Social networks for health communication in rural Uganda: A mixed-method analysis of Dekabusa Trading Centre, Luwero County

Figures & data

Figure 1. The overall network obtained by merging the five subnetworks together. The two white dots in the center are the two actors with highest power centrality.

Figure 2. Numbers of respondents in the clusters of the health subnetwork (n = 373). The coloring of the tips of some of the bars reflects the presence of influential members.

Table 1. Socio-demographic characteristics of the respondents.

Average age		45
Average nr. y in village		18
Gender	female	54%
	male	46%
Education	no schooling	9%
	done primary school	55%
	ordinary secondary	30%
Marital status	higher	3%
	married with a spouse	60%
	single	16%
	separated	13%
	widowed	8%

Table 2. Number of Dekabusa residents in largest component per subnetwork, and remainder number of people.

Subnetwork	Number of people in largest component	Remainder number of people
Giving important information	208	23
Giving help	209	22
Spend time with	213	18
Friendship	200	31
Health advice	223	5

Figure 3. Distributions of power, based on the combined network data (top) and on the health network data (bottom).

Table 3. The most central people in the health information network, limited to residents of Dekabusa.

Rank	Id	Power centrality	Indegree (direct contacts)	Betweenness (brokers linking groups)
1	2034	204	109 (1)	446 (1)
2	2058	162	76 (2)	141 (2)
3	1019	61	22 (6)	36 (9)
4	1020	52	14 (11)	14 (17)
5	2050	51	24 (4)	70 (5)
6	3059	50	8 (15)	19 (14)
7	1029	41	25 (3)	108 (3)
8	1021	35	21 (7)	96 (4)

Note: Between brackets are rank order positions for, respectively, indegree and betweenness.

Table 4. Centrality (indegree) for different sub-populations.

Id	Influence youth, under 25 (n = 62)	Influence age over 25 (n = 164)	Influence women (n = 123)	Influence men (n = 104)
2034	24	84	60	48
2058	19	56	40	35