in Ghana shaped Nathan’s ideas for what became his doctoral dissertation at Harvard and first book on the ethnic and class dynamics driving the nation’s politics. His frequent return visits to that country sparked a wealth of research that built on and branched out from this work.

    One set of studies examines the historical development of Ghana’s rural north in its colonial and post-colonial periods, the center of ethnic conflict in the 1990s. These are communities “where the state delivers few resources, doesn’t seem to do much, yet figures as a central actor in people’s lives,” he says.

    Part of this region had been a German colony, and the other part was originally under British rule, and Nathan compared the political trajectories of these two areas, focusing on differences in early state efforts to impose new forms of local political leadership and gradually build a formal education system.

    “The colonial legacy in the British areas was elite families who came to dominate, entrenching themselves and creating political dynasties and economic inequality,” says Nathan. But similar ethnic groups exposed to different state policies in the original German colony were not riven with the same class inequalities, and enjoy better access to government services today. “This research is changing how we think about state weakness in the developing world, how we tend to see the emergence of inequality where societal elites come into power,” he says. The results of Nathan’s research will be published in a forthcoming book, “The Scarce State: Inequality and Political Power in the Hinterland.”

    Politics of built spaces

    At MIT, Nathan is pivoting to a fresh new framing for questions on urbanization. Wielding a public source map of cities around the world, he is scrutinizing the geometry of street grids in 1,000 of sub-Saharan Africa’s largest cities “to think about urban order,” he says. Digitizing historical street maps of African cities from the Library of Congress’s map collection, he can look at how these cities were built and evolved physically. “When cities emerge based on grids, rather than tangles, they are more legible to governments,” he says. “This means that it’s easier to find people, easier to govern, tax, repress, and politically mobilize them.”  

    Nathan has begun to demonstrate that in the post-colonial period, “cities that were built under authoritarian regimes tend to be most legible, with even low-capacity regimes trying to impose control and make them gridded.” Democratic governments, he says, “lead to more tangled and chaotic built environments, with people doing what they want.” He also draws comparisons to how state policies shaped urban growth in the United States, with local and federal governments exerting control over neighborhood development, leading to redlining and segregation in many cities.

    Nathan’s interests naturally pull him toward the MIT Governance Lab and Global Diversity Lab. “I’m hoping to dive into both,” he says. “One big attraction of the department is the really interesting research that’s being done on developing countries.”  He also plans to use the stature he has built over many years of research in Africa to help “open doors” to African researchers and students, who may not always get the same kind of access to institutions and data that he has had. “I’m hoping to build connections to researchers in the global South,” he says. More

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    Emma Gibson: Optimizing health care logistics in Africa

    Growing up in South Africa at the turn of the century, Emma Gibson saw the rise of the HIV/AIDS epidemic and its devastating impact on her home country, where many people lacked life-saving health care. At the time, Gibson was too young to understand what a sexually transmitted infection was, but she knew that HIV was infecting millions of South Africans and AIDS was taking hundreds of thousands of lives. “As a child, I was terrified by this monster that was HIV and felt so powerless to do anything about it,” she says.

    Now, as an adult, her childhood fear of the HIV epidemic has evolved into a desire to fight it. Gibson seeks to improve health care for HIV and other diseases in regions with limited resources, including South Africa. She wants to help health care facilities in these areas to use their resources more effectively so that patients can more easily obtain care.

    To help reach her goal, Gibson sought mathematics and logistics training through higher education in South Africa. She first earned her bachelor’s degree in mathematical sciences at the University of the Witwatersrand, and then her master’s degree in operations research at Stellenbosch University. There, she learned to tackle complex decision-making problems using math, statistics, and computer simulations.

    During her master’s, Gibson studied the operational challenges faced in rural South African health care facilities by working with staff at Zithulele Hospital in the Eastern Cape, one of the country’s poorest provinces. Her research focused on ways to reduce hours-long wait times for patients seeking same-day care. In the end, she developed a software tool to model patient congestion throughout the day and optimize staff schedules accordingly, enabling the hospital to care for its patients more efficiently.

    After completing her master’s, Gibson wanted to further her education outside of South Africa and left to pursue a PhD in operations research at MIT. Upon arrival, she branched out in her research and worked on a project to improve breast cancer treatment in U.S. health care, a very different environment from what she was used to.

    Two years later, Gibson had the opportunity to return to researching health care in resource-limited settings and began working with Jónas Jónasson, an associate professor at the MIT Sloan School of Management, on a new project to improve diagnostic services in sub-Saharan Africa. For the past four years, she has been working diligently on this project in collaboration with researchers at the Indian School of Business and Northwestern University. “My love language is time,” she says. “If I’m investing a lot of time in something, I really value it.”

    Scheduling sample transport

    Diagnostic testing is an essential tool that allows medical professionals to identify new diagnoses in patients and monitor patients’ conditions as they undergo treatment. For example, people living with HIV require regular blood tests to ensure that their prescribed treatments are working effectively and provide an early warning of potential treatment failures.

    For Gibson’s current project, she’s trying to improve diagnostic services in Malawi, a landlocked country in southeast Africa. “We have the tools” to diagnose and treat diseases like HIV, she says. “But in resource-limited settings, we often lack the money, the staff, and the infrastructure to reach every patient that needs them.”

    When diagnostic testing is needed, clinicians collect samples from patients and send the samples to be tested at a laboratory, which then returns the results to the facility where the patient is treated. To move these items between facilities and laboratories, Malawi has developed a national sample transportation network. The transportation system plays an important role in linking remote, rural facilities to laboratory services and ensuring that patients in these areas can access diagnostic testing through community clinics. Samples collected at these clinics are first transported to nearby district hubs, and then forwarded to laboratories located in urban areas. Since most facilities do not have computers or communications infrastructure, laboratories print copies of test results and send them back to facilities through the same transportation process.

    The sample transportation cycle is onerous, but it’s a practical solution to a difficult problem. “During the Covid pandemic, we saw how hard it was to scale up diagnostic infrastructure,” Gibson says. Diagnostic services in sub-Saharan Africa face “similar challenges, but in a much poorer setting.”

    In Malawi, sample transportation is managed by a  nongovernment organization called Riders 4 Health. The organization has around 80 couriers on motorcycles who transport samples and test results between facilities. “When we started working with [Riders], the couriers operated on fixed weekly schedules, visiting each site once or twice a week,” Gibson says. But that led to “a lot of unnecessary trips and delays.”

    To make sample transportation more efficient, Gibson developed a dynamic scheduling system that adapts to the current demand for diagnostic testing. The system consists of two main parts: an information sharing platform that aggregates sample transportation data, and an algorithm that uses the data to generate optimized routes and schedules for sample transport couriers.

    In 2019, Gibson ran a four-month-long pilot test for this system in three out of the 27 districts in Malawi. During the pilot study, six couriers transported over 20,000 samples and results across 51 health care facilities, and 150 health care workers participated in data sharing.

    The pilot was a success. Gibson’s dynamic scheduling system eliminated about half the unnecessary trips and reduced transportation delays by 25 percent — a delay that used to be four days was reduced to three. Now, Riders 4 Health is developing their own version of Gibson’s system to operate nationally in Malawi. Throughout this project, “we focused on making sure this was something that could grow with the organization,” she says. “It’s gratifying to see that actually happening.”

    Leveraging patient data

    Gibson is completing her MIT degree this September but will continue working to improve health care in Africa. After graduation, she will join the technology and analytics health care practice of an established company in South Africa. Her initial focus will be on public health care institutions, including Chris Hani Baragwanath Academic Hospital in Johannesburg, the third-largest hospital in the world.

    In this role, Gibson will work to fill in gaps in African patient data for medical operational research and develop ways to use this data more effectively to improve health care in resource-limited areas. For example, better data systems can help to monitor the prevalence and impact of different diseases, guiding where health care workers and researchers put their efforts to help the most people. “You can’t make good decisions if you don’t have all the information,” Gibson says.

    To best leverage patient data for improving health care, Gibson plans to reevaluate how data systems are structured and used in the hospital. For ideas on upgrading the current system, she’ll look to existing data systems in other countries to see what works and what doesn’t, while also drawing upon her past research experience in U.S. health care. Ultimately, she’ll tailor the new hospital data system to South African needs to accurately inform future directions in health care.

    Gibson’s new job — her “dream job” — will be based in the United Kingdom, but she anticipates spending a significant amount of time in Johannesburg. “I have so many opportunities in the wider world, but the ones that appeal to me are always back in the place I came from,” she says. More

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    Frequent encounters build familiarity

    Do better spatial networks make for better neighbors? There is evidence that they do, according to Paige Bollen, a sixth-year political science graduate student at MIT. The networks Bollen works with are not virtual but physical, part of the built environment in which we are all embedded. Her research on urban spaces suggests that the routes bringing people together or keeping them apart factor significantly in whether individuals see each other as friend or foe.

    “We all live in networks of streets, and come across different types of people,” says Bollen. “Just passing by others provides information that informs our political and social views of the world.” In her doctoral research, Bollen is revealing how physical context matters in determining whether such ordinary encounters engender suspicion or even hostility, while others can lead to cooperation and tolerance.

    Through her in-depth studies mapping the movement of people in urban communities in Ghana and South Africa, Bollen is demonstrating that even in diverse communities, “when people repeatedly come into contact, even if that contact is casual, they can build understanding that can lead to cooperation and positive outcomes,” she says. “My argument is that frequent, casual contact, facilitated by street networks, can make people feel more comfortable with those unlike themselves,” she says.

    Mapping urban networks

    Bollen’s case for the benefits of casual contact emerged from her pursuit of several related questions: Why do people in urban areas who regard other ethnic groups with prejudice and economic envy nevertheless manage to collaborate for a collective good? How do you reduce fears that arise from differences? How do the configuration of space and the built environment influence contact patterns among people?

    While other social science research suggests that there are weak ties in ethnically mixed urban communities, with casual contact exacerbating hostility, Bollen noted that there were plenty of examples of “cooperation across ethnic divisions in ethnically mixed communities.” She absorbed the work of psychologist Stanley Milgram, whose 1972 research showed that strangers seen frequently in certain places become familiar — less anonymous or threatening. So she set out to understand precisely how “the built environment of a neighborhood interacts with its demography to create distinct patterns of contact between social groups.”

    With the support of MIT Global Diversity Lab and MIT GOV/LAB, Bollen set out to develop measures of intergroup contact in cities in Ghana and South Africa. She uses street network data to predict contact patterns based on features of the built environment and then combines these measures with mobility data on peoples’ actual movement.

    “I created a huge dataset for every intersection in these cities, to determine the central nodes where many people are passing through,” she says. She combined these datasets with census data to determine which social groups were most likely to use specific intersections based on their position in a particular street network. She mapped these measures of casual contact to outcomes, such as inter-ethnic cooperation in Ghana and voting behavior in South Africa.

    “My analysis [in Ghana] showed that in areas that are more ethnically heterogeneous and where there are more people passing through intersections, we find more interconnections among people and more cooperation within communities in community development efforts,” she says.

    In a related survey experiment conducted on Facebook with 1,200 subjects, Bollen asked Accra residents if they would help an unknown non-co-ethnic in need with a financial gift. She found that the likelihood of offering such help was strongly linked to the frequency of interactions. “Helping behavior occurred when the subjects believed they would see this person again, even when they did not know the person in need well,” says Bollen. “They figured if they helped, they could count on this person’s reciprocity in the future.”

    For Bollen, this was “a powerful gut check” for her hypothesis that “frequency builds familiarity, because frequency provides information and drives expectations, which means it can reduce uncertainty and fear of the other.”

    In research underway in South Africa, a nation increasingly dealing with anti-immigrant violence, Bollen is investigating whether frequency of contact reduces prejudice against foreigners. Using her detailed street maps, 1.1 billion unique geolocated cellphone pings, and election data, she finds that frequent contact opportunities with immigrants are associated with lower support for anti-immigrant party voting.    Passion for places and spaces

    Bollen never anticipated becoming a political scientist. The daughter of two academics, she was “bent on becoming a data scientist.” But she was also “always interested in why people behave in certain ways and how this influences macro trends.”

    As an undergraduate at Tufts University, she became interested in international affairs. But it was her 2013 fieldwork studying women-only carriages in Delhi, India’s metro system, that proved formative. “I interviewed women for a month, talking to them about how these cars enabled them to participate in public life,” she recalls. Another project involving informal transportation routes in Cape Town, South Africa, immersed her more deeply in the questions of people’s experience of public space. “I left college thinking about mobility and public space, and I discovered how much I love geographic information systems,” she says.

    A gig with the Commonwealth of Massachusetts to improve the 911 emergency service — updating and cleaning geolocations of addresses using Google Street View — further piqued her interest. “The job was tedious, but I realized you can really understand a place, and how people move around, from these images.” Bollen began thinking about a career in urban planning.

    Then a two-year stint as a researcher at MIT GOV/LAB brought Bollen firmly into the political science fold. Working with Lily Tsai, the Ford Professor of Political Science, on civil society partnerships in the developing world, Bollen realized that “political science wasn’t what I thought it was,” she says. “You could bring psychology, economics, and sociology into thinking about politics.” Her decision to join the doctoral program was simple: “I knew and loved the people I was with at MIT.”

    Bollen has not regretted that decision. “All the things I’ve been interested in are finally coming together in my dissertation,” she says. Due to the pandemic, questions involving space, mobility, and contact became sharper to her. “I shifted my research emphasis from asking people about inter-ethnic differences and inequality through surveys, to using contact and context information to measure these variables.”

    She sees a number of applications for her work, including working with civil society organizations in communities touched by ethnic or other frictions “to rethink what we know about contact, challenging some of the classic things we think we know.”

    As she moves into the final phases of her dissertation, which she hopes to publish as a book, Bollen also relishes teaching comparative politics to undergraduates. “There’s something so fun engaging with them, and making their arguments stronger,” she says. With the long process of earning a PhD, this helps her “enjoy what she is doing every single day.” More

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    Study finds lockdowns effective at reducing travel in Sierra Leone

    Throughout the Covid-19 pandemic, governments have used data on people’s movements to inform strategies for containing the spread of the virus. In Europe and the United States, for example, contact-tracing apps have used Bluetooth signals in smartphones to alert people when they’ve spent time near app users who have tested positive for Covid-19. 

    But how can governments make evidence-based decisions in countries where such fine-grained data isn’t available? In recent findings, MIT researchers, in collaboration with Sierra Leone’s government, use cell tower records in Sierra Leone to show that people were traveling less during lockdowns. “When the government implemented novel three-day lockdowns, there was a dual aim to reduce virus spread and also limit social impacts, like increased hunger or food insecurity,” says Professor Lily L. Tsai, MIT Governance Lab’s (MIT GOV/LAB) director and founder. “We wanted to know if shorter lockdowns would be successful.”   

    The research was conducted by MIT GOV/LAB and MIT’s Civic Data Design Lab (CDDL), in partnership with Sierra Leone’s Directorate for Science, Innovation and Technology (DSTI) and Africell, a wireless service provider. The findings will be published as a chapter in the book “Urban Informatics and Future Cities,” a selection of research submitted to the 2021 Computational Urban Planning and Urban Management conference. 

    A proxy for mobility: cell tower records

    Any time someone’s cellphone sends or receives a text, or makes or receives a call, the nearest cell tower is pinged. The tower collects some data (call-detail records, or CDRs), including the date and time of the event and the phone number. By tracking which towers a certain (anonymized) phone number pings, the researchers could approximately measure how much someone was moving around.  

    These measurements showed that, on average, people were traveling less during lockdowns than before lockdowns. Professor Sarah Williams, CDDL’s director, says the analysis also revealed frequently traveled routes, which “allow the government to develop region-specific lockdowns.” 

    While more fine-grained GPS data from smartphones paint a more accurate picture of movement, “there just isn’t a systematic effort in many developing countries to build the infrastructure to collect this data,” says Innocent Ndubuisi-Obi Jr., an MIT GOV/LAB research associate. “In many cases, the closest thing we can use as a proxy for mobility is CDR data.”

    Measuring the effectiveness of lockdowns

    Sierra Leone’s government imposed the three-day lockdown, which required people stay in their homes, in April 2020. A few days after the lockdown ended, a two-week inter-district travel ban began. “Analysis of aggregated CDRs was the quickest means to understanding mobility prior to and during lockdowns,” says Michala Mackay, DSTI’s director and chief operating officer. 

    The data MIT and DSTI received was anonymized — an essential part of ensuring the privacy of the individuals whose data was used. 

    Extracting meaning from the data, though, presented some challenges. Only about 75 percent of adults in Sierra Leone own cellphones, and people sometimes share phones. So the towers pinged by a specific phone might actually represent the movement of several people, and not everyone’s movement will be captured by cell towers. 

    Furthermore, some districts in Sierra Leone have significantly fewer towers than others. When the data were collected, Falaba, a rural district in the northeast, had only five towers, while over 100 towers were clustered in and around Freetown, the capital. In areas with very few towers, it’s harder to detect changes in how much people are traveling. 

    Since each district had a unique tower distribution, the researchers looked at each district separately, establishing a baseline for average distance traveled in each district before the lockdowns, then measuring how movement compared to this average during lockdowns. They found that travel to other districts declined in every district, by as much as 72 percent and by as little as 16 percent. Travel within districts also dropped in all but one district. 

    This map shows change in average distance traveled per trip to other districts in Sierra Leone in 2020.

    Image courtesy of the MIT GOV/LAB and CDDL.

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    Lockdowns have greater costs in poorer areas

    While movement did decline in all districts, the effect was less dramatic in poorer, more sparsely populated areas. This finding was to be expected; other studies have shown that poorer people often can’t afford to comply with lockdowns, since they can’t take time off work or need to travel to get food. Evidence showing how lockdowns are less effective in poorer areas highlights the importance of distributing resources to poorer areas during crises, which could both provide support during a particularly challenging time and make it less costly for people to comply with social distancing measures. 

    “In low-income communities that demonstrated moderate or low compliance, one of the most common reasons why people left their homes was to search for water,” says Mackay. “A policy takeaway was that lockdowns should only be implemented in extreme cases and for no longer than three days at a time.”

    Throughout the project, the researchers collaborated intimately with DSTI. “This meant government officials learned along with the MIT researchers and added crucial local knowledge,” says Williams. “We hope this model can be replicated elsewhere — especially during crises.” 

    The researchers will be developing an MITx course teaching government officials and MIT students how to collaboratively use CDR data during crises, with a focus on how to do the analysis in a way that protects people’s privacy.

    Ndubuisi-Obi Jr. also has led a training on CDR analysis for Sierra Leonean government officials and has written a guide on how policymakers can use CDRs safely and effectively. “Some of these data sets will help us answer really important policy questions, and we have to balance that with the privacy risks,” he says. More