Session 4: 4:00 PM - 5:15 PM

Panel A: The Science of Decision-Making: Understanding the Role of Data in International Development

C104 Hesburgh Center

Moderated by Thomas Mustillo

Before implementing novel practices and medicine, they must be tested to decipher any possible flaws. These panelists discuss the importance of data and its use in determining safe and effective health care environments.

Data Driven Health Governance

Fardad Muhammad Baig, University of Massachusetts Amherst

Abstract: The Primary Health and Nutrition Program in Pakistan aims to strengthen health system and improve health services in Pakistan. In Khyber Pakhtunkhwa, Primary Health Care Roadmap has been implemented to improve critical indicators such as medical staff presence, medicine availability and equipment functionality in more than 1500 Basic Health Units geared towards primary health care. The study shows that through use of android apps for monitoring health facilities, these indicators improved more than 20% from the baseline. The study is a secondary research of the data available from the health department. Monthly data tracks the progress on each critical indicator and clearly shows the improvement. This study is a clear indicator of a positive result of interventions that aim to improve governance in government run health systems where data from the periphery takes time to reach the center. Through the implementation of such programs, health services can improve that will benefit the public at large.

Bio: Fardad Is a Public Health major at the University of Massachusetts, Amherst. On campus, he is a member of the Pakistani Student Organization, the School of Public Health, and Rang Acapella. He is interested in researching Health System Strengthening, and the use of Data in Health Service Improvement.


Social Network Analysis for Community Capacity, from SOMOS: A Partnership for Development

Amy Hilla, College of William & Mary

Abstract: International development efforts to improve health in marginalized communities often focus on short-term “silver bullets” instead of sustainable solutions. Improved health outcomes are theorized to be more sustainable when utilizing community-based participatory methods which increase community capacity, or the ability of a community to take collective action using interpersonal networks (Bhattacharya, 2004). Social Network Analysis (SNA) can be used to empirically detect changes in these networks over time; however, the accuracy of specific SNA metrics is currently unknown. Research regarding SNA as a tool is necessary to advance projects dedicated to increasing community capacity. This project uses a case study to assess the ability of SNA metrics to measure the impact of interventions in Esfuerzo, a marginalized community in the Dominican Republic, and tests the hypothesis that SNA is an accurate gauge of social network changes impacting community action. SNA data was collected by surveying 60 of 85 total households, chosen through random sampling. The first dataset helped identify network properties at Time 1 in Summer 2017, with Time 2 data to be gathered in Summer 2019. The survey responses were used to create social network matrices, which were described by multiple SNA metrics including Breadth, Fragmentation, and Component Ratio. Comparing Time 1 data to actual conditions in Esfuerzo suggests certain metrics have the potential to accurately assess social networks. After Time 2, analysis of results will show which SNA metrics are most accurate at assessing community capacity and can aid future research in the field of community-based participatory development. 

Bio: Amy is an Economics and Data Science major at the College of William & Mary. On campus, she is a member of SOMOS: Partnership for Development, Tri Delta Sorority, and Club Sailing. She is interested in researching development economics and finance flows. Amy is afraid of pigs, and during her research, there was a huge pig by the side of the road one day. Her entire research team refused to keep walking until she took a picture standing next to it, so she could "conquer her fear." Amy claims that this is the worst picture ever taken of her. 


 

Effect of Dengvaxia campaigns in neighborhoods of differing transmission intensity as the result of socioeconomic status variation

Magdalene Walters, University of Notre Dame

Abstract: Dengue is a vector-borne disease common to countries of tropical climates. The global incidence of dengue has grown tremendously in recent years, primarily impacting lesser developed countries. Dengvaxia, a dengue vaccine developed by Sanofi Pasteur, was introduced in 2015, however it’s variation of effectiveness in those who have not experienced natural infection has shed light on the importance of small-scale variation in communities experiencing dengue. Mosquito-borne diseases have been shown to vary in transmission intensity between areas of different socioeconomic status. To date, no other studies have examined the implications of small-scale spatial variation (i.e. neighborhood-level) of dengue transmission between areas of varying socioeconomic status on Dengvaxia campaigns. This study utilized a modified SIR framework to examine the implications of differing vaccination campaigns between two areas of varying transmission intensities which experience travel between each area. It was hypothesized that targeted vaccination campaigns in one neighborhood with high transmission intensity would benefit an unvaccinated nearby area with low transmission intensity. The effectiveness of vaccination campaigns was evaluated at both individual and population levels through calculation of the relative risk of symptomatic infection and the proportion of cases averted respectively. Vaccination with Dengvaxia was found to reduce the risk of symptomatic infection for individuals and to avert up to ~8% of cases at the population level in both communities. This work has implications for vaccination campaigns in communities that experience spatial heterogeneity in transmission, including that due to socioeconomic status.


The safety of atovaquone-proguanil for the prevention and treatment of malaria in pregnancy: A systematic review

Kristin Andrejko, University of Notre Dame

Abstract: Malaria infection poses a significant risk in pregnancy, yet chemoprophylaxis for pregnant women is limited. While atovaquone-proguanil (AP) is efficacious for malaria prophylaxis and treatment, it is not recommended for use in pregnancy due to insufficient safety evidence. A systematic review was conducted to evaluate the incidence of adverse outcomes after accidental or intentional atovaquone-proguanil (AP) exposure during pregnancy. Following PRISMA guidelines, the authors identified publications which reported on infant outcomes after exposure to atovaquone, proguanil, or AP in pregnancy. Of 455 records identified in the literature search, 16 studies were included: ten AP studies and six proguanil studies. The overall proportions and 95% confidence intervals of adverse outcomes reported for the 446 women exposed to AP include miscarriage (8.08% CI: 5.07, 12.08%), stillbirth (1.05% CI: 0.03, 5.73%), early neonatal death (0% CI: 0, 7.4%), and congenital anomalies (2.56% CI: 1.28, 4.53%). The overall rates of adverse outcomes after maternal exposure to AP or proguanil were similar to expected rates in comparable epidemiological settings. The limited available data suggest that AP may be a promising option for use in pregnancy, but further data are needed to ascertain the safety of AP in pregnancy. *This work was supported and conducted in collaboration with the Division of Parasitic Diseases at the Centers for Disease Control & Prevention (CDC).

Bio: Kristin is a Science-Business major at the University of Notre Dame. Living in Walsh Hall, Kristin is also involved with The Shirt, Club Jump Rope, and the Hesburgh-Yusko Scholars Program. She is interested in researching epidemiological studies to evaluate interventions aimed at malaria elimination.


 

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