Epidemics and Agricultural Information Diffusion for Rural Farmers in Mali
In this particular study, researchers Lori Beaman and Andrew Dillon analyzed the diffusion of vital agricultural information in Mali, and used their results to evaluate whether there was evidence of gender inequality in receiving said information.
The paper focuses on two important measures of network importance — “degree” meaning the number of links in an individual’s network, and “betweenness centrality” meaning the number of shortest paths in the individual’s network that includes that individual. They overall found that women had 63% less “degree” than men overall, and 43% less “betweenness centrality”, which the researchers attributed to lower overall exposure to jobs and microloan opportunities in Mali. In addition, when researchers introduced a rivalrous good (a calendar with information on composting) to individuals, 40% of men directly connected to those individuals received a calendar, while only 13% of women directly connected to those individuals received a calendar. However, the researchers could not directly evaluate gender inequality in the spread of information, as the calendar was much more likely to be sent to males, and the effect of the inequality of calendar giving and the inequality of information spreading was unable to be separated.
This connects to our study on epidemics, where a seed (“patient zero”) receives vital information, is connected to k individuals without this information, and a certain varying probability p that they share this information with a connected individual. The researchers’ analysis therefore relies on proving a generally different probability p for samples of men and women.
Although the researchers could not make definitive claims about the difference in probabilities of receiving information between men and women, and only concluded that selecting certain seeds could be preferred over widely broadcasting information, I think the paper was overall very interesting to think about, especially as an opposite to a typical epidemic like a disease, where in this case we’d like to increase (kp) for information dissemination, especially to nodes distant from central authority nodes. As gender inequality continues to exist in less-developed countries, evaluating information flow as epidemics and finding authority nodes could be a thoughtful strategy for government agencies, nonprofits, and interest groups.