Development of a Predictive Model of Tuberculosis Transmission among Household Contacts

Figure 3

Nomogram for TB transmission in households exposed to TB patients and its algorithm. First, find point for each variable of a contact on the uppermost rule; then add all scores together and find the total point on the “Total points” rule. At last, the corresponding predicted probability of TB could be found on the lowest rule. Codes annotation: contact gender: 0, female; 1, male. Contact age (years): 1, 0 < and ≤ 10; 2 : 10 < and ≤ 20; 3, 20 < and ≤ 30; 4, 30 < and ≤ 40; 5, 40 < and ≤ 50; 6, 50 < and ≤ 60; 7, 60 < and ≤ 70; 8, age > 70; 9, unknown. Contact previous TB history: 0, no; 1, yes. Contact diabetes: 0, no; 1, yes. Contact HIV status: 0, no; 1, yes. Index patient diabetes: 0, no; 1, yes. Index patient drug resistance: 0, no; 1, yes. Index patient socioeconomic status (based on a scoring system used in the Peruvian National Census) [3]: 1, lower tertile; 2, middle tertile; 3, upper tertile. Spoligotype: 1, Haarlem; 2, Beijing; 3, Latin American Mediterranean; 4, T strain; 5, other Euro-American strains; 6, orphan or no family; 7, unknown. Index-contact sleeping in the same room: 0, no; 1, yes.